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Genetics: The Universe Within Can knowing more about your genes help you eat, move, and live better?

By Krista Scott-Dixon, PhD

With John Berardi, Phd, Alaina Hardie, and Helen Kollias, PhD

Genetics: The Universe Within Can knowing more about your genes help you eat, move, and live better?

By Krista Scott-Dixon, PhD WITH

John Berardi, PhD

Alaina Hardie

Helen Kollias, PhD

PE E R RE VIE WE D BY Ryan Andrews

Dr. Victor Peña

Cam DePutter

Alex Picot-Annand

Dr. Trevor Kashey

Jennifer Petrosino

Kenny Manson

Dr. Jennifer Zantinge

© 2017 Precision Nutrition. All Rights Reserved.

Genetics: The Universe Within Can knowing more about your genes help you eat, move, and live better? CHAPTER 1

CHAPTER 2

CHAPTER 3

Introduction

The basics of genetics

A brief introduction to genetics and what you’ll learn in this book.

An overview of how genetics works, and an introduction to some of the key ideas you’ll need to understand genetic testing and its implications.

Introduction to genetic testing

CHAPTER 4

CHAPTER 5

CHAPTER 6

Specific genetic testing services

What we found: Heredity

What we found: Metabolism

What should you think about when considering particular genetic testing services? Which services did we choose, and why?

How does heredity work? Why don’t we all share the same genetic variations? How might our ethnic background and ancestry affect our overall health?

In this chapter, we explore some of the basic metabolic processes, such as how we regulate our blood sugar or thyroid output, and how they might be affected by genetic factors.

CHAPTER 7

CHAPTER 8

CHAPTER 9

What we found: Body weight and body comp

What we found: Food preferences

What we found: Food intolerances

In this chapter, we look at some genetic factors related to energy balance, what makes our bodies “naturally” bigger or smaller, and how much lean or fat mass we’re likely to have.

Why we might dislike some foods, like others, and really like others? In this chapter, we'll cover how genetics influence how we experience the taste of food.

Why don’t some foods don’t agree with you? And how much of that may be due to genetic factors?

CHAPTER 10

CHAPTER 11

CHAPTER 12

What we found: Nutrient absorption and use

What we found: Exercise and muscle performance

What does this mean for you?

In this chapter, we’ll examine some genetic factors that may affect how our bodies digest, absorb, and use particular nutrients.

In this chapter, we look at some of the genetic factors that may shape our response to (and recovery from) exercise and training, and whether we have a “natural athletic type”.

Now that you've learned more about genetic testing, or even gathered your own data, what should you do next?

CHAPTER 13

CHAPTER 14

CHAPTER 15

Glossary of terms

References

Confused by codons? Mystified by mutations? No worries, we’ve got a handy glossary for all the technical terms we’ve used in this book.

Don’t believe us? Want to learn more? Enjoy the hundreds of references we’ve collected.

Contributors and acknowledgments

What does genetic testing involve? What are some of the general issues to think about while deciding if genetic testing is right for you?

Science is a collaborative endeavor. We are most grateful to all of those who contributed their data and expertise to help us write this book.

CHAPTER 1

Introduction “Our fate cannot be taken from us. It is a gift.” – Dante Alighieri, Inferno (1472)

“Oh, I am fortune’s fool!” – William Shakespeare, Romeo and Juliet (1595)

PRECISION NUTRITION

| GENETICS: THE UNIVERSE WITHIN

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What if you could know your future? If you could know how you would live? How you might die? Where your path might take you in the meantime? Would you do anything differently? Would you try to fight fate? Or just let yourself be swept along in the river leading to the inevitable waterfall of your ending?

Human beings have wondered about destiny for a long time. Is our life course pre-determined? Is there some kind of plan? Do we have free will? Can we do anything we like? Or are there limits? If there’s a plan, who or what creates it? In 2017 BC, we might have said: The gods. The stars. The spirits. The same powerful, invisible forces that create gusts of wind also push and pull us along the path of our lives. In 2017, we might say: Genetics.

Human beings have also wondered about who they are, and why they are that way.

Why is so much of ourselves often hidden from us? Why don’t we know why we do things?

GENETICS: THE UNIVERSE WITHIN

Again, in 2017, we often try to answer these questions with: Genetics.

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Are we really “just like” our fathers, or mothers, or second cousins? Are we basically just carbon copies of our ancestors, or are we a blank slate?

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Why is one person tall, and another one short? Why is one person quick to anger, and one calm? Why did this person get sick when the plague hit, and not that one?

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“Genetics” seems like the answer to everything. But is it really? For instance:

ΧΧWhat can we really know about ourselves using the tools of genetic analysis, and what is just speculation, wishing, and guessing?

ΧΧHow much certainty can we really gain from knowing about our genome? Are genetic data a “for sure”, a “maybe”, or “I dunno”?

ΧΧIf we find something we don’t like, how much can we change? How negotiable is the expression of our genes?

ΧΧWhat’s important and what’s not? Our genome has a lot of information. Is

all of it relevant to our concerns and interests? Do we really care about the genetic program that makes the third eyelash from the left?

ΧΧEven if we can get all the knowledge we want, what should we do with it?

Genetics is an exciting area of exploration. In 2000, scientists mapped out a “rough draft” of the human genome — our “genetic code”.

Now we had a map of ourselves — in theory, the code for all human beings on earth.

Yes, you might have diverged a billion years ago, and don’t really plan to get together at Thanksgiving, but there’s a part of your genome, and a part of their genome, that came from the same place. This system of coding created all life — from mushrooms, to dolphins, to oak trees, to us.

GENETICS: THE UNIVERSE WITHIN

You are directly related to the bacteria that live on your body.

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And not just humans. Some form of this code is in every living thing on Earth.

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In 2003, the National Human Genome Research Institute (NHGRI) in the U.S. announced that they had successfully completed the Human Genome Project.

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In 2007, commercial genetic testing services like 23andMe became available to the general public. Anyone could have their genome scanned and read. Since then, the field of genetic testing and genetic counseling has exploded. It’s now cheaper, faster, and easier to get your genome examined. Genetic testing looks to answer Big Questions like:

ΧΧWhat if we could know — not just speculate, or guess, or wonder, but

know for sure — how we work at the most basic level? What, exactly, our bodies are doing?

ΧΧWhat key opens which lock? What exact set of genetic instructions makes us a sprinter, or have heart disease, or have a funny-looking baby toe?

ΧΧWhat does our future hold? What diseases might we get (or avoid)? How might we grow and develop?

ΧΧHow can we be better? Is there something in our genetic code that could

tell us what to eat or how to exercise? What supplements to take to function better, or lower our risk of disease?

Some advocates of genetic testing suggest that they also have the Big Answers.

It’s an exciting promise.

Wow. That would be amazing. Wouldn’t it?

GENETICS: THE UNIVERSE WITHIN

A plan based on our unique, special blueprint? A one-in-seven-billion program, just for us?

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What if we could have a complete plan for everything that we wanted to do, change, or improve?

PRECISION NUTRITION

“Do this genetic test, and we’ll tell you exactly what health, fitness, and nutrition plan you need.”

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“Take a back seat, horoscopes! See ya, metabolic typing! Later, random trial and error!” “There’s a new plan in town! And it’s gonna tell me everything I would ever need to know about what to do!” Well…

We’re not quite there yet. But we are at a thrilling crossroads in human knowledge and understanding. Imagine you are standing outside a toy store. It has a small window. You can see in the window. You get a glimpse of what the store contains. But the window is too small to show you everything. If you squint and peer inside, and crane your neck, you can see tiny bits and pieces. An action figure here. A train set there. You know the toy store is full of cool, fun, interesting stuff to play with. You just can’t see it all… Yet. That’s where we’re at with understanding genetics and how we might use it.

We’ll tell you:

ΧΧWhat genetic testing can tell you… and not tell you. ΧΧWhat you can learn about your health, fitness, and nutrition through genetic testing.

GENETICS: THE UNIVERSE WITHIN

ΧΧWhat genetic testing can do… and not do.

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ΧΧWhat genetic testing is, and how it works.

PRECISION NUTRITION

In this book, we’ll peek into the toy store.

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ΧΧWhich tests might be better, more accurate, or more useful than others. ΧΧWhat you might do with any information you get from genetic testing. ΧΧWhy we think this is exciting and cool, and full of potential… but not quite a magic solution to anything yet.

All of this is “right now”. As in, here’s what we can realistically do or know right now. Here’s what tools are available right now. Of course, “right now” will change.

We want to dream, and we also want to be scientists. We’ll tell you what possibilities genetic testing can offer, and what the actual research says. We encourage you to read this book with the following mindset: There is stuff we know, and stuff we don’t know. That’s how science works. This is cool. Imagine the possibilities. It’s not magic yet… but it could be. This is complex.

Get excited, but keep it real.

GENETICS: THE UNIVERSE WITHIN

So bear in mind that any scientific claims are subject to critical scrutiny and revision. And try not to write a check that your science can’t cash.

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We may all look like ignorant idiots in 200 years as knowledge and research progresses. (Well, assuming we haven’t lit the planet on fire by then.)

PRECISION NUTRITION

There are no simple answers. There are no “hacks”, appealing as that idea might be.

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We’re personally invested. Science is not individual geniuses laboring alone in a lab. Science is a collaborative endeavor. This project is no different.

We shared our own genetic data. 18 members of the Precision Nutrition team plus 15 of their family and friends agreed to share their genetic data for this project. Throughout this book, we’ll look at what they discovered in their genes, and what that might mean for them — and you. At times, with their consent, we share some personal details about them. (You’ll find out, for instance, who’s a “sugar monster”, who’s the most Neanderthal, and who had an ancestry surprise.) At other times, we’ll present their data in anonymous aggregate.

Here’s our team. For more about the people who wrote and reviewed this book, see Chapter 15: Contributors and acknowledgments. Thanks to everyone who contributed a little part of themselves for their openness and contribution to scientific exploration.

For example, we need to understand such things as:

ΧΧthe molecular biology of genes and how they work; ΧΧhow scientists collect, process, and store genetic data;

PRECISION NUTRITION

We need to look at this from many angles.

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ΧΧhow probability and risk work; ΧΧhow we might feel about any genetic test results we get; and ΧΧwhether knowing about our genes will actually inspire us to change… and if so, how?

GENETICS: THE UNIVERSE WITHIN

ΧΧhow genetic testing relates to nutrition and exercise physiology;

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So, we’ll look at the topic from different viewpoints to give you depth and context.

The science is neat. But this isn’t just about science. It’s not just about buzzwords like bio-hacking, personalized medicine, or gene editing. It’s also about psychology and behavior. How we think about ourselves. What we’re prepared to do to potentially change our fate. As you read this book, remember an important caution:

As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

Getting started with the fundamentals CHAPTER 2

GENETICS: THE UNIVERSE WITHIN

An overview of how genetics works, and an introduction to some of the key ideas you’ll need to understand genetic testing and its implications. We recommend you review this chapter if you’re new to the topic, or if you’re looking for a refresher. If you’re already running your own biotech lab, feel free to skip it.

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The basics of genetics

PRECISION NUTRITION

Here’s what the rest of this book will cover.

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Genetic testing CHAPTER 3

Introduction to genetic testing

What does genetic testing involve? What are some of the general issues to think about while deciding if genetic testing is right for you? This chapter includes a description of the basic process of a genetic test from sample collection to discovering you’re related to Marie Antoinette. CHAPTER 4

Specific genetic testing services

What should you think about when considering particular genetic testing services? Which services did we choose, and why?

Specific topics of interest CHAPTER 5

What we found: Heredity

How does heredity work? Why don’t we all share the same genetic variations? How might our ethnic background and ancestry affect our overall health? CHAPTER 6

What we found: Metabolism

In this chapter, we explore some of the basic metabolic processes, such as how we regulate our blood sugar or thyroid output, and how they might be affected by genetic factors. CHAPTER 7

In this chapter, we look at some genetic factors related to energy balance, what makes our bodies “naturally” bigger or smaller, and how much lean or fat mass we’re likely to have. CHAPTER 8

CHAPTER 9

What we found: Food intolerances

Why don’t some foods don’t agree with you? And how much of that may be due to genetic factors?

GENETICS: THE UNIVERSE WITHIN

Why we might dislike some foods, like others, and really like others? In this chapter, we’ll cover how genetics influence how we experience the taste of food, and how they shape our food preferences.

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What we found: Food preferences

PRECISION NUTRITION

What we found: Body weight and body comp

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CHAPTER 10

What we found: Nutrient absorption and use

In this chapter, we’ll examine some genetic factors that may affect how our bodies digest, absorb, and use particular nutrients. CHAPTER 11

What we found: Exercise and muscle performance

In this chapter, we look at some of the genetic factors that may shape our response to (and recovery from) exercise and training, as well as whether we have a “natural athletic type”.

What this all means and what to do next CHAPTER 12

What does this mean for you?

Now that you’ve learned all about genetic testing, some of the data that you can discover with it, and some of the traits that might affect your general health, nutrition, and/or fitness, this chapter gives you some realistic next actions to consider.

References CHAPTER 13

Glossary of terms

Confused by codons? Mystified by mutations? No worries, we’ve got a handy glossary for all the technical terms we’ve used in this book. CHAPTER 14

Don’t believe us? Want to learn more? Enjoy the hundreds of references we’ve collected. CHAPTER 15

Contributors and acknowledgments

Take what you like and leave the rest. Skim and scan chapters. Or dig in.

GENETICS: THE UNIVERSE WITHIN

Consider this a buffet.

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Science is a collaborative endeavor. We are most grateful to all of those who contributed their data and expertise to help us write this book.

PRECISION NUTRITION

References

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We suggest you peek at Chapter 2, even though it’s kinda heavy-duty. Or check the glossary in Chapter 13 as needed if you don’t recognize a sciencey term. Think about what you want to get out of this book, and read it accordingly. Look for the “What this means for you” sections in each chapter. There, we’ll give you some practical tips for how to think about a given topic, and/or what to do next. Also, check out Chapter 12 for our overall recommendations. Let questions be there. We have some answers for you, but not as many as you’d probably hoped. Get comfortable with questions, because that’s how science works. (As the physicist Richard Feynman quipped, “Give me questions I can’t answer, not answers I can’t question.”) Get curious. Let’s go!

GENETICS: THE UNIVERSE WITHIN

An overview of how genetics works, and an introduction to some of the key ideas you’ll need to understand genetic testing and its implications.

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The basics of genetics

PRECISION NUTRITION

CHAPTER 2

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CHAPTER 2

The basics of genetics What you’ll learn in this chapter In this chapter, you’ll learn the basics about:

ΧΧWhat genes do, and how; ΧΧWhy computation and biomedical engineering are important; ΧΧThe structure of DNA; and ΧΧHow our genetic code might relate to any traits we express. PRECISION NUTRITION

| GENETICS: THE UNIVERSE WITHIN

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Warning (or challenge): This chapter is heavy. It’s meant to be a reference for the rest of the book. So there’s a lot of information here. You don’t need to understand or remember it all in order to grasp the key ideas about genetic testing. Feel free to skim this chapter, skip it, come back to it… whatever you like. If you’re new to understanding genetics or just want a refresher, we do suggest you tackle at least a bit of this material. If you’ve already done your graduate work in genetics, go ahead and breeze on past.

A quick review of key terms Before we get into this chapter, let’s learn a few basic terms. (You’ll also find any bolded term in our glossary.) DNA is a biological molecule that holds the code for making all living things.

Fun factoid!

Genes are regions of DNA that encode instructions for making specific proteins.

PRECISION NUTRITION

Some viruses do not have DNA. Some (like parvovirus) have single-stranded DNA genomes. Some (such as pox viruses) have double-stranded DNA genomes. Most have RNA genomes of some kind.

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For instance:

ΧΧThe FGF21 gene (written in italics) codes for a protein called fibroblast growth factor 21, or FGF21 (no italics).

ΧΧThe TAS2R38 gene codes for a protein called taste receptor 2 member 38, or TAS2R38.

GENETICS: THE UNIVERSE WITHIN

If genes have names, we put those in italics, like this: FGF21. This helps us tell them apart from their corresponding protein names.

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Variants of the same genes are known as alleles or polymorphisms. For instance, the type of earwax you have is controlled by a single gene known as ABCC11 (which is also involved, by the way, in how your sweat smells). If you have one of two variants / alleles of the gene, you’ll have wet earwax; if you have a third variant / allele, your earwax will be dry. Genetics is the study of genes, how they work, and how particular traits (such as eye color) are passed from parent to offspring (known as heredity). The expression of one gene can influence two or more apparently unrelated processes or traits. We’ll see examples of this as we look at specific topics, such as metabolism. This is known as pleiotropy (from the ancient Greek pleion, or “more”, and tropos, or “way”). A variant in one gene may have a wide variety of effects. Our genotype is our genetic code; our phenotype is how that code is actually expressed as it interacts with our environment. The same genotype can have different phenotypes. Different environments (for instance, our activity, our nutrition, our exposure to toxins, and so forth) can change our observable traits (for instance, our physiology or behavior).

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Epigenetics is the study of how activation and inhibition of gene expression is regulated. The same genetic “blueprint” may be used to express different things; for instance, exercising can activate expression of genes involved in the antioxidant response. We may already have had those genes, but exercising affects their epigenetic expression.

PRECISION NUTRITION

Figure 2.1: Relationship between genotype and expressed traits

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A genome is the complete set of an organism’s genetic information. For instance, the Human Genome Project studied the complete genetic code of human beings. In this book, we’ll be talking about genetic testing. Generally, this doesn’t mean we are testing the entire genome. As you’ll learn, the amount of information in an entire human genome is very, very, very large. We have about 22,000 genes, and about 3 billion base pairs, or pairs of nucleotides in our strings of DNA. (We’ll learn more about nucleotides in a moment.) With genetic testing, we usually test a single gene or single nucleotide polymorphism (SNP), which is just one single point mutation to one nucleotide within a gene. There can be several SNPs in the same gene; most widely used SNPs are in noncoding regions. Noncoding regions are parts of the genetic code that don’t code for any proteins, and they’re known as introns. Regions that do code for proteins are known as exons. (We’ll look more at coding and noncoding regions in Chapter 4, and at splicing more below.)

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Copy number variation (CNV) refers to whether chunks of genetic material are repeated, kind of like having three or more of the same socks instead of a single pair.

GENETICS: THE UNIVERSE WITHIN

Figure 2.2: Introns, exons, and mRNA splicing

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CNVs can also affect how genes work. For instance, having multiple copies of genes that make the enzyme amylase would increase our ability to break down the carbohydrate amylose. This variation may reflect our ancestral history (for instance, whether we come from an ethnic group that has traditionally eaten a high-starch diet) and may be linked to our body weight.

Figure 2.3: Duplication of genetic material

Figure 2.4: Copy number variation (CNV)

Genes are information. In the real world, we have to figure out a few things when we use information:

ΧΧHow to reproduce information properly and carefully. ΧΧHow to store information so it doesn’t degrade or take up too much space. ΧΧHow we receive and interpret informational signals that are sent.

GENETICS: THE UNIVERSE WITHIN

to another without losing it along the way.

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ΧΧHow to transmit and transport information — how to get it from one place

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What do genes do?

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Genes and their associated products and processes do all of this inside our bodies. We can think of a gene as a unit of information or a set of instructions for making something — in this case, a specific protein. In eukaryotic cells (cells that have a nucleus and distinct organelles bound by a membrane), DNA is organized in chromosomes in the nucleus. When cells divide, chromosomes are duplicated and DNA is replicated. Once cells finish dividing, each cell ends up with its own full set of chromosomes. Eukaryotes store most of their DNA inside the cell nucleus and some of their DNA in organelles, such as mitochondria or chloroplasts (in plants). Genetically speaking, we are about half of each of our parents. But we’re not exactly like our mom and dad. And we’re not a precise 50% of each. We’re more like a 49-point-something percentage of each, plus some random mutations that sneaked in along the way. We’ll learn more about mutations in a bit. For now, the key points are:

ΧΧGenes store information. ΧΧInformation is passed from parent to offspring. ΧΧIt’s not a perfect transmission every time. When we look at our genes, or particular variation in our genes, we can see this transmission of information. And we can see the variations among ourselves, even within the same family.

ΧΧHow does this work? ΧΧAnd what does this all mean for your own genetic code?

Most people tend to think of biology as just a bunch of wet squishy bits. We can also think about biology as being a type of computation.

GENETICS: THE UNIVERSE WITHIN

Biology is computation.

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To explain, let’s start with a concept that may be a little new to you.

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ΧΧWhy does this happen?

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Imagine you were trying to program a computer to do something. Computers are pretty literal and only do what you tell them, so you want to make sure you’re absolutely clear. You’ll also need to give the computer some structured parameters for making decisions, otherwise they get confused. For example, you might tell the computer: IF this is true, THEN do this thing. IF today’s date is July 18, THEN send Dr. John Berardi a birthday card. IF Dr. JB likes cake, THEN make him some. Maybe your IF / THEN instructions have conditions: IF Dr. JB likes cake OR you like cake, THEN make a cake. IF you are on a desert island AND today is July 18, THEN spell out “Happy birthday” using driftwood instead.

Biology works in similar ways. Let’s imagine something simple, like the communication between a cell and the outside world. Some cells have receptors (such as a specific type of protein) on their membranes. These receptors bind to other things, such as other proteins or simpler molecules. PRECISION NUTRITION

Each receptor is picky and will only bind to particular things (these specific molecules are known as ligands), much like a key will only work in one or two locks.

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Figure 2.5: Receptors and binding sites

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A receptor acts like a switch. If something binds to a receptor, it triggers another event, like turning a switch to “on”. So, we might imagine a situation where the instructions for our cell’s “biological computer” read something like this: IF receptor A is “on” AND receptor B is “off”, THEN make protein from gene A IF gene A is active, AND gene B is available, THEN make the protein from gene B. Note that this looks very much like the computer code you might have learned in school: IF xyz THEN do something. Computers are still pretty dumb, relative to biology. But at a basic level, the concept is similar. Genes encode a series of instructions, like a computer program… and accumulate problems, also like computer programs. Computers can start from scratch. In theory, you could make a computer that thinks in a way that nothing ever has before, using components that nobody has ever used before. Biological systems don’t work that way. They can only use the structures and systems that they have inherited (along with, of course, any new mutations, which are only a small part of a much bigger whole). Sometimes this can mean that biological systems are pretty efficient — perhaps evolution has done a lot of work to tidy things up.

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Figure 2.6: Simple H20 molecule

GENETICS: THE UNIVERSE WITHIN

Remember high school chemistry with diagrams like this?

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Biology is engineering.

PRECISION NUTRITION

Sometimes the systems can be less efficient. They have a lot of what computer folks call “cruft”: clutter and redundant junk such as old equipment or code that just hangs around and either does nothing or actively gums up the works.

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(That’s water.) Or these?

Figure 2.7: Simple caffeine and nicotine molecules

(Those are caffeine and nicotine, maybe two of your best friends in high school, you rebel you.) You might have been left with the impression that “molecules” are basically flat polygons and lines.

However, molecules are three-dimensional. So water actually looks more like this: PRECISION NUTRITION

| GENETICS: THE UNIVERSE WITHIN

Figure 2.8: 3-dimensional H20 molecule

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And nicotine looks more like this:

Figure 2.9: 3D nicotine molecule

Molecular structures in the body are the same way. For instance, here is a three-dimensional protein (a Cas9 nuclease, in case you’re wondering) that our co-author Alaina printed in her lab:

PRECISION NUTRITION

| GENETICS: THE UNIVERSE WITHIN

Figure 2.10: 3D protein

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You’ll notice that proteins are not abstract line drawings, but actual, tangible objects. If you blew that nicotine protein up larger, it would look like this:

Figure 2.11: 3D nicotine protein

The physical shape of the protein would affect how you could interact with it. The same thing happens at the molecular level. For instance, let’s imagine you have a protein that is shaped like this: PRECISION NUTRITION

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It has a straight end and a hooked end. Let’s imagine that 3-dimensional J-shaped protein is moving around in your body.

GENETICS: THE UNIVERSE WITHIN

Figure 2.12: Hook-shaped protein

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Then it finds a protein that looks like this:

Figure 2.13: Eye bolt-shaped protein

What happens? Well, if conditions are right, maybe the hook-shaped part of the first protein will latch on to the eye-shaped part of the other protein, and stick there.

Figure 2.14: Hook and eye proteins connected

If you just have this:

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The physical shapes of the proteins determine how they will interact.

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Figure 2.15: Column-shaped protein

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…then the J-hook has nothing to connect to. In other words: Shape matters. The physical characteristics of molecules determine whether and how they will interact (or react) with other molecules. And biology is, after all, just a whole lot of reactions with the final result of making something be alive.

DNA is a 3-dimensional structure. First: What does the acronym “DNA” stand for? Yes, eager student in the front with your hand up, the answer is deoxyribonucleic acid. Aside from making you the team champ on trivia night, knowing the full name of DNA actually gives you clues to how DNA is constructed, and to understanding how genetics work. Part of that has to do with the physical shape of DNA and how the molecules fit together. A DNA strand is shaped like a ladder, and made out of two pieces:

ΧΧA deoxyribose “backbone”, i.e., the side rails of the DNA ladder. (RNA has ribose here.)

ΧΧBases or nucleotides, i.e., the ladder’s rungs.

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Figure 2.16: DNA “ladder”

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Ribose is a simple sugar. “De-oxy” means “without oxygen”, so “deoxyribose” means a ribose without an oxygen. OK, now imagine that the deoxyribose sugar is actually a sort-of T-shaped piece of Lego, like this:

Figure 2.17: Deoxyribose “Lego”

And imagine a few of those Legos stacked on top of each other, like this:

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Figure 2.18: Deoxyribose “Lego” stack

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Then imagine you’re getting real fancy with the Lego stack and you want to indicate which way is up. So you draw an arrow along the stack, like this.

Figure 2.19: Deoxyribose “Lego” stack with arrows

Congratulations. You just built the deoxyribose backbone of DNA.

Remember our Lego structure? We can stick bases, or nucleotides, on it. Bases are the building blocks of nucleic acids.

GENETICS: THE UNIVERSE WITHIN

Except imagine that in DNA computation, we aren’t making numbers, but amino acids.

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DNA uses computation.

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And, since you have 3 pokey-outy parts to which other things can attach, you have also built the foundation for a specific unit of DNA, known as a codon (aka a sequence of three nucleotides).

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Figure 2.20: Nucleotides on deoxyribose “backbone”

With DNA, we have 4 options for nucleotides:

ΧΧAdenine (A) ΧΧCytosine (C)

ΧΧThymine (T) RNA (which we’ll look at in a moment) gives us one more: uracil (U), which replaces thymine.

GENETICS: THE UNIVERSE WITHIN

Like this:

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Two of these nucleotides (A and G) are long. Two (C and T) are short. So in a full strand of DNA, short nucleotides pair with long ones, and vice versa.

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ΧΧGuanine (G)

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Figure 2.21: Short and long pairs of nucleotides

The nucleotide formula for proteins You can imagine that each nucleotide is like a box that could have 1 of 4 possible nucleic acids inside: either an A, a C, a G, or a T, like this:

PRECISION NUTRITION

Figure 2.22: Nucleotides in boxes

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With 3 boxes, we get 4 x 4 x 4 values = 64 possible combinations. DNA codes for proteins. Proteins are made of amino acids. So part of that DNA has to code for a particular amino acid. We need to make about 20 amino acids.

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With 2 boxes, we get 4 x 4 values = 16 possible combinations.

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We can’t do that with 1 box (which can only contain 1 of 4 possible nucleotides), or 2 boxes (which only gives us 16 possible combinations). We need 3 boxes. Hence, a codon is 3 units. BIO MATH!! We need many different 3-nucleotide codons to code for these 20 amino acids. Keeping it all straight can be confusing. Thus, researchers have come up with some ways to help us catalogue and interpret codons, such as a codon wheel (shown below). A codon wheel helps us in both directions: We can decipher what amino acid a particular codon codes for, and what codons code for a particular amino acid. To read the wheel, start from the center. That’s one nucleotide. Then go outwards and pick another one of 4. And outwards again, picking another one of 4. For instance:

ΧΧStarting with C in the middle → moving outwards and picking another C →

then moving outwards again and picking a U, C, A or G gives you the amino acid leucine.

ΧΧStarting with G in the middle → moving outwards and picking an A → then moving outwards again and picking an A or a G gives you glutamine.

You might also notice that some amino acids can be made with more than one combo of nucleotides.

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Figure 2.23: DNA codon wheel

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We’ll learn more about codons and how they work later. For now, just remember this structure of DNA:

Figure 2.24: Basic structure of DNA

Genes have “geography”. The shape of DNA is not random. To go back to the idea that genes store information, this shape is not an accident. Because of the way the DNA Lego blocks fit together:

ΧΧOur bodies can copy it with extremely high fidelity and accuracy.

GENETICS: THE UNIVERSE WITHIN

Remember our little ribose Lego? Deoxyribose is a carbohydrate, which means it has carbon. In biochem, we number the carbons. Each little Lego block has one carbon called the 5-prime (written as 5’) and another called the 3-prime (written as 3’).

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This is good, because as we’ll see later, we don’t really want things falling apart or getting sloppy with reproduction. Errors happen all the time, but we have biological proofreaders to catch them.

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ΧΧThe molecule is extremely stable.

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Our bodies will always read DNA in a certain order (hence the arrow): from 5-prime to 3-prime, and they go in opposite directions. One side will be 5’ to 3’ reading up, the other 5’ to 3’ reading down.

Figure 2.25: Directionality of DNA pieces

This directionality of each DNA piece is important. Think about how you read. If you read English: YOU READ FROM LEFT TO RIGHT. .TFEL OT THGIR MORF DAER T’NOD UOY DNA reading works the same way. It has to go in a particular direction.

ACTTGAATGCATC and so on. It has to go in that direction, because the reverse (reading from 3’ to 5’) would be something totally different:

DNA isn’t just floating around randomly in cells. It’s packed into highly organized structures, tightly wrapped around proteins called histones like beads on a string, so that massive amounts of this genetic material can fit into the tiny space of a cell’s nucleus.

GENETICS: THE UNIVERSE WITHIN

Different “letters”, different meaning.

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CTACGTAAGTTCA

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Imagine you were making a machine to read DNA. It’s a simple computer, so it can only read one nucleotide at a time. It scans down the strand, reading from 5’ to 3’, reading the name of each nucleotide, like this:

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Unspooled, your strands of DNA would be around two meters long. Yet they fit into a space about 1/1,000 of a millimeter. This protein-DNA complex is called chromatin, and it’s what makes up your body’s chromosomes.

Figure 2.26: Structure of chromosomes

The ways that our chromosomes are folded in space, and physically organized in the nucleus, can significantly affect how genes are expressed. For example: gene will be transcribed, need to be located close to the regions that they act on.

ΧΧMuch of epigenetics (which we’ll look at briefly below), or the regulation

This research revealed that the way in which chromatin was packed into the nucleus — its shape as well as its density — affected its function.

GENETICS: THE UNIVERSE WITHIN

Recent groundbreaking research at the Salk Institute for Biological Studies has just revealed that we are now able to see how chromatin is organized in a living cell. (Previously, we had to pull the cell apart to see this, so we could not see how chromatin worked “in the wild”.)

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of gene expression, is related to histone modification, or changes to the physical configuration of the histone proteins that DNA wraps around.

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ΧΧFactors known as enhancers, which increase the likelihood that a given

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What this means is that:

ΧΧThe shape of molecules is important. Shape affects how molecules work, and how they interact with other molecules.

ΧΧThus, genetic expression is not just about the genes we have, but where they’re located.

ΧΧCommercial genetic testing can tell us about some of the specific genes we

have, but not about how they’re physically organized. We can’t know the geography of our genes from a commercial test, which means we can’t know a lot about how those genes may be expressed.

How are proteins made from genes? The central dogma of molecular biology All of this adds up to what is sometimes known as the central dogma of molecular biology: DNA to RNA to proteins.

ΧΧDNA is read in groups of three nucleotides called codons. ΧΧThese DNA codons are transcribed to an “in-between” molecule,

messenger ribonucleic acid (mRNA). (We’ll look at this in more detail in a minute.)

ΧΧThe mRNA is read and each mRNA codon is translated to one amino acid. ΧΧAmino acids are linked together to make proteins.

All of molecular biology revolves around this basic principle.

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Thus, again, DNA’s job is to store the information to make proteins.

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Figure 2.27: DNA to RNA to protein

Gene expression and making proteins There are two general steps to make a protein. Together, they’re called gene expression.

2 | Protein synthesis (translation): Making proteins, using the instructions from RNA. RNA has many jobs, and there are several types, which we’ll look at in a moment.

GENETICS: THE UNIVERSE WITHIN

For a long time, scientists thought that one gene coded for one mRNA, that then coded for one protein: If you had 100 genes, you’d make 100 different mRNAs, and then 100 different proteins. That way, if you knew all the genes, you’d know all the proteins.

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For now, we’ll focus on messenger RNA (mRNA). mRNA is the intermediary between DNA and proteins.

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1 | RNA synthesis (transcription): Making RNA, using the instructions from DNA. At this step, double-stranded DNA is “unzipped” like a zipper by enzymes called polymerases into single, complementary strands of RNA.

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It’s more complicated than that. (Warning: We’re going to say this a lot. Like, a lot.)

RNA splicing One gene can code for many related proteins through RNA splicing. RNA splicing is like producing alternative cuts of movies — think of director’s cuts, alternative endings, 20 year anniversary edition cut, and what-have-youdone-to-my-favorite-movie?? cut. Some cuts could be minor. Some could completely change the movie (i.e., the protein that’s expressed).

PRECISION NUTRITION

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Figure 2.28: DNA to RNA to splicing to proteins

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Now, imagine your movie is also full of commercials. You have to watch the movie in little bits. This is annoying. So, imagine that you re-cut the movie, take out the commercials, and stick all the movie bits back together so you get one uninterrupted full-length feature. You can think of introns (sometimes known as “intervening sequences”) as the commercials. Remember, introns don’t code for proteins. You can think of exons (sometimes known as “expressing sequences”) as the movie itself. Since exons code for proteins, they’re like the “story” of what will happen, genetically speaking. Just like a movie with irritating and useless commercials removed, mRNA is spliced so that all the introns are taken out, and only the exons, the expressing sequences, remain. Now, sometimes there’s a small problem: Our editor is excellent but not perfect. So, when our “mRNA movie” is “re-cut” during the RNA splicing process:

ΧΧWe might end up with a perfect, commercial-free copy of the original

movie. Just some nice exons all stuck together in an uninterrupted, faithfully reproduced sequence.

ΧΧOr, if alternative splicing occurs, we might end up with a few scenes missing from our movie. A few exons might get cut out.

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Figure 2.29: RNA splicing

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Transporting mRNA in and out of the nucleus Remember that DNA and RNA live mainly in the nucleus. (In Chapter 6, we’ll talk about another kind of DNA, mitochondrial DNA, that doesn’t.) Before it can be used to code for protein, mRNA has to clear a couple more hurdles. Enter mRNA export.

ΧΧmRNA needs to get out of the nucleus and to ribosomes, the protein-making factories in the cytoplasm.

ΧΧIt also needs to keep itself from breaking down. If it’s broken down (degraded), then it can’t be used.

You don’t want RNA just randomly escaping the nucleus, just like you don’t want drunken texts to your ex or boss escaping your phone at 3:00 AM. Thus, you need to regulate mRNA degradation and stability so it can make it to the ribosome and be translated into a protein. Nuclear exporting involves nuclear transport receptors that chaperone the mRNA through a nuclear pore, which means that trying to get the mRNA out of the nucleus can be a bit of a bottleneck.

The cap and the tail protect the mRNA from being broken down and keep it stable. The more stable the mRNA is, the more protein it can make.

GENETICS: THE UNIVERSE WITHIN

Mature mRNA has a bunch of extra nucleotides stuck on one end (a 3’ poly-A tail) that acts a bit like the little plastic ends on your shoelaces that keep them from getting frayed. On the other end of the mRNA (the 5’ end), it has a cap (a 7-methylguanosine cap).

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Once precursor mRNA grows up and becomes mature mRNA (via splicing and some accessories stuck on for stability), it’s selected and moved out of the nucleus.

PRECISION NUTRITION

Figure 2:30: RNA movement through nuclear pore

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Other types of RNA Besides pre-mRNA and mRNA, there are several other types of RNA we need to make proteins.

ΧΧTransfer RNA (tRNA). tRNAs are RNA molecules that carry specific amino acids to the ribosome. They match mRNA codons with their respective amino acid.

ΧΧRibosomal RNA (rRNA) is an RNA enzyme that links amino acids together

in the ribosome to make a polypeptide chain. Remember that ribosomes are where the mRNA is read and matched with tRNA that carry amino acids, which are then assembled to make the protein.

Other RNAs — such as small nuclear RNA (snRNA), microRNA (miRNA), and small interfering RNA (siRNA) — regulate how much and what type protein will be made. There’s no exam. Just remember: It’s much more complicated than “One gene, one protein.”

MAIN FUNCTION

mRNA

Codes for protein

rRNA

An RNA enzyme that links amino acids together

tRNA

Bridges between mRNA codons and the amino acids they code for

snRNA

RNA splicing

miRNA Generally block translation of specific mRNA, though can also upregulate (increase) it

GENETICS: THE UNIVERSE WITHIN

Selectively target specific mRNA for degradation

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siRNA

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TYPE OF RNA

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Controlling gene expression: from DNA to protein There are 5 steps going from DNA to protein that are controlled via mRNA production, processing and transport. 1 | Transcription: making RNA from DNA 2 | RNA processing: splicing RNA 3 | RNA export: exporting mRNA out of the nucleus 4 | Translation: making protein from mRNA 5 | Post-translational processing: getting rid of unwanted or harmful mRNA, which can happen before proteins are made (kind of like a quality control mechanism) Your body doesn’t constantly make RNA from DNA. It’s a very regulated process. Only certain genes are transcribed, and only at certain times. Genes have three control regions:

ΧΧpromoters ΧΧenhancers ΧΧterminators Promoters and terminators (basically starters and stoppers) are similar for all genes.

Sometimes you lose or mismatch socks — maybe one sock, maybe a pair of socks, maybe a few pairs. Sometimes you even end up with new socks… socks that aren’t even yours.

GENETICS: THE UNIVERSE WITHIN

Think about nucleotide pairs like matching pairs of socks. Ideally, you have all your socks properly sorted and paired after doing laundry. Sometimes, that happens. Sometimes, not.

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How do mutations happen?

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But enhancer regions are different. Their variations allow them to match transcription factors with some specificity, allowing systems to activate and deactivate transcription of certain genes by the presence and absence of their transcription factor(s).

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The same can happen with the nucleotide pairs of DNA. This is called a mutation — some type of permanent change to the nucleotide pairing sequence. This can happen in a few different ways, and for different reasons. The example of antioxidants and reactive oxygen species You may have heard the term “antioxidant” (for instance, as an ingredient in “superfoods”, or vitamins C and E). But why do we need antioxidants in the first place? In normal metabolism, we create what are called reactive oxygen species (ROS). ROS are unstable, oxygen-containing molecules that are normal byproducts of cellular respiration. Oxidative damage happens naturally during cell metabolism — some estimates suggest this occurs 10,000 times a day per cell. Usually, our cells are able to balance oxidative damage with their own antioxidant system. However, under environmental stress (such as exposure to toxins), ROS can build up faster than the cell can clear them. This can cause mutations by chemically modifying the nucleotides to become a slightly different molecule. Types and causes of mutations Having a lot of ROS hanging around is one cause of mutations. There are many other ways for oxidative changes to occur, such as:

ΧΧexposure to ionizing radiation (such as X-rays or radioactive material); ΧΧcertain types of chemicals (such as heavy metals or pesticides); sensitive to UV light); and

ΧΧspontaneous (and uncorrected) errors in the DNA replication/copying process.

GENETICS: THE UNIVERSE WITHIN

Small mutations can sometimes have big effects that change a protein’s amino acid composition:

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Mutations can affect anything from only a single nucleotide, to large-scale alterations to chromosomes. They can change the structure and function of genes.

PRECISION NUTRITION

ΧΧultraviolet light (two nucleotides — cytosine and thymine — are particularly

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ΧΧSubstitution mutations: In a codon, one nucleotide is exchanged for another (for instance, an A for a G or a C for a T). These can end up being:

ΧΧSilent mutations that code for the same or a similar-enough amino acid (e.g., both CCA and CCT result in proline)

ΧΧMissense mutations, which code for a different amino acid (e.g., CCA results in proline, but CTA results in leucine).

ΧΧNonsense mutations, which create stop codons and can truncate the

protein (e.g., TAC makes tyrosine, while TAA signals “stop”). This means that a cell’s ribosome (the protein-making factory), will stop producing the protein before that protein has all of its amino acids. Consequently, this can affect the way the protein works.

ΧΧFrameshift mutations: Sometimes, the DNA copying process can insert or

delete one or more nucleotides, which means that the whole reading frame has shifted. Everything after the frame might now be nonsense, or the gene may simply be missing some amino acids.

ΧΧInsertions, as the name implies, add one or more extra nucleotides into the DNA.

ΧΧDeletions remove one or more nucleotides from the DNA.

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Figure 2.31: Insertions and deletions

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More significant mutations that can affect one or more entire genes can include:

ΧΧAmplifications or duplications, or more than one copy of genes or regions of a chromosome.

ΧΧDeletions of large parts of a chromosome, which results in losing some genes in those regions.

ΧΧBringing together previously separated chunks of DNA, which may mean

different genes come together to form new ones (known as fusion genes). An example of this is the unique seaweed-digesting bacterial enzyme in the gut bacteria of people with Japanese ancestry, which researchers speculate may originally have come from the genes of marine bacteria that live on seaweed. This “jump” of DNA from unicellular organisms (such as bacteria) to multicellular organisms (such as humans) is known as horizontal gene transfer.

ΧΧChromosomal translocations, which happen when unrelated chromosomes swap parts.

ΧΧTerminal and interstitial deletions, which happen when a piece of DNA is

removed from a single chromosome. Large deletions can be severe or even catastrophic to an organism. Prader-Willi Syndrome, which affects many aspects of normal growth, development, and metabolism, is a result of an interstitial deletion.

ΧΧChromosomal inversions, which “flip” the order of a segment of a chromosome. These mutations are usually benign.

ΧΧLoss of heterozygosity, or losing an allele from the (possibly different) pair of genes that you inherit from your parents, so that you only get one “regular” allele.

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Figure 2.32: Other mutations

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Sometimes mutations have observable effects, sometimes not. For instance:

ΧΧGenes can be partly or completely “de-activated”. These are known as loss-

of-function mutations, or inactivating mutations. For example, in androgen insensitivity syndrome (AIS), a mutation inactivates the androgen receptor and can cause chromosomally XY people to develop physically as female.

ΧΧThe effects of genes can get stronger. If we have extra copies of a gene in a genome (copy number variation, or CNV), there are more copies of the gene to be transcribed, and the effect can be more pronounced.

ΧΧGenes can change their function. For example, a mutation at codon 6 of

HBB, the β-globin gene (which changes the amino acid code from glutamic acid into valine) can mean that hemoglobin can’t carry as much oxygen. You may know of this mutation as sickle-cell anemia.

ΧΧSometimes mutations are helpful, perhaps giving us some kind of advantage in our environment. Sometimes they are harmful. Sometimes they have no apparent effect at all.

ΧΧMutations that gave us an advantage in one environment (such as the ability to store energy when food was scarce and required lots of effort to get) might not give us an advantage in a different environment (e.g., now that food is abundant, cheap, and energy-dense).

However, sometimes mutations kill an organism. These are known as lethal mutations. While there are some exceptions, if you’ve made it to adulthood, you’ve likely escaped most of the major lethal mutations.

Fixing DNA damage

Like the Quality Assurance process of factory production, our bodies carefully check for DNA damage and quality at various “checkpoints” in the cell cycle.

Our bodies can repair DNA damage in several ways:

GENETICS: THE UNIVERSE WITHIN

In fact, given how many components our genome has, it’s quite amazing how effective and efficient our genetic copying process is — as accurate as only one major error per every 1010 (or 10,000,000,000) nucleotides. Try finding a factory with that level of precision!

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If the “QA testers” spot damage, they (ideally) stop the “production line”, pause cell division, and fix things.

PRECISION NUTRITION

How does the body reach that high fidelity we mentioned earlier? By precisely spotting and quickly repairing some of the more common mutations.

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ΧΧMismatch repair (MMR) happens when a set of genes “notices” errors in DNA replication and recombination.

ΧΧWe know of 7 DNA MMR proteins (MLH1, MLH3, MSH2, MSH3, MSH6,

PMS1 and PMS2) that work in an orderly process to find and fix things.

ΧΧWhen MMR doesn’t happen correctly, we may get what is called

microsatellite instability (MSI), which means that small, variable, highly mutation-prone chunks of DNA (aka microsatellites) end up as part of our genetic material. MSI has been linked to many cancers.

ΧΧBase excision repair (BER) and nucleotide excision repair (NER) processes fix lesions and physical damage that can lead to DNA mis-pairing or breaks during replication. Deficiencies in BER / NER have been linked to cancer as well as neurodegeneration.

ΧΧNonhomologous end-joining (NHEJ) and homologous recombination

repair (HRR) are processes that repair double-strand lesions, or breaks. You can think of double-strand breaks as your DNA “ladder” being cut between the rails. These are some of the most dangerous types of DNA damage. One double-strand break is enough to kill a cell or destroy the integrity of its genome.

ΧΧTranslesion synthesis (TLS) DNA polymerases let unrepaired lesions get through the process of DNA replication, to be fixed later.

Sometimes, critical mutations occur not to particular genes that do things like make body structures, but to the genes involved in finding and fixing mistakes. So diseases of genetic origin occur from not having a strong enough “repair crew”. You could spend your life studying the details of genetics. (Heck, we had a hard time keeping this “basics” chapter under 10,000 words.)

Just get the general idea:

Sometimes mutations don’t affect the reproduction process (for instance, it’s something that only affects people over 60, or it gives you a funny-shaped nose but someone loves you anyway).

GENETICS: THE UNIVERSE WITHIN

Sometimes mutations take an organism out of the game before it can reproduce. Or, if the organism does manage to reproduce, the mutation isn’t passed to its offspring.

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Mutations and variations are complex.

PRECISION NUTRITION

But you don’t need to know all the details if you simply want to grasp the basics of genetic testing.

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Often, mutations and genetic variations can be inherited, and as a result, they can affect our health, nutrition, and fitness. Early in genetic research, scientists often wondered if a single gene could be responsible for particular diseases. For instance, could there be a “cancer gene”? We now know that most diseases result from combinations of factors. For instance, the BRCA1 and BRCA2 gene variants play a strong role in the development of breast and ovarian cancers. Many other genes do too, such as genes involved in DNA repair.

PRECISION NUTRITION

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Figure 2.33: Genes involved in breast cancer

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Different types of ovarian cancer



TYPE 1

TYPE 2

Mutations

 TEN, KRAS, BRAF, P PIK3CA, ERBB2, CTNNB1,  ARID1A, PPP2R1A, and microsatellite instability

TP53 BRCA1 BRCA2

Prevalence

About 30%

About 70%

Tumor type Serous, endometrioid, mucinous, and clear-cell tumors

Serous, mixed malignant mesodermal tumors carcinosarcomas, and undifferentiated tumors

Grade & progression Low and borderline, slow and often isolated to ovary

High and aggressive

These variations affect not only the origins of particular types of ovarian cancer, but also their locations, clinical progressions and outcomes. Diseases such as cancer are not just one “thing”. They are diverse phenomena that result from complex genetic and environmental interactions. We’ll be emphasizing this throughout the text:

There is almost never one single gene that inevitably leads to a given result.

PRECISION NUTRITION

As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors.

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Any genetic data we share are simply clues for further exploration.

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Epigenetics: Environment matters. Have you ever met identical twins that were different? Different personalities, different habits, maybe even different physical traits — despite being genetically the same? Studies have compared what happens when one identical twin exercises or eats nutritiously and the other one doesn’t. For example, one study compared 10 pairs of twins. One twin of each pair exercised regularly; the other twin was sedentary. The researchers found that the more active twins were leaner and metabolically healthier. They also had more grey matter in their brains than their genetically identical but inactive counterparts. Other studies have found similar results. Why aren’t two people with the same genetic blueprint exact copies of one another? The answer is epigenetics, the regulation of whether or not our genes are expressed. Our environment (such as what we eat, what’s around us, our exercise habits, what happened to us as children, and so forth) affects gene expression.

A full discussion of epigenetics is cool, but beyond the scope of this book. Just get the general ideas here:

ΧΧGenetic expression depends on more than just the genetic blueprint

understand what it means, or how it may shape our phenotype (for instance, our health, our risk of disease, our physical characteristics like height, and so forth).

Many other factors can affect how and whether specific genes are expressed.

GENETICS: THE UNIVERSE WITHIN

ΧΧJust knowing our genetic code (our genotype) is not enough to fully

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we received at conception.

PRECISION NUTRITION

There are many ways that this can happen, such as histone modification. You’ll remember that histones are proteins that make up part of the package of DNA, and can affect how parts of that DNA are activated or repressed.

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What’s up next Now that you have some fundamentals under your belt, we’ll explore how genetic tests work, and what they look for.

What does genetic testing involve? What are some of the general issues to think about while deciding if genetic testing is right for you?

GENETICS: THE UNIVERSE WITHIN

A brief introduction to genetics and what you’ll learn in this book.

Introduction to genetic testing

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Introduction

CHAPTER 3

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CHAPTER 1

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CHAPTER 3

Introduction to genetic testing What you’ll learn in this chapter In this chapter, we’ll cover:

ΧΧThe idea that biology is about probability rather than a given outcome; ΧΧHow genetic testing works; ΧΧWhy and how genetic testing might be helpful or unhelpful; ΧΧGuidelines for genetic testing; and PRECISION NUTRITION

ΧΧQuestions you can ask yourself when considering genetic testing.

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Biology is probability. Probability is prediction and potential, not perfection. Biology rarely gives us a definitive, simple answer to questions like: “What is the best diet?” or “What is the best exercise routine?” or “When exactly will I die, and how?” So any genetic testing service (along with any book, website, or coaching service) that promises to give you a perfect nutrition plan or workout regime, or exactly predict your health risks, is being misleading. (And scientifically dodgy.)

There will almost never be a “perfect solution” for anything related to biology. As we like to say around Precision Nutrition: “Progress, not perfection.” It’s almost impossible to control all the factors involved in a complex system.

Genetic information can tell us how we might change (if we wanted to), and what the payoff from that change might be.

For instance, let’s say that you know from genetic testing that you have a 70% probability of dying from Alzheimer’s disease by age 70. Now let’s say that there is also a medication available. This medication will bring your risk from 70% down to 30%. And it works in 90% of people.

GENETICS: THE UNIVERSE WITHIN

(Just to be clear, we’re definitely not there yet. It’s imagination time only.)

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Let’s imagine that based on your genetic tests, you knew exactly how likely it was that you would get a particular disease, and exactly how that disease might progress.

PRECISION NUTRITION

Plus, knowledge and development are incremental. We learn bit by bit. Change bit by bit. Grow bit by bit.

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Would you take it? Let’s think about that.

No medication: 70% chance of dying at 70 from a known disease.



Medication: 30% chance of dying at 70… but you may be in the 10% for whom it doesn’t work.

Many people would probably figure OK, I am probably more likely to be in the 90% of medication responders, and I like that 30% is much less of a chance than 70%, so let’s do it. What if the medication only brought your risk down to 60%? Or if it only worked in 30% of people? What then? Here’s another example. We know that many breast and ovarian cancers are related to mutations in the BRCA1 and/or BRCA2 genes. Data suggest that in healthy 30-year old carriers of these mutations, removing ovaries may add 0.2 to 1.8 years in life expectancy, and a mastectomy may add 0.6 to 2.1 years. Is that enough certainty to book surgery if you know you carry those mutations?

Of course, there’s no right answer.

The point is: Unless a mutation has taken you out of the game right off the bat, there’s almost never 100 – 100 – 100.

PRECISION NUTRITION

Some people might grab for any chance, and take the medication, or have surgery. Other people might say Eh, not good enough odds for me, and not take those chances.

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Sometimes we don’t even know with 50% certainty… or 10% certainty… or at all. At best, we can only make informed guesses.

GENETICS: THE UNIVERSE WITHIN

As in: We know with 100% certainty that in 100% of cases, this genetic risk will 100% lead to this outcome.

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Proceed with caution and critical thought. Now that you know from Chapter 2 the basics of how genes work, remember a few key ideas:

ΧΧGenetic interactions are vast and complex, and we don’t have most of them mapped.

ΧΧGenetics isn’t the whole story. Many physiological interactions aren’t genetic.

ΧΧThis domain of research is still very new. ΧΧMutations and alterations to our genetic code happen all the time. Sometimes they matter. Sometimes not.

ΧΧWe still can’t make strong predictions or recommendations about most things.

Keep these concepts in mind, and wear your “skeptical scientist” hat.

Genetic testing is easier than ever. What does that mean? In the last few decades, technologies that measure DNA and RNA have developed rapidly, becoming cheaper, faster, and more accessible.

ΧΧIn 2001, sequencing a full human genome (all the DNA in a human cell ΧΧIn 2011, it cost about $10,000 US. ΧΧIn 2016, two members of our PN team got their full genome sequenced for $1,000 US each.

The graphic below compares when various genetic sequencing technologies were introduced to how much analytic power those technologies have.

GENETICS: THE UNIVERSE WITHIN

For only $200 US, you can buy a 23andMe kit and get hundreds of thousands of your genetic variations tested without ever leaving your house. Just spit in a tube and mail it away for analysis — no fancy lab coat required.

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Still too much money?

PRECISION NUTRITION

nucleus) cost about $100 million US.

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The graphic below compares when various genetic sequencing technologies were introduced to how much analytic power those technologies have. When more material can pass through the process, accuracy goes up and costs go down. Researchers can now do high-fidelity sequencing on the entire human genome at a cost that even projects that survive on grants can afford. Note that the Y axis increases logarithmically (10, 100, 1,000, 10,000, etc.). What looks like a small step on this graph’s Y axis is actually a huge step forward: The Illumina HighSeq X Ten sequencer has 10,000 times the throughput as the Sequence Analyzer Illumina created just ten years before.

Figure 3.1: Improvements in gene sequencing with decreases in cost

This means we also need to consider how to deal with all the data we generate, which has to be compiled, converted, and stored. We must then analyze the results and balance any clinical advice or interpretation that we give.

ΧΧ“reading” a sample correctly; ΧΧanalyzing the sample; ΧΧstoring the data; and ΧΧinterpreting the data — deciding what it all means, and what to do next.

GENETICS: THE UNIVERSE WITHIN

ΧΧcollecting, transporting and storing a sample properly;

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This means that each stage of the genetic testing process is significant, such as:

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We can look at the genetic code with more precision and accuracy than ever before.

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Generating so much data means that we have to think about where to put it, how to understand it, and what to eventually do with it. We can think about it in terms of bioinformatics — combining technical domains like computer science, statistics, mathematics, and engineering to analyze and interpret the data we’ve collected. We can also think of it in terms of behavior change and genetic counseling — what we might do with any data or insight we gain.

We have to be careful about making too many assumptions about this process. There is a lot that we don’t yet know. A lot of things can go wrong with this complex process. This affects the quality of the data we get, and the conclusions that we can draw. For example:

ΧΧMany diseases or health conditions with a strong genetic basis are

rare or less common. Testing for these genetic variants may not apply to most people.

ΧΧMany diseases and health conditions are complex. There may be a genetic

contribution, but it may be from several interacting genes, or even regulatory pathways that don’t involve genes. And environmental or lifestyle choices may affect the outcome more anyway.

ΧΧOther outcomes, such as athletic performance, are also complex. For

ΧΧData are limited. There may not be a lot of research about a particular gene, or its relationship to health and function.

ΧΧWe don’t always know what to do about test results. In fact, research

suggests that just knowing what’s in our DNA rarely changes our behavior.

ΧΧGenetic testing services — perhaps driven by commercial interests, or

patient advocacy groups — are not always completely honest about what their tests can and cannot do. They may market their products as more useful or revealing than they really are.

To understand this better, let’s look more closely at the process of genetic testing.

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continue to evolve and change quickly.

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ΧΧThe technologies for testing, analyzing, and interpreting genetic materials

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instance, is there a “sprinter gene”? (Spoiler: No.) What if you have a certain set of genes that give you muscularity and power, but not the set of genes that give you the motivation to show up in the morning for a workout?

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What does clinical genetic testing involve? In general, clinical genetic tests:

ΧΧanalyze DNA for specific genetic variants (SNPs), that code for gene products such as enzymes or other proteins;

ΧΧlook for variations that are related to disease or health (and, increasingly, athletic capacity);

ΧΧfocus on a particular population (such as an ethnic group with a higher risk of a specific hereditary disease); and

ΧΧare aimed at producing information that patients can somehow use — for instance, to lower their risk of a disease, to choose the right medication, or adjust their nutritional regime.

Some genetic tests (such as 23andMe) also include ancestry and ethnic heritage. We’ll look at the importance of ancestry in Chapter 5. An assay is a method for determining the presence or quantity of a particular component, or a method to analyze or quantify a particular substance in a sample. A genetic test is a laboratory assay specifically for clinical testing. It identifies specific genotype(s) to diagnose a specific disease in a specific group of people for a specific purpose. Genetic testing is very targeted compared to a genetic assay, which may be scanned, or may be targeted.

A closed assay identifies beforehand what it’s seeking, such as a particular mutation or another variant. Genetic tests might be used for:

ΧΧcarrier testing (in other words, if you carry a gene variant that isn’t active in you, but that you may pass along to your offspring);

ΧΧprenatal testing, to identify particular conditions in fetuses; ΧΧnewborn screening, done soon after birth to look for potential diseases;

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ΧΧhealth risk predictions;

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ΧΧdisease diagnosis;

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An open-ended assay looks for anything of interest, like scanning a landscape to see what pops out.

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ΧΧpharmacogenomic testing, to explore how you might respond to a particular medication; or

ΧΧresearch — either for a specific purpose, or for general investigation. Increasingly, some people are also exploring genetic testing for nutritional needs and athletic performance. For instance, genetic tests can currently help us explore such traits as:

ΧΧhow quickly you process caffeine; ΧΧhow your body processes vitamin D; ΧΧhow much inflammation you’re likely to have (for instance, by testing for C-reactive protein, a marker of inflammation);

ΧΧhow well you may recover from exercise; or ΧΧwhat your body weight range is more likely to be (for instance, whether you are more likely to have a higher BMI).

Yet few of these are definitive or clear.

Test types You might think that a genetic test would look at the entire genome, but this is rarely the case. (We’ll talk more in upcoming chapters about studying entire genomes, and why most commercially-available tests don’t do it.)

ΧΧMolecular genetic tests look at the smallest “chunks” of DNA — perhaps a

ΧΧChromosomal genetic tests look at longer pieces of DNA, such as whole

chromosomes, to look for larger-scale genetic changes (such as an extra chromosome copy). An example of this might be testing for Down syndrome.

ΧΧGenetic sequencing involves “reading” a strand of DNA by looking at its

nucleotides, one by one. The first sequencing of a full genetic code was done on a simple virus (known as Phi X 174) in 1977; the human genome sequence (or at least, 90% of it) was published in 2001. A test that reads the entire genome is known as whole-genome sequencing.

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active that protein is. Here, the test doesn’t look at the DNA, but rather the protein that it might be coding for. By looking at differences in the proteins, testers can speculate about genetic variations. An example of this might be a c-reactive protein (CRP) immunoassay; CRP is a protein marker of inflammation.

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ΧΧBiochemical tests look at how much of a certain protein we have, or how

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single gene or short pieces of DNA — usually looking for a specific variation or mutation. An example of this might be testing for the cystic fibrosis variant or the BRCA1/2 mutations that are linked to breast and ovarian cancers.

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Again, commercial tests don’t usually sequence entire genomes. In fact, usually the opposite is true: Most commercially available genetic tests examine single-nucleotide polymorphisms (SNPs), a variation in a single nucleotide (e.g., having a cytosine, or C, where there’s normally an adenine, or A). You’ll remember from Chapter 2 that small substitutions like this are one way that we can get genetic variation.

SNPs and noncoding DNA The testing service 23andMe’s genotyping test covers about 600,000 SNPs of the potentially 3 billion SNPs that each person has… or just 0.02% of the genome. Even the most comprehensive genotyping services covers less than 0.15% of the genome. Of those SNPs, 98.6% are in noncoding DNA, which means they are stretches of DNA that aren’t transcribed into mRNA to make proteins. (This is what people used to call “junk DNA” until they realized that it wasn’t junk. Sure, some of it includes leftover odds and ends from our evolutionary history, but a lot of it has a purpose.) Noncoding DNA includes a lot of different things. Much like after family gettogethers when you end up with lots of leftovers and macaroni-salad-encrusted Tupperware, our genome contains lots of leftover bits from millions of years of our evolutionary process. For instance, we have:

ΧΧPseudogenes: genes that used to be active but aren’t any more. ΧΧProviruses: There is a class of viruses, known as retroviruses, that transcribe PRECISION NUTRITION

their genome and insert it into the genome of the cells they infect. This genetic material is known as a provirus. HIV is probably the best-known example of a retrovirus, but there are many others. Because the process by which this happens (known as reverse transcription) is relatively unstable and prone to error, many of these retroviral sequences are inactive. Inactivated retroviral sequences make up a surprisingly large proportion of our genome — about 10%.

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expression: They can “turn it up” (increase the genetic expression of a certain protein), “turn it down” (decrease expression), or even “turn it off” completely (prevent expression).

So, genetic testing services may test for functional SNPs, or they may test for SNPs found in noncoding regions.

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ΧΧRegulatory sequences: parts of DNA that act like a volume knob on gene

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On one hand, we can get a lot of useful information from SNPs, such as predictions about our ancestry, or well-known associations with certain heritable traits or diseases. On the other hand, using SNPs depends on having known associations, or identifying regions and points of common variation. We must already have identified and interpreted these SNPs — where they are, how common they are, and sometimes what they do, to what degree, and in which population. This is much like only getting information from books you’ve already read. We also can’t see copy number variation (again, how many copies of a particular DNA sequence you have) nor translocation mutations (where a gene moves from one chromosome to another, or from one part of a chromosome to another). Both of these can affect our phenotype, but simply knowing SNP markers won’t tell us anything about their effects. Thus, there are tradeoffs.

Genome-wide association studies (GWAS) While commercial tests rarely look at whole genomes, laboratory research that is looking for the relationship between particular gene variants and outcomes such as health problems or biological processes might do genome-wide association studies (GWAS). With most GWAS, participants are usually picked based on some characteristic that they share, such as having high blood pressure or osteoporosis. They are then compared to a control group without that characteristic to see if the test group shares any genetic variants, or somehow differs from the control group.

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Figure 3.2: Sample genome-wide association study model

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A GWAS is usually a broad scan.

ΧΧSometimes researchers are looking to confirm that Gene Variant X is, indeed, significant.

ΧΧOr maybe they’re looking to find novel loci — in other words, new SNPs or

other variants such as haplotypes (which we’ll look at in Chapter 5) that are associated with the characteristic.

ΧΧThey’re also looking to see whether the SNPs have predictive value: In

other words, does having this SNP make it significantly more or less likely that you will have a certain trait or other outcome? Or is the relationship between the SNP and the outcome just kinda random?

Often, the data that commercial genetic testing services use to look for certain SNPs come from laboratory GWAS that have already identified those SNPs as significant.

Commercial direct-to-consumer testing vs. experimental lab testing While we can now access many of the same scientific methods and tools that researchers might use in high-end experimental labs, there are a few key differences between them. Partial vs. full-genome testing At the time of writing this book, no one currently offers a commercial fullgenome testing service. (However, we did get our co-author Alaina’s genome sequenced in a private lab. More on that later.)

The only challenge is that research hasn’t uncovered all the different relationships between our genes and our genetic expression. The scientific community has only scratched the surface.

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It’s faster, cheaper, and easier to look at only the regions of interest, so you aren’t looking for a needle in a haystack. Instead, you already know where the needle is; you just need to know how long it is.

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It may seem like a commercial test is only offering you a half-assed version of a “real” full-genome test, but when you know what parts of the genome you need to look at, there’s no reason to sequence the entire genome.

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Right now, whole-genome sequencing is expensive. However, as the price drops and researchers make discoveries about the intricacies of the human genome, whole-genome sequencing will probably become more and more common. Eventually your whole-genome sequence will just be a normal part of your medical records.

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So:

ΧΧCommercially available testing services can tell us things about ourselves based on what research knows today. That’s great if we’re looking for a specific, well-researched genetic factor and belong to a population that’s been extensively studied.

ΧΧThese services are really only telling us a small fraction of all there is to

know about ourselves. That’s challenging if we’re looking for the best way to eat, or exercise, or live to 120.

What is the process of genetic testing? Although there are various types of genetic tests, here’s a general overview of how most of them work.

Step 1: Collect a sample. First, the test requires some type of sample material to analyze. In theory, this can be any type of biological material, but is most often:

ΧΧblood (though red blood cells would have to be removed); ΧΧbuccal cells (aka a swab of skin cells from the inside of the cheek); ΧΧamniotic fluid (the fluid that surrounds a fetus in the womb); or ΧΧhair (specifically, the cells from the follicle).

Step 2: Prepare the sample.

This means that first, the cells have to be ruptured, a process known as lysing (from the ancient Greek lusis, or loosening). Because cell walls are lipid-based, we have to use some kind of surfactant or detergent, much like dunking the cells in dish soap.

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Step 2A: Get stuff out of cells.

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Once the sample is collected and sent to the lab for analysis, we have to somehow get the DNA out of its container, the cell, and read it.

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Criminal investigations using DNA as evidence may also use “discarded DNA”, such as material left behind on coffee cups, straws, or cigarette butts.

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Some processes may also use a base such as sodium hydroxide (NaOH) along with the surfactant sodium dodecyl (lauryl) sulfate (SDS). (The combination of a base like NaOH and a surfactant is known as alkaline lysis, and it was first described in 1979 as a way to get DNA out of bacteria.) Once the DNA is out of the cell, testers break up proteins using proteases (protein-degrading enzymes) and break up RNA by using RNases (same idea). Without this step, the sample can degrade rapidly and cause sampling errors. Luckily, DNA is remarkably stable outside of the cell, much more than RNA or protein. This is why we can do DNA matching days or even years after a sample has been left. In fact, ancient DNA can be extracted and analyzed from samples thousands of years old.

Step 2B: Separate the solution to get what you want. Now that you’ve got a solution of cell crud, add a concentrated salt solution to make all the bits and chunks clump together. You need to pick apart the crud from the DNA, so the next step is centrifuging, which spins the mix in a wheel to separate things out (much like that spinning wheel ride at the county fair that separates you from your stomach contents). Solid chunks are flung to the bottom of the test sample tube, and the DNA is left behind, dissolved in the solution. Next, you want to tidy and purify the DNA from all the stuff you used to get it out of the cell. Do one of the following:

ΧΧUse ethanol (the same alcohol as in your martini) or isopropanol (aka rubbing

ΧΧUse phenol-chloroform: Denature proteins with phenol; whisk nucleic acids

away with chloroform. This works sort of like making a salad dressing with oil and vinegar.

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alcohol, definitely not in your martini) to come out of the solution (precipitate it). DNA won’t dissolve in this, so it clumps when you centrifuge it. If this clump is clear it’s pure DNA. If there’s still some non-DNA, the clump is white.

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sort of like dumping sawdust on spilt liquid. Most labs that have money use silica bound to a membrane. This is faster and it gives us clean DNA.

ΧΧUse a protease to break up and cleave off cellular and histone proteins bound to the DNA.

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ΧΧUse something solid, like silica, to which nucleic acids will bind. This works

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Step 2C: Amplify the DNA. Let’s say you’re trying to listen to music, but you’re somewhere with lots of background noise. So what do you do? You turn up your music — in other words, you amplify it. The same thing happens in DNA analysis — you often have to amplify it and make a lot more copies of the strand of DNA in order to make sure you get a good “signal” to test. This is most often done using the polymerase chain reaction process, or PCR. The upside of this process is that after several rounds of amplification, you have a nice big sample — more DNA than you know what to do with. The downside is that if there’s contamination, that’s amplified too. In tightly-controlled experimental studies, researchers control for contamination. The same may not be true of commercial tests.

Fun factoid! Legend has it that the inventor of PCR, the Nobel Prize-winning American biochemist Karey Mullis, got the idea for PCR while on an acid trip in 1983. Also, he believes he was visited by an extraterrestrial bioluminescent raccoon and denies anthropogenic climate change. Goes to show that winning a Nobel Prize and transforming molecular biology doesn’t mean you aren’t also a crackpot. PRECISION NUTRITION

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Step 3: Analysis Once you have a nice big pile of DNA, you can start to “read” (i.e., sequence) and analyze it. “Reading” DNA isn’t as simple as reading a book from start to finish. It’s more like this:

ΧΧTake a book. ΧΧOpen the book to a randomly-chosen page. ΧΧStart reading at a randomly-chosen word. ΧΧRead a few letters, or a word, or a phrase. Maybe a sentence. ΧΧClose the book. ΧΧOpen the book to another randomly-chosen page. ΧΧRead a few more randomly-chosen bits. ΧΧAnd so on. ΧΧDo that about a zillion times until you understand what the book says. In real-life terms, that means that sequencing creates a bunch of data that need to be put together into an order that makes sense. We do this with complex computing methods and algorithms, using bioinformatics techniques to identify, understand, and analyze the raw data.

Step 4: Interpretation

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Obviously, you could write a Ph.D. thesis on a single aspect of genetic testing alone.

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What do you need to know about this process?

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Finally, once you have your data, and it’s been read and analyzed, you can decide what your findings mean. For example, did your sample have the variant you’re looking for?

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But here are a few key points:

ΧΧThere are several types of tests, depending on what you want to find. ΧΧDifferent tests use — and look for — different amounts of genetic material. ΧΧThere are several methods for testing. ΧΧThere are several steps in the process, each with the potential for variation or mistakes.

ΧΧIt’s complicated.

How do you know if genetic testing is useful or valuable? Why test? Defining “useful”, “beneficial”, or “valuable” depends a lot on what we are seeking from a genetic test. For instance:

ΧΧA researcher may be interested in the test methods themselves, and how they advance basic science.

ΧΧA computational biologist may be interested in new forms of data analysis. ΧΧA clinician may want to explore associations between particular genetic ΧΧA family doctor may want to know how to advise their patients about medications, family planning, or lifestyle choices.

ΧΧA genealogist may be curious about ancestry.

ΧΧA sports scientist may want to know how to select or train athletes for optimal performance.

ΧΧA family lawyer settling a patrimony case (or a sleazy TV talk show host

doing an “OMG! Who’s Your Baby Daddy?!” episode) may want to know which kids are the genetic offspring of a particular parent.

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features of specific populations, their origins, or how a trait spread across a population.

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ΧΧAn evolutionary anthropologist may want to know about interesting

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variants and disease risk.

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For many people, genetic testing is a way to explore their risk of disease or health conditions. Yet there is much we still don’t know about genetic contributions to disease, and how we might use information about our DNA to either treat specific diseases, or improve our odds of staying healthy and fit.

In general, one definition of a genetic test is that it has a purpose. Researchers are trying to find something, even if they aren’t always exactly sure what. And there is some reason for them to look, such as advising people about reproduction or disease risk.

A cautionary tale about the science of testing In 2006, some scientists published their findings about a method for how to use gene expression profiles to personalize chemotherapy and other cancer drug regimes. When a second group of scientists tried to replicate these findings, they found that, as they said, “poor documentation hid many simple errors that undermined the approach.” This is a polite sciencey way of saying that the first team might have fibbed a bit. However, these problematic profiles were used anyway to direct patient therapy in clinical trials at Duke University in 2007. When the second group of scientists protested the poor science, trials were suspended in 2009, then re-started, and then finally ended in 2010. The original 2006 study was retracted.

Yet the scientific reality did not hold up under scrutiny. That isn’t to say that this couldn’t happen one day. It very likely could.

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The point is that the science is young, and all results must be reproduced reliably before we can have confidence in them, or use them to guide our decisions.

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The initial exploration held exciting promise: What if cancer patients could have their treatment individualized, based on their genetic profile?

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Establishing guidelines for genetic testing The researchers who protested the Duke study suggested that all genetic tests share the following:

ΧΧthe raw data, such as the reads produced by a sequencer; the called

genotyping data in the file you can download from 23andMe; or the images taken of gels;

Figure 3.3: A sample gel that Alaina ran in her lab

software and algorithms computed and analyzed the findings);

ΧΧevidence of the origin of the raw data so that labels could be checked; ΧΧwritten descriptions of all the steps in the analysis; and

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Originally, these were meant as guidelines for researchers who wanted to publish their work in scientific journals, but the scientists also suggested that anyone starting a clinical trial that used genetic data to guide treatment should meet these requirements.

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ΧΧhow the researchers planned to run the analysis.

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ΧΧthe code used to derive the results from the raw data (in other words, how

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In 2004, the Centers for Disease Control and Prevention in the United States established the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative to “establish and test a systematic, evidence-based process for evaluating genetic tests and other applications of genomic technology that are in transition from research to clinical and public health practice.” The EGAPP wanted to have a broad perspective on genetic testing. The group’s founding members included experts in:

ΧΧevidence-based review; ΧΧclinical practice; ΧΧdeveloping clinical guidelines; ΧΧpublic health; ΧΧlaboratory methods; ΧΧgenomics; ΧΧepidemiology; ΧΧeconomics; ΧΧethics; ΧΧpolicy; and ΧΧhealth technology assessment. EGAPP aimed to help healthcare practitioners and their patients understand some of the results of genetic tests.

ΧΧOnly a few had enough evidence to be considered clinically useful. ΧΧMany simply did not have enough evidence yet to help patients and their doctors make decisions about health risks and treatment.

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For instance, many tests could not be reproduced accurately; many clinical trials based on genetic data were called into question. Along with more complex problems like statistical analysis, researchers were making basic mistakes like mislabelling data.

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The group concluded, based on reviewing how genetic testing was being used, that “problems were more widespread and severe than we knew”.

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In 2010, the United States Institute of Medicine’s (IOM) Review of Omics-Based Tests for Predicting Patient Outcomes in Clinical Trials met to discuss the challenges of genetic testing.

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After reviewing many genetic tests, they concluded that:

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Clearly, a better system for scientific rigor was needed. This reminds us to always be critical and careful of grandiose claims for genetic testing. Genetic testing holds exciting promise, and may help us make incredible breakthroughs in human understanding. This promise must be tempered by thoughtful and careful review.

How can you decide whether a genetic test makes sense? If you’re not a scientist, it can be hard to figure out whether a particular genetic test is helpful. Here are two ways to think about the answer: a simple 4-question rubric from us, and a more complex checklist from the ACCE.

Keeping it simple: 4 questions to ask about genetic testing Is this particular test: 1 | Descriptive: Does it tell me something about the person being tested?

3 | Predictive: Does it allow me to predict some future challenge or occurrence, such as a disease or health risk later in life? 4 | Prescriptive: Does it tell me what to do next, or in the future?

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If you want to think more deeply about how good or useful a genetic test is, you can use the framework proposed by the ACCE (established by the Centers for Disease Control and Prevention in the United States).

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More complex: ACCE criteria for disease-related genetic testing

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2 | Diagnostic: Does it allow me (or a medical professional) to diagnose a problem or characteristic?

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ACCE takes its name from the four criteria for judging the value of a given genetic test:

ΧΧAnalytical validity: ΧΧHow accurately does a given test detect a gene variant or mutation? ΧΧHow reliable and repeatable is a given test? ΧΧAre test results “lab significant” or “real world significant”? In other words, if we find anything, does it mean anything?

ΧΧClinical validity: ΧΧWhat evidence supports the relationship between particular gene variants and risk of disease?

ΧΧWhich variants in particular are important? ΧΧHow great are those risks? ΧΧHow have those risks been estimated? ΧΧClinical utility: ΧΧHow useful are these findings for making informed judgments about one’s health and medical treatment?

ΧΧWhat should healthcare practitioners and patients do about genetic test results?

ΧΧEthical, social, and legal issues: ΧΧHow might privacy, social wellbeing, or legal status be affected by the ΧΧAre patients informed of all their rights and obligations beforehand? ΧΧWould prenatal screening be considered appropriate? ΧΧWho has access to these tests?

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results of a genetic test?

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To help explore these questions, the ACCE has produced a checklist that can help evaluate particular genetic tests, especially those aimed at finding relationships between gene variants and disease risk.

The ACCE checklist 1 | Test purpose and context a | What is the specific clinical disorder to be studied? b | What are the clinical findings defining this disorder? (In other words, what does the existing clinical evidence tell us about diagnosing this disorder, and its specific features?) c | What is the clinical setting in which the test is to be performed? d | What DNA test(s) are associated with this disorder? e | Does this test include preliminary screening questions? For instance, does the test also ask about family history, or look at overall medical and lifestyle factors? f | Is it a stand-alone test or is it one of a series of tests? g | If this test is part of a series, are all tests done at once, or are some tests done based on the results of previous tests? (e.g., if Test A finds something, then do Test B?) 2 | Analytic validity

b | How sensitive is the test analysis? How often is the test positive when a specific mutation is present? c | How specific is the test analysis? How often is the test negative when a specific mutation is not present?

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a | Is the test qualitative or quantitative? For instance, is it based on something self-reported or subjective, or on something numeric or objectively measurable?

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e | Have repeated measurements been made on specimens? f | What is the within- and between-laboratory precision? In other words, if the same lab were to run the tests twice, or different labs were to repeat

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d | Is the test method regularly monitored and evaluated for quality control by an external body? In other words, who and what tests the test?

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the tests, how close would the test results be? (We’ll look at this more in an upcoming section, when we look at what we found with sending samples to different labs.) g | If appropriate, how is confirmatory testing performed to resolve false positive results in a timely manner? h | What range of patient specimens have been tested? i | How often does the test give a useable result? Or fail to do so? j | How similar are results obtained in multiple laboratories using the same, or different technology? 3 | Clinical validity a | How sensitive is the test for clinical purposes? How often is the test positive when a specific disorder is present? b | How specific is the test for clinical purposes? How often is the test negative when a specific disorder is not present? c | Are there ways to resolve clinical false positives quickly? d | How often is this disorder found using this method? e | Has the test been adequately validated on all populations to which it may be offered? f | How many false positives or negatives does the test produce?

h | What are the genetic, environmental or other modifiers? In other words, how significant is the role of the genetic component compared to other factors, such as lifestyle choices?

b | How will the test results affect patient care? c | Are there other diagnostic tests available to confirm the results?

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a | How does the disease normally progress? Can we actually intervene in that process?

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4 | Clinical utility

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g | What are the genotype/phenotype relationships? In other words, does a genetic variant actually do anything noticeable? Can we see or measure that impact? If there’s a gene for a trait, does that trait show up a little, a lot, or not at all?

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d | What can be done about these results, if anything? For instance, are there medications, actions, or some other measurable benefit to knowing these genetic test results? e | If the patient can do something about the results, can they access that? For instance, can they get the medication that may help them, or make any applicable lifestyle changes? f | Is the test being offered to a socially vulnerable population? g | What quality assurance measures are in place? h | What are the results of pilot trials for these specific conditions or diseases? i | Are there known health risks that benefit from follow-up testing / intervention? j | Is testing affordable? k | Are there service providers able to help people understand or take action with the test results? l | Are there evidence-based educational materials that can help patients understand their results? m | Are there informed consent requirements? n | Are there methods for long term monitoring? o | How well does this program work over the long term, and how do we know?

a | When it comes to this particular test, do we need to think about: 1 | social stigmatization; 2 | discrimination;

b | Are there legal issues regarding consent, ownership of data and/or samples, patents, licensing, proprietary testing, obligation to disclose, or reporting requirements? c | What safeguards are in place to protect participants?

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4 | personal/family social issues?

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3 | privacy/confidentiality; and/or

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5 | Ethical, social, and legal issues

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Other questions to ask about genetic testing Genetic testing isn’t just about the science or clinical use. There are other factors to think about as well.

How strong or compelling are these results? Can these results be replicated reliably? (We’ll look at this in an upcoming chapter.) Are these results a “for sure”, a “maybe”, or “I dunno”? How high is the risk or probability of a particular outcome? Do you have a 0.5% higher chance of something? 5%? 50%? What happens if you find a gene variant, but don’t know what it does? Or don’t have any evidence-based strategies for what to do next?

How do these results matter in context? Are you just a hobbyist who is curious about what’s in your DNA? Are you someone who’s looking to start a family, and wondering what you might pass along to a child? Are you someone with a family history of a particular disease, and looking to explore your risk for that disease?

Speaking of that…

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Are you curious about your ethnic ancestry?

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Do these results align with your genetic and ethnic ancestry? What group was the genetic research done on? If you’re ethnically Hmong from Vietnam, or Quechua from Peru, how applicable are genetic studies done (for example) on British Europeans?

What environmental factors could affect these results? For instance, does a gene you carry only “turn on” if you’re exposed to cigarette smoke, or sunshine, or shift work?

What legal and regulatory factors are involved? Each jurisdiction may have different rules about what can be tested and shared. Who can access your genetic information, and for what purpose? For instance, can insurance companies review your genetic test results before deciding to insure you? What about employers, before hiring you?

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Where are you protected from genetic discrimination? Different regions have different legislation and regulation of genetic testing. In March 2017, Canada passed Bill S-201, the Genetic Non-Discrimination Act. The Act prevents people being pressured to undergo genetic testing in order to be eligible for goods or services (such as insurance); or from having to disclose their results. It prohibits employers from discriminating against workers on the basis of any genetic test results. It also amends the Canadian Human Rights Act to prohibit discrimination based on genetic characteristics. The Canadian Coalition for Genetic Fairness is made up of several advocacy groups, such as the Parkinson Society of Canada or Muscular Dystrophy Canada. They also promote genetic nondiscrimination. In the United States, the Genetic Information Nondiscrimination Act of 2008 (GINA) prohibits discrimination based on genetic information in health insurance and employment. Health insurance companies are not allowed to deny coverage to healthy people based solely on potential genetic risk, nor are employers allowed to discriminate based on genetic data. In the UK, the 2010 Equality Act prevents employers from discriminating based on genetic data. In the European Union countries, the 2010 Lisbon Treaty prohibits discrimination based on “genetic features”. PRECISION NUTRITION

The United Nations Educational, Scientific and Cultural Organization (UNESCO) adopted the Universal Declaration on the Human Genome and Human Rights in 2003 and International Declaration on Human Genetic Data in 2012, which includes provisions for preventing genetic discrimination and any use of genetic information that would contravene dignity, freedom, and human rights.

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What behavioral factors are involved? Once you get your test results, what could you do? What should you do? What are you willing to change, or not change? Who can help you understand all the information?

What moral and ethical questions are involved? Are you fully informed about the test, and what it involves, before you do it (a.k.a. “informed consent”)? Are you obligated to do anything once you know your results? For instance, if you’re young enough and considering having a family, should the results of genetic testing change your choice to reproduce? What if you discover some awkward truths about your genetic heritage or parentage? Can, and should, we patent genes?

Fun factoid!

We won’t always have the “right” answers to any of these questions.

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In one key case (Association for Molecular Pathology v. Myriad Genetics, No. 12-398 [569 U.S.June 13, 2013]), Judge Robert Sweet found that the claims on DNA molecules were invalid because “DNA represents the physical embodiment of biological information, distinct in its essential characteristics from any other chemical found in nature”.

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But we should be asking them.

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What’s up next: Exploring specific tests In this chapter, we’ve given you a broad background to consider. In the next chapter, we’ll look at specific types of tests, and what we discovered about them with our own testing practices.

What should you think about when considering particular genetic testing services? Which services did we choose, and why?

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An overview of how genetics works, and an introduction to some of the key ideas you’ll need to understand genetic testing and its implications.

Specific genetic testing services

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The basics of genetics

CHAPTER 4

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CHAPTER 2

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CHAPTER 4

Specific genetic testing services What you’ll learn in this chapter In this chapter, we’ll cover:

ΧΧWhat types of tests are available commercially? ΧΧHow scientifically credible are they? ΧΧHow well-replicated are they? (In other words, are they the same from lab to lab?)

ΧΧWhy did we choose particular tests? PRECISION NUTRITION

ΧΧWhat does this mean for you as a consumer?

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But first:

Here are some things to keep in mind. Some quick refreshers and reminders:

ΧΧOne gene can affect many outcomes and processes. It’s not usually a simple one-to-one ratio where Gene X completely controls Process Y.

ΧΧMany links between specific genes or SNPs are only associations, not causes.

We can’t say right now that having a certain genetic variation necessarily makes something happen. We can only say that in this particular population studied, we can see that there is maybe something happening with a particular gene or SNP. That’s all.

ΧΧGenes are not destiny. Outside of some highly genetically determined diseases (such as Huntington’s disease, cystic fibrosis or Down syndrome), we can, to some degree, affect the outcome of our biological programming. Even if one particular gene determines 70% of an outcome (which is a lot, relatively speaking), we may be able to affect the other 30%. Many genes and SNPs we’ll look at have much less of a role.

ΧΧWe’re usually talking about possibilities and probabilities.

Rarely can we know for sure that something will happen… or even what that something is. This might be disconcerting and hard to understand, so celebrate this feeling of ambiguity. It runs throughout biology.

ΧΧThe research is new, often un-reproduced, and unreplicated.

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You’ll see words like maybe, could be, sometimes, risk, percentages, odds, likely.

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We can’t say for sure based on a single study of fifty people of Finnish, Fijian, or Filipino descent whether that study has any relevance to you — even if you’re Finnish, Fijian, or Filipino too.

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4 questions to ask about genetic testing We also suggest you review our 4 simple questions to ask about genetic testing: Is a particular test: 1 | Descriptive: Does it tell me something about the person being tested? 2 | Diagnostic: Does it allow me (or a medical professional) to diagnose a problem or characteristic? 3 | Predictive: Does it allow me to predict some future challenge or occurrence, such as a disease or health risk later in life? 4 | Prescriptive: Does it tell me what to do next, or in the future? Keep these points and questions in mind as you read through this chapter, and the rest of the book.

Genetic testing services: What’s available? There are many genetic testing services available, which have different purposes, such as:

ΧΧspecific disease risks (such as cancer); may not want to pass on to your offspring);

ΧΧancestry and migration patterns; ΧΧpaternity and relatives (e.g., whether two people are related, or screening for donor tissue matches);

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ΧΧcarrier status (in other words, whether you’re carrying something that you

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ΧΧnewborn health; ΧΧdrug response; or ΧΧindividualized health, nutrition, and fitness recommendations.

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ΧΧspecific traits;

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A study of 246 direct-to-consumer genetic testing services found that while nutrigenetic tests were popular, the pressing question of “What should I eat?” was outweighed by “Is my kid mine?” Some genetic testing services even offered a discreet “surreptitious” option, as in, “Steal a few bits of someone’s body and send it to us; we’ll tell you whether you’re about to have an awkward family conversation.”

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Figure 4.1: Specific reasons for testing as a percentage of all commercial services offered

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A health, nutrition, and fitness focus Of course, we’re interested in general health, nutrition, and fitness or athletic performance, so that’s where we focused our attention. We looked for services that tested genetic markers known to be related to particular traits, such as: Metabolism

ΧΧBlood sugar and insulin ΧΧBlood lipids and lipoproteins (HDL, LDL, etc.) ΧΧResting metabolism ΧΧOther factors (such as thyroid health) that can affect metabolism ΧΧBody weight, size, and fatness (or leanness) Food and nutrition

ΧΧTaste preferences and sensitivity ΧΧFood intolerances ΧΧNutrient processing (e.g., vitamins, salt, caffeine) Exercise and athletics

ΧΧSprint-type vs endurance-type muscle fibers ΧΧMuscle performance

ΧΧRecovery from exercise We’ll cover these in more detail in upcoming chapters.

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ΧΧResponse to exercise

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What else were we looking for? Along with a focus on general health, nutrition, and fitness, we looked for services that fulfilled a few other criteria:

Scientific credibility What claims were the companies making? Research on direct-to-consumer tests has shown that many companies are making claims about their data that are not supported by scientific evidence. For instance, they may claim to be able:

ΧΧto exactly predict your athletic talent (or your child’s); ΧΧto tell you exactly what you should eat; ΧΧto tell you exactly how you should exercise; or ΧΧto tell you exactly what choices you are likely to make (for instance, whether you’re likely to give in to sugar cravings).

Unfortunately, none of these claims are true. (Yet.) A 2015 article in the British Medical Journal examined 39 direct-to-consumer testing services, and found that:

ΧΧOver half (21 of the 39) companies didn’t actually identify the specific DNA sequence variants they tested.

ΧΧ16 of 18 tested the ACTN3 R577X polymorphism (which we’ll look at in Chapter 10).

ΧΧ11 of 18 tested for the angiotensin I converting enzyme 1 (ACE) I/D polymorphism.

ΧΧThe number of variants tested overall was small. Most companies tested around 6. Some tested only 1, others up to 27.

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research, they haven’t yet been conclusively shown to make a major difference in strength, muscularity, or athletic performance — certainly not compared to environmental influences like training.

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ΧΧThough ACTN3 and ACE polymorphisms are promising areas of

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ΧΧOf the 18 companies that did identify what genetic markers they used:

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When we consider that we have 3 billion base pairs of DNA, you can imagine that this is still a pretty small sample for drawing potentially big conclusions. Another large-scale meta-analysis study reviewed research from nearly 1,200 studies on 38 genes tested by nutrigenomics companies. They concluded that:

ΧΧMost studies couldn’t predict any useful relationship between particular genes of interest.

ΧΧWhen there seemed to be a link, the studies or sample sizes were too small to make broad recommendations.

Finally, what about the data used by genetic testing itself? What if, for instance, a particular study finds an association between SNP X and Nutrient Intake Y… but the study is based on something like people’s recall of what they ate — a method known to be often so inaccurate that it’s potentially useless? If a genetic testing service bases their interpretation on this study, there’s a chance that they might not be making valid scientific claims. This doesn’t mean, obviously, that nutrigenomics or other related types of genetic testing services are useless. Even the skeptical meta-analysis authors called genetic testing a “highly promising tool for precision medicine”. We just need to understand what claims are substantiated, and which ones aren’t. (Yet.) So we looked for genetic testing services whose claims:

ΧΧwere reasonable, relatively conservative, and realistic; and ΧΧincluded a discussion of both limitations and advantages of their testing methods and findings.

To ensure that high-quality, standardized scientific practices are followed, most countries somehow regulate laboratory testing.

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What processes did each lab follow?

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Quality control

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ΧΧwere supported by the most current scientific evidence;

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This includes ensuring:

ΧΧtechnical personnel are competent and qualified; ΧΧexperimental processes are recognized as legitimate and correct; ΧΧequipment is calibrated and accurate; and ΧΧlaboratories are impartial and independent. For instance:

ΧΧIn the United States, all labs that test human specimens for health

assessment or to diagnose, prevent, or treat disease must abide by federal Clinical Laboratory Improvement Amendments (CLIA) regulations.

ΧΧIn Canada, the Standards Council of Canada gives accreditation to labs that meet International Standards Organization (ISO) requirements for medical labs and analysis.

ΧΧThe International Laboratory Accreditation Cooperation is an umbrella

organization that covers other international lab certifying bodies such as EA in the European Union, APLAC in Asia-Pacific countries, IAAC in the Americas, AFRAC in Africa, SADCA in Southern Africa, and ARAC in the Arab region.

So we looked for genetic testing services:

ΧΧwho had a legitimate scientific staff; ΧΧthat use certified/accredited labs, or operate certified labs themselves; and ΧΧwho were involved in or had produced peer-reviewed research.

If we sent the same sample to two different labs, would they come up with similar results?

ΧΧWould the same samples sent to different commercial labs come back with similar results?

ΧΧIf we sent two of the same sample to the same lab, would we get the same results?

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We wanted to do our own review of the commercial services we used. So we checked:

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Professional laboratories produce extremely reliable results — over 99.9% accuracy. They are also heavily scrutinized and monitored by industry and scientific agencies, whereas commercial labs are not.

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Reliability

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The answers: Yes, and yes. The results we got were a match with over 99.9% accuracy. Our experience closely matches other studies that compared the largest directto-consumer testing services (such as 23andMe, deCODE, and the now-defunct Navigenics) to one another, and found that lab-to-lab correlation (in other words, how closely each lab’s results matched the others’) was 99.6 to 99.7%, though accuracy did vary somewhat for specific SNPs or disease risks. In particular, predictions were less reliable when labs used genetic markers with only weak associations (such as, “Well, in some people, some of the time, given some environmental conditions, this SNP may be linked to a 0.1% higher chance of X”). Predictions were more reliable with strong associations, like “Yep, you have OCTFN1, the gene that always gives people ‘octopus fingers’ 100% of the time.”

Fun factoid! “Octopus finger” is not a thing. Do not be alarmed. Also, do not hate on octopodes, who are simply “differently digitized”.

So we looked for genetic testing services:

ΧΧwhose results were reliable and repeatable; and ΧΧwho distinguished between stronger and weaker genetic markers and

Vested interests Are the testing services selling something else?

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These other services may indeed be helpful, but that help didn’t actually come from knowing your genetic information.

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In many cases, genetic testing services may offer extended services (such as an app, “individualized” meal planning or tracking of other indicators like physiological performance) that actually have nothing to do with genetic data.

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associations.

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For instance, while tracking your sleep habits or food intake is very useful and can help you make some important decisions, that useful data is not based on your “sleep DNA” or “menu DNA”. It’s just plain old daily-life observation that anyone can do. (Back in the old days, we just called that kind of careful observation and outcome-based decision making “coaching”. Harrumph.) Other services may sell supplements once they have determined your “genetic requirement” for extra vitamins, minerals, antioxidants, etc. At the time of writing, there are very, very few known, evidence-based, genetic requirements for specific supplements. (You may benefit from supplements for other reasons, but likely not because of any particular SNP that you have.) So we looked for genetic testing services that:

ΧΧwere primarily testing, analysis, and/or interpretation services; and ΧΧdid not sell additional products, unless those products and services were clearly relevant to the genetic data (such as genetic counseling).

Testing methods and technologies How were the samples tested and analyzed? There are several technologies and methods that can be used for genetic testing.

ΧΧSNP genotyping arrays are fast and cheap. They look at a series of

ΧΧSequencing is building a list of actual nucleotides, in order. While a

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SNP array might be able to tell you if you have a nucleotide at a certain position, sequencing can tell you the actual genetic code around that position. SNPs can tell you whether it’s A or T; sequencing can tell you that it’s AACCTAATTAGA or TACCTAATTAGA, or even that it’s AACCTACTACTAATTAGA. An intrepid researcher can still do sequencing by hand, but it is a tedious and laborious process, sweated over by graduate students and postdocs toiling in the basement. These days, most sequencing is done by high-throughput machines that perform the chemical processes of sequencing, automated signal processing to transform chemical information to digital and computers to turn the vast amounts of raw data into usable information.

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predetermined locations on the genome (usually hundreds of thousands to millions) to look for SNP variations. SNP genotyping works well if you know which SNPs you are looking for, or want to search for novel associations among well-known regions. It’s less useful when the variations are not SNPs, or when you are looking for variations that aren’t well characterized or understood.

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ΧΧExome sequencing provides the genetic code for the exome (every part

of the genome that codes for a part of a protein), which is about 1% of the total human genome. If researchers are specifically interested in the protein-coding regions of the genome, exome sequencing gives the most accurate and cost-effective data. It doesn’t include the DNA regions outside of exomes, which have important regulatory features.

ΧΧWhole-genome sequencing can give researchers a view of the entire

genome. The entire genome is sequenced, regardless of whether a given DNA region codes for a gene, provides a regulatory function, or just happens to be a retroviral genome that lodged itself in one of our ancestors and got cozy.

If researchers need a detailed, accurate view of a specific set of targeted stretches of DNA, they might use amplicon sequencing. In this technique, technicians use the polymerase chain reaction (PCR) to make billions and billions of copies of a previously-identified stretch of DNA, and sequence these copies (known as amplicons). Sequencing PCR products gives a very high-fidelity view of the genetic code, but is of very limited use if researchers don’t know what they are looking for. There are other preparation techniques that allow researchers to target specific functions or regions of DNA. For example, chromatin immunoprecipitation (ChIP) targets DNA-binding proteins so you are only sequencing regions of DNA that are bound to chromatin. All sequencing technologies will have some bias and error. Biology and chemistry are inherently chaotic processes, so nothing is perfect.

So we looked for genetic testing services that:

ΧΧexplained their process and method, including what they tested and how; and

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But of course, we want to get as close as possible to that magical 100% accuracy.

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industry standards.

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ΧΧused testing methods (such as the Illumina chip) that are widely accepted as

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Analysis and interpretation How valid is the analysis, and how useful is the interpretation of the results? An analysis that says, “Here is a specific SNP that you have, here’s what we know about it, and here’s what it might say about you if you’re from X Population, but we’re not totally sure just yet so check back in 10 years” is probably accurate. An analysis that says, “BEHOLD YOUR GENES!! BROCCOLI IS DEAD TO YOU NOW!!”… Hmm, maybe not so valid. So we looked for genetic testing services that:

ΧΧoffered cautious, careful, conservative analyses and presentation of findings; and

ΧΧsupported those findings with specific citations of peer-reviewed studies.

Risks and probabilities in context How well does the test explain absolute and relative risk? As we learned in the last chapter, biology is probability. Probability is almost never perfection. Risks are possibilities, not destinies. Thus, we want genetic testing services that give us our test results in context. If we have, for example, a 1.5 higher lifetime risk of Disease X, what does that really mean?

ΧΧwhat “lifetime risk” means: Will we likely get this disease at age 20? 50? 99? ΧΧhow prevalent this disease is in our population: Is it a serious health threat, or a rare condition?

Let’s say there’s a disease known as Crepitus Umbilicus. It’s terrible, really; people’s bellybuttons spontaneously explode and shoot through their spine. It’s an awful way to go out — it happened to your dad while he was peacefully watching a hockey game on TV one day.

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Disease X by doing Behavior Y? For instance, if we have a higher genetic risk of lung cancer, can we avoid that cancer by not smoking?

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ΧΧwhat other factors besides this genetic variant are involved: Can we escape

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We have to know:

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So you’re worried: Will your bellybutton explode too? You get genetic testing to see if you carry the deadly CRUMB gene variant. Now let’s say that Crepitus Umbilicus affects, for example, 50% of the population. That’s the absolute risk — in other words, everyone’s risk all lumped together. That means 1 in 2 people will likely, at some point, die by exploding bellybutton. Let’s say you have a 1.5 higher chance of getting that disease. That’s your relative risk — in other words, how your particular probability stacks up against everyone else. You might also want to know your odds ratio, which is the relationship between an exposure and an outcome. An odds ratio (OR) tells you how likely it is that Outcome X will happen if you’re exposed to Condition Y — for instance, how likely it is that you’ll get this disease given your genetic makeup. With an absolute risk of 50%, a 1.5 higher chance of getting it is a strong possibility for you, and you should probably consider taking steps to change your odds, such as surgically removing your bellybutton before it blows up. (Don’t worry, there are many very realistic bellybutton prostheses these days.) But if Crepitus Umbilicus affects only 0.00000005% of the population (in other words, 1 in 2,000,000 people rather than 1 in 2), a 1.5 higher chance of getting it… eh, probably don’t worry too much. Just pack a little flame retardant foam in your navel before you go to sleep each night, and you’ll likely be just fine. So we looked for genetic testing services that:

ΧΧgave us probabilities based on known epidemiological data;

ΧΧput results in context as much as possible by telling us the absolute risk as well as the relative risk.

Support for next steps

Again, research suggests that simply knowing about your DNA — while very cool — may not change your behavior. In some cases, people may feel as though they have less control over their choices once they know their genetic test results.

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If so, how? And how appropriate are the recommendations?

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Does this genetic testing service help me understand what to do next?

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ΧΧwere clear about the limitations of these data and risk predictions; and

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It might not be within the testing service’s scope of practice to make specific recommendations about what to do next, but were they able to help us identify where else we might look for guidance? So we looked for genetic testing services that:

ΧΧoffered relatively impartial interpretations and support that might help people take realistic, productive next steps.

Choosing testing services For general health, nutrition, and fitness information, there are many services available. For instance:

ΧΧ23andMe was one of the first on the commercial testing scene, and offers

a wide array of genetic data ranging from ancestry, to health risks, to traits. You can spend days deep-diving into all the scientific research and analysis that they’ve collected. https://www.23andme.com/

ΧΧDNAFit tests about two dozen genes that are related to metabolic health, nutrition, and athletic performance, and then offers comprehensive recommendations for what to do with the test results. https://www.dnafit.com/

ΧΧOrig3n has a variety of kits available that test sets of variants for fitness and performance. https://orig3n.com/

ΧΧHabit offers genetic testing, personalized nutrition prescriptions, and even

ΧΧLifeGenetics is heavily focused on weight loss, offering menu planning based on test results. http://lifegenetics.net/

ΧΧNutrigenomix, based out of the University of Toronto, uses a panel of 45

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genetic markers to explore factors related to weight management and body composition, nutrient metabolism, eating habits, cardiometabolic health, food intolerances, and physical activity. https://www.nutrigenomix.com/

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meal delivery based on your “individualized nutrition plan”. https://habit.com/

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Other services will analyze existing data (for instance, from 23andMe) in ways that the original labs might not. For instance:

ΧΧGenetic Genie explores genetic markers linked to detoxification and methylation. It’s also free. http://geneticgenie.org/

ΧΧAthletigen doesn’t do their own testing (they send it to a lab), but they

offer analysis and interpretation of particular genetic indicators of athletic performance. https://athletigen.com/

What we chose and why We’d love to say that we’re actually shills for Big Genome and that they gave us a bunch of cool swag like personal polymerase shaker cups, Happy the Haplotype stuffed toys, or a protruding-eyebrow-ridge piercing for our co-author Krista, who scores big with the highest percentage of Neanderthal DNA. But no. In most cases, we don’t know the testing services, and they don’t know us. (Well, they know us, kinda… since DNA is us. But they don’t usually know us, like “Hey what’s up how are the kids and your sports team?” know us.) We chose three services to explore in particular for this book: 23AndMe, GeneByGene, and Nutrigenomix. Here’s why.

ΧΧThey’re relatively cheap. Hey, we ain’t made of money. At time of writing, for instance, 23andMe cost $200 US.

get your data. (Co-authors Helen and Alaina also took and prepped blood samples for GeneByGene, who offered us the ability to test with both blood samples and DNA we prepped ourselves in PN’s lab.)

ΧΧThey’re relatively accessible. Anyone who can afford it can do it.

23andMe data file, for instance, you can link it to other services (such as Athletigen or Genetic Genie) who will run different analyses on it.

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ΧΧThey can connect to other services and analysis. Once you have your

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You don’t need to be a healthcare professional or a researcher to get access to your genetic data. The basic Nutrigenomix kits are used in undergraduate courses.

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ΧΧThey’re easily available. Spit in a tube, mail it off. A few weeks later, you

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ΧΧThey’re relatively accurate. For instance, 23andMe uses the Illumina

HumanOmniExpress-24 format chip (considered an industry standard) in a CLIA-certified, CAP-accredited laboratory in the United States. Nutrigenomix uses a similar process in a top university laboratory in Canada, and clinicallyfocused GeneByGene has an excellent facility in Texas.

ΧΧ23andMe and Nutrigenomix analyze and interpret the data for you.

(GeneByGene provided us only raw data that we had to analyze, which makes sense in a clinical setting.)

ΧΧThey focus on what we’re interested in as a health, fitness, and nutrition company. We want to know about stuff like which factors will affect key physiological processes, our movement, our health risks, and how our bodies process nutrients. If you’re reading this, you likely have the same interests for yourself (or perhaps for your clients). Other services, such as National Geographic’s Genographic Project and Ancestry.com‘s DNA service are also cool, but focus more on ancestry and migration patterns.

What does this mean for you? Be a critical consumer. Research shows that the average person expects genetic testing results to be much more helpful or directive than they really are.

So, if this area interests you, you may want to brush up on your math skills.

Consider your reasons for genetic testing.

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Your goals and reasons for testing will probably affect what test types you choose, and how you view the test results.

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A survey that asked people why they tested their DNA found that most people wanted to improve their health or learn more about their ancestry. But they were also curious, thought it would be fun, and/or simply wanted to help advance the cause of science.

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Research also shows that people are better at correctly interpreting their results when they are numerate — that is, if they understand things like percentages, odds and risks, and how to understand number-based data like “This SNP increases your odds of Health Condition X by 1.16” or “This SNP is associated with Health Condition Y (p A) ate more complex, higher-fiber carbs, they were leaner; when they ate fewer complex carbs, they were more likely to be obese. Interestingly, at least in this study, simple sugars or total carbohydrates didn’t seem to have any relationship to body fatness, nor did other PLIN variants. Other studies have confirmed that PLIN variants predict both metabolic syndrome and weight loss. Similar results with some PLIN variants and insulin resistance were found in a Singaporean population made up of Chinese, Malay, and South Asians. These variants of the PLIN genes may be old ones, present before human populations diverged. The association between specific PLIN gene variants and fatness also seemed related to fat intake, particularly saturated fats — when people with two copies of a PLIN variant consumed carbohydrates and saturated fats, they were significantly more likely to have insulin resistance, a precursor to Type 2 diabetes. Other genes related to obesity susceptibility, such as FAIM2, FLJ35779, FTO, LRRN6C, RBJ, and SEC16B also seem to interact with dietary carbohydrates to increase BMI.

What this means for you Studies on human diets are generally self-reported (rather than carefully controlled, like in lab animals). Ways of measuring dietary responses also vary. So we have to be careful about how we interpret results from any single study.

ΧΧNot all bodies respond the same way to the same diet. Your friend may

thrive on a low-carb, high-fat diet (or a high-carb, low-fat diet), whereas you may find yourself feeling and performing worse when you try the same thing.

ΧΧGenetic testing can give us some clues, but not a detailed prescription,

for your “best diet”. We still don’t completely understand the complex relationship between genetic variants and metabolic health. Genetic testing may suggest particular dietary strategies that might help you make wise dietary choices for your physiological needs.

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time. It’s important to test, observe, and assess (based on evidence) what nutrition protocols work best for your unique body.

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ΧΧThere’s no one-size-fits-all diet plan that will work for everyone, all the

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Nevertheless, the findings suggest:

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ΧΧUnderstanding the impact of genetics on metabolism helps you make

informed decisions about your diet. At the very least, genetic testing may help explain why a particular diet may affect your health or physical performance. At best, you may find a diet that matches your “metabolic strengths” (i.e., what your body prefers).

ΧΧProcessed sugars seem to cause the most metabolic problems, regardless of specific genetic variations.

Fasting glucose predictions What predicts our risk of Type 2 diabetes (T2D)? We know that T2D is correlated with many physiological and lifestyle factors, such as:

ΧΧhaving more body fat (and less lean mass); ΧΧbeing sedentary; and ΧΧeating a diet with lots of processed foods. We also know that adipose (fat) tissue is a hormonally active tissue. Early studies on Type 2 diabetes (T2D) often used people with more body fat, who were more likely to develop T2D. It wasn’t always clear whether the progression of T2D was due to environmental effects (for instance, a highsugar diet), having a certain amount of body fat, or an underlying genetic predisposition (in other words, what someone was born with).

One way to test for insulin resistance and prediabetes is with fasting glucose: measuring blood sugar levels after a person hasn’t eaten for several hours.

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Alhough research suggests that genetic variants linked to higher fasting glucose don’t always correlate neatly with T2D risk, there’s a lot of overlap and fasting glucose is still a pretty good predictor.

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Later studies looked at relatively leaner people to account for the environmental component of T2D, or for the role that adipose tissue gained in later life might play.

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G6PC2 23andMe looks at a SNP known as rs560887, which is associated with fasting blood glucose levels in European populations. This SNP appears in the G6PC2 gene, which codes for glucose-6-phosphatase catalytic subunit-related protein (also known as IGRP), a protein that is expressed in islet cells of the pancreas. This SNP is associated with the function of pancreatic beta cells, which store and release insulin, as well as C-peptide and amylin (which helps control how quickly glucose is released into the bloodstream). In the study used by 23andMe, each T at rs560887 lowered subjects’ fasting plasma glucose level by 0.06 mmol/L (1 mg/dl).

Allele

Average fasting glucose levels

CC

5.18 mmol/L (about 93 mg/dl)

CT

5.12 mmol/L (92 mg/dl)

TT

5.06 mmol/L (91 mg/dl)

For reference, a fasting blood glucose level lower than 5.6 mmol/L is considered normal, while anything over that is considered prediabetic.

We had some blood tests lying around, so we looked for correlations. One person from of our PN sample had just been diagnosed with prediabetes. Yet according to the G6PC2 SNP, with a CC profile, they should have had lower than average blood sugar.

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What we found in our sample

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Not surprisingly in our health-and-fitness-oriented population, many CT people had normal or lower than average fasting blood glucose. This suggests that lifestyle choices play a bigger part than a single SNP.

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We also had 2 TTs, who were predicted to have higher than average blood sugar but whom, to date, seem healthy.

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What this means for you

ΧΧBlood glucose is an important health indicator. Don’t rely only on a

genetic test. At best, a genetic test can only predict possible risk. It can’t tell you what your blood glucose actually looks like. While blood glucose normally rises and falls as we eat and fast between meals, chronically elevated blood sugar can tell you that there is an underlying health problem.

ΧΧGet regular bloodwork done. Generally, by the time fasting glucose is

affected, people may be well on their way to metabolic syndrome. So having your fasting glucose tested, along with your blood lipids (see below) as part of your regular medical checkup (for instance, annually) is a good idea, especially as you age.

ΧΧIf you are a do-it-yourself kind of person, you can buy a home glucose

monitor and test your glucose throughout the day, including after meals. Postprandial — “after meals” — blood sugar levels will give you a better idea, sooner, of what your blood glucose is up to, compared to fasting glucose.

ΧΧIf you’d like to improve your overall wellness, see our strategies for healthy metabolism in Chapter 12.

Blood lipids and lipoproteins Once we eat and digest foods containing dietary fats, these fats (aka lipids) are packaged into various formats (such as triglycerides) to be transported around the body and used.

As with glucose, it’s normal to have some circulating lipids and lipoproteins, but we don’t want too many, too often.

On one level, that’s a good question.

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Everyone has that proverbial great-aunt who lived to be 103 and swore by her daily whiskey and buttered bacon sandwich. And as we witness this fiercely unrepentant and apparently immortal boozing, buttering, and bacon-ing, we ask ourselves, Why am I eating all this damn healthy food anyway?

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Lipid and lipoprotein levels are strongly influenced by how much body fat we have along with our environment and our choices, such as our nutrition, our activity, smoking or drinking, or other medications. They can also be influenced by genetic factors.

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Much like blood glucose, levels of these blood triglycerides and lipoproteins (proteins that transport lipids) are important indicators of metabolic health. (We’ll look more closely at lipids, triglycerides, and lipoproteins below.)

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Some people seem able to consume “unhealthy” food, drink like a fish, smoke a pack of cigarettes a day, and make it to triple digits completely unfazed. Other people seem to do everything “right” and get taken out by a heart attack or some other metabolic disease far too early. Frankly, it seems deeply unfair sometimes. And, indeed, it may be unfair, in the sense that some people may be naturally better at managing their blood lipids than others. This relative advantage may, in part, be due to genetic factors.

The genetics of lipids To date, we know of about 160 genetic variants associated with lipid levels. Of course, not all are equally important or strongly linked. Some operate mainly in particular processes (such as regulating the expression of other genes) or particular tissues (such as the liver). We still don’t fully know how all genetic variants interact with blood lipids and other relevant biomarkers.

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Diagram adapted from Willer CJ, Schmidt EM, Sengupta S, et al. Discovery and Refinement of Loci Associated with Lipid Levels. Nature Genetics. 2013;45(11):1274-1283. doi:10.1038/ng.2797.

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Figure 6.3: Genes involved in lipids and lipoproteins.

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Lipoproteins and the basic blood lipid panel If you go to your doctor and get a “cholesterol test” done, it’s helpful to understand what this really means. Cholesterol is a waxy lipid (imagine something like lard). We make cholesterol in our liver, but it’s also in our food. We use cholesterol to make many important molecules that our bodies use, including our sex hormones. Triglycerides are molecules of fat made of three fatty acids hooked to a glycerol backbone. When we digest fat, our bodies package fatty acids into this format, and transport them through the bloodstream to be stored in adipose cells. Lipoproteins are proteins that transport lipids. Oil and water don’t mix, and neither do lipids and blood. Fats have to hitch a ride on lipoproteins, like a bunch of passengers on a little inner tube floating down a river. Lipoproteins come in different sizes, amounts, and densities. Density refers to the fat-to-protein ratio: When there’s more fat and less protein, the particles are considered less dense, and they become more buoyant. Apolipoproteins are protein-based components of lipoproteins. They’re encoded by genes that start with the letters APO (such as APOB or APOE). We’ll look at apolipoproteins a little later. We can divide lipoproteins into a few general categories based on density:

ΧΧHDL-C is high-density lipoprotein, aka the “good cholesterol”. This brings cholesterol back to the liver for recycling.

ΧΧLDL-C is low-density lipoprotein, aka the “bad cholesterol”. This transports

ΧΧIDLs, or intermediate-density lipoproteins, somewhere between LDL and VLDL particles.

ΧΧVLDL is very low-density lipoprotein, also a kind of “bad cholesterol”. We also want this to be lower.

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ΧΧChylomicrons, also known as ultra-low-density lipoproteins (ULDLs).

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cholesterol away from the liver to elsewhere in the body, and can be part of the process of inflammation that underlies cardiovascular disease risk.

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When we get a basic blood lipid panel done at our doctor’s appointment, it will most commonly measure:

ΧΧBlood triglycerides: how much total triglyceride is in all the lipoprotein particles combined.

ΧΧTotal cholesterol: how much cholesterol is in all the lipoprotein particles combined.

ΧΧHDL-C: how much HDL-C we have. ΧΧLDL-C: how much LDL-C we have. Generally, we want most of these to be lower, except for HDL, which we want to be relatively higher. Having too many triglycerides circulating in our blood is known as hypertriglyceridemia. Very high cholesterol levels are known as hypercholesterolemia. The combination of these, which creates a poor blood lipid profile, is known as dyslipidemia. All of these are risk factors associated with metabolic syndrome and its associated diseases, although they don’t necessarily mean that someone will always develop health problems. All of these risk factors can be affected by diet and exercise, along with other lifestyle choices and environmental factors… but can also be partially shaped by genetics.

Compared to people of European ancestry, people of African descent (including West African, Afro-Caribbean and African-American) were more likely to have particular lipase variants that protected them from coronary atherosclerosis (aka hardening of the arteries).

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For instance, research has found ethnic differences in the LPL and LIPC genes, which code for lipases (enzymes that help us break down fats) and are expressed in liver, heart, muscle and fat tissues.

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What this means for you

ΧΧBlood lipids are important health indicators. If you’d like to know what they are, measure them directly with a blood test.

ΧΧDon’t rely only on a genetic test. At best, a genetic test can only predict possible risk. It can’t tell you what your blood lipids actually look like.

ΧΧGet regular bloodwork done. Having your blood lipids tested along with your blood glucose (see above) as part of your regular medical checkup (perhaps annually) is a good idea.

ΧΧIf you are diagnosed with dyslipidemia or other metabolic health

concerns, discuss this with your health care professional. If you have heritable dyslipidemia, you should still be doing all the things that promote healthy metabolism (you know, the whole “Don’t smoke, keep a healthy body fat level, get some exercise” thing), but you may need additional medical support.

ΧΧReview our strategies for healthy metabolism in upcoming chapters.

Hypertriglyceridemia and zinc fingers Normally, we want triglycerides to be stored safely in our fat cells, waiting to be used for energy. We don’t want too many of them roaming around our bloodstream for too long. Some people are genetically more likely to have higher blood triglycerides, aka hypertriglyceridemia.

23andMe tests for a SNP known as rs964184 on the ZNF259 gene (which is also sometimes known as ZPR1). The ZNF in this gene name stands for “zinc finger”.

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Most proteins with zinc fingers are “interaction molecules” that are designed to bind to DNA, RNA, or other protein molecules. So their shape crucially affects how they are able to do this job.

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While Zinc Finger would be a terrific band name (and, indeed, someone has already created a song that uses the primary structure of another ZNF protein), it actually refers to a zinc-based part of a protein that gives a protein a particular shape. (You’ll remember from Chapter 2 that the physical shape and structure of a protein affects how it works.)

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ZNF259 and rs964184

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The protein coded by ZNF259 binds proteins that are involved in insulin sensitivity, glucose and fat metabolism, and fat storage, such as peroxisome proliferator-activated receptor gamma (PPAR-γ) or hepatocyte nuclear factor 4α (HNF4A). ZNF259 is also located close to another gene complex that is strongly linked to blood lipids: APOA5–A4-C3-A1. Variants in APOA5 affect metabolism of chylomicrons, VLDL-C, and HDL-C. (We’ll look at the APO gene family below.) In one study of people of European descent who had hypertriglyceridemia, each copy of a G at the rs964184 SNP on ZNF259 increased people’s risk of hypertriglyceridemia by about 3.3 times. Other research in Japanese and South Asian populations has found a similar relationship between ZNF259 and the overall risk of metabolic syndrome. In this case, having the G form of the rs964184 SNP was linked to having higher blood triglycerides along with higher fasting plasma glucose and lower HDL cholesterol. This suggests, again, that many features of metabolic syndrome are related.

Hypercholesterolemia Like hypertriglyceridemia, hypercholesterolemia (excessively high blood cholesterol) can be inherited, a condition known as familial hypercholesterolemia (FH). FH is a risk factor for metabolic syndrome and related health problems like cardiovascular disease. FH happens when genetic variations affect our body’s ability to clear LDL effectively from the blood. Over time, LDL and its cholesterol passengers can build up in tissues such as our blood vessels or connective tissues.

ΧΧR3500Q, found mainly in people with European ancestry. ΧΧR3500W, found mainly in people of Asian ancestry.

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23andMe looks at two variations in the APOB gene that are linked to FH:

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The second most common cause of FH (only about 5% of cases) is variations in the APOB gene. You’ll remember that APO genes code for apolipoproteins — in this case apolipoprotein B.

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The most common genetic cause of FH is variations in the LDLR gene. LDLR codes for the low-density lipoprotein receptor that determines whether LDL-C can bind to a cell, and then be transported into it for safe storage. About 80-90% of people with FH who are genetically tested show variations in this gene.

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What we found in our sample Several PN team members sampled reported having had a total cholesterol test that was higher than average. Yet none of these people had the genetic variants of APOB that suggested they should have this profile. Interestingly, all of these people were fit, often leaner than average. This tells us that other factors are probably at work in these higher-than-average blood tests. What this means for you

ΧΧBlood lipids are important health indicators. If you’d like to know what they are, have them measured directly with a blood test.

ΧΧDon’t rely only on a genetic test. At best, a genetic test can only predict possible risk. It can’t tell you what your blood lipids actually look like.

ΧΧGet regular bloodwork done. Having your blood lipids tested along with your blood glucose (see above) as part of your regular medical checkup (perhaps annually) is a good idea.

ΧΧIf you discover hypertriglyceridemia, hypercholesterolemia, or other

metabolic health concerns, discuss this with your health care professional. If you have a heritable condition, you should still be doing all the things that promote healthy metabolism (you know, the whole “Don’t smoke, keep a healthy body fat level, get some exercise” thing), but you may need additional medical support.

ΧΧReview our strategies for healthy metabolism in upcoming chapters.

Alzheimer’s disease is a neurodegenerative disease in which brain cells and their connections slowly break down, while wastes, plaques, and other bits of crud (such as neurofibrillary tangles, which are sort of like the hairballs that clog up drains) build up.

Alzheimer’s is a frightening prospect, and this fear may affect our choice to have our DNA tested.

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Alzheimer’s is now sometimes called “diabetes of the brain”, since some researchers suggest that it may be related to the same types of dysregulated glucose and insulin mechanisms as we find in Type 2 diabetes.

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(Here’s more reading on Alzheimer’s from our PN blog.)

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Alzheimer’s disease

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Many of us at PN researching genetic data asked our parents to take part. Some parents were game. Some parents were not. The most common reason given?

“I don’t want to find out I’ll get Alzheimer’s or something.”

We fear neurodegeneration. Losing our mind and physical function in an irreversible, inexorable march is a scary prospect. Our co-author Krista watched her once mentally-agile, fiercely self-reliant grandfather become confused, frail, and terrified as Alzheimer’s punched holes in his brain. Now she (and her mother) wonder: Who’s next? Currently, more than 5 million people in the US alone are diagnosed with Alzheimer’s disease, and this number is expected to triple by 2050. 1 in 9 people over 65 has some form of neurodegeneration attributed to Alzheimer’s; over 1 in 3 people over 85 does. It’s one of the fastest-growing causes of death for older people. Alzheimer’s does, indeed, run in families. But, much like Type 2 diabetes and other chronic diseases, while Alzheimer’s is a genetic risk, it is not a genetic destiny. One of the known genetic risk factors in developing Alzheimer’s disease is our friend the apolipoprotein — in this case, a variant on the APOE gene, which codes for the protein apolipoprotein E, a cholesterol carrier found in the brain and elsewhere in the body. The APOE protein comes in three forms: ε2, ε3, and ε4. (The “ε” is the Greek letter epsilon.)

ΧΧAmong people of African descent, one copy of the ε4 variant is associated with 1.5 times higher odds of developing Alzheimer’s; two copies is associated with about 4 times higher odds in people of African descent.

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associated with 4 times higher odds; two copies is associated with 12 times higher odds.

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ΧΧAmong people of East Asian descent, one copy of the ε4 variant is

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The APO ε4 variant is a major risk factor for Alzheimer’s in many populations, and seems to span people of European, African, and East Asian descent. In fact, compared to the averages for both of those groups:

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While the APO ε4 variant is associated with a higher risk of developing Alzheimer’s, it doesn’t act alone. For instance, risk increases when — in addition to the APO ε4 variant — people also have:

ΧΧA particular variant of rs2373115, a SNP in the GAB2 gene, which codes for

the growth factor receptor-bound protein 2 (GRB2). This protein is involved in signaling and communication within and between cells.

ΧΧA particular form of rs1799724, a SNP near the tumor necrosis factor (TNF) gene, associated with altered levels of beta-amyloid plaques (one of the particular plaque types linked to Alzheimer’s) in cerebrospinal fluid (CSF).

ΧΧVariants in genes that regulate polymerases, enzymes involved in DNA and

RNA assembly. For instance, having an I-G-T haplotype of 3 SNPs in the POLD1 gene and the ApoE-ε4 variant almost doubles the risk of Alzheimer’s, compared to just having the ApoE-ε4 variant alone. The POLD gene, which codes for the protein polymerase delta 1, is also associated with colon cancer, deafness, and lipodystrophy.

What this means for you

ΧΧMaintain good overall health. Body health includes brain health. ΧΧIf you’re concerned about possible genetic risk, this is worth

getting tested for. We still don’t have cures for Alzheimer’s and other neurodegenerative diseases yet, but it does help to act preventively and catch potential issues early.

ΧΧUnderstand your data clearly. Be sure to discuss all results with your doctor and/or genetic counsellor, to understand the findings and discover what you can do to lower your risk.

ΧΧReview our strategies for healthy metabolism in upcoming chapters. PRECISION NUTRITION

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What’s up next Now that we have a basic understanding of how metabolism works, and a few genetic factors that may affect it, let’s look at how genetics can also influence our body size, shape, and fatness (or leanness).

In this chapter, we look at some genetic factors related to energy balance, what makes our bodies “naturally” bigger or smaller, and how much lean or fat mass we’re likely to have.

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How does heredity work? Why don’t we all share the same genetic variations? How might our ethnic background and ancestry affect our overall health?

What we found: Body weight and body comp

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What we found: Heredity

CHAPTER 7

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CHAPTER 5

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CHAPTER 7

What we found: Body weight and body comp What you’ll learn in this chapter In this chapter, we’ll look at:

ΧΧHow body size, weight, and composition (i.e., our ratio of lean mass to fat mass) are complex phenomena that are in part, shaped by genetic mechanisms… but not as much as we might assume;

ΧΧThe role of genes involved in energy balance and regulation, and evolution’s legacy of protecting us from scarcity; and reward, eating behaviors, and so on.

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ΧΧThe role of other environmental factors, such as food availability, food

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Two important points to keep in mind:

ΧΧWhile science is cool, and we have some interesting genetic findings and areas for further exploration, we still know comparatively very little.

ΧΧJust because a genetic test can tell you what body weight or composition you might have, it doesn’t mean that it can tell you the “perfect” diet, supplement, or exercise plan for you.

As you read this chapter, remember our usual caution:

As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

The complexity of body weight and body fat When it comes to weight and body fat, many people will say things like:

ΧΧI must have a slow metabolism. ΧΧI think I’m genetically programmed to be fat / skinny / muscular / whatever.

But is it really that simple? (Spoiler alert: Ha ha! It’s biology! You already know by now that it ain’t.) The key points in this chapter are:

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ΧΧThat person is in good shape because they have good genetics.

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body fat levels are influenced by our genes.

ΧΧBut they are also affected by our environment and lifestyle choices.

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ΧΧBody weight, body composition (i.e., our ratio of lean to fat mass) and

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Energy balance, nutrient processing, and eating behavior Why do you eat? (Or not eat?) Why are you the body size that you are? The answer is complex. It’s not just about “willpower” or your workout program. There are many processes that affect body weight and composition:

ΧΧEnergy balance: The balance between food energy consumed, and energy

being expended to support our metabolism and activity. If more energy comes in than goes out, we will gain mass. If less energy comes in than goes out, we will lose mass. Thus, our energy balance determines body mass.

ΧΧEnergy sensing: Our bodies’ ability to know how much energy we have available (for instance, in the form of stored fat).

ΧΧNutrient partitioning: Will the nutrients you eat be stored (e.g., as fat or

muscle glycogen) used (e.g., to build muscles, to repair damaged tissues, to fuel cellular activities), or burned off as heat?

ΧΧAppetite and food reward: Do we want to eat? Does eating seem fun and interesting?

ΧΧEating behavior: What foods do we choose? How do we know when to stop eating?

As you can imagine, there are many genes involved in regulating metabolism, body weight or fatness, and eating habits.

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Of course, all of these are influenced by the interactions between our genes and our environment.

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Here are just a handful. As you read about what each one does, try to imagine how mutations in these genes might have a physiological consequence:

ΧΧThere are 21 APO family genes that code for apolipoproteins, a large family of molecules involved in lipid transport and processing. We looked at the role of some APO proteins in the previous chapter.

ΧΧTCF7L2, which codes for transcription factor 7 and is linked to balancing

blood sugar; variants of this gene are associated with a higher risk of Type 2 diabetes.

ΧΧPPARG, which codes for one of the peroxisome proliferator-activated

receptor (PPAR) subfamily of nuclear receptors (you’ll remember we learned about nuclear receptors in Chapter 6 with the vitamin D receptor). PPARs are involved in regulating the expression of metabolic genes. Depending on the tissue and PPAR, they can promote fatty acid storage or breakdown, glucose metabolism, antioxidant responses, and so on. Because of this, they are likely involved in metabolic diseases such as cardiovascular disease or diabetes.

ΧΧLEPR, which codes for the leptin receptor. Leptin is a hormone involved in

sensing how much energy we have available, whether stored in the form of body fat, or how much we’ve recently eaten.

ΧΧMC4R, which codes for the melanocortin receptor. The encoded protein

interacts with adrenal and pituitary hormones. Defects in this gene can cause autosomal dominant obesity, meaning that you only need one copy of a gene variant to see effects.

ΧΧFTO, which codes for fat mass and obesity-associated protein, is related to

ΧΧLRP5, which codes for bone mass. LRP5 gene mutations are associated with lower bone density and a higher risk of osteoporotic fractures.

There are also genes involved in regulating eating behavior and energy balance (the balance between energy in from food, and energy out from metabolism and activity).

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glucose and energy metabolism, as well as the regulation of body fatness and size. FTO is also an RNA editor and is involved in regulation of muscle. We’ll look at FTO more below.

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These include:

ΧΧUCP codes for mitochondrial uncoupling proteins (UCPs), which separate

oxidative phosphorylation from ATP synthesis and dissipate energy as heat. People who “naturally” maintain a lower body weight may be more likely to convert excess energy from food to heat, rather than storing it as body fat.

ΧΧRelated to this process is the gene ADRB3, which codes for a protein in the

beta adrenergic receptor family. Beta adrenergic receptors are found mostly in fat tissue, and help regulate lipolysis (fat breakdown) and thermogenesis (heat production).

ΧΧAGRP codes for agouti-related peptide (or agouti-related protein). Along with other substances such as neuropeptide Y, this protein works in the hypothalamus, aka the body’s metabolic Mission Control, to regulate appetite and eating behavior.

ΧΧGHRL codes for two proteins: ghrelin and obestatin. Ghrelin goes up when

we are hungry, stimulating hunger. The function of obestatin isn’t completely clear yet, but it may oppose the action of ghrelin.

Measuring body size and composition Body mass Many studies that explore the relationship between genes and body size or fatness use body mass index, or BMI. PRECISION NUTRITION

BMI is simply a measure of the relationship between someone’s height and weight. The higher BMI is, the heavier someone is for their height.

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The World Health Organization divides BMI into the following categories.

BMI Category Below 18.5

Underweight

18.5–24.9

Normal weight

25.0–29.9 Overweight 30.0–34.9

Obesity class I

35.0–39.9

Obesity class II

Above 40

Obesity class III

To put this in real terms, let’s say we have a person who is 5’6” (1.68 m) tall. How might various BMIs look for them?

Below 18.5

Underweight

Less than 114 lb (~52 kg)

18.5–24.9

Normal weight

115 to 154 lb (~52-70 kg)

25.0–29.9

Overweight

155 to 185 lb (~70-84 kg)

30.0–34.9

Obesity class I

186 to 216 lb (~84 kg-98 kg)

35.0–39.9

Obesity class II

217 to 247 lb (~98 kg-112 kg)

Above 40

Obesity class III

Over 247 lb (~112 kg)

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Category Sample weight

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BMI

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What can BMI tell us? In general, we know that at the population level (in other words, in a big group of people), if you have a higher BMI (past a certain point), you are more likely to:

ΧΧdevelop chronic diseases such as cardiovascular diseases, Type 2 diabetes, and cancer;

ΧΧhave more body fat; and/or ΧΧhave certain kinds of metabolic problems. At the population level, BMI is a proxy for body fatness. If we took a randomly-selected group of 100,000 people, people’s BMI would be closely related to their body fat levels. Having a much higher-than-average BMI would likely mean higher-than-average body fat. At the individual level (i.e., you), BMI is often too broad to be helpful. The relationship between BMI and body composition is just an average. It doesn’t necessarily tell us about you specifically. BMI tells us only how much body mass someone has, not what that mass is made of. So a fit and lean but heavy rugby or American football player may have the same BMI as a sedentary person with much more body fat and much less dense muscle and bone. Similarly, an extremely lean ultramarathoner with naturally lighter bones may be designated as “underweight” though they are still also very fit and strong.

So when we look at how BMI is correlated with genetic data, we want to be careful about how we draw conclusions from that correlation.

Some genetic studies use waist circumference (WC) as a measure of body composition. Fewer genetic studies have used more accurate methods (such as caliper skinfolds, BodPod or hydrostatic immersion) to look for precise relationships between genes and how much fat or lean mass a person has.

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Thus, along with height and weight, we also look at body composition: the relative proportion of fat and lean mass (which, again, includes muscle, bone, and connective tissues).

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Body composition

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In our PN sample, not surprisingly, many people were “overweight” or even “obese” despite being fit and athletic, perhaps even leaner than average.

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We’ll look at data from some genome-wide association studies (GWAS) that uses the extremely precise computed tomography (CT) method, below. As with BMI, we need to carefully interpret studies that correlate body composition with genetic data. How measurements of BMI and body composition are taken and used can affect our conclusions.

Variations in BMI Though many risk factors (such as FTO gene variants, which we’ll look at below) seem to be common across most groups, various populations differ in their risk. For instance, although people of East Asian and South Asian origin tend to be among the world’s lightest and smallest (both traits shaped by heredity), they have a higher risk of metabolic disease at a lower BMI than people of European ancestry. This means that knowing BMI alone, or potential links between genes and BMI, may not fully predict health or disease for people from certain groups. As with many biological factors, both heredity and environment matter. Height is strongly shaped by genetics, but we’ve been getting taller and taller over the last several decades. We’re also getting heavier. Population-wide genetic changes are typically slower than this, while environmental conditions can change much more quickly (for instance, imagine how moving from a poor, rural region to an affluent, industrialized urban region might change many factors in a person’s body). PRECISION NUTRITION

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Figure 7.1: Changes in average height, 1810-1980

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In 1996, about 52% of Bangladeshi women were considered underweight (BMI lower than 18.5). Today, it’s only about 30%. Conversely, in 1996, only about 3% of Bangladeshi women were considered overweight (BMI ≥ 25); that’s now quadrupled to about 12%. Lightest countries in the world: Percentage of women with BMI lower than 18.5

% with BMI 30

Average height (cm))

Average height (ft/in)

American Samoa 37.30 NA NA USA

35.60 151.9 cm 5’0”

African American 56.6

163.6 cm

5’4” ½

Latin American

44.4

158.9 cm

5’2” ½

Asian American

11.4

158.4 cm

5’2” ½

European American 32.8 165.0 cm 5’5”

Australia

24

163.8 cm

5’4” ½

United Kingdom

23

164.5 cm

5’5”

Croatia

22.7

166.49 cm

5’5” ½

Malta

19.3

163.8 cm

5’ 4” ½

United Arab Emirates 16 156.4 cm 5’4” ½

Greece

13.5 166 cm 5’5” ½

Data from Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in

BMIs here and elsewhere in the world are going up, often quickly. This suggests that other factors besides genes are probably contributing.

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If, as we’ve seen, body size and mass depend on factors like energy balance or sensing, as well as eating and activity patterns, then changing environments can often disrupt our natural regulatory systems as well.

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How might environment play a role?

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the United States, 2011-2012. JAMA. 2014;311(8):806-814. doi:10.1001/jama.2014.73

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This can include, for instance:

ΧΧchanges to physical environments — e.g., increasing industrialization of

previously rural areas, or living out of sync with normal light-dark cycles in a 24/7 society.

ΧΧchanges to social environments —e.g., changing social norms of eating and activity.

ΧΧchanges in microbial environments —e.g., introducing new pathogens or having less diversity in our own personal microbiome.

ΧΧchanges in physical activity —e.g., being able to commute long distances by car instead of walking.

ΧΧchanges in food availability and production —e.g., a shift from working in

the field growing staple crops to buying processed foods in supermarkets.

ΧΧchanges in food palatability and reward —e.g., traditionally boiled handdug potatoes may become delicious, crave-able potato chips.

ΧΧchanges in economic conditions and living standards —e.g., having an

emerging middle class that does less physical labor and can buy more and better food.

ΧΧchanges in crucial developmental conditions —e.g., childhood vaccinations that prevent diseases, or better maternal and infant nutrition, both of which can affect adult BMI.

ΧΧchanges in chronic stressors —e.g., well… everything that we’re all freaking out about right now.

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So even if we have “light / small genes” or “heavy / big genes” (were there such things), our environment would still strongly affect our BMI and body composition.

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What this means for you

ΧΧUnderstand how genetic research measures body size, composition, and weight, and what that means (or doesn’t). Genetic testing may look for genes related to BMI, or amount of body fat, or both.

ΧΧUnderstand that populations are different than individuals. Your

experience and body size, shape, or fitness is unique to you. Two people with the same body weight but different ancestry or environment will have a different probability of metabolic disease, and that metabolic disease may emerge through slightly different signaling pathways. Even if your genetic test results suggest, for example, you have a given risk of BMI-related metabolic disease based on a sample of 100,000 people… that risk may not apply to you.

ΧΧUnderstand that human variation is normal. There’s about 11” of height

difference between the average woman in Bosnia-Herzegovina (5’7”) and the average woman in Bolivia (4’8”). There is a wide range of BMI that can be normal and healthy, and a wide range of people that can be healthy at a given BMI. So even if your BMI is genetically predicted to be higher or lower than average… you may be perfectly fine.

ΧΧLook at the interaction between genes and environment. We’ll mention this often through this chapter.

The genetics of body weight and fat Evolution’s legacy

In fact, most of us who struggle to maintain a healthy body fat level or say “no” to that second donut are perfectly normal in genetic and evolutionary terms.

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The medical and fitness communities have debated whether people who have “excess” body fat, or who have trouble managing their weight and/or their eating habits have a “disease” or “addiction”.

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For example:

ΧΧMost humans evolved to store body fat. Humans who couldn’t do this well

would risk starvation during times of scarcity. In particular, women need to have enough body fat to support the potential long-term energy demands of pregnancy and breastfeeding.

ΧΧMost humans evolved to prefer things that taste good, and to want to

eat lots of food when it’s available. For most of our history, food was hard to get, and sweetness signaled things that were energy-dense and good to eat. This legacy affects our appetite, hunger, and fullness signals and regulation, especially in the 21st century when delicious, energy-rich foods are everywhere.

ΧΧMost humans evolved to conserve energy. In other words, we are naturally less inclined to move around if there’s no reason to do it. Why waste valuable energy when you don’t have to?

ΧΧMost humans evolved to seek rewards. What gets us off our butts and out of the safety of the burrow? The promise of something good. Our brains have complex circuits that inspire us to explore, be curious, and chase things that reward us (such as food, fun, and mates). Many types of energydense foods give us a chemical “hit”, helping us synthesize feel-good neurotransmitters.

So having some squish on your body, or loving ice cream, or preferring to lie on the couch rather than go to the gym, doesn’t mean your body is broken. It probably means your genes are doing their job of finding and conserving precious energy.

For genetic expression, environment matters.

Epigenetics and environments

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Traits that were evolutionary advantages for most of our history — when food was scarce, daily energy demands were high, and rewards were hard to come by — are simply a mismatch now. Especially if we want to be lean or stay away from the chocolate-covered pretzels.

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Let’s say we have two genetically identical people — in other words, identical twins. One twin is leaner. The other is heavier and/or fatter.

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In Chapter 2, we introduced you to the concept of epigenetics — the ways in which our genetic expression is regulated.

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Why the difference? Good question. One of the most useful ways to explore the contribution of genes and environment, particularly when it comes to body size and metabolism, is to look at twin studies. Identical twins, of course, share the same genetic blueprint, and often the same early-life experiences. Yet they end up looking different as adults if they do different things, or live in different environments. If we examine our two different-looking twins — perhaps one twin is leaner and lighter, while the other is significantly overweight or obese — what might we find? Well, differences may have started in utero. For instance, if one twin hogs all the nutrients while both twins are in the womb, this also affects genes such as IGF1R, which codes for insulin-like growth factor 1. IGF1 is an important protein involved in anabolism (growth) and development, and thus affects body size and mass.

Fun factoid! The gene that codes for another insulin-like growth factor, IGF2, is only expressed from paternal inheritance — in other words, the genetic material you got from dad.

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This epigenetic phenomenon is known as imprinting: the silencing of genetic material from one parent or another.

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As adults, compared to their leaner twins:

ΧΧObese twins tend to have more fat in the areas we’d expect: under the

skin (subcutaneous fat), around the internal organs (visceral fat), marbled in muscle tissue (intramuscular fat) and laced into the liver and kidneys.

ΧΧObese twins tend to be less sensitive to insulin (which is related to how much fat they have in their liver).

ΧΧObese twins express some gene pathways more strongly, particularly

genes involved in inflammation, as well as genes involved in organizing cell structures, cell growth, and transport between cells.

ΧΧObese twins’ immune systems are more highly activated (aka upregulated), as if preparing to fight off pathogens. One study found that the most overexpressed gene in obese twins is SPP1, which codes for osteopontin, a cytokine (cell signaling molecule) that helps recruit immune cells such as macrophages and T cells during inflammatory processes.

ΧΧObese twins have other gene pathways that are less expressed (i.e.,

downregulated), such as pathways involved in energy metabolism and/or breaking down fatty acids and amino acids.

ΧΧObese twins have fewer copies of mitochondrial DNA in their fat tissue

— sometimes nearly half as much as their leaner twins. This might partly explain the metabolic problems we see. Defects in mitochondrial energy metabolism in subcutaneous adipose tissue may encourage the body to store fat elsewhere, particularly in tissues that are especially sensitive to insulin (such as the liver, skeletal muscle, and pancreas), resulting in severe insulin resistance.

ΧΧObese twins often prefer fatty or sugary foods more than their leaner siblings.

Body size, fatness, and metabolic health are not just about the genetic code we are given.

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Rather, epigenetic expression of these genes is also crucially important.

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Given, again, that each pair of monozygotic (identical) twins are essentially genetic clones, these differences tell us:

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The good news, though, is that many of these up- or down-regulations can change if:

ΧΧbody weight / fat changes; ΧΧpeople change what they eat; and/or ΧΧthey change their physical activity. We’ll look at this more in the final chapter on what to do.

The polygenic basis of obesity Regulating all of these functions above (such as energy balance and storage, hunger and appetite, etc.) is pretty important for our survival. To date, we know of about 185 genes that are implicated in obesity — or more accurately, in making it slightly more likely that a person may be heavier or fatter than average. These genes may be expressed differently in adults and children, and/or in various populations, due to environmental factors or genetic variations. More advanced GWAS using computed tomography (CT) let researchers look at various types of body fat and differentiate visceral fat (around the internal organs) from subcutaneous fat (under the skin). Such studies have, to date, only confirmed links between fat and 8 SNPs near the following genes:

ΧΧETV5, which codes for ERM proteins, an ancient protein family of ΧΧFLJ35779, which codes for POC5, a protein involved in regulating cell

mitosis and structure. POC5 is mostly expressed in the prostate. Other key sites include thymus, mammary gland, and bone marrow.

ΧΧFTO, which we’ll look at more below.

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transcription factors.

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polypeptide (GIP), one of the incretin (insulin-stimulating) hormones released by the gastrointestinal tract that enable our bodies to process glucose. Variants in this gene may be related to developing Type 2 diabetes or having more visceral fat. Some research also suggests that high levels of GIP might be involved in adipose tissue inflammation, a characteristic of obesity.

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ΧΧGIPR, which codes for receptors involved with signaling for gastric inhibitory

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ΧΧLINGO2, which codes for a protein called leucine-rich repeat and

immunoglobulin domain (LINGO), involved in growth and regulation of axons in the nervous system (for instance, it’s linked to Parkinson’s disease). It’s also involved in cell signaling (aka signal transduction), the process by which cells send chemical messages to each other. (You’ll remember we learned about signaling pathways in Chapter 6.) It’s not clear exactly how this protein contributes, though.

ΧΧNEGR1, which codes for neuronal growth regulation factor 1 (NEGR1). This

protein, strongly expressed in the hypothalamus (which, you’ll remember from Chapter 6, helps regulate body weight and appetite), seems to play a role in brain function and structural integrity. It’s also expressed in adipose tissue, particularly subcutaneous fat. This gene showed up in a study of patients with bulimia nervosa, and correlated with some of the cognitive dimensions of disordered eating, such as having poor interoception (i.e., being able to correctly read signals from inside one’s body).

ΧΧSH2B1, which codes for sarcoma homology 2 B adaptor protein 1 (SH2B1).

This protein is part of a family of proteins involved in signaling for many hormones, peptides, and cytokines (cell signaling molecules), such as leptin, insulin, growth hormone (GH), IGF-I, nerve growth factor (NGF), and brain-derived neurotrophic factor (BDNF), which we’ll look at below. These regulate energy balance, body weight, insulin and glucose, anabolism, and other metabolic activities.

ΧΧTMEM18, which is an evolutionarily conserved gene (in other words, it’s

Each of these genes can affect a different yet related physiological process: fat or glucose metabolism, cell signaling and gene regulation pathways, membrane transport, etc.

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been around a long time and appears in many species) that codes for a transmembrane protein (a protein that runs through a cell membrane, usually as a bridge between the inside and outside of the cell). We don’t completely know what this protein does. 23andMe tests for a SNP, rs6548238, that seems to predict small variations in body weight (between about 1-3 lb of difference). Each copy of a T rather than a C at rs6548238 near the TMEM18 gene was associated with 0.26 units lower BMI (equivalent to 1-3 pounds, depending on height).

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Outside of environmental effects, simply having a single genetic variant (or even a collection of variants) might only affect body weight by a pound or two (0.5 to 1 kg).

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While there are certainly some rare genetic conditions that can make a few people more likely to be obese, it’s not as clear-cut as many people might think.

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Even in extreme cases of apparently genetic obesity that don’t respond to nutrition and exercise, the most common mutations (in the melanocortin-4 receptor gene) only appear in 1-6% of people with obesity.

Allelic heterogeneity Let’s say on a few separate occasions, you eat:

ΧΧsuicide-spicy chicken wings ΧΧan extra helping of pie with whipped cream ΧΧan entire bag of gummy candy ΧΧa hot dog with fried onions, cheese curds, and sauerkraut Each time, you are wracked with heartburn afterwards. The foods that caused that heartburn were different, but all might fall loosely under the heading of “foods you might eat at a carnival”. Allelic heterogeneity works the same way: Related genetic variants, or alleles (different types of “junk food”), in the same general location (our carnival) are associated with the same trait or outcome (heartburn). This means that if we look only at hot dogs, or only at pie-eating contests, we might miss the fact that a wide variety of foods might lead to the same result. We might even come up with inaccurate theories like “Round-shaped foods are bad”, instead of looking at carnival food overall as a broader, more complex phenomenon.

(And come to think of it, most carnival foods don’t do our metabolism any favors.)

This score simply adds up all the known possibilities from each combination of variants, and decides how likely (or not) a certain outcome is.

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Many studies on the relationship between body fatness / size and genetics look at several genetic variants, and create a “risk score”.

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Probabilities and risk score

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Similarly, if we look only at one gene variant, we might not realize that many related gene variants can affect the same biological process. In the case of obesity, this is certainly true.

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Let’s say a study looks at 10 different genetic variants that are known to affect body fatness / size. And let’s say you have 4 of those variants. Now you have a “risk score” of 4, which may explain 0.1% of your body fatness. Most research has found that even with elaborate “risk scores” (for instance, with a dozen or more genetic variants known to affect body fatness / size), specific genetic combinations may only explain 1 or 2% of the differences in body weight. So even if you have, say, 15 or 20 of the known genetic variations that make you more likely to have more body fat than average, those variations may only explain 2% of the reasons why you’re bigger than your buddy. For instance, a study done in people with Han Chinese ancestry explored 26 genetic variants that might affect BMI. Of those, four variants (TMEM18, PCSK1, BDNF and MAP2K5) were statistically significant – for a BMI 0.13 higher per variant. Thus, having all four statistically significant variants might give you a BMI that’s 0.52 higher than average, assuming all your other environmental conditions are the same as everyone else. To put that in real terms: Let’s say you’re from that population. You’re 5’6” (1.68 m) tall:

ΧΧYour “average” buddy might be 150 lb (68 kg), with a BMI of 24.2, in the healthy range.

ΧΧYou with your four genetic variants might be 153 lb (69.4 kg), with a BMI of 24.7.

Another study that looked at approximately 12,500 people of European descent concluded that lifestyle factors, particularly exercise, explained about 6 times more of the BMI variation than genetic factors. Overall, researchers estimate that only about 50-60% of BMI is inherited.

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Hardly a shocking difference.

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What you eat, how you exercise, your daily routines, your stress level — all of these are far more important in shaping how your genetics are expressed. Obviously, we can’t look at all the genes that might affect your personal body size and shape.

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This means that even if you have quite a lot of genetic variations that make you more likely to be heavier or fatter, those variations only play small roles.

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But let’s look at one that may play a major role: FTO.

FTO The FTO gene codes for a protein known as fat mass and obesity-associated protein. It regulates the expression of genes involved in metabolism by demethylating nucleic acids. Methylation is an important process in epigenetics that involves attaching a methyl group (a carbon and 3 hydrogens, aka CH3), to a strand of DNA or RNA, often to the cytosine molecule. When DNA or RNA is methylated, certain genes are often “switched off”, which can be a problem if you want those genes to be transcribed and protein made. FTO can reverse this process with demethylation — removing the methyl group, and “switching on” certain genes by increasing gene transcription. We’ll look more at methylation in Chapter 8. The FTO gene is an ancient one, found in many vertebrates. It may have appeared about 450 million years ago. It even appears in algae, though not other invertebrates, which suggests that perhaps a horizontal gene transfer occurred. Originally, researchers discovered the FTO gene in mice with odd-looking feet, leading to the original gene name of Ft — fused toes. FTO was one of the first genes to be identified in GWAS. Unlike many other genes linked to particular traits, its effects in many populations have been fairly well replicated.

Importantly, these SNPs may not cause changes in body fat; they may simply predict it. Other factors may be involved.

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Many SNPs on the FTO gene have been explored, and potentially linked to differences in body fatness.

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Along with FTO’s potential effects on things like growth or metabolism, this implies that FTO genetic variants can have widespread effects on both physiological processes and behaviors that affect body size and fatness. Indeed, FTO is upregulated during periods of food deprivation.

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FTO is expressed throughout the body (for instance, in fat, stomach, and skeletal muscle tissue) but most strongly in the brain, particularly in regions associated with energy balance and reward-seeking. This suggests that FTO may also be involved in particular behaviors, such as appetite regulation, self-control or impulsivity.

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These SNPs include:

ΧΧrs1121980, strongly linked to adult obesity (BMI > 40) with odds ratio of 1.55 in a population of French individuals of European ancestry.

ΧΧrs1421085, found to be significant in a smaller study of about 600 women

of European ancestry who were currently obese (BMI > 40) and who had gained weight quickly and dramatically as teenagers. Interestingly, this study was also able to compare about 100 women with their sisters, who had much lower BMIs (≤25), and show that the heavier sisters were, indeed, genetically different in this SNP. The role of rs1421085 was also shown in a population of Hispanic Americans.

ΧΧrs17817449, which was found to have a strong predictive value in a small

group of about 200 people in Western Spain who not only gained weight quickly as teenagers, but also had two or more close relatives with BMI higher than 40.

ΧΧrs8057044, found to be most predictive of higher body weight in a

population of about 500 African American girls compared to their classmates of white European ancestry. rs3751812 was also found to be significant in a similar African American population, as well as Hispanic Americans.

ΧΧrs9939609, which we’ll look at more below. FTO expression seems to be connected specifically to fat tissue, rather than other types of tissue that could affect body weight, such as muscle and bone. Thus, having particular FTO variations probably means that if you have more body weight (i.e., a higher BMI), it’s from body fat rather than lean mass.

23andMe tests for 124 SNPs on FTO.

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To date, about 90 genetic variants within FTO have been associated with BMI.

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That said, other more detailed studies in smaller populations (such as Old Order Amish or Japanese) have also found other SNPs that seem significant to that specific population — for instance, rs1861868 was found to be significant in Old Order Amish, but hadn’t been previously associated with obesity in other studies.

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In populations with European and East Asian ancestry, there seems to be a larger cluster of FTO SNPs that may relate to BMI, whereas in populations of African ancestry, there seem to be fewer BMI-related SNPs across a smaller region.

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In particular, 23andMe highlights the SNP rs9939609. People with an AA genotype for this SNP tend to have a higher BMI, while people with TT tend to be lower. (ATs are typical odds.) For some people of European ancestry, having the AA form of rs9939609 does seem to relate to being heavier. This seems to start younger, and persists into adulthood. The 16% of European adults who were AA weighed about 6-7 lbs (about 3 kg) more than those who were AT or TT. Their chance of being obese was 1.67 times greater. Other research in Europeans suggests that the AA form was linked to feeling less satisfied after meals. Some AAs also seemed to have “loss-of-control eating episodes”, especially with high-fat foods. Researchers have found similar relationships between an AA variant of this SNP and being heavier in Japanese populations, Korean populations, Pakistani and North Indian populations, indigenous North American populations (such as Ojibway-Cree or Inuit) and Mexican-mestizo populations (i.e., people who have indigenous Central American ancestry). Yet, this SNP did not always seem to have the same relationship for people of Han Chinese descent, nor did it appear as often in general in that population. Same goes for several Oceanic populations (Melanesians, Micronesians, and Polynesians) and a Gambian population in Africa. In addition, the rs9939609 SNP seemed to “flip” its function depending on age — before about age 3, having the AA version was associated with lower body weight. OK… it sounds like FTO plays some important role, right?

Basically: Some studies suggest that FTO can affect body size, fatness, and weight loss, but it’s not clear to what extent.

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Well… we still don’t have the whole picture just yet.

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For instance, if you’re more active, you’re often leaner. As with other genetic variants that may predispose people to more body fat, physical activity often seems to override any potential FTO effect on body mass.

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On top of this, lifestyle choices and environmental factors can strongly change the outcome.

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One systematic review found that no matter what type of rs9939609 FTO variant people had, they responded equally well to weight-loss interventions such as improving their diet, getting more exercise, or taking weight-loss drugs. In other words: Regardless of your genetic makeup, the way to get and stay relatively lean, fit, and healthy is the same for everyone. Darn you biology! Why must you be so complicated and fickle?! Interestingly, this SNP was also linked to other traits, such as:

ΧΧAlcohol use — people of European descent with the AA variant tended to drink less.

ΧΧADHD in preschool children ΧΧAge-related cognitive decline, such as Alzheimer’s or memory loss.

Particular FTO SNPs (such as rs9939609, rs8050136, rs3751812) may interact with the Alzheimer’s apolipoprotein E (APOE) ε4 risk allele, increasing the risk for dementia and Alzheimer’s nearly three times. You’ll remember we looked at Alzheimer’s in the previous chapter.

What we found in our sample In our PN sample of 32 people, we found some interesting things. We looked at 8 SNPs with a suggested relationship to BMI. PRECISION NUTRITION

Note that each SNP combination has a slightly different possible outcome. For instance, some predict a higher, typical, and lower BMI. Others might predict only higher-than-typical and typical (rather than lower).

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Gene

SNP

Variants and trait associated with each

near MTCH2 rs10838738 GG – higher AG – typical AA – lower BMI BMI BMI near MC4R rs10871777 GG – higher AG – slightly AA – typical BMI higher BMI BMI near GNPDA2 rs13130484 TT – higher CT – typical CC – lower BMI BMI BMI near SH2B1 rs4788102 AA – higher AG – typical GG – lower BMI BMI BMI near TMEM18 rs6548238 CC – typical CT – lower TT – much BMI BMI lower BMI near FAIM2 rs7138803 AA – higher AG – typical GG – lower BMI BMI BMI near BDNF rs925946 TT – higher GT – typical GG – lower BMI BMI BMI FTO rs9939609 AA – higher AT – typical TT – lower BMI BMI BMI

First, there seemed to be no strong or consistent correlation between particular SNPs and BMI.

(This makes sense if we think about the PN population, which is likely to have more lean body mass than average.)

Along with objective measurement of BMI, we also asked people to self-report on whether they struggled with managing their weight or body fat. Some people’s self-reports were objectively accurate.

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For instance, people whose SNP combos said they “should” be heavier were actually lighter. People who “should” be lighter were actually heavier — often significantly.

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Second, many people had the “wrong” SNPs for the predicted outcome.

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On average, the trend for the PN folks was to be heavier than predicted by a given SNP.

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For instance, if they said they’d always been lean / normal, their histories and BMI showed this. Or if they said they’d always struggled with their weight / fat, their histories and BMI showed this as well. In particular, some people who were heavier also said they didn’t feel like they had a “shutoff switch” with eating. They often found it hard to stop when they’d had enough. However, this trouble with satiety didn’t necessarily correlate to alleles associated with obesity. There are probably other factors at work (such as stress or habit). Nor did liking sugar correlate to body weight. Some of the biggest sugar fiends in the group were normal weight, perhaps even on the low end of normal. Other people’s self-reports were not objectively accurate. In particular, many people reported struggling with their weight even if they had maintained a consistently normal or even low BMI or body fat level for most of their lives. What does this tell us?

ΧΧBMI (and body fat percentage) can be objectively measured, and potentially connected to genetic variants, especially with a large population.

ΧΧHowever, some SNP associations may not be strong enough to show a

consistent trend. They might not give us enough useful information to help us make decisions.

ΧΧPeople’s subjective experience of feeling heavier / fatter (or smaller / skinnier)

ΧΧOnce we get our test results, which results will we “believe”? For instance,

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you are technically “obese” but your genetic test tells you that you have “skinny genes”, how might you respond? Will this result inspire you, puzzle you, demotivate you, or somehow change your perspective about your body?

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may affect their perception of what their genetic makeup is, or should be. This perception may affect their behaviors. If we think we are “destined” to be a certain way, might we make choices that reflect that? Might we selfreport as different than we really are, thus confounding the data?

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What this means for you ΧΧYour genes are probably working just fine. Most humans have evolved to

store body fat, enjoy eating tasty things, and avoid unnecessary activity. If you have more body fat than you (or current social norms) would prefer, like eating tasty things, and don’t always feel motivated to exercise, it doesn’t mean there is anything genetically “wrong” with you.

ΧΧUnless you have a measurable genetic condition, you are probably

somewhere within the zone of “genetically average” for your age and ancestry. While genetic tests seem to help predict risk, the evidence doesn’t support this — yet.

ΧΧIn most cases, energy balance, lifestyle choices, and environment affect

our body weight and fatness much more than genetics. Though it may sometimes feel like it’s harder or easier to gain or lose weight, this may be more related to how your unique body is living in its environment, and less related to a “genetic blueprint”.

ΧΧEven if you carry a ton of genetic variants that may make it more likely

that you’ll be heavier or have more body fat than average, these will likely only explain a small percentage of your body size and fat levels.

ΧΧIf you want to change your body weight and/or body fat levels, look at

your environment and behaviors. Nutrition and lifestyle habits (such as smoking or drinking), plus regular physical activity are the most important factors affecting body weight and body fat.

Again: No matter what your genes are, the path to get and stay lean, healthy, and fit is more or less the same for everyone.

Outside of childhood wasting diseases and clinical cases of anorexia nervosa, this domain of genetic research has gotten less attention. As with a genetic propensity to be heavier and/or fatter, a genetic propensity to be lighter and/or thinner probably involves many factors such as natural body structure, energy balance regulation, and/or eating behaviors.

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What about the opposite end of the spectrum of BMI — being lighter, smaller, or thinner than average?

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The polygenic base of underweight and anorexia

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We’ll look specifically at what you can do in the last chapter of the book.

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One group of researchers initially studying extreme cases of apparently genetic obesity discovered that the “opposite” of a particular genetic configuration — that is, duplication of a short region on chromosome 16, rather than a deletion — resulted in the “opposite” body weight as well. Duplication was often associated with being underweight, while deletion was associated with being obese. As with the higher end of the BMI spectrum, being significantly thinner / smaller / lighter than average often means that energy balance is out of sync with normal physiological demands. Of course, this often happens when we are sick, injured, or under extreme stress. But when circumstances are otherwise normal, very low BMI usually means that people are eating much less food than their body might need in order to function properly.

The terminology of “orexia” The ancient Greek word orexis, or appetite, gives us many words. Orexins are hormones that regulate appetite. (Interestingly, no clear link has been found between HCRT, the gene that codes for orexins, and weight.) The term anorexia simply means “without appetite”. Low appetite can happen for many reasons: illness, injury, stress, aging, medications, and so forth. Anorexia nervosa is a form of disordered eating and persistent food restriction that’s usually accompanied by an unusually low body weight, an intense fear of gaining weight, and a distorted perception of body weight.

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Again, there are many factors involved in having a significantly lower body weight or less body fat than average, including several possible genetic contributors.

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People may be choosing to eat less (thus overriding their natural desire to eat). Or they may be responding to strong signals from their appetite centers that tell them to stop eating, even though the body is not necessarily getting the energy or nutrients it requires. (This latter situation is common in older people for various physiological reasons, and is known as the anorexia of aging.)

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BDNF One of the most-studied genes is variations on the BDNF gene, which can affect metabolism, eating behaviors, and activity. BDNF codes for brain-derived neurotrophic factor (BDNF), which is part of a family known as neurotrophins. The suffix “-troph” comes from the ancient Greek trophe, meaning “food” or “nourishment”, and generally refers to growth. Thus, neurotrophins are chemicals involved in the growth, development, differentiation, and survival of neurons, the cells of our nervous system. BDNF is found throughout our nervous system, as well as in our blood and other tissues such as the retinas of our eyes, the kidneys, skeletal muscle, and the prostate. Not surprisingly for something so widespread, BDNF has many jobs. For instance:

ΧΧIt regulates the development of neurons as well as neuronal plasticity (i.e., changing neural pathways).

ΧΧIt’s involved in learning and memory. ΧΧIt can affect our perception of pain. ΧΧIt’s involved in behavior (such as aggression or addictions). ΧΧIt’s involved in many mood disorders (such as anxiety or depression),

ΧΧIt helps regulate metabolism, body weight, and energy balance (food energy in versus metabolic or movement energy out).

ΧΧIt seems to play a role in eating behavior and activity, including excessive activity or disordered eating.

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personality disorders (such as schizophrenia or bipolar disorder), and neurodegenerative diseases (such as Alzheimer’s).

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Conversely, exercise can increase BDNF levels, suggesting that even if we have a particular genetic variant of the BDNF gene, we can change how much BDNF protein we actually have circulating.

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Since BDNF is involved in so many metabolic, energy-regulating, eating, and activity behaviors, variations in the BDNF gene can be related to both lower and higher body mass. BDNF protein levels are often low in people who are obese or have Type 2 diabetes.

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BDNF expression can also be affected by other epigenetic factors from the environment, such as:

ΧΧrecreational drug use; ΧΧearly life stress; and ΧΧintellectual stimulation and learning. One particular BDNF allele known as Val66Met (SNP: rs6265) is so named because the nucleotides adenine and guanine vary, which results in a variation between valine and methionine at codon 66. Some research has found that people with the methionine-methionine combination (aka met66) tended to be thinner than those with other combinations (i.e. valine-methionine or valine-valine). Other research in participants of European descent has found that people with the met66 variant of BDNF were more likely to have various types of disordered eating behaviors, such as restricting food, binge eating, or purging. These variants of BDNF didn’t just affect eating behavior; they were also involved in other behaviors like avoiding harm or taking risks.

Other genetic contributors Researchers estimate that about 40-60% of our risk for disordered eating behaviors may be inherited. By the way, remember our FTO gene from above, particularly the rs9939609 SNP? Of course you do! Well, it too may be involved in disordered eating, including restricting-type behaviors. PRECISION NUTRITION

This tells us that FTO’s role is more complicated than simply being a “fat gene”.

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Other sets of genes that may be involved in disordered eating behaviors include:

ΧΧgenes such as MAOA (monoamine oxidase A), NET (NE transporter), and/or SERT (serotonin transporter) related to synthesizing and transporting feelgood neurotransmitters like oxytocin and serotonin;

ΧΧgenes such as CNR1 (endocannabinoid CB1 receptor) and FAAH (fatty acid

amide hydrolase) related to endocannabinoid pathways. These are involved in various processes such as our stress response, maintaining homeostasis, perceiving or dulling pain, and regulating food motivation and appetite (which is why using cannabis often gives you “the munchies” and is used for medical patients who have lost their appetite);

ΧΧgenes involved in monitoring energy balance, such as LEP, which codes for leptin, a hormone that senses how much stored fat we have;

ΧΧgenes related to appetite peptides such as GHRL, which codes for ghrelin, a potent stimulator of hunger; and

ΧΧgenes such as DRD2, which codes for dopamine, related to the

neurobiological reward and decision-making pathways (which are also involved in addictions).

What we found in our sample We asked our test population whether they’d consistently or often done any of the following disordered eating-type behaviors:

ΧΧGoing on a strict diet or cutting back a lot on their eating; ΧΧOver-eating well past the point of satiety; ΧΧEating foods they craved, even though they weren’t hungry; day, or by exercising a lot);

ΧΧWorked out a lot (more than 7 hours a week of purposeful “exercise”); ΧΧPurged (e.g. vomiting, used laxatives, etc.); or

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ΧΧCompensated for their eating (for instance, by restricting their food the next

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working out, etc.

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ΧΧThought a lot about restricting food, going on a diet, specific food choices,

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Here’s what they said:

Figure 7.2: Percent of people reporting disrupted eating and exercise behaviors

OK, so does that mean that three-quarters of our sample has the “genes for disordered eating” because they’ve gone on strict diets? Or that over two-thirds have a genetic inability to manage their appetite because they over-ate, or ate foods they craved when they weren’t hungry? Or does that mean that this is common behavior in 2017? Especially for healthconscious, fitness-oriented people?

ΧΧstressful and anxiety-provoking; ΧΧfocused on “healthiness”, fitness, nutrition and food fads;

isolating; and

ΧΧfull of tasty, easily accessible, “crave-able” foods that are hard to stop eating.

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ΧΧincreasingly preoccupied with social comparison while also being socially

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ΧΧfocused on bodies and “body discipline”;

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Our guess is that it probably means that “average” or “normal” genes (in other words, a genetic makeup without any unusually strong predisposition to do these things) can interact with our 21st-century environment that is:

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What this means for you ΧΧGenes affect our body shape, size, and leanness or fatness. You are at

least slightly predisposed to have a certain physical makeup. However, you are not destined to have a certain physical makeup.

ΧΧGenes also affect the processes that happen when our body shape is

smaller or bigger, leaner or fatter. For instance, if we gain or lose body fat, we can up- or down-regulate genes involved in processes like inflammation or blood sugar regulation.

ΧΧHuman body shape and size is normally variable and diverse. There are many ways to have a “healthy”, fit, and functional body. Bodies come in all shapes and sizes. Some of that is inherited and some it is acquired or influenced by our environment. Even if you have many genetic variations that might predispose you to be a certain body shape or size, you are probably well within the range of “average” in most ways. Few genetic disorders are so extreme that they put you outside of normal human variation.

ΧΧYour body size and shape does not necessarily tell us everything about your genes or your behavior. For instance, we don’t know for sure that:

ΧΧa person with a specific body type is necessarily more or less likely to have problems with their metabolism, or how they eat.

ΧΧa person with a lower body weight is purposely eating less. They may also be genetically more likely to burn off excess energy as heat, for example, or have a stronger “stop eating” signal.

ΧΧa person with a higher body weight is purposely eating more. They may

ΧΧEnergy balance, metabolism, and eating behaviors are all complex phenomena. A change in one can affect the others.

ΧΧOur environment matters. Consider what is around you: the cues, foods available, social norms, stressors, and so forth.

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Despite our natural inclinations and makeup, we can choose to eat less or more, to be more or less active, to eat particular foods, and so on. We’ll look specifically at what you can do in Chapter 12.

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ΧΧMany factors that affect body weight and fat are within our control.

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also be genetically inclined to store nutrients as fat, or have a stronger appetite and reward system.

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What’s up next In the next chapter, we’ll continue with the theme of food to look at food preferences, and how these may be affected by our genetic makeup.

Why we might dislike some foods, like others, and really like others? In this chapter, we'll cover how genetics influence how we experience the taste of food.

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In this chapter, we explore some of the basic metabolic processes, such as how we regulate our blood sugar or thyroid output, and how they might be affected by genetic factors.

What we found: Food preferences

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What we found: Metabolism

CHAPTER 8

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CHAPTER 6

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CHAPTER 8

What we found: Food preferences What you’ll learn in this chapter In this chapter, we’ll look at:

ΧΧsome of the genetic and environmental factors that can affect food choices and preferences, such as whether we like:

ΧΧsweet tastes; ΧΧfatty tastes; ΧΧbitter tastes; or

ΧΧwhat genetic testing can tell us (or not) about food preferences.

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ΧΧcilantro (coriander); and

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Two important points to keep in mind:

ΧΧWhile science is cool, and we have some interesting genetic findings and areas for further exploration, we still know comparatively very little.

ΧΧJust because a genetic test can tell you what kinds of tastes you might

prefer doesn’t mean that it can tell you the “perfect” diet or supplement for you.

As you read this chapter, remember our usual caution:

As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

Why is there no single “best” diet or exercise plan? At PN, we’ve long been interested in the idea of a “best diet” — debunking it, that is. Over the years, we’ve explored human variation and why the concept of a single, one-size-fits-all “perfect diet” doesn’t make sense.

Non-genetic factors can affect nutrition and food choices.

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There are many non-genetic factors to consider in developing an “optimal” nutrition plan for each one of our clients.

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You can read more about that here.

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For instance, we might ask:

ΧΧWhat do people know about nutrition? ΧΧWhat can people do? (For instance, can they cook?) ΧΧWhat can people do consistently? What habits can they stick to realistically and reliably?

ΧΧWhat else is happening in their lives? Are they busy? Working? Students? Parents?

ΧΧWhat’s around them? Do they have access to fresh food? ΧΧHow fit and active are they? ΧΧIf they’re active, in what sports or activities? ΧΧHow old are they? Babies? Seniors? Teens? ΧΧWhat do they like and enjoy? ΧΧWhat’s their cultural and social environment? ΧΧWhat are their food traditions and values? ΧΧHow healthy is their gastrointestinal tract right now? What about their dental health?

ΧΧHow is their overall health right now? Are they injured or ill? ΧΧWhat emotional associations do they have with food? ΧΧEtc.

For example:

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Genetic factors can affect nutrition and food choices too.

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Genetic factors may affect taste preferences.

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This may be because:

ΧΧof the physical structures of tasting (such as how many taste buds we have, or how densely packed they are);

ΧΧof how we process those tastes at the molecular signaling level (for instance, whether we can chemically sense some types of compounds); and

ΧΧwe are naturally predisposed to find some tastes “good” or “compelling”.

Genetic factors may affect what foods we can tolerate. Does food feel physically good… or bad? When you drink milk or eat ice cream, do your intestines regret it? What about a few slices of bread, or some high-fructose fruit? Along with other factors, such as the health of our gastrointestinal tract, our genetic makeup can affect which foods we digest well, and which ones we don’t. We’ll look at food tolerance in Chapter 9.

Genetic factors may affect how we process nutrients.

Vitamin D isn’t the only nutrient whose digestion, absorption, or use can be affected by genetic variation. We’ll look more at nutrient use in Chapter 10.

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In this chapter, we’ll start with food preferences.

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In Chapter 6, we saw how various forms (aka polymorphisms) of the cell receptor for vitamin D, and genes coding for proteins involved in vitamin D metabolism and transport, may affect our risk for chronic diseases or whether we need to supplement additional vitamin D (if we aren’t getting enough from sunlight).

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Why do we prefer particular tastes? Our taste preferences are strongly shaped by the culture and social milieu that we grew up in. If you grew up Anglo in North America, you probably have particular taste preferences and food routines. For instance, breakfast for you might be toast or cereal with orange juice. You probably like things to be sweet, and you might not like too many things that are bitter or pungent. Meanwhile, in Japan, you might be enjoying fish and miso soup for breakfast. In Sweden, you might be tucking into a smoked herring and dark rye bread smorgås (open-faced sandwich) with strong coffee. In Nigeria, you might be longing for your grandmother’s traditional akamu, or fermented sour corn porridge. Tastes are malleable. They can change. We can discover (and learn to love) new tastes and textures with travel — whether we literally go to new places, or simply explore the world of cuisine around us. Genetic data suggest that to some degree, our tastes are also shaped by heredity. If you have had a lifelong preference for sugar, or a lifelong hatred of cilantro (coriander), or struggle to enjoy vegetables… there may be a reason.

How does tasting work? Taste receptors, like other receptors that we’ve learned about, are proteins that bind to particular molecules.

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Like all sensory input (such as sights, smells, and sounds), perceiving and interpreting taste requires an interaction between one or more specialized receptors and our brains.

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Taste receptors

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A chemical must interact with a taste receptor, which sends a signal to our brains. Our brains then decide whether the taste is good, bad, or something to ignore completely.

ΧΧTAS1R receptors detect sweetness. ΧΧTAS2R receptors detect bitterness. ΧΧTRPV1 receptors detect “heat” (e.g., from chili peppers). ΧΧCMR1 receptors detect “cold” (e.g., from mint). ΧΧOther tastes (salty and sour) are detected by ion channels, such as the

epithelial sodium channel (ENaC), or the acid-sensing ion channels (ASICs), which can tell how much of a substance (such as salt) is in a solution.

ΧΧOlfactory receptors in our nose add information from what we smell, which also affects our brain’s perception of taste.

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Figure 8.1: How taste receptors work

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We can vary in:

ΧΧHow many taste receptor proteins we have, as well as the physical structures of our taste buds.

ΧΧHow sensitive they are (or how much of a certain chemical signal they require to “get the message”).

ΧΧHow our brains interpret the information they get from our receptors. ΧΧWhere these receptors are — in addition to those in our mouths, we actually have “taste” receptors throughout our gastrointestinal tract, including in our nasal epithelia, our tracheas, our stomachs, our bile ducts, and our small intestines. These types of receptors even show up in the skin, thyroid, bladder, testes, and bone.

Taste receptors aren’t just for tasting. They may, for instance, be involved in:

ΧΧimmunity; ΧΧour response to prescription drugs; ΧΧappetite control (for instance, TAS2R receptors can communicate

with hormone-secreting cells in our GI tract like those that produce cholecystokinin (CCK), one of our satiety hormones);

ΧΧglucose homeostasis; or ΧΧwhether we like to drink alcohol or smoke. PRECISION NUTRITION

Again, many of these factors are shaped by our genes, which means that genes (to some degree) can affect what foods we instinctively like, or avoid.

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Some examples:

ΧΧVariants in the TAS2R16 gene can affect how we perceive the bitterness of certain plant compounds and our preferences for alcohol.

ΧΧA TAS2R19 variant may predict how well we taste and/or like grapefruit or

quinine (a bitter extract used in some soft drinks like Brio, or the tonic water in your cocktail)

ΧΧTAS2R31 polymorphisms seem to be related to our perception of artificial sweeteners such as saccharin and acesulfame-K. TAS2R4 and TAS2R14 variations can affect whether we notice a yucky aftertaste to steviol glycosides, some of the active compounds in stevia.

ΧΧSpeaking of sweeteners, humans can taste many artificial sweeteners, such as aspartame, neotame, cyclamate, and neohesperidin dihydrochalcone. We can also taste sweet-tasting proteins, such as brazzein, monellin, and thaumatin, that other species like mice can’t.

ΧΧGustin is a protein that promotes taste bud development. Variations in the

CA6 gene that codes for gustin can affect “super-tasting”, which we’ll look at below.

There are many genes that contribute to taste perception and food preferences. And there can be many genetic variations within one person, and between people, which means that we can’t definitely say what a person’s preferences or taste experiences will be.

Do you like sweetness? This makes evolutionary sense. Sweetness usually meant something was good to eat and energy-dense (like honey or fruit). Even newborn babies typically prefer sucrose (sugar) solutions to water. So what are a few genetic contributions to sweet taste preference?

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Most of us naturally prefer sweetness.

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Two genes — TAS1R2 and TAS1R3 — code for taste receptor proteins that react to sweetness.

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TAS1R2 and TAS1R3

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In one study in a European population, researchers looked at two types of sweetness preference:

ΧΧhow sweet something was (intensity); and ΧΧhow much people liked it. They found that genetic variance didn’t explain people’s preference for intensity, but did partly correlate (between 30-50%) to people’s liking for sweetness.

FGF21 FGF21 codes for fibroblast growth factor 21, a protein that’s involved in many metabolic processes, including glucose uptake and the adaptive response to starvation. According to crowd-sourced 23andMe data, about 120,000 people of European descent with the AA (adenine-adenine) variation in the rs838133 SNP of FGF21 were a little more likely to prefer sweet tastes to savory or salty tastes, compared to people with AG (adenine-guanine) or GG (guanine-guanine). Interestingly, almost none of us surveyed at PN had the AA genotype for the FGF21 variant. We were about half-and-half AG or GG. Indeed, the folks who had GG are “meh” about sugar. One bite of it and they’re bored. However, John, who’s an AG, says he’s a “dessert monster”.

Fun factoid!

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The short version, though, is that sweet taste preference is likely just one small part of a much larger system of genetic and epigenetic metabolic regulation.

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The FGF21 gene and its protein product don’t just affect whether we’re more likely to reach for the candy dish. They also play other roles in metabolism, and may have relationships with metabolic health. We’ll look more at FGF21 in Chapter 10.

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Note from Krista: This is true. I have personally witnessed John’s passionate love for cookies.

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SLC2A2 and GLUT2 As we saw in the chapter on metabolism, glucose transport in the body can affect health. Research suggests that it can also affect taste preferences. After we eat something sugary or starchy and break it down to glucose, we need to move it somewhere to do a metabolic job (such as storing nutrients in cells). This is done by a family of glucose transporter proteins known as GLUTs. The SLCA2 gene codes for one of these GLUT transporters, GLUT2, which is found in the pancreas, liver, small intestine, kidney, and brain. Because of these locations, it’s probably involved in local glucose transport as well as sensing overall glucose levels throughout our bodies. The rs5400 SNP of SLC2A2 may be related to sweet taste preferences. Two studies of prediabetics as well as young, healthy people in their 20s found that in both populations, people with a CT (cytosine-thymine) or TT (thyminethymine) at rs5400 ate more sweet foods. These variants of SLCA2 rs5400 and another SNP, rs5393, are also associated with a higher risk of Type 2 diabetes.

What did we find in our sample? You may remember our friend, the FTO gene, from Chapter 7 about body weight. Along with the FGF21 SNP rs838133, the FTO SNP rs1421085 is associated with sweet taste preference. Here’s what we found in our sample:

FGF21 rs838133

CC – higher odds of sweet 16% AA – higher odds of sweet 3% preference preference 53%



50%

GG – typical odds

47%

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TT – lower odds of sweet 31% preference

AG – typical odds

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CT – typical odds

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FTO var rs1421085

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How do you feel about sugar? I LOVE sweet stuff. I find it hard to stop eating sweets once I get started

30%

Sweet stuff is OK but I’m not a sugar-holic.

39%

I don’t really care much for sugar.

30%

First, you’ll notice that genetically, most people had typical odds of preferring sweet foods. And yet, about one-third of people said they loved sweet stuff and found it hard to stop eating sugar once they’d started. Many people’s preferences did not match their SNPs. For instance, many people with a TT allele of the FTO SNP, who should have liked sugar less, liked it more. Some people with an AA version of the FGF21 SNP, who should have liked sugar more, liked it less. You might ask:

ΧΧHow does being a health- and fitness-conscious population affect sweet taste preferences?

ΧΧIs it more likely that the PN sample is less likely to prefer sugar, simply out of healthy eating habits that have retrained their palates?

Right now, we can’t know for sure.

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But the potential effect of practicing several years of good nutrition, as well as exercising regularly and having a lean and healthy body composition (which typically means that glucose and insulin mechanics work as they should) are important factors we can’t ignore.

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ΧΧDo other genes contribute to our taste preferences?

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What this means for you ΧΧYour genetic makeup may affect your preference for sweet foods. Genetic testing may tell you more about your natural tendencies.

ΧΧ23andMe tests for FTO rs1421085 and FGF21 rs838133. ΧΧNutrigenomix tests for the rs5400 variation on the GLUT2 gene. ΧΧYour environment will also affect your preference for sweet foods. If you

grew up eating Sugar Frosted Marshmallow Flakes for breakfast, there’s a good chance that these and other types of sweet processed foods shaped your taste habits.

ΧΧYou probably don’t need a genetic test to tell you if you like sweet foods. Most people already know whether they do.

ΧΧFinding sweetness rewarding doesn’t mean you’re a “sugar addict” or

“doomed by your genes”. It simply means that in an environment where sugar and sweetness is abundant, you’ll have to be careful to make wise choices, and might have to work a little harder to counteract your natural tendencies.

ΧΧTastes can change. Though taste is shaped by our genes, it’s not

determined by it. Taste is one of the most malleable of our senses. We can learn to like or dislike all kinds of foods, regardless of our genetic makeup. You may also notice that your preference for sweet foods changes as you age.

ΧΧRegardless of your genetic makeup, basic nutritional principles still apply. If want to improve your food quality and choices because of health or other reasons, we’ll give you some more ideas in Chapter 12.

You order salad in a restaurant. It comes with an oily dressing, plus avocado, bacon, and blue cheese. What’s your response?

There’s too much lettuce in this blue cheese! If you’re in the second camp, you might have a genetic predisposition for liking fatty tastes and textures.

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Or

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Euw, too rich!

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Do you like fat?

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Whether it’s butter, cheese, avocado, bacon, extra olive oil for dipping, or that peanut butter that’s like a black hole for your spoon, fat can make food delicious. Yet not everyone likes rich, creamy, oily foods. Why not?

CD36 The CD36 gene codes for a glycoprotein, CD36, with many roles. Glycoproteins are proteins with carbohydrates stuck to them (you’ll remember we talked about lipoproteins, proteins that can bind to lipids, in the metabolism chapter). Some of our hormones, such as follicle-stimulating hormone (FSH), luteinizing hormone (LH), and thyroid hormone are glycoproteins. Because glycoproteins can bind to all kinds of molecules, they can do lots of jobs. They’re often cellular receptors. CD36 is a transmembrane protein (a protein that crosses a cell membrane, bridging inside and outside) that binds to things like:

ΧΧconnective tissue proteins; ΧΧimmune and vascular system proteins; and ΧΧlipoproteins, phospholipids, and long-chain fatty acids. That last role is what interests us the most, because CD36 is expressed in our mouths, our small intestines, and our hypothalamus, all sites of taste and energy balance regulation.

This may mean that less is more — for these people, since fat packs more of a taste punch, they may prefer to eat less fat, or find some foods too rich.

The association between having CD36 variations and body weight seems to be consistent in many populations, including people of European, Latin American, Middle Eastern, and African ancestry.

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And, indeed, research suggests that people who are more sensitive to fatty tastes tend to eat less overall and less fat specifically; they also tend to weigh less.

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Conversely, people (such as the folks with an AA at rs1761667) who taste fat less may like it more.

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CD36 bonds strongly with certain types of fatty acids. It seems that people with variants of the CD36 gene (such as a GG or GA at the rs1761667 SNP, or a TT or CT at rs1527483) might perceive fattier tastes more acutely than others.

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Just a reminder that biology in general and metabolism in particular are complex systems: CD36 variations are also associated with:

ΧΧrisk of hypertension and cardiovascular diseases; ΧΧrisk of Alzheimer’s disease; ΧΧrisk of cancer; and ΧΧfatty acid oxidation during exercise. We’ll look more at exercise in Chapter 11.

What this means for you ΧΧYour genetic makeup may affect your preference for fatty foods. Genetic testing may tell you more about your natural tendencies.

ΧΧNutrigenomix tests for the rs1761667 SNP of CD36. ΧΧYour environment will also affect your preference for fatty foods. As with sweet foods, what we grow up with and habitually choose will shape our taste habits.

ΧΧYou probably don’t need a genetic test to tell you if you like fatty foods. Most people already know whether they do.

ΧΧFinding fatty tastes rewarding doesn’t mean you’re a “fat addict” or

ΧΧTastes can change. Though taste is shaped by our genes, it’s not

determined by it. Taste is one of the most malleable of our senses. We can learn to like or dislike all kinds of foods, regardless of our genetic makeup. You may also notice that your preference for fatty foods changes as you age.

ΧΧRegardless of your genetic makeup, basic nutritional principles still apply.

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If want to improve your food quality and choices because of health or other reasons, we’ll give you some more ideas in Chapter 12.

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“doomed by your genes”. It simply means that in an environment where fatty foods are abundant, and often combined with sugars or starches (which makes them doubly delicious) you’ll have to be careful to make wise choices, and might have to work a little harder to counteract your natural tendencies.

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Do you dislike bitterness? While many of us learn to like bitter tastes as adults (think coffee or tea, lime, radicchio (aka red chicory), hoppy beers, and dark chocolate), some of us will have a lifelong aversion to bitterness. In our evolutionary past, we tended to avoid bitterness, which can tell us that certain foods might be bad for us. So it makes sense that genetically, some of us might be more sensitive to bitter tastes than others. Indeed, being extra-sensitive to bitter tastes is a highly heritable trait that is strongly shaped by your genes, and less affected by environment or learning. Because of their chemical composition, many vegetables have a bitter taste that sensitive people can detect, and generally don’t like. Think of foods like:

ΧΧcabbage; ΧΧBrussels sprouts; ΧΧkale; ΧΧdandelion greens; ΧΧrapini; ΧΧgreen peppers; ΧΧturnips and rutabaga; and ΧΧbroccoli.

There are about 25 known genes that code for TAS2R bitter taste receptor proteins in humans. Historically, bitterness usually meant poison, so it was handy to have several mechanisms for detecting it.

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Many of these foods contain compounds (such as sulfur compounds and/or terpenes — yes, related to turpentine) that make them taste bitter.

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Here’s just one example of how this might affect your preferences.

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TAS2R38 A gene known as TAS2R38 affects how well you can taste the presence of bitter compounds such as 6-n-propylthiouracil (PROP), phenylthiocarbamide (PTC), goitrin (found in cruciferous vegetables), and related molecules. TAS2R38 is also associated with different preferences for alcohol. 23andMe tests for the SNP rs713598 on this gene. The G variant of the SNP in TAS2R38 is dominant. This means we’ll be able to taste bitter PROP-like compounds even if we only have one copy, rather than two. If you get one C and one G, you might also be able to taste another type of bitter chemical along with the PROPs. This gives you a double evolutionary advantage, something known as heterozygote advantage.

What we found in our sample For this SNP at least, there were few surprises. People’s preferences were pretty consistent with their predicted genetic correlations.

Picky eaters and “don’t-like-vegetables” people Most of the GGs, the homozygous bitter tasters, didn’t like vegetables, and were also likely to describe themselves as “picky eaters” who would only eat a limited range of foods. The CGs who didn’t like vegetables were also likely to describe themselves as “picky”, suggesting that their heterozygous combination of this SNP leaned towards bitter tasting.

But… there’s always gotta be those few outlier people that mess up the data.

How does being a health-conscious population affect people’s eating habits?

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Once again, it’s worth asking:

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We had a couple of predicted bitter tasters with the GG version of the SNP that liked vegetables just fine. And they said they’d eat anything.

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Conversely, the “I’ll eat anything” crowd was more likely to be CCs or the CGs who probably got the heterozygous variant that didn’t allow them to over-taste bitterness.

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In the case of the PN sample, the more bitter-averse people have learned to like many vegetables, or prepare them in ways that taste better (for instance, by adding a dash of maple syrup to a kale salad dressing, or roasting Brussels sprouts to amplify their sweetness). They tend to prefer cooked vegetables to raw. So, they’re still eating vegetables, but in ways that work for them and their taste preferences.

What this means for you If you’re bitter-taste-averse:

ΧΧGenetic testing may give you insight about why you don’t like bitter foods. ΧΧ23andMe tests for rs713598, a SNP on the TAS2R38 gene. ΧΧYour environment will also affect your preference for bitter foods. As with sweet and fatty foods, what we grow up with and habitually choose will shape our taste habits.

ΧΧTastes can change. Though taste is shaped by our genes, it’s not

determined by it. Taste is one of the most malleable of our senses. We can learn to like or dislike all kinds of foods, regardless of our genetic makeup. You may also notice that your preference for bitter tastes changes as you age.

ΧΧTry a wide variety of healthy foods. You may discover some that you like better.

ΧΧTry foods in season or at different stages. For instance, you may find that baby kale is fine, but mature kale tastes too bitter.

ΧΧTry a wide variety of preparation methods. You may discover that small

Cilantro taste Cilantro, or Coriandrum sativum, is a herb that looks a bit like parsley and is found in many cuisines. And many people don’t like it.

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changes to how you prepare, cook, and/or season foods make a big difference.

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Generally the fresh leaves are known as “cilantro”, while the dried seeds are known as “coriander”.

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Fun factoid!

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Along with our taste receptors, our olfactory (scent) receptors help us perceive particular chemical compounds. Many volatile chemicals in fragrances are aldehydes, a particular type of molecule. A SNP known as rs72921001 is found near a cluster of olfactory receptor genes (genes involved in recognizing the volatile chemicals that make odors), including the gene OR6A2, which likes to bind to several of the aldehyde molecules that give cilantro its recognizable scent. Two other markers, rs2741762, and rs3930459, also located near the olfactory receptor gene OR10A2, may help determine whether someone likes cilantro.

What we found in our sample In our sample, we didn’t have enough people who actively found cilantro disgusting to make predictions about who might dislike it. But in terms of actively liking it (thus definitely not disliking it) the OR10A2 rs2741762 SNP was a bit equivocal. Every single person who should have been a cilantro hater… thought it was yummy. The rs3930459 SNP did a bit better: Out of all the people who actively liked cilantro, only one person should theoretically have hated it, based on their CC variation of this allele. Just under half of the cilantro likers were TTs, people with lower odds of finding cilantro nasty. The rest were CTs and the aforementioned CC.

What this means for you ΧΧGenetic testing can tell you whether you carry the genetic variant for

being less likely to appreciate cilantro. But even if you do carry the “hatin’ on cilantro” variant, you might like it anyway.

ΧΧIf you’re a cilantro hater, you probably don’t need a genetic test to tell you. Ignore the people who mock you for picking off the garnish at Mexican, Thai, or Indian restaurants. You do you.

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friends are flavor troglodytes. It really does taste like soap or dirt to some people.

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ΧΧIf you’re a cilantro lover, don’t keep insisting that your cilantro-hating

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ΧΧ23andMe tests for rs2741762, and rs3930459 on OR10A2.

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What’s up next In the next chapter, we’ll look at food intolerances, which can also affect our food preferences.

Why don’t some foods don’t agree with you? And how much of that may be due to genetic factors?

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In this chapter, we look at some genetic factors related to energy balance, what makes our bodies “naturally” bigger or smaller, and how much lean or fat mass we’re likely to have.

What we found: Food intolerances

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What we found: Body weight and body comp

CHAPTER 9

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CHAPTER 7

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CHAPTER 9

What we found: Food intolerances What you’ll learn in this chapter In this chapter, we’ll look at:

ΧΧthe basic physiology of immune system and inflammatory responses; ΧΧhow food allergies, intolerances, and sensitivities work; ΧΧhow these can be affected by our genes; and ΧΧwhat you can learn from genetic testing about your reactions to PRECISION NUTRITION

particular foods.

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In previous chapters, we’ve explored the idea of whether there’s a single “best diet”. By now, it should be obvious there isn’t. Two important points to keep in mind as you read through:

ΧΧWhile science is cool, and we have some interesting genetic findings and areas for further exploration, we still know comparatively very little.

ΧΧJust because a genetic test can tell you about your risk of particular food sensitivities doesn’t mean that it can tell you the “perfect” diet for you.

And remember our usual caution:

As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

Almost all of us have eaten something that “didn’t agree with us” in some way Of course, this doesn’t mean we have any special sensitivity.

Aside from situations in which We Really Should Have Known Better, many people find that certain, normally innocuous foods — such as bananas, avocados, berries, shrimp, eggs, etc. — are just bad news for them in general.

It’s also important to understand that these and related digestive and autoimmune disorders, like most chronic diseases, are polygenic (i.e. many genes contribute) and emerge from complex interactions between genes, behaviors, and environment.

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It’s important to understand the difference between a food allergy, a food sensitivity, a food intolerance, and a specific disease, such as celiac disease or Crohn’s disease, all of which have a genetic basis.

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In general, we might loosely call these “food sensitivities” or “food intolerances”, but we want to be careful with our language.

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It might just mean we should have said “no” before the third pound of suicidespice chicken wings.

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Antibodies, immunoglobulins, and inflammation An antibody is a type of protein that is produced by the immune system when it identifies a foreign substance, known as an antigen. Antibodies help identify pathogens (such as bacteria or viruses) as well as allergens and toxins. Antibodies can also be known as immunoglobulins, and get the abbreviation “Ig”. There are 5 main antibodies: IgA, IgD, IgE, IgG, and IgM. Antibodies are Y-shaped proteins that share the same general structure, but their tips vary quite a lot. This helps them match a specific antigen.

Figure 9.1: Antibody structure and antigen binding sites

Inflammation can be local — restricted to a small area, such as a patch of skin. Or it can be systemic — affecting various parts of our physiology, such as our respiratory system, our joints, our nervous system, and/or our digestion.

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Typically, the response includes some form of inflammation.

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Over time, with repeated exposure, these immunoglobulins can build up and create a physiological response. This response can be acute (immediate, sudden, often dramatic) or it can be chronic (ongoing, persistent, often lower-grade).

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If our bodies think a particular food or part of a food is harmful or foreign, it’ll create a targeted antibody to defend against it.

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We can often see inflammation emerge in real time, with redness, swelling, rashes, hives or a combination of these symptoms. Chemically speaking, we can also “see” inflammation by the presence of particular substances, such as interleukins (IL), histamine, prostaglandins, and so forth. The expression of all of these, of course, is shaped by our genes.

There are many types of immune and inflammatory responses Because many types of food-related immune and inflammatory responses can have similar symptoms (such as stomach pain or diarrhea), it can be hard to tell which is which. In addition, people can have more than one health condition (for instance, a food allergy plus celiac disease).

Food allergy An allergen is something that causes a histamine response, known as an immunoglobulin E (IgE) immune reaction. White blood cells (mast cells and basophils) release histamine molecules when exposed to an allergen and cause an inflammatory response such as:

ΧΧhives; ΧΧswelling; ΧΧtrouble breathing; and ΧΧa sudden drop in blood pressure.

Food allergies, like other allergies, do seem to run in families. This suggests that we can, to some degree, inherit our allergy risk.

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Food sensitivities tend to present more with things like abdominal pain and bloating, which are related to the actions of immunoglobulin G (IgG) rather than IgE, as in allergies, above. IgG responses tend to be slower than IgE responses, often taking hours or even days to show up.

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Food sensitivity

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Allergies are generally characterized by “sudden and strong”. IgE spikes quickly, but also tapers off relatively quickly, generally dissipating within a few days (though it can last up to a week or two).

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People with health problems such as inflammatory bowel syndrome / disorder (IBS / IBD), Crohn’s disease, or ulcerative colitis tend to have higher IgG levels than healthy controls. IgG antibodies can also infiltrate and affect other tissues, such as the pancreas, thyroid, respiratory system, kidney, lymph nodes, or salivary glands.

Food intolerance Other types of food intolerances, such as the example of lactose intolerance, below, are typically caused by not making enough of the right types of enzymes (for instance, lactase). Without enough of a particular enzyme, we can’t digest some foods properly.

Autoimmune-related problems Gluten sensitivity and celiac disease Gluten is a protein found in wheat, barley, and rye. It’s a type of storage protein known as prolamins, and made up of two proteins: gliadin and glutenin. (Barley prolamins are hordeins, rye prolamins are called secalins and oat prolamins are avenins). Gluten is what gives wheat its elasticity and viscosity so that it can be made into bread, pasta, or other baked goods. You may have heard of “gluten intolerance” or even “gluten allergy”. You may have heard that gluten is the root of all human disorder and dysfunction. (Move over, money and power! Gluten is the new gangster in town!) As with all things, humans are diverse.

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A few people notice a strong, immediate reaction, even to trace amounts of gluten or the proteins in other grains.

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Other people notice some sensitivity to gluten and similar proteins in other grains. Perhaps their joints hurt a little bit; perhaps they get a bit of a stuffy nose; perhaps a slight skin rash.

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Some people — those blessed with iron constitutions — seem to be able to eat anything. They munch on the bread basket cheerfully, crumbs falling out of their mouths, apparently unaffected.

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Why? Well, at least part of this is, of course, genetic. But we don’t yet know all the factors involved.

Celiac disease Celiac disease is an autoimmune condition triggered by gluten. Because it’s autoimmune, which means that the body’s immune system attacks its own healthy tissues, symptoms can be widespread through the entire system. As we’ve seen in our chapter on metabolism and thyroid autoimmunity, genes related to autoimmunity can play many roles. You’ll see here that many autoimmune disorders share common genetic components and there is no single “autoimmunity gene”. As with most diseases, our risk for celiac disease appears to be polygenic. To date, research suggests that genetic factors can explain about 55% of celiac disease cases. Not surprisingly, research has found links between celiac disease and several genes related to immune and inflammatory responses, including:

ΧΧCCR3 codes for the C-C chemokine receptor type 3. Chemokines are a

type of cytokine, or cell signaling molecule, that tell other cells to move somewhere, like directing immune cells to move to the site of an infection. The CCR3 protein is highly expressed in immune system cells such as eosinophils and basophils (types of white blood cells), or T-helper cells, as well as in the epithelial cells of our airway.

ΧΧHLA-DQ, which we’ll look at more below. IL12A helps to direct the activities of T-helper cells.

ΧΧIL18RAP, which codes for interleukin 18 receptor accessory protein. It’s

involved in the binding and signaling of IL-18. Variations in this gene have been linked to inflammatory bowel and Crohn’s diseases, as well as leprosy and atopic dermatitis.

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ΧΧIL12A, which codes for interleukin 12A (interleukins are a family of cytokines).

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integrity of the intestinal lining. It has also been associated with inflammatory bowel conditions. People with variants of MYO9B may have more intestinal permeability, aka “leaky gut”.

ΧΧPFKFB3, which codes for a protein that plays a role in cancer progression, circadian clocks, autophagy, and insulin signaling.

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ΧΧMYO9B, which codes for myosin IXB and is involved in maintaining the

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ΧΧPRKCQ codes for protein kinase C, which is involved in T-cell immune system signaling.

ΧΧPTPRK codes for protein tyrosine phosphatase, receptor type K, involved in

cell growth, differentiation, migration, and division. Levels of this protein are associated with some types of cancer.

ΧΧRGS1 codes for regulator of G-protein signaling 1, which has been used as

a marker of intestinal tissue quality in studies of colorectal cancer. It’s also been linked to mental health and multiple sclerosis (along with IL12A).

ΧΧSH2B3: Remember this little guy from Chapter 6 on metabolism and autoimmune thyroid health? Here he is again!

ΧΧTAGAP codes for a protein involved in T-cell signaling; like other genes in

this list, is linked to autoimmune disorders such as rheumatoid arthritis, Type 1 diabetes, and multiple sclerosis.

ΧΧTHEMIS-coded proteins are related to T-cell maturation, appear in lymphoid tissues, and are highly expressed in celiac disease.

These genes, and others like them, are probably involved in a wide variety of immune system function. For instance, Type 1 diabetes and celiac disease share HLA-DQ, IL2/IL21, CCR3 and SH2B3 SNPs in populations of European ancestry. And vitamin D seems to interact with IL2RA and TAGAP. There’s no test on this, of course. Just get the general idea: It’s complicated.

You may remember that in Chapter 6, we talked about the human leukocyte antigen (HLA) gene complex that codes for major histocompatibility complex (MHC) proteins in humans.

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HLA-DQ is a type of protein that appears on the membrane of what are known as antigen-presenting cells, cells that tell other cells of the immune system (such as T cells) that there’s trouble spotted (such as a pathogen), and it’s time to go to work.

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These proteins, which are found on the surfaces and membranes of cells, regulate our immune system.

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HLA-DQ

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The most significant genetic risk factor for celiac disease seems to encode the HLA-DQ2/DQ8 heterodimers (molecular complexes of two macromolecules stuck together). When immune cells that have HLA-DQ2 or DQ8 on their membranes come in contact with gluten (for instance, in the small intestine), this complex can incorrectly tell the immune system to attack the threat — in this case, healthy tissues. This creates the symptoms of celiac disease, such as gastrointestinal pain and diarrhea. However, as we’ve seen, other genetic variants may also contribute. There are several dozen known factors so far. Some genes appear to be altered only in adults or children with celiac disease, suggesting that age may also change the genetic expression of the disease. Not everyone with genetic variations will develop the disease, but most people who have celiac disease do seem to share some related genetic variants. For instance, 23AndMe tests for a subtype of HLA-DQ2 called HLA-DQ2.5, using a SNP called rs2187668 located in one of the genes encoding HLA-DQ2.5 This subtype is found in roughly 15% of the general population but in over 90% of people with celiac disease, though only about 3% of people with this specific variation will actually develop celiac disease. 23andMe also tests for rs6822844, a SNP that lies in a block of genes (KIAA1109/ Tenr/IL2/IL21) that, along with another SNP in the same area (rs13119723), are strongly associated with autoimmune disease, including celiac disease. Like many chronic diseases with a strong genetic component, the prevalence of celiac disease varies with geography and population.

Yet celiac disease prevalence is increasing quickly. This suggests that environmental or other physiological factors (such as the health or diversity of our gut microbiota) may be contributing.

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Celiac disease is most often found in populations of European descent (North America, Europe, Australia, some parts of South America) as well as populations in India. It is relatively rare in most local populations in Asia.

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Getting diagnostically tested for celiac disease is a painful business. In order to produce enough antibodies to show up on a lab test, patients must eat more gluten. You can imagine how that feels if you already have a sensitivity. It’s sort of like having to get stung by more bees if you have a potential bee venom allergy.

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So, in this case, genetic testing is a much more pleasant option. However:

ΧΧThe solution would still be the same: remove gluten from the diet. ΧΧResearch suggests that non-celiac gluten sensitivity (sensitivity to gluten without overt antibodies) is a thing.

Non-celiac gluten sensitivity Most people in our co-author Krista’s extended family have trouble with wheat and some other grains. They get skin rashes, coughs and snuffles, even intestinal bleeding (in worst cases). You’d think that this would be an obvious case of genetically-determined celiac disease, and perhaps in some folks, it could be. Krista, too, avoids wheat, because the connection between eating it and inflammatory symptoms is pretty clear. Yet Krista’s 23andMe test for celiac risk showed that based on a few different markers, she actually had half the average risk of celiac. So what gives? Is Krista’s family just full of hypochondriacs who are hating on pasta? Or is there another explanation? Many other frustrated people who know they don’t respond well to wheat may, nevertheless, have been told that they don’t have legitimate celiac disease, so they should quit bellyaching (so to speak). In fact, we are coming to realize that non-celiac gluten sensitivity (NCGS) can also be a problem.

That said, over half of people who have NCGS do carry similar genetic variants as people will full-blown celiac disease, and both NCGS and celiac sufferers are much more likely to have these variants than the general population.

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For instance, the researchers in the Nutrigenomix lab looked at the relationship between genetic markers of celiac and α2-macroglobulin, a protein that goes up in response to inflammation. They found that eating more gluten was correlated with more α2-macroglobulin, but this happened regardless of people’s HLA-DQ.

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At this point, there’s no direct-to-consumer test for NCGS, although in research labs we can look at whether inflammatory markers (such as interleukins or immune system proteins) are elevated.

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With NCGS, we don’t see the same chemical markers (such as immunoglobulin A, or IgA, antibodies), or the destruction of intestinal tissue that we see with fullblown celiac disease, but we still see inflammation.

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What we found in our sample With the HLA-DQA rs2187668 SNP tested by 23andMe, each copy of a thymine (T) increases celiac risk. So TTs (thymine-thymine) are most at risk. We had no TTs in our sample, but about 16% of the sample had CT (cytosinethymine), a slightly increased risk. Several people said they were “definitely” intolerant of wheat. Four of those had had a celiac test done, which suggests that they had enough wheat intolerance symptoms to check. Yet none of these wheat-intolerant folks were CTs. All were CCs — the lowestrisk group for celiac. Moreover:

ΧΧAll the people who said they were “definitely” intolerant to wheat were CCs, which, again, is the group that theoretically shouldn’t have problems.

ΧΧA few people said they were “definitely” not intolerant, and could crush

croissants with no problems. Most, not surprisingly, were CCs, but one of those was a CT.

What this means for you ΧΧIf you suspect you may have celiac disease, see your doctor. Genetic

testing can help you see if your risk of celiac disease is higher, but other tests can also confirm whether you have active antibodies to gluten.

ΧΧResearch suggests that even if you do not have celiac disease, you may

ΧΧIf you notice gluten intolerance or other food sensitivities, consider

working with a nutrition coach or dietitian to come up with menus that accommodate these.

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still have a sensitivity to gluten or other related proteins. This may be genetic or may also be related to a wide variety of other factors, such as your lifestyle, your gastrointestinal health, and your environment.

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Food intolerances Lactase persistence / lactose tolerance Lactase is an enzyme, secreted by the brush border cells of the small intestine, that helps us digest lactose, a sugar in milk. Almost all of us can digest lactose when we are born. We need to: Breast milk is our only source of nourishment. But not all of us keep this ability as we age. Being able to make lactase into adulthood — a trait known as lactase persistence — is determined almost completely by our genes, although other factors (such as gut microbiota) can also affect how we digest milk and dairy. In Europeans, particularly northern and western Europeans (such as Scandinavians and Irish), the gene that codes for lactase has remained fairly common, which probably reflects the importance of milk and dairy foods for European populations. The same is true of particular farming populations in eastern / northern Africa, the Middle East, or northeast Asia where herding and dairy consumption are common. Other populations who don’t consume as much milk and dairy — for instance, people with southeast Asian ancestry — tend not to carry this gene. In fact, not being able to digest lactose is more the global norm than the exception. Some estimates suggest that worldwide, about 65% of adults cannot digest lactose.

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The ability to digest lactose probably evolved separately in different populations.

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Figure 9.2: Who can drink milk? Global rates of lactase persistence

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LCT At the moment, we know of many different alleles of LCT, the lactose tolerance gene, that can affect this ability. These alleles tend to travel with different haplotypes. This means that the outcome (being able to digest lactose, or not) is the same, but the reason (a specific gene variant) can be different, depending on a person’s ancestry. For example:

ΧΧ−13838G/A, −13906T/A and −13908C/T variations may have appeared

independently in Tibetans, a traditionally cattle and yak-herding population.

Fun factoid! Tibetans have also crossed domestic cattle (Bos primigenius) with yaks (Bos grunniens) to create a hybrid called a dzo.

ΧΧ−13910*T (aka rs4988235) appears in Europeans, and correlates almost

perfectly with lactose tolerance. This variant almost never appears in SubSaharan African populations, though it does appear among the Fulani of Sudan, who originally migrated from western Africa. It also appears in South America among populations with a history of European colonization.

ΧΧ−13907*G, which is an East African variation appearing in Afro-Asiatic Beja populations and in the Afro-Asiatic Kenyan populations.

in Saudi Arabians and Bedouins — which may not relate to cow’s milk but to camel’s milk. (Despite their high lactose tolerance, the characteristically European −13910*T variation doesn’t seem to appear much in this population either.)

ΧΧ−14009 T>G, one of a few Ethiopian variations.

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ΧΧ−13915*G, the founder mutation for the unusually high lactase persistence

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(known as Nilo-Saharan, from people who lived along the Nile and Sahara).

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ΧΧ−14010*C, typically found in a single haplotype in Kenya and Tanzania

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Other candidate variations still being tested include:

ΧΧ−13779 G>C, found to date only in Amhara people (aka Abyssinians) originating in the northern and central highlands of Ethiopia.

ΧΧ−13806*G, found only in Ethiopian milk drinkers, but actually associated more with non-digestion.

ΧΧ−13909 C>T, another European variation. You may remember in our previous chapter that we explored the idea of ethnic ancestry. Superficial characteristics (such as skin color) don’t actually tell us much about a person’s full set of genes. Supporting this idea is the fact that there are at least seven different rare alleles associated with lactase persistence in one small ethnic group (Somali cattle herders from Ethiopia). In terms of understanding genetic variation, simply lumping this group into a large category called “African” or “black” would be useless at best.

MCM6 and enhancers Along with variations upstream of the LCT gene, there is evidence that related variants in the minichromosome maintenance complex component 6 (MCM6) could also play a role. Although MCM6 doesn’t directly affect lactose digestion, it contains two of the regulatory regions for LCT. You’ll hopefully remember that back in Chapter 2, we talked about how genes are made, the process that regulates whether a gene is made or not, and a key region of DNA called the enhancer.

If enhancers vary genetically, expression of other genes can vary too.

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That’s what happens with the LCT gene and MCM6. Some people have a particular SNP (rs49882359) in the MCM6 gene that increases the activity of the LCT enhancer and leads to the expression of the LCT gene and most lactase.

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Enhancers for different genes are different, since you don’t want all the genes to be made at the same time. You want some to be turned on, and others to be turned off, depending on the situation.

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Sweeps, spreads, and selection These genetic variations, and the other possible variations that we haven’t yet found, give us clear evidence of convergent evolution, or a trait emerging independently, more than once (rather than developing in a straight linear path). As an example of convergent evolution, consider the concept of food in “wrap” format. For instance, wrap-type foods include sushi hand rolls, rice paper wraps, dosas, crepes, burritos, shawarma, and so forth — all having evolved independently in world cuisines. Sushi didn’t directly evolve from burritos (although now we have the sushi burrito, another one of Nature’s magnificent miracles). In this case, we have a situation where various populations are able to produce lactase, but by different pathways. Some of these variations also give us evidence of what is known as a selective sweep. In a selective sweep, a particular variation becomes much more common among a population, to the point where the alternative may be completely lost. Once 100% of the population have a particular form of the gene, that form is said to be “fixed”. Selective sweeps can happen when a beneficial mutation starts out relatively rare, but quickly moves through the population, pushing out genetic rivals. This can often happen when environmental conditions change and favor the new mutation. For example, if climate rapidly changes, genes that were previously neutral but now help the organism adapt to the new climate will likely spread.

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Many have speculated that lactase persistence emerged over and over among various populations because it was helpful for pastoral populations who might have consumed a lot of milk and dairy from cows, sheep, goats, and camels.

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Lactase persistence is an example of positive selection: a genetic mutation that promotes the emergence of new phenotypes, usually by offering some kind of advantage. (The other type of selection is purifying selection, which helps keep an existing phenotype the same.)

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When the Ice Age suddenly hits, everyone with the genes for a furry pelt, short limbs, and plenty of subcutaneous fat will be left standing, while everyone with the genes for squeaky-smooth-as-a-dolphin skin, lanky heat-dispersing limbs, and six-pack abs will be quickly wiped out.

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Genetic studies seem to support this hypothesis, since populations with higher lactase persistence also tend to include milk and dairy as part of their regular diets. (After all, try to imagine northern Europe without cheese or yogurt — no Icelandic skyr, no British Stilton, no Swiss fondue.) Indeed, early humans don’t appear to have had much lactase persistence. The genetic variations that now let some of us enjoy ice cream and milkshakes emerged relatively recently — perhaps 10,000 to 25,000 years ago or so (some estimates even put it around 3,000 years ago). This, again, suggests that we actively adapted to innovations in agriculture, otherwise known as “figuring out how to make animals hold still long enough for us to milk them”. Consistent dietary pressure in a small population can actually help us make pretty quick genetic changes, perhaps within 150-400 generations. This milk-lactase persistence connection isn’t true for all populations. For instance, Dinka and Nuer in Sudan and Somalis in Ethiopia don’t seem to have lactase persistence despite consuming dairy. In genetically lactoseintolerant populations that consume dairy but seem to digest it fine, gut microflora may also be helping out.

What we found in our sample 23andMe tests for the rs4988235 SNP of the LCT gene. The GG (guanineguanine) variant is more likely to be lactose intolerant. In this case, having the GG variant did seem to predict dairy intolerance. All the people who said they had significant problems digesting dairy were GGs. That said: no problems with dairy, while other GGs said their tolerance was sometimes an issue, sometimes not.

ΧΧSome AAs (adenine-adenine, the lowest-risk group) also said they had some

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problems digesting dairy, though nobody said it was as serious as some of the GGs did.

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ΧΧLactose tolerance still varied. One gut-of-steel GG said they had absolutely

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AG or CT? When we were writing up our results for the rs4988235 SNP of the LCT gene, and checking both 23andMe and Nutrigenomix’s reports, we stumbled across something that seemed confusing.

ΧΧ23andMe listed the SNP variants as A/G. In other words, the 3 options would be AA, AG, or GG.

ΧΧNutrigenomix listed them as C/T. In other words, the 3 options would be CC, CT, or TT.

Which one was right? As it turns out, both of them. Genetic analysis uses what are called “reference genomes”. If you ask the question about what variant an individual has, you have to know what they vary from. Researchers have settled on reference genomes, which are compiled and released as a set by the Genome Reference Consortium, an international consortium of experts from some of the top research institutions. The current human reference genome is called GRCh38.p11 (GRC human genome build 38, patch level 11), released in July 2017. (Use that little factoid to stimulate interesting conversations at cocktail parties! It is a crowd-pleaser!)

For example, if there’s an A on one strand, you know there’s a T at the same position on the opposite strand. If there’s a C on one, you know it has a G buddy.

For determining SNP variation, this is fine — the location varies and you don’t really care about it.

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The identifiers for SNPs are unique to each genome build, so the position might be reported as A in one build because one strand is sequenced, and a T in the next build because the complementary strand is sequenced.

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Sometimes, when a build of a reference genome is released, the opposite strand is used.

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Remember that DNA has two complementary strands.

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However, we discovered that 23andMe always uses the letter on the forward (i.e., transcribed) strand, independent of the reference genome. This is an unusual choice. Most research and clinical literature use the genotypes defined in the reference genome. You can see why 23andMe might make this choice, though — it makes it easy to say “This is the A or T that gets transcribed, so this is the one we will use”.

What this means for you ΧΧIf you can’t digest lactase, it may be genetic. ΧΧ23andMe tests for the rs4988235 SNP of the LCT gene. ΧΧIf you still want to enjoy dairy but it gives you trouble, you have a few options.

ΧΧYou can try lactase pills or lactose-free milk. ΧΧYou may find that fermented dairy (e.g. yogurt, kefir, etc.) is OK, as

the process of bacterial fermentation tends to break down sugars. Supplementation with a probiotic may also help.

ΧΧIf you can digest lactase, It may be from one (or more) of a number of different gene variants, depending on your ancestry. Congratulations! Enjoy the lattes, thanks to convergent evolution.

gut microbiota can play a role; you can also be sensitive to other proteins in dairy.

ΧΧIf you have been diagnosed with lactose intolerance, or if you’re noticing

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other food sensitivities, consider working with a nutrition coach or dietitian to come up with menu options and strategies to accommodate your food needs.

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ΧΧThere are other reasons you may be dairy-intolerant. For instance, your

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Hereditary fructose intolerance Hereditary fructose intolerance (HFI), as its name suggests, is a genetic condition in which people can’t break down fructose properly. Fructose is found in fruit, as well as many processed foods (such as soda). People with HFI can’t make enough aldolase B, an enzyme encoded by the ALDOB gene that helps metabolize fructose. If aldolase B isn’t working properly, our bodies can’t properly convert sugar into energy, which can result in hypoglycemia (low blood sugar). Hypoglycemia, if severe and left untreated, can lead to seizures, coma and death. In addition, the accumulation of partially metabolized fructose molecules becomes toxic to the cells and causes liver and kidney damage. People who have HFI may avoid many sweets and fruit instinctively, which means they may never get properly diagnosed. This also means that researchers aren’t completely sure how common HFI really is. HFI is an autosomal recessive disorder, which means that to have HFI, a person must inherit two copies of the ALDOB gene variant that causes the problem. While it can be fatal if not properly treated, people can remain healthy and free of symptoms if they avoid fructose. There are at least 40 known ALDOB mutations that have been linked to HFI. 23andMe looks at four of the most common ALDOB mutations in people with European ancestry:

ΧΧrs1800546, aka A149P (which accounts for about 65% of all HFI-causing mutations in this population)

ΧΧrs78340951, aka N334K (about 5-8%) ΧΧrs387906225, aka delta4E4 (about 3%)

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Together, these mutations make up about 75% of the HFI-causing mutations in this population.

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ΧΧrs76917243, aka A174D (accounting for about 11-14% of mutations)

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What we found in our sample Luckily for our PN team members, nobody had two of the ALDOB HFI mutations tested for: rs1800546 and rs76917243.

What this means for you ΧΧIf you’re concerned about HFI, consult your doctor. You may still have an

ALDOB mutation or have HFI even if your genetic tests for these particular variations are negative.

ΧΧEven if you do not have HFI, you may find that you have digestive

symptoms from eating particular types of carbohydrates known as FODMAPs: fermentable oligo-, di-, mono-saccharides and polyols. This group includes fructose.

ΧΧIf you have been diagnosed with HFI, or if you’re noticing other food

sensitivities, consider working with a nutrition coach or dietitian to come up with menu options and strategies to accommodate your food needs.

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What’s up next In the next chapter, we’ll look at how genetic factors other than food intolerances or sensitivities can affect how we absorb and use nutrients.

In this chapter, we’ll examine some genetic factors that may affect how our bodies digest, absorb, and use particular nutrients.

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Why we might dislike some foods, like others, and really like others? In this chapter, we'll cover how genetics influence how we experience the taste of food.

What we found: Nutrient absorption and use

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What we found: Food preferences

CHAPTER 10

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CHAPTER 8

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CHAPTER 10

What we found: Nutrient absorption and use What you’ll learn in this chapter In this chapter, we’ll look at:

ΧΧgenetic variations that may affect how our bodies respond to specific diets, such as high-carbohydrate or high-fat / ketogenic diets;

ΧΧmethodological problems in drawing clear links between diets and genes;

ΧΧMTHFR variants that affect folate (vitamin B9) use; ΧΧgenetic differences in caffeine metabolism; and particular nutrients, and what other ways you can discover this.

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ΧΧwhat genetic testing may tell you about how your body processes

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What role might genes play in nutrient processing? We all know that person who seems to be able to eat “anything they want” and stay lean and fit. Is that genetic? Possibly. We also know that person who seems to “do everything right” and ends up with a nutrient deficiency or health problem. Is that genetic? Possibly. Nutrient processing (in other words, how our bodies digest, absorb, and use both macronutrients like fat, carbohydrates, and protein, along with micronutrients such as vitamins and minerals) can also be affected by many factors, such as:

ΧΧhow often we exercise; ΧΧhow much body fat we have; ΧΧthe health and diversity of our gut microbiota; ΧΧany medications we might be taking; ΧΧetc. In this chapter, we’ll look at what you might learn from genetic testing about the possible effects of a few dietary patterns. Two important points to remember as you read through: areas for further exploration, we still know comparatively very little.

ΧΧJust because a genetic test may tell you how you might metabolize a

particular nutrient doesn’t mean that it can tell you the “perfect” diet or supplement for you.

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ΧΧWhile science is cool, and we have some interesting genetic findings and

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As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

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As you read this chapter, remember our usual caution:

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How do our bodies process nutrients? When you eat an orange or some ripe blackberries that are high in vitamin C, how does that vitamin C get into your cells? How does your body know how to extract vitamin C — or any other nutrient — from your food, absorb it, transport it where it needs to go, use it in various chemical reactions, and then get rid of any waste products it creates? What if a nutrient needs to be in two places at once? How does your body know which one to prioritize? Does your body prefer a certain form of a nutrient, such as the retinol form of vitamin A, instead of the plant-based carotenoid forms? Does your body prefer to store a particular nutrient, use it immediately, or excrete it? Does your body completely ignore an important nutrient as it sails by? All these and many other processes and physiological decisions are governed by genetics. Although we are more the same than different, there can be subtle genetic differences in how our unique bodies digest, absorb, use, and excrete the nutrients from the food we eat. We can learn about some of these through genetic testing.

Carbs have been getting a bad dietary rap lately. Perhaps you’ve “counted carbs” or bought a “low-carb” product… or cut them out altogether. Perhaps you’ve been told that to stay lean, carbs are the enemy. Or that needing glucose is some kind of moral failure.

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Macronutrients: Carbohydrates

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For instance, researchers studying indigenous populations living on highcarbohydrate ancestral diets full of tubers, fruit, beans, squash, honey, and heritage grains (such as maize or wild rice) reported that these traditional diets didn’t seem to make people fat or sick.

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As usual, science ruins our conveniently simplistic theories.

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In fact, the prestigious British medical journal The Lancet recently reported on one population, the Tsimane of Bolivia, whose diet is over 70% carbohydrate from foods like manioc (cassava) and plantains, and who have some of the healthiest hearts in the world. Such findings of metabolic health in people eating traditional diets have been consistently reported for decades. And instead of high-carb diets inevitably making people obese (as is often suggested about processed-food Western diets), people in many other foraging societies with a traditional high-carbohydrate diet (such as the Hadza people of Tanzania) are smaller and lighter than the world average. (By the way, the !Kung of Namibia, Botswana and Angola, and the Fulani people of northern Nigeria also have a traditionally low body mass index, or BMI, and enjoy cardiovascular health, but live on higher-fat diets. We’ll look more at potential genetic adaptations to higher-fat diets below.) Now, of course, there are many environmental factors involved. For instance:

ΧΧTraditional societies eat certain types of carbohydrates, generally higher-

fiber, nutrient-dense types such as starchy tubers, whole grains, fruit, vegetables, and/or beans and legumes. Traditional carbohydrates are almost always lower in sugar, and digested more slowly, than modern, processed carbohydrates.

ΧΧTraditional societies are not known for their high-tech labor-saving

conveniences. People would have had to work hard to get these carbohydrates (for instance, they might have to dig for tubers, or process maize or cassava so that they’re digestible). industrialized, urbanized regions. This can affect nutrient partitioning, or how our bodies use and store those carbohydrates.

And, of course, there are genetic factors.

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People who have lived a relatively traditional lifestyle for hundreds or thousands of years may also share genetic features that have made them uniquely suited to their local, ancestral diet. Over time, genetic selection helps them adapt to their environmental conditions.

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ΧΧTraditional societies get more daily-life physical activity than people in

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Amylase and copy number variation (CNV) In Chapter 2, we looked at the concept of copy number variation (CNV). This refers to whether chunks of genetic material are repeated. CNVs can also affect how genes work. We used the example of genes (AMY1 and AMY2) that make an enzyme (amylase) that helps us break down the carbohydrate amylose. Digestion starts in the mouth, where salivary amylase begins the process of breaking down the starches we eat as we chew them. Research on various populations has found that those groups with a traditionally high-carbohydrate diet (for instance, people in Japan, who consumed rice, buckwheat, sweet potatoes, and so forth) had more copies of AMY1, while people with a traditionally low-carbohydrate diet (such as people living near the Arctic Circle in places like Yakut, Russia) had fewer copies of AMY1.

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Image adapted from Perry GH, Dominy NJ, Claw KG, et al. Diet and the evolution of human amylase gene copy number variation. Nature Genetics. 2007;39(10):1256-1260.

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Figure 10.1: Average number of amylase gene copies in selected populations

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Copy number variation of the AMY1 gene has also been linked to BMI. People who had more amylase-making genes tended to be leaner; while people with fewer copies of the genes tended to be heavier.

Image adapted from Falchi M, Moustafa JS, Takousis P, Pesce F, Bonnefond A, AnderssonAssarsson JC, et al. Low copy number of the salivary amylase gene predisposes to obesity.

In short: More copies of AMY1 might mean better starch digestion and more effective use in our bodies.

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AMY1 may also play a role in postprandial (after-meal) glucose digestion and disposal. People with more copies of the gene tend to have lower blood sugar after a starch-containing meal.

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Nature genetics. 2014 May 1;46(5):492-7.

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Figure 10.2: AMY1 copy number and body size

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Having more AMY1 may have been a helpful adaptation for populations with high-carbohydrate diets, and it may mean that people from those populations may do well on such diets. We don’t know for sure whether all the lean and healthy indigenous populations of the world eating high-carb diets share this genetic feature of multiple copies of amylase, or perhaps some other mechanism that helps them digest carbohydrates effectively. (For instance, a 2017 study that looked at the relationship between AMY1/2 genes and body mass index also found that AMY1A’s effects also interacted with the actions of gut microflora in digesting starches.) But it’s an interesting working hypothesis.

What this means for you ΧΧGenetic testing may tell you about your ability to digest carbohydrates. ΧΧNutrigenomix tests for the rs4244372 SNP of the AMY1 gene;

people with the AA variant do not digest starch as well people who are AT or TT.

ΧΧMost direct-to-consumer tests do not (yet) test for CNVs. So, we don’t

have any PN sample data to share here. Many CNVs don’t have clear start and stop points (which would normally help us see where the DNA segment occurs). However, higher-end labs do have many techniques for identifying CNVs, and sequencing the exome or genome can help identify CNV.

ΧΧGenetic testing can tell you about your ancestry. As we saw in Chapter 5

ΧΧYour ancestry may also teach you about your food heritage. As we’ve

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seen, food isn’t just about survival or delivering nutrients; it’s about history and culture too. Learning about your genetic heritage may also inspire you to learn about your cultural food traditions and stories. This knowledge and practice is part of a “healthy diet” too.

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with examples like lactase persistence, knowing your ancestry may suggest what types of foods or dietary patterns you might be better-adapted to eat. Research on indigenous populations who have gone back to more traditional modes of eating and living (for instance, First Nations or Inuit in Canada who have gone back to hunting, trapping, fishing, and harvesting wild foods) shows that they become healthier and fitter when following dietary patterns that better suit their evolutionary history.

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Insulin and glucose management Digestion of starches begins in our mouths, with salivary amylase. Another important step in carbohydrate metabolism is signaling the pancreas to release insulin. This, too, can be affected by genetic factors. For instance:

ΧΧThe KCNJ11 gene codes for a protein that regulates insulin release.

Gain-of-function mutations in this gene prevent insulin secretion in response to glucose. This gene has 219 SNPs, six of which have been linked to diabetes (rs5219, rs5215, rs5210, rs5218, rs886288, and rs2285676). 23andMe tests for the rs5219 SNP of KCNJ11. Having a T version of this allele results in a protein that doesn’t respond as well to glucose. When this happens, we can’t clear glucose as well from the bloodstream. More glucose hangs around, causing problems such as hyperglycemia, Type 2 diabetes, and tissue damage.

ΧΧWe aren’t quite sure yet what the protein encoded by CDKAL1 does, but it

seems to be similar to another protein that plays a role in insulin resistance. Some studies have linked SNPs in CDKAL1 (such as rs4712523) to problems with insulin secretion in European and South and East Asian populations, though other studies haven’t found the same links.

ΧΧThe TCF7L2 protein, which is encoded by the TCF7L2 gene, seems to play

Chapter 6 on metabolism reviews other factors that can affect glucose and insulin regulation in our bodies.

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a role in developing pancreatic islets, where we have beta cells that make insulin. If we have the T version of the rs7903146 SNP, we may make less insulin; if we are female we may also have a higher chance of developing diabetes during pregnancy (known as gestational diabetes). This link between the TCH7L2 SNP and problems with insulin has been shown in populations with European, Asian, and African ancestry.

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Our diverse pancreas? The INS insulin gene can contain a variable number of tandem repeats (VNTRs), which we looked at in Chapter 5. As per our discussion of African genetic diversity, also in Chapter 5, in African populations the INS VNTR has been divided into 22 lineages, whereas in non-African populations there are only three (grouped as class I, IIIA, and IIIB). This particular feature is an unusually significant genetic difference between African and non-African populations. For most polymorphisms, only 10%-15% of genetic variation is due to differences between population groups. Yet in the case of this particular gene, estimates suggest that about 28-45% of total genetic variance is due to differences between Africans and non-Africans. It’s not clear why this specific gene diverged so much, but it’s consistent with the hypothesis that Homo sapiens originated in Africa, and that humans who remained in Africa (while others migrated in smaller, more genetically homogeneous groups) had plenty of time to diversify. Even more interesting, we can’t find a modern primate relative for this gene. So we can’t tell which line of the gene is the oldest. Variation in the INS VNTR is associated with a wide range of traits and health conditions, such as Type 1 and 2 diabetes, polycystic ovarian syndrome (PCOS), birth weight, and body fat levels. This diversity may also help to explain different rates of diseases and health concerns in different populations. PRECISION NUTRITION

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What we found in our sample 23andMe tests for these genes and variants:

ΧΧCDKAL1 (rs4712523) ΧΧCDKN2A/B (rs2383208), ΧΧHHEX (rs1111875), ΧΧIGF2BP2 (rs4402960), ΧΧKCNJ11 (rs5219), ΧΧKCNQ1 (rs2237892), ΧΧMTNR1B (rs1387153), ΧΧSLC30A8 (rs13266634), ΧΧWFS1 (rs10012946), and ΧΧPPARG (rs1801282), which we looked at in Chapter 7. They use the above to create a combined Type 2 diabetes “risk score”. Along with genetic data, we asked people whether they’d ever had their blood sugar tested, and if so, what it was. Not everyone had, but some were able to share. The figure below shows the results of our multi-SNP “risk score assessment”, along with known fasting blood glucose test results. PRECISION NUTRITION

Each row is one person. Read across to see each person’s risk score by allele, and what their actual tested blood sugar levels were (if they had been tested via blood test; if not, the space will be blank).

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Figure 10.3: Type 2 diabetes-linked variants in PN population

You might notice a few things here:

ΧΧNobody had the highest possible “risk score”. Most people were, in fact, rather boringly average: a slightly higher risk here, a normal risk there.

ΧΧA few of us had lower-than-average blood sugar. One of those had a homozygous risk allele at MNTR1B.

ΧΧOf the two people who had higher-than-average blood sugar, nobody had

a high-risk homozygous allele. For them, environmental factors were more relevant.

What this means for you to problems with glucose regulation. Mutations with gain or loss of function may affect how your body processes sugars and starches, as well as the function of other hormones (such as melatonin, in the case of MTNR1B) that interact with insulin.

ΧΧ23andMe tests for the following and uses them to develop a diabetes

ΧΧCDKN2A/B (rs2383208), ΧΧHHEX (rs1111875), ΧΧIGF2BP2 (rs4402960),

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ΧΧCDKAL1 (rs4712523),

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“risk score”:

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ΧΧGenetic testing may tell you if you have gene variants that have been linked

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ΧΧKCNJ11 (rs5219), ΧΧKCNQ1 (rs2237892), ΧΧMTNR1B (rs1387153), ΧΧSLC30A8 (rs13266634), ΧΧWFS1 (rs10012946), and ΧΧPPARG (rs1801282), which we looked at in Chapter 7. ΧΧAgain, they use these to create a combined Type 2 diabetes risk score. ΧΧWe probably don’t (yet) know all the genes involved. Even if you don’t have any of the “risk SNPs”, you may have others that affect your carbohydrate tolerance.

ΧΧHowever, other factors besides genetics can also affect your metabolic health and digestion of carbohydrates. These include:

ΧΧThe type of carbohydrate you eat; ΧΧHow much you eat; ΧΧHow active you are; ΧΧHow old you are; ΧΧEtc. ΧΧBlood glucose is an important health indicator. Don’t rely only on a

ΧΧGet regular bloodwork done. Generally, by the time fasting glucose is

monitor and test your glucose throughout the day, including after meals. Postprandial — “after meals” — blood sugar levels will give you a better idea, sooner, of what your blood glucose is up to, compared to fasting glucose.

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ΧΧIf you are a do-it-yourself kind of person, you can buy a home glucose

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affected, people may be well on their way to metabolic syndrome. So having your fasting glucose tested, along with your blood lipids, as part of your regular medical checkup (for instance, annually) is a good idea, especially as you age.

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genetic test. At best, a genetic test can only predict possible risk. It can’t tell you what your blood glucose actually looks like. While blood glucose normally rises and falls as we eat and fast between meals, chronically elevated blood sugar can tell you that there is an underlying health problem.

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ΧΧRegardless of genetic makeup, basic nutritional principles still apply.

Avoiding added sugars, minimizing processed foods, and choosing highfiber, nutrient-rich options such as fruits and vegetables, starchy tubers, whole grains, and beans / legumes is still an excellent strategy.

ΧΧIf you want to know whether your body will thrive on a higher-carb diet,

just try a higher-carb diet for a month or two and see what happens. We’d define “higher-carb” as something that’s more than 50% of your total calories from carbs. Track how you feel and perform, as well as your body weight, body composition, and blood sugar if possible. The data you gather from this simple experiment will probably give you a clearer answer than most genetic predictions we could make right now.

ΧΧIf you’d like to improve your overall wellness, see our strategies for healthy metabolism in Chapter 12.

Macronutrients: Fat High-fat versus low-fat diets: Which is “healthier”? Which diet helps us stay leaner, or lose weight better? The debate has raged for decades. One reason we can’t say definitively how much fat people should eat, or what type of fat is “best”, is because different people respond differently to different diets. Many people are curious about whether genetic testing can answer questions like:

ΧΧHow might eating a higher-fat diet change our:

ΧΧrisk of premature death? ΧΧblood chemistry? ΧΧHow might these changes be connected to our genetic makeup, if they are?

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only associations, not causes.)

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ΧΧWhat specific genetic factors might be involved? (Remember that these are

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ΧΧbody fat / weight?

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Methodological problems in studying dietary responses Research suggests that there are, indeed, genetic differences in how people might respond to higher-fat diets. Yet there is still no clear link between particular genes and particular outcomes. For one thing, few studies exploring genetic responses to high-fat diets have a control group. Few are based on data where people’s food intake was strictly monitored (for instance, people getting a strict menu in a lab). Instead, many studies about dietary intake are based on people self-reporting what they ate, which is known to be quite inaccurate. (What did you eat for lunch last Tuesday? Tuna? What was the exact portion of tuna? Oh wait, was tuna on Wednesday? And maybe it was salmon? Difficult, right?) So, in fact, none of the data in any study that used dietary self-reporting may be particularly useful. This is a common problem in nutritional research in general. Other problems in studying high-fat diets include:

ΧΧ“Higher in fat” may be 30% of total calories in some studies; in other studies, it may be more.

ΧΧFat type may differ from study to study (for instance, comparing unsaturated

To draw good conclusions, we need good data. So, before you get your genetic test results, recognize that the scientific research that many of these proposed genetic links are based on may have significant methodological problems.

Yet some people swear that a high-fat diet helped them lose weight.

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All weight loss diets need to control energy balance (energy in versus energy out). There is nothing magical about eating a given percentage of any particular macronutrient.

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High-fat diets and body weight

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fats to saturated fats, or processed oils to naturally occurring fats such as butterfat).

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This may be because some people find higher-fat diets more satiating due to the effects of gastrointestinal hormones such as CCK, which respond to the presence of fat and protein in the gut. More satiating means people eat less, which then creates an energy deficit that helps them lose weight. Other people, hearing the exciting tales of the miraculous high-fat diet, might leap on the lipid bandwagon, only to discover that, sadly, cheese and butter were not their personal path to getting ripped. Here’s what 23andMe suggests as potential genetic markers and how they might work in European populations:

ΧΧAPOA2 SNP rs5082: Associated with increased odds of obesity in those who ate a diet high in saturated fat.

ΧΧAPOA5 rs662799: Having 2 copies of the G version was associated with

higher BMI among those eating a diet high in fat (30% of calories from fat). The GG version of this SNP is also associated with double the risk of early heart attacks.

Other studies have looked at other links between dietary fat, other SNPs, and BMI. Results are equivocal. For example:

ΧΧSome earlier research suggested there may be a link between the PPAR-

gamma (usually written as PPAR- ) pathway (which you’ll remember from Chapter 7), dietary fat, and BMI. Yet a later 2016 study involving about 11,000 European men and women found that the influence of dietary fat on associations between SNPs in the PPAR- pathway and body size was probably “absent or marginal.” a “genetic risk score” of 32 combined genetic variants found that yes, if people ate more fried foods they were likely to be heavier. But was this due to the greater energy intake (in other words, the fact that fried foods are high in calories), or other factors (such as other behaviors of people who eat a lot of fast food) as well? (If you’re curious, the full list of variants is here: http://www.bmj.com)

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ΧΧA study that looked at whether consumption of fried food interacted with

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We have a lot of informed hypotheses and areas for further research. And we can pretty confidently say that different people have different responses to different diets.

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This doesn’t mean there’s no genetic link, just that we haven’t closed in on a precise connection just yet.

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High-fat diets and metabolic health The rs662799 and rs662799(C) alleles of APO5 have been shown to be associated with weight gain and higher triglyceride levels on high-fat diets in a variety of ethnic groups, such as Han and Guangzhou Chinese, Pakistanis, Caribbean Hispanics, and Israelis of European (Ashkenazi), Middle Eastern (Sephardic) and Yemenite origin. This suggests that for some people at least, high-fat diets may result in a poorer blood lipid profile. One study in a South Korean population looked at people with a variant of the APOA5 gene that made them more likely to have high blood triglycerides. (We looked at triglycerides in Chapter 6.) Researchers asked participants to increase their vegetable intake to six servings a day, and replace processed carbohydrates — in this case, the familiar Korean staple of white rice — with higher-fiber carbohydrate sources: whole grains (such as barley) and legumes. This higher fiber intake resulted in better blood sugar and triglycerides, and improved markers of insulin resistance (HOMA-IR), regardless of their genotype. In other words, no matter what genes you have, eating more vegetables and fiber is a good idea for most people. This study didn’t track weight loss. But, given what we’ve seen in our PN Coaching program, we’d guess that improving food quality and fiber intake might have loosened some people’s belts.

What we found in our sample

However, the APOA5 rs662799 SNP was a different story. With this SNP, AAs were considered “normal” because they’d theoretically gain weight on a high-fat diet. GGs would be theoretically more likely to lose weight.

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In our PN sample, only one person had the GG allele of APOA2 rs5082, so it was hard to draw any conclusions.

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A few people did, however, report that they typically lost weight on a high-fat diet. All were AGs, not GGs.

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Nearly 80% of our sample were AAs. Some AAs did say they’d usually gain weight on a high-fat diet. This would be expected, since high-fat diets are often also high in calories. Other AAs said they’d just stay the same.

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We had no GGs in our sample. The potential rarity of this allele may help explain why some people in the fitness industry sing the praises of high-fat diets for weight loss, but also why many other people find that their personal reality doesn’t match the promise. Of course, again, there are many other factors involved, such as:

ΧΧthe energy density of fat: it packs a calorie punch and is easy to over-eat; ΧΧpeople’s individual preferences for eating more fat, which may also be affected by genetics (see Chapter 8 for more on fat taste preference);

ΧΧwhy people might be eating a high-fat diet in the first place, since some of our PN population might be looking to gain weight on purpose; and

ΧΧhow people are defining and measuring a “high-fat diet”; or ΧΧhow they were tracking their intake and observing the results. So, we can’t really say with certainty that the APOA2 or APOA5 variants really made that much of a difference.

What this means for you ΧΧGenetic testing may tell you whether you might gain or lose weight on a

high-fat diet, or whether a high-fat diet might negatively affect your blood lipids. But right now, the research still isn’t definitive.

ΧΧYou may need to watch your total fat intake — how much fat you eat in general.

ΧΧYou may need to watch your saturated fat intake. calories out) is still the most important factor. This doesn’t mean that if you have the “wrong” genes, you’re doomed to never enjoy butter or bacon again. You might simply have to moderate your intake, stay active, and make generally healthy choices… you know, all the boring non-magical stuff.

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triglycerides, such as getting enough fruits and vegetables, as well as fiber from whole grains and beans / legumes.

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ΧΧOther dietary factors are probably also important for managing

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ΧΧYou may gain weight on a high-fat diet. But energy balance (calories in vs.

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ΧΧIf you want to know whether your body will thrive on a higher-fat diet…

try a higher-fat diet for a month or two, and see what happens. We’d define “higher-fat” as something that’s more than about 35-40% of your total calories from fat. Track how you feel and perform, along with your body weight, body composition, and blood lipids if possible. The data you gather from this simple experiment will probably give you a clearer answer than most genetic predictions we could make right now.

ΧΧInclude a blood lipid profile as part of your regular medical checkups (e.g., annually or biannually). Again, this will give you a much clearer picture of what is actually happening right now, rather than simply speculating based on genetic markers without clear data.

Ketogenic diets High-fat diets are often discussed together with terms like “ketosis” and “ketogenic diet”. A high-fat diet is not necessarily a ketogenic diet. However, given that people commonly equate them, and that some form of ketogenic diet regularly comes in and out of fashion, we thought we’d discuss ketogenic diets here as well. Ketone bodies are particular types of molecules (acetoacetate, betahydroxybutyrate, and acetone) that our liver can make from fatty acids. We can use these for energy, especially at times when other sources of energy aren’t readily available, such as when we’ve gone without food for a while (when fasting, most people go into ketosis within 2-3 days).

We can also raise our blood levels of ketones without changing our diets by taking ketone supplements, though this isn’t necessarily the same physiological state as ketosis via fasting or carbohydrate restriction. (Here’s a link to more reading about ketogenic diets.)

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Dietary ketosis simply means that blood levels of ketones are above a certain level. Again, this most often happens when we are fasting, or when we are eating a very low carbohydrate diet (which tends to be a high-fat diet, hence the confusion between high-fat, low-carb, and ketogenic diets).

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However, as with most other ways of eating, variation in key genes involved in certain metabolic pathways may shape how we respond to this or any other diet.

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A quick skim of diet support groups will reveal that ketogenic dieting has its raving fans — people who tried ketosis-stimulating ways of eating, felt terrific, and now want everyone else to do it.

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FGF21 and HMGCS2 You might remember FGF21 from Chapter 8 on food preferences. The FGF21 gene codes for FGF21, a protein that helps to regulate energy balance and insulin sensitivity. Early work in mice found that the FGF21 protein increased in the liver in response to one of three states: fasting, ketogenic diets, or low-sugar / lowprotein diets. This increases fat oxidation, decreases inflammation, increases energy expenditure and increases glucose tolerance. (Generally, all good things.) However, in humans, FGF21 is only stimulated by fasting for more than 72 hours, not with other diets. Lab models suggest that FGF21, along with other genetic and epigenetic factors, may also affect our response to ketogenic (low-carbohydrate / high-fat) diets. The models show that: 1 | FGF21 protein production is turned on by ketone bodies (namely, acetoacetate) through epigenetic remodeling by a protein called SIRT3. 2 | This then increases the production of a protein called HMGCS2 (3-hydroxy3-methylglutaryl-CoA synthase 2, in case you need to win biology trivia night). HMGCS2 is the first enzyme in a chain of enzymes needed to make ketone bodies. 3 | Ketone bodies make more FGF21 and HMGCS2.

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4 | HMGCS2 then is able to make more ketone bodies, unless there’s a polymorphism in the HMGCS2 gene (rs28937320). There are several types of polymorphisms, one of which can be completely inactive. In that case, a ketogenic diet wouldn’t trigger FGF21, as little to no ketone bodies will be made.

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Figure 10.4: Ketone body metabolism and regulation Image adapted from Newman JC, Verdin E. Ketone bodies as signaling metabolites. Trends in Endocrinology & Metabolism. 2014 Jan 31;25(1):42-52.

Mutations in the HMGCS2 gene are associated with a genetic condition known as HMG-CoA synthase deficiency.

HMG-CoA synthase deficiency isn’t a medical condition that needs treatment. Affected people simply need to avoid long periods of fasting… and probably also need to quit reading diet support groups.

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When eating normally, people with HMG-CoA synthase deficiency are fine. But when fasting, they cannot go into ketosis properly (aka hypoketotic); they may become hypoglycemic enough to go into a coma.

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Most of us won’t have this rare genetic disorder. Yet given the complexity of metabolism, it’s still quite possible that we may differ in our responses to a ketogenic diet.

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If you’re worried you might have this, probably don’t worry too much: It’s a relatively rare, autosomal recessively inherited disorder (in other words, you need two copies of the mutant gene) that only affects fewer than 1 in 1,000,000 people.

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What this means for you ΧΧGenetic testing may tell you whether you have the HMGCS2 rs28937320 variant that could affect your response to a ketogenic diet and fasting. 23andMe doesn’t test for the variant, but other commercial services may. Again, this variant is quite rare, so there’s a strong chance you don’t have it.

ΧΧIf you want to know whether your body will thrive on a ketogenic diet…

try a ketogenic diet for a few weeks, and see what happens. A standard ketogenic diet protocol that is used to treat childhood epilepsy typically uses a 4:1 ratio of dietary fat to protein and carbohydrate combined (in other words, 4 grams of fat per 1 gram of combined protein and carbohydrate). Generally, it takes 2-3 days of eating this way to get into ketosis. If you try several weeks of keto dieting and feel terrific… or terrible… or “meh”… then you have your answer. The data you gather from this simple experiment will probably give you a clearer answer than most genetic predictions we could make right now.

ΧΧExperiment and discover the diet that is right for you. Other people’s results with a given diet may not match yours, in part due to possible genetic factors.

Micronutrients: Folate and MTHFR variations The MTHFR gene codes for the enzyme methylenetetrahydrofolate reductase (MTHFR).

Two common MTHFR polymorphisms (rs1801133 and rs1801131) affect how our bodies metabolize this nutrient. Approximately 60 to 70% of people will have one of these variations. About 10% of people will have both polymorphisms.

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When MTHFR protein levels are lower (particularly when one has two copies of the rs1801133 polymorphism), we don’t process folic acid as well. Homocysteine levels may go up. Higher homocysteine is linked to inflammation and chronic diseases such as heart disease and stroke.

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This enzyme helps us process Vitamin B9, or folate (specifically, folic acid), which occurs naturally in a wide variety of foods and is involved in many physiological processes, including having a healthy pregnancy.

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Table 10.1: Two common MTHFR polymorphisms and their effects

rs1801133 (677 C>T)

rs1801131 (1298 A>C)

Allele

What it means

Allele What it means

CC

Normal folate metabolism

AA

CT

65% efficiency in AC processing folic acid

Possibly impaired folate metabolism

TT

10-20% efficiency in processing folic acid

Number of risks. Complex.

CC

Normal folate metabolism

However, these more common MTHFR polymorphisms don’t cause severe MTHFR deficiency, which is a rarer, genetically recessive condition that can result in major neurological, movement, and psychiatric disorders as people age. MTHFR, like most genes, doesn’t act alone. For the MTHFR protein to do its job, it also needs riboflavin (aka vitamin B2) as a cofactor, a substance that’s required for an enzyme to work. Riboflavin is involved as a cofactor in a wide range of reactions and biological processes. Thus, genes involved in the absorption, metabolism and utilization of riboflavin will influence the effect of whatever MTHFR gene variant one has.

This means that our ability to use MTHFR effectively may depend on many complex factors beyond having a genetic MTHFR variant.

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Right now, we know of about 90 genes in the human genome that code for proteins that depend on riboflavin. There are six genes for riboflavin uptake and conversion to the active coenzymes flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), and two for converting the enzyme to another form, dihydroflavin.

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While there are quite a few genetic testing services out there that offer advice on B vitamin supplementation based on genetic data, the U.S. Academy of Nutrition and Dietetics argues that currently, there isn’t enough evidence about MTHFR polymorphisms to change current folate recommendations.

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Likewise, the American College of Medical Genetics and Genomics actively discourages testing for the two common polymorphisms in the MTHFR gene, arguing that:

ΧΧit has “minimal clinical utility”; ΧΧthere is no evidence that specific treatments lower the risks of high

homocysteine or other health conditions linked to MTHFR variants; and

ΧΧconcerned patients might be better off simply testing their homocysteine levels directly.

What we found in our sample 23andMe tests for a variety of MTHFR polymorphisms. Here’s what we found for the two most common risk variants.

However, it wasn’t clear whether having any of these variants had actually led to any health problems for the affected people.

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Figure 10.5: MTHFR variants in PN population

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What this means for you ΧΧAs usual, it’s complicated. Genes, proteins, and nutrients interact in highly complex ways.

ΧΧIf you have a MTHFR polymorphism, your body may not be as efficient

as others’ at processing folate. This is especially important for women considering pregnancy. However, it’s worth exploring if you have other health concerns that have been definitively linked to low folate, such as anemia.

ΧΧWork with a qualified healthcare provider if you have concerns. You can get your homocysteine levels tested directly with a blood test. Don’t rely only on genetic testing data, which at best is simply a prediction of risk rather than a definitive measure.

Caffeine metabolism You might have noticed conflicting reports in the media about whether caffeine is “good” or “bad” for you. One problem in judging research studies on things like the link between, say, coffee and heart disease, is that we vary genetically in how we process caffeine. The gene CYP1A2 codes for the cytochrome P450 “superfamily” of enzymes, involved in the breakdown of drugs along with cholesterol, sterols, and other lipids. Caffeine is mainly metabolized by the liver enzyme known as P450 1A2, and breaks down into byproducts like theophylline, paraxanthine, and theobromine (the compound in dark chocolate that is supposed to make us feel good).

ΧΧIf you have the “slow” version, more caffeine seems to raise your chronic disease risk.

ΧΧIf you have the “fast” version, more caffeine seems to lower your chronic

It doesn’t mean that your caffeine consumption habits are determined by your genes, though there may be some genetic basis for that as well. Studies comparing genetically identical twins suggest that inheritance may explain between 34-58% of caffeine-related effects and consumption patterns… unless you’re a heavy caffeine user, in which case the contribution of inheritance went up to around 77%.

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However, this is just about how your body processes caffeine.

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disease risk.

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Variations in the CYP1A2 gene at the rs762551 SNP determine how quickly a person will metabolize caffeine.

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For people who were light or moderate caffeine consumers, inheritance seemed to matter less than environment — for instance, what people around them were doing, whether they liked the taste of coffee or tea (for more on food preferences, see Chapter 8), etc. But for people who were heavy caffeine consumers, heredity seemed to play a bigger role… though still not 100%.

What we found in our sample Many of us at PN are big coffee and tea fans — so much so that having high-end coffees and teas is a much-coveted part of PN gatherings. People roast their own beans, argue over the best coffee roast or place in a given city, and would never be caught drinking cheap green tea. You’d think that given this love for the magical alkaloid caffeine, all of us might be fast metabolizers. In fact, only half of us are. Would we change if we knew our caffeine processing type? It’s hard to say, but… If we’re being honest… probably not.

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What this means for you ΧΧThis one might be worth getting tested for… but only if you’ll actually do something about it. If you have the “slow” version but won’t give up your daily pot of coffee, well… you might as well save your testing money and spend it on espresso instead.

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Figure 10.6: Differences in caffeine metabolism in PN population

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What’s up next In the next chapter, we’ll look at how genetic variation might affect our athletic performance and response to exercise.

In this chapter, we look at some of the genetic factors that may shape our response to (and recovery from) exercise and training, and whether we have a “natural athletic type”.

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Why don’t some foods don’t agree with you? And how much of that may be due to genetic factors?

What we found: Exercise and muscle performance

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What we found: Food intolerances

CHAPTER 11

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CHAPTER 9

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CHAPTER 11

What we found: Exercise and muscle performance What you’ll learn in this chapter In this chapter, we’ll look at what genetic testing can tell us about:

ΧΧhow we might respond to or recover from exercise; and ΧΧwhether we can predict our athletic performance or talents from the makeup of our muscle fibers.

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Two important points to keep in mind:

ΧΧWhile science is cool, and we have some interesting genetic findings and areas for further exploration, we still know comparatively very little.

ΧΧJust because a genetic test can tell you (for instance) what kinds of

muscle fiber types you might have, it doesn’t mean that it can tell you the “perfect” exercise plan for you.

As you read this chapter, remember our usual caution: As with most preferences, health risks, and genetic traits, there are many complex, interrelated factors. There is almost never one single gene that inevitably leads to a given result. Any genetic data we share are simply clues for further exploration.

What determines our physical capacity? Maybe you’ve looked out your window early one morning, watched the dedicated runners glide past, sleek and lean, and thought, “That will never be me.” Maybe — likely around December 31 each year — you’ve thought, “I should take up running”. Then you abandoned it around January 12 when your knee said, “Bad idea. Smarten up next year.”

Maybe your personal trainer is telling you that sprinting is awesome, but all you want to do is chill out with an easy trail run. Or the other way around — every time you try to run more than 5 minutes, you want to lie down until the world stops spinning.

Or to do any other type of sport? It’s a good question, one without clear answers. (Yet.)

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Have you ever wondered whether you are “naturally” meant to run (as Christopher McDougall suggests in his book Born to Run)?

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Maybe you’ve already run 3 miles in the time it took us to read this.

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Maybe you are a runner, and wondering how you could be better.

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Human physical capacity is complex. Human movement is complex. There are no known “golf genes”, “parasailing genes” or “hip-hop dance genes”. Yet genetic data can give us some clues about how we might play to our potential.

Are you a tortoise or a hare? Sprint versus endurance performance You might have seen some version of a photo series floating around the Internet that compares a sprinter’s muscular, powerful body to an endurance athlete’s lean, sinewy one. Here’s an example we found:

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Figure 11.1: Sprinter versus endurance athlete

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The usual implication is that if you want to look like a sprinter, train like one.

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Indeed, fitness media is full of workout programs that promise you the body you’re seeking:

ΧΧWant “long, lean muscles”? Do Pilates or yoga. ΧΧWant to be tall, slim, and graceful? Do ballet. ΧΧWant to be jacked and lean? Do Crossfit. ΧΧWant to be a human tank? Do rugby. And so on.

Is it that simple? Nope. Of course, nobody is “genetically gifted” enough to just roll out of bed and into an Olympic-caliber performance or a magazine-cover-worthy physique. In other words, training and nutrition matter… a lot. Certain types of training do, indeed, amplify physical abilities and characteristics such as muscle size or mobility. So you could probably become more graceful after years of ballet classes, more muscular after years of bodybuilding, or more likely to grind other people’s faces into the mud after years of rugby. Yet athletically “ideal bodies” — in other words, bodies that demonstrate elite, world-class performance and physique development — involve a statistically unusual collection of physical characteristics that are, for the most part, present on Day 1 of training. In other words, as Lady Gaga sings, genetically speaking, these top athletes were born this way.

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Although most youth coaches know intuitively that some athletes show up with better physical raw material than others, it’s hard to say exactly what the genetic basis of those gifts might be.

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Yet other events that include sprint or endurance performance also include other elements, such as hand-eye coordination and reaction speed. Our cocontributor John, a highly-ranked master’s-level sprinter, reports that although he could easily match NFL skill position players in a 40-meter sprint, he got “obliterated” when competing in a reaction time contest against them.

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This is particularly true with events at the polar ends of the running continuum (e.g., 100-meter sprints compared to endurance or ultra-endurance), or the size continuum (e.g. gymnastics and horse racing versus basketball and sumo wrestling).

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What parts of athletic performance come from our so-called “genetic potential”? And what parts are a result of training and practice? Exercise physiologists have suggested that many factors could contribute to running performance in particular, such as:

ΧΧCreatine kinase (CK), an enzyme involved in cellular energy production

cycles and in passively moving this energy from mitochondria to myofibrils (muscle fibers) in contracting muscle. Some studies suggest that having the AA version of the rs8111989 SNP in the CK-MM gene, which codes for CK, may improve physical performance in various tasks. CK-MM polymorphisms have also been linked to differences in muscle damage after exercise.

ΧΧMaximal oxygen uptake, aka VO2 max, which may be responsible for the

better endurance performance of athletes from mountain populations, such as the East African highlands, the South American Andes or northern Mexico’s Sierra Madres, home of the famed indigenous Rarámuri / Tarahumara runners. Although we can improve VO2 max a fair bit with training, there’s also a significant genetic contribution: researchers speculate that between 40-50% of variance in oxygen uptake is genetically determined.

ΧΧTendon stiffness, particularly in the lower leg, which could offer more elastic “spring” to a stride.

ΧΧSkeletal structure, including narrower hips. enzyme activity: Since mitochondria are the “power generators” of a cell, better mitochondrial function may mean more sustained energy for athletic activity.

ΧΧPGC-1α is a protein that binds to and activates transcription factors,

Even something that may seem as “fixed” as skeletal structure can be affected by our environment.

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These are a mix of environmental and heritable factors.

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including most nuclear receptors. It’s strongly expressed in skeletal muscle, particularly Type I oxidative fibers. Transgenic mice with more PGC-1α have improved endurance performance and preserve muscle mass better, particularly as they age. (More on muscle types below.) In humans, PGC-1α increases when we exercise, and may coordinate the activation of metabolic genes in muscle in response to exercise. It may also improve the function of mitochondria and peroxisomes, which break down fatty acids.

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ΧΧMitochondrial gene expression, mitochondrial DNA and mitochondrial

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For instance, let’s say we have genetically-identical twins separated at birth.

ΧΧOne grew up in an affluent region with plenty of good nutrition and early-life sports training.

ΧΧThe other grew up in a poor region with frequent food deprivation and

malnutrition, where “sports training” was kicking an old soccer ball around and walking miles to get fresh water.

Although there will obviously be a family resemblance, the second twin will probably end up with a somewhat different build — likely lighter and smaller than the first twin.

There’s no single “sprinter gene” or “marathoner gene”. At last count, researchers have found more than 200 genetic variations that may contribute to physical performance, or how well people respond to training. Even capacities that may seem fairly simple, like “endurance”, are actually complex abilities that depend on many factors. For instance, among endurance athletes from East Africa, how much do cultural factors contribute to developing endurance capacity and performance — for example, is there a “running culture” where children are encouraged and supported to run early in life? Do strong runners have a high social status? What about the diverse geography of countries like Ethiopia and Kenya, which contain both highlands and lowlands — is there an “oxygen advantage” for athletes who grow up at higher altitudes?

Do athletes from these isolated regions have distinct genotypes?

Jornet specializes in FKTs, or “fastest known times” for ultra-endurance activities — for instance, he set the record for a round trip up Mount Kilimanjaro in 2010 (7 hours 14 minutes). His VO2 max is around 85-90 mL per kg of body weight per minute, compared to the average fit male’s VO2 max of between 45-55.

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The Spanish ultra-athlete Kilian Jornet is an example of why it’s hard to answer such questions.

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Or have they simply adapted their fitness and behavior to match to lower-oxygen environments and/or “movement cultures”?

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Similarly, Chris McDougall’s book Born to Run looks at the Rarámuri / Tarahumara population, who have physiological features that make them good runners, but who also live in mountainous regions where running is a favored activity.

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This sounds like he’s a genetic freak designed for endurance work, and maybe he is… but he also grew up as the son of a mountain guide in the Spanish Pyrenees, in a rustic mountain hut at an altitude of about 6,500 ft (2,000 m). So what is responsible for his performance?

ΧΧHis genes? ΧΧHis lifetime physiological adaptation to living at high altitude? ΧΧHis upbringing? ΧΧHis family environment? ΧΧHis training? Of course, the answer is probably “All of the above, and more.” One study looked at genetic polymorphisms that may be involved in endurance performance. Using 46 world-class endurance athletes and 123 controls (all white Europeans in Spain), this study set out to explore whether there was an “ideal endurance type”. Researchers tested the subjects for the following seven genetic variants, involving many factors that are part of endurance performance:

ΧΧThe insertion / deletion variant of ACE, which codes for angiotensin-

producing enzyme (ACE). ACE helps control blood pressure and inflammation. The relationship between variants in this gene and endurance performance were first noticed in high-altitude British mountaineers who were able to climb higher than 7,000 meters without using supplementary oxygen.

we’ll look more at below.

ΧΧAMPD1 Gln12Ter, which codes for an enzyme that deaminates AMP

(adenosine monophosphate) to IMP (inosine monophosphate); variations can lead to impaired exercise performance or myopathy (damage to or diseases of muscle tissue).

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ΧΧThe Arg577Ter variant of ACTN3, which codes for alpha-actinin-3, and which

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genetic variant associated with aerobic performance.

ΧΧHFE His63Asp mutation; HFE codes for the human hemochromatosis protein and is involved in iron uptake.

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ΧΧMuscle-specific creatine kinase (CKMM 1170 bp/985 + 185 bp variant), a

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ΧΧGDF-8 Lys153Arg mutation, aka MSTN, which codes for myostatin, a major determinant of how much muscle mass we can have.

ΧΧPPAR-

(PPARGC1A Gly482Ser), related to genes involved in energy metabolism, muscle fiber type, blood pressure, cholesterol metabolism, and obesity.

Would endurance athletes likely have more of the particular variations that promote athletic performance than average? Yes. But only three of the 46 top world-class endurance athletes had the best possible score for up to six genes. More significantly, none of them had the “perfect profile” of genetic variations. Other researchers took this speculation one step further, asking: Could the “perfect” endurance athlete (at least based on what we currently know about genetic polymorphisms that favor endurance) theoretically exist? These researchers put together 23 polymorphisms that were strong contenders for individually influencing endurance, and considered how likely it was that this “perfect endurance athlete” could exist. They speculated that among people of white European backgrounds, only 0.0005% of them might have this profile. In the United States, there are around 224 million people who report their main ethnicity as white European. This means that using this model, 1,120 people might have this genetic profile. Should those 1,120 people report for marathon training immediately? Well, even if we could find them, lots of other factors might affect their performance, such as:

ΧΧWhether they are motivated to train; ΧΧWhether they have the mental skills to stay focused during long events; ΧΧWhether they want to spend hours pounding the pavement, or would rather

ΧΧWhether people around them are doing the same activity; ΧΧEtc.

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ΧΧWhether they live near somewhere they can train;

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watch Netflix;

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ΧΧWhether they actually like endurance exercise;

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Some researchers suggest that among top athletes, about two-thirds of their athletic capacity can be explained by genetic factors that add up, with the remaining one-third being explained by environmental factors. Yet that theoretically “perfect profile” may also depend on an athlete’s ancestry. In a study that compared white European and East Asian swimmers, top swimmers did have the ACE Ins/Del variation, but top Europeans tended to have the D allele, while the top East Asians tended to have the I version (ACTN3 was also tested, and it didn’t seem to make a difference).

What this means for you ΧΧIt’s complicated. (Darn it.) Most sports and physical activities involve a mix of capacities, only some of which are strongly genetically influenced.

ΧΧWhile we might be able to predict which people have the highest ceiling for athletic development, we can’t predict if a person will ever hit that ceiling. We have some compelling clues and strong hypotheses, but not enough data yet to build a model.

ΧΧMost coaches will probably tell you that they would get better data from simply knowing, observing, and understanding their athletes than from genetic testing. Standing in a field with a clipboard, watching an athlete train for several months or years, is probably the best data of all.

ΧΧHeredity is not destiny. Even if you come from a population of people that

have traditionally done well at a certain activity, it’s no guarantee that you will do the same, or that you have any intrinsic “natural ability” by virtue of heredity. Conversely, even if you come from a population of people that traditionally haven’t done well at a certain activity, it’s no guarantee that you can’t succeed at that activity. PRECISION NUTRITION

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The genetic makeup of muscle fibers Muscles are made up of fibers. Within each muscle fiber are many myofibrils, bundles of long polymers of the proteins myosin and actin. When myosin and actin filaments slide past each other, we get muscular contraction.

Figure 11.2: Muscle fibers

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There are likewise many classes of myosin proteins; myosin II is the type involved in muscular contraction. Nearly 20 known genes contribute to myosin II.

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Actin is an ancient protein that has long been conserved through evolution. In mammals, there are six actin paralogs: different yet related forms encoded by separate genes. One study describes actin as “cellular steel”, because actin can act as an “alloy” to form various mixes of protein-based structures in cells.

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ACTN3 The ACTN3 gene makes a protein called alpha-actinin-3, which (unlike its buddy ACTN2) is only expressed in fast-twitch muscle fibers, which we use for speed and power movements like weightlifting, sprinting, and/or jumping. Research suggests that particular forms of this gene correlate to sprint and endurance performance. 23andMe looks at a particular SNP (rs1815739) on the ACTN3 gene. The T form of the rs1815739 SNP prevents the full alpha-actinin-3 protein from being made, and people with two copies of T lack alpha-actinin-3 completely. Thus, many elite sprinters and strength athletes have the CC type, while few have the TT type. CT is a mixed type. Among athletes, power athletes were much more likely to have at least one working copy of the gene than non-athletes, and at elite levels, nearly everyone has at least one working copy (in other words, they were either CC or CT). Seems pretty straightforward: If you have the right ACTN3 variant, you should be crushing all the strength-power events, right? As it turns out, so far, only running seems to be strongly affected. It doesn’t seem to make a difference for other movements like throwing and jumping. Nor does it seem to matter for team sports. This doesn’t necessarily mean that TT makes you a better endurance athlete (since research suggests that being a TT gives elite cyclists no advantage), but rather that if you’re a TT, you may perform less well in sprint and power-type events.

Nor does a TT type seem to cause any type of disease. This may be because there are other related proteins that can do the job, though less well. For instance, ACTN2, which is expressed in all muscle fibers, might compensate for the loss of ACTN3 in fast Type II fibers.

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On the plus side, while TTs started out weaker in workout programs, they often made significant gains when trained.

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Alpha-actinin-3 may also affect how muscles use oxygen. Research suggests that having less ACTN3 might make muscles greedier for oxygen, which might be metabolically costly and slow the CT or TT people down. Studies in mice have found that muscle fibers lacking alpha-actinin 3 are weaker and smaller, but more efficient and fatigue-tolerant — a perfect recipe for an endurance athlete.

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What we found in our sample ΧΧAbout one-third of us have the “pure fast-twitch” or “sprinter” CC type of ACTN3 SNP variation

ΧΧAbout one-sixth of us have the TT, or “endurance-type”, variation. ΧΧThe rest of us are CT, or mixed.

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Figure 11.3: Distribution of ACTN3 rs1815739 alleles within survey population

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How does this compare to real-world experience? Among the people we surveyed:

ΧΧAbout half of them matched their expected genetic profile, i.e.: ΧΧCCs preferred sprint-type activities. ΧΧTTs preferred long slow endurance-type activities. ΧΧCTs preferred a mix. ΧΧA little less than half of them sort of matched their profile — in other words,

they were CTs who preferred either sprint or endurance-type activities. We counted this as a partial match, since in terms of their muscle fiber makeup, CTs could likely go either way.

ΧΧ5% of them were the opposite: either CC hares who nevertheless preferred endurance-type activities, or TT tortoises who nevertheless preferred sprinting-type activities.

Our PN sample is a handy one for this particular SNP, because it contains many people who have achieved significant athletic success (i.e., who were competitive at the national or international level). Interestingly, there was no clear correlation between a given SNP combination and a predicted “match” for a given sport. In fact, this high-achieving athlete group included someone with the “opposite” SNP to what they “should” have been doing.

ΧΧGenetic testing can tell you what form of the ACTN3 variant you have. ΧΧBoth 23andMe and Nutrigenomix test for the rs1815739 SNP in the ACTN3 gene.

ΧΧIf you like particular activities but aren’t “genetically destined” to do them, enjoy them anyway. You probably won’t get to the Olympics (though based on our sample, who knows?), but if you’re a CC who appreciates a leisurely Sunday morning jog, have fun.

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preferences and abilities if you have a “pure” form of the ACTN3 variant — in other words, either a CC (sprinter type) or TT (endurance type). If you’re a mixed type, you might notice you could go either way.

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ΧΧYou’ll likely notice a difference in your sprint versus endurance

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What this means for you

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How well can you recover from exercise? Being good at movement, sports, and exercise isn’t just about how well you perform during those activities. It’s also about how well you recover afterwards. After all, it’s hard to become a world-class athlete if most of your training time is spent sitting on an ice pack. When we move with vigor, we do minor damage that must be repaired, and we put stress on our structures, which then remodel themselves to manage the strain. It’s this repair and remodeling process that makes us stronger and fitter, not the workout itself.

Non-genetic factors in recovery Age and life stressors play a major role in recovery. You simply can’t recover as well at 81 as you did at 18, nor will you be able to sustain a tough training load if you’re also working full-time as an emergency room doctor with a newborn baby at home. Biological sex is also a factor, though this is usually hormonal rather than genetic per se (in other words, these are not necessarily characteristics linked to X or Y chromosomes). For instance:

ΧΧWomen tend to have more tissue laxity than men (which may mean more

joint injuries) as well as a higher rate of many autoimmune diseases (which are typically aggravated by stress, including training stress). means that they build more muscle faster.

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ΧΧMen’s higher average testosterone, which helps with protein synthesis,

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Then there are emotional, social, and cultural components. For instance:

ΧΧAre you a perfectionist, type-A, “second place is first loser” kind of thinker who would rather tango with an alligator than miss a workout? (Or maybe tangoing with the alligator is your workout?)

ΧΧDo you choose sports and activities that push your limits? Or are you more of a “chill out with a restorative yoga class” kind of person?

ΧΧDo you train on a team where the motto is “Pain is weakness leaving the body” or “Tape it up and get back in there, ya baby”?

ΧΧDid you grow up doing manual labor from an early age, and/or in a family

where sports, exercise, and movement were encouraged? (In other words, did you start building titanium tendons as a toddler?)

Genetic factors in recovery And, of course, many factors in recovery are shaped by our genetic expression. For instance:

ΧΧHow fast and effectively can your body make connective tissue proteins to repair damage in structures like ligaments, tendons, and cartilage?

ΧΧHow fast and effectively can your muscles clear waste products and repair themselves?

ΧΧHow fast and effectively does your immune system respond to the stress of exercise? (Or does it over-respond and start attacking healthy tissues?) fire? Or a carefully controlled tactical operation, complete with fast and efficient cleanup crew?

Given all the factors involved in recovery, there are naturally many potential genetic contributors. Here are just a few.

ΧΧWe still have a lot to learn about what genetic factors affect our recovery from exercise.

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ΧΧIt’s complex.

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We won’t look at all of these in depth. Just get the main ideas:

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ΧΧHow does your body manage inflammation? Is it a constantly raging forest

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Gene / variation

What it’s related to

Angiotensin gene ACE (I/D) (rs4646994)

Creatine kinase and recovery from eccentric muscle lengthening

Actin protein gene See above for more on ACTN3; some forms ACTN3 (rs1815739) may predispose people to exercise-induced rhabdomyolysis (excessive muscle tissue breakdown) Chemokine (cell signaling) ligand and receptor genes

Markers of exercise-induced skeletal muscle damage; soft tissue injuries

CCL2 −3441(C>T) (rs3917878) CCL2 −289 (G>C) (rs2857656) CCR2 −941(A>C) (rs3918358) CCR2 4439 (T>C) (rs1799865) Remodeling of connective tissues; variants (especially in COL5A1) are associated with higher rates of anterior cruciate knee ligament injury, tennis elbow, carpal tunnel and Achillles tendon tears

Creatine kinase gene CKM Ncol (A>G) (rs1803285)

Creatine kinase as well as C-reactive protein (CRP), a marker of inflammation

Insulin-like growth factor genes

Associated with muscle damage (particularly in

IGF-II (C13790G, rs3213221)

men)

IGF-II (ApaI, G17200A, rs680) IGF-II antisense (IGF2AS) (G11711T, rs7924316) IGF binding protein gene

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IGFBP-3 (−C1592A, rs2132570) Inflammatory response to exercise and muscle

IL1B −3737 (C>T) (rs4848306)

damage

IL1B 3954 (C>T) (rs1143634) IL6 −174 (G>C) (rs1800795)

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Interleukin genes IL1B −511 (C>T) (rs16944)

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Collagen repair genes COL1A1 rs1800012, COL5A1 rs12722, rs3196378 BstUI RFLP COL27A1 rs4143245, rs1249744, rs753085, rs946053 TIMP2 rs4789932 TNC

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Gene / variation

What it’s related to

Insulin gene INS 1045 (C>G) (rs3842748)

Codes for the insulin protein, which transports nutrients into cells

Myosin light chain kinase genes MLCK 49 (C>T) (rs2700352) MLCK 37885 (C>A) (rs28497577)

Myosin muscle protein phosphorylation; may affect how well muscle fibers can tolerate mechanical force

Osteopontin promoter gene OPN −66 (T>G) (rs28357094)

Muscle size and weakness; muscle damage marker

Solute carrier family 30 (zinc transporter) gene SLC30A8 (C>T) (rs13266634)

Zinc transport and insulin secretion; associated with recovery

Superoxide dismutase 2 gene SOD2 (C>T) (rs4880)

Recovery from oxidative stress

Tumor necrosis factor gene Creatine kinase (CK) response to eccentric TNF −308 (G>A) (rs1800629) exercise; also regulates muscles’ ability to repair and grow

COL and TNC genes One interesting genetic contribution to recovery is our ability to regenerate collagen proteins, which make up much of our tendons, ligaments, and other connective tissues.

Variations of this gene have been linked to connective tissue disorders such as osteogenesis imperfecta (aka brittle bone disease) or Ehlers-Danlos syndromes, a group of connective tissue disorders that can range from mild joint laxity to potentially fatal complications if the connective tissues of major organs are affected.

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The gene COL5A1 codes for the alpha-1 chain of type V collagen.

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COL5A1 gene variants also seem to affect the mechanical properties of collagenous tissues, such as its stiffness during moderate to intense contractions (for instance, running, jumping, or other explosive movements).

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The rs12722 SNP on the COL5A1 gene has been linked to chronic connective tissue injuries such as Achilles tendinopathy.

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For many sports, having stiffer tendons and ligaments is an advantage, as these tissues can bear more load and produce more elastic energy to help generate force. Conversely, “looser” joints with laxer tissues may be more prone to injuries, as the tendons and ligaments are less able to maintain stability around the joint. Similarly, variations in the COL1A1 gene, which codes for collagen type I, are associated with several complex connective tissue disorders, as well as shoulder dislocations and ruptures of the anterior cruciate knee ligament (ACL) and/or Achilles tendon. Tenascin-C, encoded by the TNC gene, is a glycoprotein that is also involved in wound healing as well as formation of tendons, ligaments, cartilage, and bone. Like variations in the COL genes, variations in the TNC gene are linked to tendon injuries.

What we found in our sample We didn’t test for any recovery-related genetic variants such as the COL genes, but we did ask people about their experiences of joint injury. There were clear variations in people’s experiences: Some people felt like they were always injured; others said they almost never had problems despite regular and rigorous workouts. In addition, only one person who’d been a high-achieving athlete (but started athletics later in adulthood, rather than in childhood, as most others had) reported frequent joint injuries. Most other athletes in the sample said they rarely suffered from joint pain or injuries (or only had problems if they were really pushing their training hard). Does this mean that athletes “naturally” have better recovery?

In our sample, it’s hard to say whether there’s any definite connection, but one possible hypothesis could indeed be that to succeed in athletics, you need to survive the training, and this includes joints as well as muscles.

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Or perhaps that people who started athletics young had better-conditioned connective tissue?

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What this means for you ΧΧGenetic testing services may be able to tell you about some of the gene

variants linked to recovery from exercise. If you’re considering using genetic testing to explore this question, try to find a service that offers as broad an analysis as possible, rather than just one or two exercise-related SNPs.

ΧΧEven if you don’t know your genetic makeup, or don’t have genetic

variants that put you at risk, you still have to train intelligently. The freebie of a genetic advantage (such as some theoretical mutation that gives you Wolverine-like recovery powers) will run out eventually with age and cumulative stress.

ΧΧPay attention to how well you recover from exercise. Look for how often

you feel joint pain or other aches and pains, and how strongly. These may be related to your genetic makeup; they may be related to other environmental factors. Regardless, you still have to address them. If you’re always dealing with some minor problem, consider addressing your recovery more aggressively. You may not be recovering as well as you could be, or you may be following inappropriate training methods for your body.

ΧΧTime is a thing. Tissues remodel on their own schedule, no matter what

you want. Good nutrition and regular movement help (by getting blood flow to the tissues as well as a mechanical signal to kick-start remodeling). Yet aside from “aggressive supplementation” with illegal drugs, we can’t do much about our natural tendencies. Give your tissues the time they need to build a strong foundation, and recover from training.

ΧΧFollow YOUR body’s cues, and don’t try to stick to a rigid workout

schedule, or someone else’s workout plan. It might be too much work for you, or not enough. Schedules and plans are only as good as the bodies that can manage them.

But does exercise always help us lose weight easily?

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Exercise does many good things: improves our fitness and strength; build lean mass (muscle, bone, connective tissues); helps us beat stress; and so forth.

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As we’ve seen, exercise and daily-life movement are part of a healthy lifestyle plan for everyone.

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Does exercise help you lose weight easily?

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Many people who want to be smaller or leaner find themselves frustrated when they hit the gym regularly, and don’t seem to make much progress. This may be due to poor training practices (in fact, it often is). It may be due to other factors, such as not addressing energy balance. It may also, in part, be influenced by genetic factors. The FTO gene seems to be involved in various aspects of energy balance regulation, body size and fatness, along with other possible functions. For instance, recent research in mice suggests that it also contributes to skeletal muscle differentiation. (For more on FTO, see Chapter 7.) One SNP on the gene is associated with both a higher BMI, and seeing different benefits from exercise, at least among people of European descent. In one large study of several thousand people:

ΧΧPeople with the AA variant at rs9939609 tended to have a higher BMI (in

other words, they were heavier), but also lost weight more readily when they exercised.

ΧΧPeople with the TT variant tended to be lighter, but lost less weight when they exercised.

But wait: There’s a wrinkle. In the study used to support this finding, the effect was seen in people living in North America, but not in Europe. This may be because on average, Europeans tend to get more daily-life physical activity, such as walking or cycling, than North Americans.

People with the same ancestry and genetic variant see different effects depending on their environment and choices.

In our experience coaching over 45,000 clients, we’ve found that the simplest explanations are often the most common.

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In fact, it suggests that exercise is more important, and more helpful, for people who might be genetically predisposed to being heavier.

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At first glance, you might think this research says that exercise isn’t as helpful for weight loss people with a TT variant, and some people shouldn’t bother.

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In other words:

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While exercise alone doesn’t necessarily help people lose weight (if that’s their goal), exercise plus a few basic nutrition and behavioral habits, done consistently, does. In other words, no matter what your genetic makeup involves, if you want to lose weight, the pathway to get there is still the same as everyone else’s. Of course, exercise isn’t just about losing weight. Indeed, there are two key problems with predictions about “exercise” and “weight loss”:

ΧΧThere are many ways to exercise. “Exercise” can be all kinds things, ranging from yoga to extreme sports. Different types of exercise will affect our bodies differently.

ΧΧThere are many reasons to exercise, such as having better metabolic

health, better movement quality, less pain, more physical capacity, more strength, more muscle and bone mass, better athletic performance, and so forth.

Weight loss is just one of many possible effects of exercise, but certainly not an inevitable one, regardless of our genetic makeup.

What we found in our sample In our PN sample, this FTO variant seemed to have little relationship to people’s response to exercise. Only about 22% of our sample matched their predicted FTO profile; about 78% did not.

So, at least in our sample… FTO’s ability to predict weight loss from exercise… meh.

What this means for you

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People who “should” have lost weight quickly didn’t (or perhaps even put on mass when exercising); people who “shouldn’t” have lost weight quickly did.

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moderately… or not so much. This might mean you need to adjust your workout plan, be more consistent with exercise, or simply enjoy the health and stress-busting benefits of movement while looking for other ways to keep your body fat and body weight so that it’s in a healthy range.

ΧΧ Movement is important for all of us, regardless of whether we are “genetically optimized” to benefit from it, or whether it helps us lose weight. (More on this in the next chapter.)

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ΧΧYou might find that exercise helps you lose weight quickly… or

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What’s next: Real-world strategies By now, you may be wondering what you can do about your genetic makeup, whether you know you have risk factors or advantages. In the next chapter, we’ll look at all the things that you can do to give yourself the best chance of living a healthy, happy, functional life… no matter what your genetic code is.

Chapter 12: Now that you've learned more about genetic testing, or even gathered your own data, what should you do next?

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In this chapter, we’ll examine some genetic factors that may affect how our bodies digest, absorb, and use particular nutrients.

What does this mean for you?

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What we found: Nutrient absorption and use

CHAPTER 12

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CHAPTER 10

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CHAPTER 12

What does this mean for you? What you’ll learn in this chapter Wow. You made it all the way through. Congratulations. That was heavy stuff, right? A lot to know and remember. In this chapter, you’ll learn what to do with it all. Which is:

ΧΧKeep your sense of wonder. ΧΧKeep it simple. ΧΧKeep asking good questions. regardless of your genetic makeup.

ΧΧKeep contributing to the cause of science, if you can.

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ΧΧKeep practicing the basic good habits that you know are helpful,

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At the edge of possibility In 1868, Swiss doctor Friedrich Miescher extracted a compound from the nuclei of cells, which he called “nuclein”. Today, we call this DNA, the code of life. Around this time, Czech monk Gregor Mendel was breeding peas and developing ideas about how these plants inherited their traits. In 1944, American scientist Oswald Avery created what we might consider the first transgenic bacteria by transferring nuclear material from one type of bacteria to another. In the early 1950s, British scientists Rosalind Franklin and Maurice Wilkins used X-rays to explore the structure of DNA molecules. Chemist Linus Pauling took a crack at proposing the shape of DNA as a triple helix. Eventually, with a landmark research paper in 1953, James Watson and Francis Crick laid claim to the double helix format that we recognize today. It’s hard to believe it’s been only 64 years since then. A baby boomer could have been born the day that Watson and Crick published their paper, and not even be old enough to get the senior’s discount at their local movie theater by the time they’re able to enjoy the benefits of genetic science. We’re writing this book in 2017. And we are standing on the edge of major scientific discoveries that will forever change the way we think about ourselves. Our connections to a larger ecosystem. And our potential.

Now we can literally watch our cells work. Now we can see DNA “unzip” itself. Now we can look at long tangles of chromatin tucked into tiny nuclei. Now we can see proteins folding.

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We’ve gone from making ball-and-stick models of a molecule that we barely understood to fully mapping the human genome.

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We can now create a child with three parents, and treat or even cure diseases that have plagued humanity forever. And we are just a few years away from perfecting the technology that can let us remove genetic diseases or grant additional abilities to our species.

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We can now see processes inside our bodies that previous generations could barely imagine.

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Every day, we discover new genes, new proteins, new pathways, new chemical reactions, new possibilities and opportunities. Our computing and bioinformatics processing are becoming faster, stronger, more accurate. And, of course, genetic testing becomes cheaper and more available. We can speculate about the future. We can imagine great things. But:

What does this mean for you, right now? Let’s go back to the fundamental questions we asked earlier in the book.

4 simple questions to ask about genetic testing You’ll hopefully now remember our 4 questions about how to decide whether a particular genetic test is a good idea. Is this particular test: 1 | Descriptive: Does it tell me something about the person being tested? 2 | Diagnostic: Does it allow me (or a medical professional) to diagnose a problem or characteristic?

4 | Prescriptive: Does it tell me what to do next, or in the future?

There is so much more to learn about genetics. We are just getting warmed up.

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We also hope that you’ve gained a new appreciation of how incredible it is to be a complex biological organism with so many moving parts.

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Hopefully by now you’ve gotten some general ideas about genetics, genetic testing, and how these might relate to your health, fitness, physical makeup, and performance.

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3 | Predictive: Does it allow me to predict some future challenge or occurrence, such as a disease or health risk later in life?

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What’s next for you? Reading through this book, you probably wondered things like:

ΧΧWhat’s in my genes? ΧΧWhat happens if I discover stuff I don’t like in my genetic test results? ΧΧI got my test results back… how do I make sense of them? ΧΧWhat am I supposed to do with all this stuff? ΧΧI’m a health and fitness professional… what do I tell my clients about their genetic potential and risk factors?

Here’s our suggested road map through the land of genetics. There are many ways to navigate this terrain. This is just one way. We think it’s a pretty good one, though.

1. If you’re thinking about getting your genetic code tested, start with why. Get clear on your objectives and reasons. Ask yourself questions like:

ΧΧWhat would be useful to me? Why? ΧΧWhat do I plan to do with the results? Why?

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ΧΧWhat emotional response might I have to my test results? Why?

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ΧΧWhat am I comfortable with knowing or not knowing? Why?

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ΧΧWhat would I like to find out? Why?

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2. If you’ve already had genetic testing done, start with how. Understand how things work and what that means.

ΧΧHow was this sample collected? ΧΧHow was the test done? ΧΧHow were the results presented? ΧΧHow was research and evidence used to support any claims made? ΧΧHow were the possibilities and risks discussed? ΧΧHow might the results be shaped by the agenda of the testing agency? (In other words, what else is the testing agency looking to sell?)

3. Once you have your results, start with what. Consider what you need to move forward with what you have learned. Ask yourself questions like:

ΧΧWhat information is useful, and what is not? ΧΧWhat does this information mean for how I think about my potential, and my risks?

ΧΧWill the results change my future choices? If so, how? ΧΧWhat more do I need to know in order to make informed decisions?

ΧΧWho can coach me through my choices in the future, once I know what (if anything) might help me?

If you have survived to healthy, functional, and relatively fit adulthood, congratulations! You have probably escaped most of the congenital genetic conditions with major, inevitable effects.

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Few genetic tests offer clarity or certainty.

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Genetics: The game of probability

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ΧΧWhat kind of health professional can help me answer the questions I have?

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You probably have few “for-sures” in your genetic code. More likely, you have complex probabilities. You have possibilities. Maybes. Risks. Could-bes. Your game, should you choose to play it, is optimizing your genetic potential while reducing your risks. The problem is, we don’t know exactly what this means for every single genetic combination, or even most individual variations. However, based on the research we do have, we can say what optimizes some potentials and reduces some risks. Here are some solid, evidence-based strategies for doing that.

What to do next Think like a scientist. Appreciate the complex, wondrous universe of biology. DNA unites us with all living things in the world. We are all connected. Your cells carry ancient stories, and at least parts of those stories can also be understood by every other organism — whether octopus or orchid, mouse or mushroom, bird or bacteria. Be critical, skeptical, and curious.

Be aware of your own biases and desires.

If you are someone who likes data and exploration, you might also be tempted by the utopian promise of “quantifying the self” and “optimizing” or “hacking” human function.

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If you have a mysterious health problem, or are someone who’s always looking for the “edge”, you will naturally want to find solutions, or connect dots that aren’t related.

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Notice when you may be engaging in magical thinking (“Maybe genetic testing will solve all my problems!”) or becoming emotionally attached to the results that you get.

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Ask what evidence supports any claims made.

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This isn’t bad. It’s normal. Simply be aware of your own perspective and potential prejudices. No amount of testing on its own will change your habits. A genetic result will not somehow scare or motivate you into sustainable behavioral modification. Expect complexity. There’s no single, simple explanation. Distrust “one size fits all” or “one factor explains all” solutions, and people trying to sell you something based on them. If someone is giving you an answer that sounds too straightforward (such as “You have Gene X, so you should do Exercise Program Y”), that’s probably not the whole picture. Gather your research team. If you don’t have enough training to interpret the evidence, look for a genetic counsellor and/or other qualified healthcare provider who is informed and relatively unbiased. Help research be better. Share your data, if you’re comfortable. 23andMe asks users to answer survey questions about their experiences, to better correlate the genetic data with what actually happens.

The more data we gather, the better science works.

Embrace and discover your ancestry.

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You can also contribute to things like the Personal Genome Project, Human Longevity Inc. (HLI), 1000Genomes, or National Geographic’s Genographic Project.

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Some genetic tests might not even apply to you if your specific ethnic group hasn’t been well-studied. (And, if possible, demand that your group is studied. Science should not be an elite club.)

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Recognize that your ethnicity, heredity, and ancestry will affect your results.

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Be curious about the paths your ancestors travelled. A very long and complicated series of events led to you being here right now. Infinite biological equations and social choices had to happen to make you (or even to give you eyes and a brain so you could read this). Where are your people from? How did they get here? Learning about your history can add to your own sense of identity and pride. Be curious about food, movement, and health traditions in the regions where you’re from. Some traditions may be about convenience or belief. Others may reflect actual data on what has worked in the past for a specific population. For instance, if people where you’re from never drink milk but always win weightlifting events, this may tell you that your population of origin likely doesn’t have the lactase persistence gene, but could have an inherited tendency for being strong.

Start gathering data for your “Owner’s Manual”. The “Owner’s Manual” is a concept that we use at Precision Nutrition to help clients and coaches create an individualized, data-based “handling instructions” for themselves and their lives. An “Owner’s Manual” isn’t a real thing (although it could certainly be if you kept a physical file of your observations). It just means noticing and gathering evidence from your own experiences, and recording it (whether mentally or literally).

If your genetic test says you may have one trait, but you don’t seem to, that’s useful data.

Medical tests can be extremely helpful. They can give us an objective picture of what is actually happening in our bodies, based on known and relatively reliable indicators.

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Be an informed assessor of your own health and fitness.

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If your genetic test says you may have a high risk for a certain health condition, but you’re not sure, that’s useful data too. Go and get other types of tests done, such as blood work.

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Corroborate any genetic test results to observed reality.

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At the same time, you can also observe many simple and important indicators on your own. Such as:

ΧΧWhat is your daily energy level like? ΧΧHow much pain or inflammation do you have day-to-day? ΧΧHow well do you sleep, and for how long? ΧΧWhat’s your general mood like? ΧΧHow’s your digestion? ΧΧHow much body fat versus lean mass do you have? (Even if that’s just a general guess.)

ΧΧHow often do you get sick? ΧΧAre you able to handle physical challenges of daily life? What about more strenuous challenges?

And so on. In our coaching programs, we teach clients to identify and interpret their own basic physical cues in order to get a simple snapshot of their own overall health.

Exercise regularly. Recognize that everyone benefits from exercise, movement, and activity. Regardless of your genetic makeup, your body will work better when you’re consistently active. PRECISION NUTRITION

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For instance, exercise and movement help us:

ΧΧstay mobile and functional; ΧΧkeep our balance and stay agile, preventing falls; ΧΧmanage stress; ΧΧprocess and partition nutrients (in other words, food does its job properly); ΧΧbuild lean mass (muscle, bone, and connective tissues); ΧΧkeep our brains smart and nervous system responsive; ΧΧprevent age-related muscle loss (aka sarcopenia); ΧΧdigest our food better by promoting gastrointestinal motility; ΧΧthink in different ways with our kinesthetic “movement brains”; and ΧΧmaintain healthy body fat levels. Exercise can also help us prevent, treat, and/or manage many chronic diseases as well as slow the aging process. Exercise may be one of the most powerful tools in our toolbox, as it improves almost everything, often relatively quickly. For instance, exercise:

ΧΧmay briefly decrease methylation in skeletal muscle; ΧΧincreases messenger RNA (mRNA) expression; and such as mitochondrial function and fuel use (e.g. PGC-1α, transcription factor A, mitochondrial (TFAM); peroxisome proliferator-activated receptor δ (PPAR-δ); and pyruvate dehydrogenase kinase, isoenzyme 4 (PDK4) and so forth).

So don’t get frustrated or criticize yourself if you’re working hard but not seeing the same results as your buddy who seems to be a “natural” athlete.

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Recognize that genetically speaking, not everyone sees exactly the same results from exercise.

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At the same time…

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ΧΧchanges the protein levels of many genes that regulate metabolic factors

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Or, if your body “naturally” seems to respond well to exercise, don’t expect other bodies to do the same (especially if you’re a coach who works with all kinds of clients). Exercise helps us metabolize sugar and fat properly, but we vary genetically in how well or quickly we respond to exercise in this way. For example:

ΧΧOne study looked at the rs1801282 variant on the PPARG gene that codes

for PPAR-γ, which helps regulate metabolism of glucose and fatty acids. While some people with a particular variant of rs1801282 (also known as the Pro12Ala variant) were better at clearing glucose during exercise, everyone benefited metabolically from exercise.

ΧΧIn another study, people with the -514C allele of LIPC were more likely to significantly improve their insulin sensitivity if they exercised regularly.

ΧΧVarious APO genotypes affected people’s lipase (fat-mobilizing enzyme) activity.

And so on. Other genetic variants may affect a wide variety of exercise results, such as heart rate, vascular function during exercise, and other measures of aerobic performance. If you have a particular variant of the AMPD1 gene, which codes for an enzyme known as adenosine monophosphate deaminase (one of the enzymes used to process ATP), you might get more muscle pain and cramping during intense exercise. Though you aren’t alone: At least one world-class runner has this variant.

And not someone else’s. Your mileage may vary.

If it’s pretty clear you’re a fast-twitcher, enjoy your strength and power sports, and don’t feel like you “should” be doing distance running.

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If you’re looking for the best results possible, then try to match your physical activities to your most informed hypotheses about what your unique body prefers. Over time, gather data about your hypotheses and refine your action plan.

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Choose physical activities that suit your body as much as possible.

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Your body is your body.

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If it’s pretty clear that you’re a slow-burner, enjoy your endurance sports, and don’t try to beat the world high-jump record. (Well, you can try, just don’t get mad if you don’t succeed.) Of course, if you enjoy a sport that you aren’t naturally well-suited for, go and have fun doing it. You probably won’t be the best in the world at it, but who cares?

Control what you can control. We can’t control what mom and dad (or, these days, maybe mom, mom, and dad) gave us. We also can’t necessarily control many environmental factors, such as airborne pollution, chemical contaminants in our food and water, occupational hazards, early-life trauma, and other things that may affect our epigenetic expression. We may find ourselves struggling to maintain a healthy body composition if we don’t have the skills and habits to do so, or if we have underlying genetic factors that make this more difficult. Our skeletons may be wider or narrower; denser or lighter; shaped this way or that way. But, for the most part, we have a fair bit of control over such factors as:

ΧΧwhat we eat; ΧΧwhether we drink alcohol; ΧΧwhether we smoke; ΧΧwhat drugs we take (assuming that these are non-life-saving medications, of course);

ΧΧhow we respond to daily-life stressors; and ΧΧhow and whether we choose to reproduce and pass on our DNA to offspring.

Now, that’s a bit of a disturbing analogy that makes genetics sound like a professional but ambivalent hitman, but it gives you the idea: What’s around you matters.

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You may have heard the expression, “Genetics loads the gun; environment pulls the trigger.”

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Consider your environment.

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ΧΧhow often and intensely we exercise and move around;

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This includes “real things” like chemicals as well as more intangible things like social support. (See below.) One researcher has coined the term “exposome” to describe all the environmental factors that might affect genetic expression throughout our lives. Environmental stressors (such as pollution, toxic chemicals, medications, or pathogens like viruses) can all affect expression. This, in turn, can affect things like our metabolic health. Regardless of your genetic makeup, it’s probably not a great idea to stew in a soup of potentially toxic or DNA-altering chemicals. Look around your immediate environment and consider the products you’re using, and/or what you’re exposed to. Consider whether any of this can be improved.

Consider your ability to respond to stress. Environmental stressors also affect the length of our telomeres, which work at the ends of our DNA strands like the little caps on the ends of your shoelaces that prevent them getting frayed. (The term comes from the ancient Greek telos, or end, and meros, or part. So telomeres are literally “end parts”.) The longer our telomeres are, the healthier we’re likely to be, and the less cellular aging we likely have. Shorter telomeres, on the other hand, indicate more aging and degeneration — again, sort of like a shoelace fraying. So, how long our telomeres are can tell us about how healthy our DNA is, and how quickly or slowly we’re aging in a biological sense. PRECISION NUTRITION

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Figure 12.1: Telomere shortening

Being exposed to environmental stressors like chemicals can shorten our telomeres, but so can social stress.

However, stress isn’t just what’s around us. It’s how we respond to what’s around us.

When humans and other mammals get ongoing social support in an interesting and engaging environment with a small dose of growth-promoting “good stress”, they thrive.

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If you’re a parent, choose wisely.

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So even if you’re exposed to a social stressor (such as something bad happening to you as a child), if you can respond resiliently to that stressor and have other people supporting you, you’ll have better DNA health than someone who is isolated and panicking.

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For instance, a study that looked at women caring for a child with a major disability or serious chronic illness found that the long-term stress of caregiving and worry over a child’s health was linked to shorter telomeres. Feeling socially isolated and lonely can change our genetic expression too.

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Parents can play a major role here, not just in offering their own genetic material, but also in creating surroundings that help their children optimize their epigenetic expression. For instance:

ΧΧBuild your own healthy habits. Many of our clients come to us because

they’ve decided to be healthy role models for their children. And, as a parent (especially if your children are younger and they live with you), you can shape their food and activity choices… which will be a lot easier if your own fundamental habits are in place.

ΧΧMake wise choices before conception and during pregnancy. This goes for you too, dad. Both parents’ genetic material can be affected by their own health habits. So if you’re hoping for a baby but haven’t gotten started on the project yet… start building those healthy habits now. And, of course, if you’re currently pregnant, choosing healthier options will improve what’s known as the maternal effect — the role that the mother plays in her offspring’s epigenetic expression. (More on this below.)

ΧΧIntroduce your child to a wide range of tastes. (If you’re currently pregnant, try a wide range of tastes yourself.) Evidence suggests both prenatal and early childhood exposure to various foods helps set taste preferences for later on. If you want your kids to eat healthy foods, eat healthy foods yourself, and make them readily available.

ΧΧIntroduce your child to a wide range of microbes. Research suggests

that pre- and post-natal exposure to diverse microbial environments (like bacteria, viruses, and fungi) can change the epigenetics of the immune system. Don’t keep your house too antiseptically clean, and it’s probably OK if your kid licks the dog. we’re moving, and when we’re connected to other people. Even if you got every single one of the “exercise nonresponder / metabolic disruptor / excess adiposity” genes, you can still (to some degree) change the expression of these, especially if you start as early in life as possible. (But of course, it’s never too late to make some healthy changes.)

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our epigenetic expression in a bad way. It affects both the smoker and anyone else exposed to secondhand smoke, especially a child with a developing system.

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ΧΧDon’t smoke. This should be obvious, but it’s pretty clear: Smoking changes

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ΧΧBe active as a family. Whatever your genetic makeup, we’re healthier when

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Maternal effects Although, of course, both parents contribute genetic material to their offspring, given the mother’s role in gestation, she can have a powerful effect on her developing fetus’ epigenetic expression. In particular, what she eats and the environment she’s in can affect the outcome. For instance:

ΧΧIf mothers have persistently high blood sugar (known as hyperglycemia)

during pregnancy, this may affect methylation of the fetus’ leptin gene, and potentially the child’s body fat levels as they mature.

ΧΧHigh-fat diets during pregnancy may affect expression of the fetus’

adiponectin genes; in particular, methylation may go up while acetylation may go down. This may mean that later in life, the child may have a higher risk of some types of metabolic problems such as Type 2 diabetes or cardiovascular disease. (It isn’t clear whether the type of fat matters here, though.)

ΧΧIn a famous study on the effects of undernutrition during pregnancy,

offspring of mothers who’d endured the so-called Dutch Hunger Winter famine during WWII showed hypomethylation on the IGF2 gene, later correlated with higher risks of cardiovascular disease.

Along with physical health, mothers’ mental and emotional health is also important. For instance, the NR3C1 gene codes for the glucocorticoid receptor (GR). Glucocorticoid hormones, such as cortisol, are involved in our stress response and inflammation.

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In other words: A stressed mother may mean a stressed child.

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When mothers were anxious, depressed, or otherwise distressed during pregnancy, this often affected methylation of their fetuses’ NGFI-A binding site in NR3C1. This epigenetic change then predicted increases in infants’ HPA stress reactivity.

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Our stress response is organized by a complex set of feedback loops known as the hypothalamic-pituitary-adrenal (HPA) axis. HPA axis function shapes how we are able to respond to stress, and how generally anxious and physiologically or psychologically reactive we tend to be.

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Other research suggests that there are similar links between mothers’ mood or distress level during pregnancy, and their offspring’s epigenetic expression of other genes such as HSD11B2, which codes for a protein that converts cortisol to cortisone and vice versa, as well as protecting other tissues from the damaging effects of corticosteroids. Of course, as a parent, you can’t control all the factors involved in your child’s epigenetic expression. (See above: Control what you can control.) Rather than worrying too much about the genetic blueprint you or your child got, focus on how you can help build the best house possible from those blueprints.

What’s next for you? At Precision Nutrition, our motto is “Life-changing, research-driven nutrition coaching for everyone.” Genetics (and genetic testing) highlight one of the fundamental tensions of coaching:

ΧΧThe outer limits of our health, ability, function, and performance are

determined by factors outside our control (factors that include genetics).

ΧΧAt the same time, we have tremendous potential for change, growth, improvement, and adaptation.

So, for instance, a person who is 5 feet tall can learn to run, jump, and throw a basketball better — perhaps even at a world-class level of shot accuracy. But that person will never be able to dunk a basketball like a 7-footer.

On the other hand, most of us will never find most of those limits, because the playing field of our physiology is wider and bigger than we can imagine.

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We contain limits, but also opportunities and potential.

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Disciplines that specialize in finding the boundaries of human function and performance have discovered that the human body has far greater resources of recovery, resilience, and capacity than most of us realize.

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At some point, we bump up against our own limits, and some tasks are simply impossible for some people.

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So, if you’re curious about what that looks like for you:

ΧΧTreat your body as a set of possibilities rather than limitations. Explore, build, practice, and see what you can do after putting in the reps.

ΧΧConsider coaching. Coaches specialize in finding, bettering, and amplifying the raw material you already have.

ΧΧCheck back on our site for updates. Research is always evolving. ΧΧBe curious. Ask us questions on our Facebook page. ΧΧAnd, of course: Keep science-ing!

Confused by codons? Mystified by mutations? No worries, we’ve got a handy glossary for all the technical terms we’ve used in this book.

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In this chapter, we look at some of the genetic factors that may shape our response to (and recovery from) exercise and training, and whether we have a “natural athletic type”.

Glossary of terms

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What we found: Exercise and muscle performance

CHAPTER 13

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CHAPTER 13

Glossary of terms

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# 6-n-propylthiouracil (PROP): A compound that tastes bitter to some people, but is tasteless to others; the ability to detect it is genetically determined.

A Absolute risk: In terms of health conditions, the prevalence of a disease within an entire population (e.g., 3% of all people will get Disease X in their lifetime). Actin: A protein within muscle tissue. Adenine: One of the nucleotides that forms DNA / RNA, along with cytosine, guanine, and thymine (uracil in RNA). Often abbreviated as A. In base pairing, adenine pairs with thymine (T) and uracil (U). Adipocyte: A fat cell. Adiponectin: A protein produced in adipose (fat) tissue that helps to regulate many processes, including glucose metabolism and fatty acid oxidation. Alkaline lysis: A process for breaking down cell membranes in order to extract genetic material, using a base like sodium hydroxide and a surfactant. Allele: A variant of the same gene (usually emerging through mutation), found at the same place on the chromosome.

Allergen: Something that causes a histamine response, known as an immunoglobulin E (IgE) immune reaction.

Amplicon: A piece of DNA or RNA that has been amplified or copied, especially through the polymerase chain reaction (PCR).

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Amino acid: The basic building block for a protein.

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Allergy: A hypersensitive immune system response.

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Allelic heterogeneity: When related genetic variants, or alleles, in the same location are associated with the same trait or outcome.

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Amplicon sequencing: A technique that uses the polymerase chain reaction (PCR) to make billions and billions of copies of a previously-identified stretch of DNA, and sequence these copies (known as amplicons). Amplification: An increase in the number of copies of a gene, possibly along with the RNA and protein made from that gene. Gene amplification is common in cancer cells. Anabolism: Metabolic pathways of molecular and tissue growth, synthesis, and development. Opposite of catabolism. Androgen insensitivity syndrome (AIS): A type of intersexuality that happens when a chromosomally male (XY) body does not respond to masculinizing hormones (i.e., androgens), and develops with a body that looks female. Antibody: A type of protein that is produced by the immune system when it identifies a foreign substance, known as an antigen. Antibodies help identify pathogens (such as bacteria or viruses) as well as allergens and toxins. Antigen: Any foreign substance that stimulates an immune response, particularly antibody production. Antigen-presenting cells: Cells that tell other cells of the immune system (such as T cells) that there’s trouble spotted (such as a pathogen), and it’s time to go to work. Apolipoproteins: Protein-based components of lipoproteins. They’re encoded by genes that start with the letters APO (such as APOB or APOE). Apoptosis: Programmed cell death.

Autoimmune thyroid disease (AITD): A form of thyroid disease in which the body attacks normally healthy thyroid tissue.

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Autosomal dominant: A form of inheritance in which you need only one copy of a gene from a parent to express a trait.

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Autonomic nervous system (ANS): The branch of the nervous system that controls basic functions such as heart rate and breathing.

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Assay: A method for determining the presence or quantity of a particular component, or a method to analyze or quantify a particular substance in a sample.

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Autosomal recessive: A form of inheritance in which you need two copies of a gene (one from each parent) to express a trait. Avenins: A protein in oats that is similar to gluten in wheat, and which can cause an immune system reaction in some people.

B Bamforth–Lazarus syndrome: A rare genetic disease in which thyroid tissue is underdeveloped or missing entirely. Basal metabolic rate (BMR): The body’s “idling speed”, i.e., the rate at which metabolic reactions take place and use energy to do so. Base excision repair (BER): A method that our cells use to repair damaged DNA. Base pair: A pair of complementary nucleotides (bases) on a strand of DNA or RNA. β-adrenergic receptors: Receptors that respond to catecholamine hormones like adrenaline, and activate processes to help us free up stored energy, get our muscles moving, and do other autonomic nervous system jobs. Bioactive form: A form of a molecule or compound that has an effect on a biological organism (e.g., “Before we can absorb Substance X, it must be converted into its bioactive form”). Biochemical genetic tests see Genetic test types.

Biological sex: The collection of physical characteristics (such as chromosomes or reproductive organs) that identifies a body as male, female, and/or intersex. Body composition: The relative amount of fat mass to lean mass.

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Body mass index (BMI): A measure of weight relative to height.

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Bioinformatics: The analysis and interpretation of biological data using methods drawn from computer science, statistics, mathematics, and engineering.

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C Carbohydrate: A family of biological molecules that includes sugars, starches, and soluble and insoluble fiber. Catabolism: Metabolic pathways of molecular and tissue breakdown for energy or disposal. Opposite of anabolism. Catecholamines: A group of hormones that includes epinephrine (adrenaline), norepinephrine (noradrenaline) and dopamine, which have similar effects on the nervous system. Celiac disease: An autoimmune disorder in which the body makes antibodies to gluten, causing damage to the gastrointestinal lining. Central dogma of molecular biology: The fundamental concept of how genetic information and instructions “flow” from DNA to RNA to proteins. Thus, DNA contains all the information and instructions required to make proteins via the action of RNA. Chemokine: A cell signaling molecule (cytokine) that attracts white blood cells to the site of tissue damage. Chip: See microarray. Cholesterol: A waxy lipid that we can make in our liver or consume from food. We use cholesterol to make many important molecules that our bodies use, including our sex hormones.

Chromatin immunoprecipitation (ChIP): A molecular biology technique that identifies proteins that interact with known DNA sequences. Chromosomal genetic tests See Genetic test types.

Chromosome: A long strand of tightly wound chromatin that contains genetic information. Humans have 23 pairs of chromosomes.

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Chromosomal translocations: Occurs when material from one chromosome migrates to another, and/or is swapped between chromosomes.

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Chromosomal inversions: Occurs when a single chromosome breaks and rearranges itself, reversing end to end.

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Chromatin: The material, composed of DNA, RNA, and proteins, that makes up our chromosomes.

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Chylomicrons: Small lipoprotein particles that circulate in the blood after fat is absorbed from the small intestine. Clinical Laboratory Improvement Amendments (CLIA) regulations: A set of federal standards applicable to all US facilities or sites that test human specimens for health assessment or to diagnose, prevent, or treat disease. Closed assay: An assay that identifies beforehand what it’s seeking, such as a particular mutation or gene variant. Codon: A set of three nucleotides that codes for a specific protein. Cofactor: A substance that’s required for an enzyme to work. Riboflavin (vitamin B2) is an example of a cofactor. Convergent evolution: Occurs when unrelated species develop traits independently of each other, without a common root of that trait (for instance, bat, bird, and insect wings evolved independently from one another). Copy number variation (CNV): Repetition of specific sections of genetic material; the number of repetitions can vary from person to person. Cruft: A computer term for “crud” or leftover bits of stuff; poorly designed, unnecessarily complicated, or unwanted code or software. Cytokine: A cell signaling molecule. Cytoplasm: The fluid within a cell. Cytosine: One of the nucleotides that forms DNA / RNA, along with adenine, guanine, and thymine (uracil in RNA). Often abbreviated as C. In base pairing, cytosine pairs with guanine (G).

Diploid: Containing two sets of chromosomes. (Opposite: haploid.) DNA: A biological molecule that holds the code for making all living things. Dominant traits / genes: Traits and/or genes that are more likely to be expressed, and which require only one copy to do so.

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Deoxyribose: The sugar-based structural “backbone” of DNA.

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Deletion: A mutation in which some genetic material is lost during the process of DNA replication.

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D

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Double-strand breaks: A mutation or damage that occurs when both strands of DNA are severed. This often happens in response to ionizing radiation. Duplication: Reproduction of chunks of DNA that contain genes, resulting in multiple copies of those genes. A common basis for genetic evolution. Dyslipidemia: Having a poor / unhealthy blood lipid profile.

E Electrolytes: Dissolved salts such as sodium or potassium. Epigenetics: The study of factors that affect genetic expression — for instance, how the same genetic “blueprint” may actually be used to build different things. Endocrine system: The coordinated system of glands that secrete hormones that act elsewhere in the body. Energy balance: The relationship between energy (calories) in (from food) and energy out (from metabolism / excretion / activity). Energy sensing: Mechanisms in the body that monitor how much energy is available. Enhancer: A part of the genome that, when bound by a given transcription factor, increases the likelihood that a particular gene will be transcribed.

Eukaryote: Organisms that have cells with a nucleus and organelles surrounded by a membrane. The nucleus contains genetic material in the form of chromosomes. Organisms without this are known as prokaryotes.

Exome: The part of the gene formed by exons.

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Exon: The parts of the gene that code for protein sequences (the opposite of introns).

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Evolutionarily conserved: Preservation of genetic information and gene function over time, even through the division into different species. Evolutionarily conserved genes tend to keep their functions.

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Enzyme: A substance that helps initiate a particular biochemical reaction, often breaking things down (e.g. protease enzymes break down proteins).

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Exposome: The combination of all environmental factors that might affect epigenetic and genetic expression. Expressing sequences: Another term for exons.

F Feedback loop: A coordinated series of “if-then” actions in which output determines future input; information at a given outcome is used to determine the next action. First messenger: A substance that binds to the outside of a cell, stimulating certain actions from second messengers within the cell. Fixation: When multiple alleles from a gene pool are removed and only one remains. Once this happens, the gene is said to be “fixed” in the population. Forkhead box (FOX) proteins: FOX proteins are transcription factors that control the expression of other genes. They are typically involved in regulating cell growth, development, differentiation, and survival. Fusion gene: A single gene formed from two separate genes.

G

Gametes: A haploid germ cell of sexual reproduction (i.e., egg / ovum or sperm).

Genetic sequencing see Genetic test types.

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Genes: Regions of DNA that have instructions for making specific proteins.

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Gel electrophoresis: A technique used in molecular biology where an electrical current is applied across an agarose gel to separate DNA, RNA and/or protein fragments by size.

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Gain of function mutation: A type of mutation that results in the altered gene having new or enhanced activity, a new molecular function, or a new pattern of gene expression. These mutations are often dominant.

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Genetic test: A laboratory assay specifically for clinical testing purposes that is used to identify specific genotype(s) to diagnose a specific disease in a specific group of people for a specific purpose. Genetic testing is very targeted compared to a genetic assay, which may be scanning, or may be targeted. Molecular genetic tests look at the smallest “chunks” of DNA, perhaps a single gene or short pieces of DNA, usually looking for a specific variation or mutation. Chromosomal genetic tests look at longer pieces of DNA, such as whole chromosomes, to look for larger-scale genetic changes (such as an extra chromosome copy). Biochemical genetic tests look at how much of a certain protein we have, or how active that protein is. Here, the test doesn’t look at the DNA but rather the protein that it might be coding for. By looking at differences in the proteins, testers can speculate about genetic variations. Genetic sequencing involves “reading” a strand of DNA by looking at its nucleotides, one by one. Genetics: The study of genes, how they work, and how particular traits (such as eye color) are passed from parent to offspring (known as heredity). Gender identity: One’s deeper sense of self as having a particular gender (or not). Genome: An organism’s total set of genetic material. Genome-wide association studies (GWAS): A type of genetic test that examines locations across the entire genome to identify potential associations with a particular phenotype or phenotypes.

Gliadin: A protein found in wheat; one of the components of gluten. Glucose: A simple sugar that is the raw material for building ATP, our cells’ energy.

Gluten: A protein found in wheat to which some people (such as those with celiac disease) have an immune system reaction.

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Glutamine: An amino acid.

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Glucose transporter (GLUT): A family of proteins found on cell membranes that help move glucose across those membranes. GLUT4 is the insulin-regulated glucose transporter.

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Genotype: The genetic code of an organism.

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Glutenin: A protein found in wheat; one of the components of gluten. Glycoprotein: A type of protein with a carbohydrate attached. Guanine: One of the nucleotides that forms DNA / RNA, along with adenine, cytosine, and thymine (uracil in RNA). Often abbreviated as G. In base pairing, guanine pairs with cytosine (C).

H Haploid: Containing one set of chromosomes. (Opposite: diploid.) Haplotype: A common set of genetic variants that tend to be inherited across generations. Often used to track ancestry or to identify population groups with shared ancestry or common disease risk. Hematopoiesis / hemopoiesis: The production of platelets and blood cells, which occurs in bone marrow. Hereditary fructose intolerance (HFI): A genetic condition in which people can’t break down the sugar fructose properly. HFI is an autosomal recessive disorder, which means that to have HFI, a person must inherit two copies of the ALDOB gene variant that causes the problem. Heredity: The transmission of particular characteristics from one generation to another.

Heterozygocity / heterozygous: Inheritance of two different copies of the same gene. (Opposite of homozygous.)

Histones: A type of protein found in chromatin, which acts like a “spool” or “bead” around which the strings of DNA are wound. Because of this structure, they can affect genetic expression.

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Histamine: A substance released by cells in allergic and inflammatory reactions (and injury), which causes contraction of smooth muscle and dilation of blood vessels.

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Heterozygote advantage: Having a better evolutionary adaptation than a homozygous combination, due to having two different copies of the same gene.

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Heterodimer: A complex, or dimer, of two large molecules, such as proteins, bound together. A heterodimer occurs when the two proteins are different.

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Histone modification: Changes to histones (such as acetylation or various types of methylation) after RNA translation that can affect genetic expression. Homeostasis: A dynamic state of balance within the body. Hominin: The taxonomic group that contains genera that have descended from a common ancestor, the genus Homo (e.g. modern humans H. sapiens, H. habilis, H. neanderthalensis) and the extinct genera Australopithecus, Paranthropus and Ardipithecus. Some taxonomists also consider the genus Pan to be hominin. Pan includes our closest living relatives: chimpanzees and bonobos. Homology/homologous: A state of similarity. Homologous recombination repair (HRR): A method of repairing DNA by exchanging nucleotide sequences between two similar or identical molecules of DNA. Homozygous: Inheritance of two of the same copies of the same gene. (Opposite of heterozygous.) Hordeins: A protein that occurs in barley and can trigger the same type of immune response as gluten. Horizontal gene transfer: The exchange of genetic material between organisms (e.g., between bacteria and humans). Human leukocyte antigen (HLA): A gene complex that codes for major histocompatibility complex (MHC) proteins in humans. These cell surface proteins regulate our immune system by helping our cells recognize foreign molecules. Hydroxylate: To add a hydroxyl group (an oxygen-hydrogen pair) to a molecule.

Hyperthyroidism: Increased thyroid function. Hypertriglyceridemia: Elevated triglycerides (fats) in the bloodstream.

Hypothyroidism: Decreased thyroid function.

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Hypothalamus: A small gland in the brain that controls many key metabolic functions.

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Hypomethylation: A natural modification of DNA involving loss of a methyl group.

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Hypercholesterolemia: Excess cholesterol in the bloodstream.

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I Immunoassay: A biochemical test that measures the presence of proteins or other substances through their properties as antigens or antibodies. Immunoglobulin: A type of protein in the serum and cells of the immune system that functions as an antibody. Immunoglobulin E (IgE): A type of immunoglobulin, only found in mammals, that is involved in allergic reactions. Immunoglobulin G (IgG): A type of immunoglobulin that binds to and neutralizes pathogens and toxins. Imprinting: An epigenetic modification inherited from only one parent, with the other gene copy from the second parent being “turned off”. Inactivating mutations: See loss-of-function mutations. Inflammation: A complex and coordinated process of response to injury and illness that is characterized by elevated inflammatory chemicals (such as interleukins) and pain, heat, redness and swelling. Insulin: A crucial hormone for nutrient storage and anabolism that is released by the pancreas in response to higher blood sugar (glucose) levels.

Insulin sensitivity: How able our cells are to respond appropriately to insulin. We want this to be working well, and to have high insulin sensitivity. If we have poor sensitivity, we develop insulin resistance.

Interstitial deletions: Deletions that don’t involve ends of chromosomes.

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Intersex: A normal, though less common, biological phenomenon in which people have variations in reproductive or sexual characteristics that do not match typical definitions of male or female.

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Interleukins (IL): A group of cytokines, expressed by white blood cells, that are involved in regulating the immune system response.

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Insulin resistance: A condition in which our cells cannot respond appropriately to the presence of insulin by transporting glucose into cells. As a result, we have high circulating insulin and high circulating glucose. This is often a precursor to Type 2 diabetes.

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Intervening sequences: Another term for introns. Intron: A part of the gene or gene transcript that is removed before the mature RNA is translated to a protein (the opposite of exons).

L Lactase: An enzyme that allows us to digest lactose, a sugar in milk. Lactase persistence: Presence within a population of the ability to digest lactase as an adult, which is largely genetically determined. Lactose tolerance: The ability to digest lactase. Lethal mutation: A mutation that kills the organism, and/or results in the organism being unable to reproduce. Leucine: An amino acid. Ligand: A molecule that binds to another for some biological purpose (such as initiating a biochemical reaction). Lipids: Fat-based molecules. Lipodystrophy: Disorders of fat metabolism that result in wasting of fat stores, or fat deposits in unusual places (such as on the hands). Lipolysis: The breakdown of fats (lipids).

Locus (plural: loci): A position of genetic material on a chromosome that describes exactly where that genetic material is located.

Lyse: To break down the membrane of a cell. This occurs in genetic testing to allow the researcher or technician to remove the genetic material from the cell.

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Loss-of-function mutations: Mutations that result in a gene being inactivated or silenced.

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Loss of heterozygosity: A major mutation that results in loss of an entire gene and its surrounding region. This often happens in cancer.

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Lipoproteins: Proteins that transport lipids. Since lipids can’t dissolve in water but proteins can, lipoproteins help many fat-based molecules move around the body through the blood.

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M Macrophage: A type of immune system cell that’s part of our cellular “cleanup crew”. Major histocompatibility complex (MHC): Cell surface proteins that regulate our immune system by helping our cells recognize foreign molecules. Maternal effect: The role that the mother plays in her offspring’s epigenetic expression, whether through her genetic material, in the environment she provides, or both. Maternal haplogroups: A family of mitochondrial DNA that can be traced back to a single common female ancestor. Mendelian genetics: A simple model of genetic inheritance originally developed by Gregor Mendel in the 1860s. Messenger RNA (mRNA): See RNA. Metabolic syndrome: A collection of physical risk factors that are related to a cluster of chronic diseases, such as Type 2 diabetes and stroke. These include elevated blood pressure, elevated triglycerides, high fasting blood sugar, and significant deposits of fat around the midsection and internal organs.

Microarray: A chip with a large array of sensors to detect certain DNA or RNA sequences.

Missense mutations: A mutation in which a single nucleotide change results in a codon that codes for a different amino acid.

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Mismatch repair (MMR) a system for identifying and fixing errors in DNA replication and recombination.

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Microsatellite instability (MSI): Increased likelihood of genetic mutation due to poorly functioning DNA mismatch repair (MMR); microsatellites are repeated sequences of DNA.

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Methylation: The addition of a methyl group (a carbon and 3 hydrogens, aka CH3) to a molecule. Two important processes in epigenetics are the methylation of bases in DNA (usually cytosine, or C) and the methylation of histone proteins that affect gene expression. When DNA or histones are methylated, certain genes are often “switched off”, which can be a problem if you want those genes to be transcribed and protein made.

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Mitochondria: An organelle within a cell that’s involved in energy production and respiration. Mitochondrial DNA (mtDNA): A form of non-nuclear DNA that is round and transmitted maternally. We can use mtDNA to trace maternal ancestry. Mitosis: Division of one cell into two genetically identical cells. Mobile genetic element: A type of DNA that can move around the genome. Molecular genetic tests see Genetic test types. Muscle-specific creatine kinase (CKMM): A test used to measure levels of creatine kinase, a marker of muscle damage. Mutation: Changing the structure or function of a gene in a way that can potentially be transmitted to future offspring. Myosin: A protein found in muscle tissue.

N Neurotrophins: Chemicals involved in the growth, development, and survival of neurons. Non-celiac gluten sensitivity (NCGS): An inflammatory response to gluten that does not depend on making IgG antibodies, as in celiac disease.

Nonhomologous end-joining (NHEJ): A pathway for repairing DNA doublestrand breaks.

Nuclear pore: A channel between a cell’s nucleus and cytoplasm that regulates movement of substances in and out of the nucleus.

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Nuclear exporting: Chaperoning mRNA through a nuclear pore, using nuclear transport receptors.

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Nonsense mutation: A mutation that creates stop codons and can truncate the protein in the process of being created. This means that a cell’s ribosome (the protein-making factory), will stop producing the protein before that protein has all of its amino acids.

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Noncoding regions / noncoding DNA: Parts of the genetic code that don’t code for any proteins, but that might be involved in other genetic regulatory and structural functions.

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Nuclear receptor: A type of protein found in the nuclei of cells that can bind directly to DNA and regulate the expression of genes. Nuclear transport: Entry and exit from a cell’s nucleus. Nucleic acid: Linked chain(s) of nucleotides. DNA stands for deoxyribonucleic acid. Nucleotide: The basic structural unit of DNA and RNA; a nitrogen-containing base plus a phosphate and sugar molecule (such as deoxyribose or ribose). Nucleotide excision repair (NER): A method of repairing DNA, particularly damage from ultraviolet light. Nucleus: An organelle within a cell where genetic material is stored (in eukaryotes). Nutrient partitioning: What our bodies do with the food we eat (e.g., use it for repair, use it for energy, and/or store it).

O Open-ended assay: An assay that looks for anything of interest, like scanning a landscape to see what pops out. Organelle: A structure within a cell that has a specialized function (e.g., a nucleus, mitochondrion, or ribosome).

Paralog: One of two or more genes that come from the same ancestral gene as a result of gene duplication.

Perilipin: A protein that surrounds lipid droplets in fat cells, helping to control the metabolism of adipocytes by regulating how fat-mobilizing enzymes (lipases) interact with the stored fat.

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Phenotype: The combination of traits and features that results after an organism’s genetic code interacts with its environment; how a genetic “blueprint” is actually expressed.

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Paternal haplogroup: A haplogroup traced through the Y chromosome.

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Pituitary: A small endocrine gland within the brain that’s involved in regulating many other endocrine glands, such as the thyroid. Pleiotropy: From the ancient Greek pleion, or “more”, and tropos, or “way”, one gene influencing two or more apparently unrelated processes or traits. Polygenic: Many genes involved (e.g., in the cause or progression of a disease). Polymerase: An enzyme that synthesizes long chains (polymers) of nucleic acids. Polymerase chain reaction process (PCR): A laboratory technique used to make multiple copies of a specific region of DNA, for instance for genetic testing. Polymorphism: Multiple forms or variants of a gene at the same location. Polypeptide chain: A long strand or set of strands of peptides, amino acids strung together. Positive selection: a genetic mutation that promotes the emergence of new phenotypes, usually by offering some kind of advantage. Post-transcriptional modification: The modification of an RNA transcript into mature mRNA. Post-translational modification: The modification of a protein after it is translated from mRNA. Prader-Willi Syndrome: A congenital genetic syndrome caused by the loss of function of genes in a particular region of chromosome 15. Predictive value: How well a given factor, such as a genetic variant (or set of variants), can explain an outcome, such as a disease or trait.

Proline: An amino acid.

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Pronuclear transfer: A method of 3-parent artificial reproduction that uses two eggs (one egg from the mother, and one egg from a donor) that are both fertilized with the father’s sperm. Once eggs are fertilized, but before they start dividing, their nuclei are removed; the nucleus from the donor’s fertilized egg is replaced with the nucleus from the mother’s egg.

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Promoter: A region of DNA that binds with RNA polymerase and transcription factors to initiate transcription of mRNA.

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Prokaryote: Simple organisms whose cells do not contain specialized organelles or a nucleus with genetic material bound into chromosomes. Many bacteria, for instance, are prokaryotic. Compare to eukaryote.

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Prostaglandins: A group of lipid-based chemicals that have hormone-like effects, including regulating inflammation. Protease: An enzyme that breaks down proteins. Protein: A biological molecule, made of amino acids, that a gene codes for. Pseudogene: Segments of DNA that are related to real genes, but are not functional. Purifying selection: Removal of genetic variants that are maladaptive.

R Reactive oxygen species: Waste products generated from the normal process of cellular metabolism, which contain oxygen and are chemically reactive. Reading frame: A method of separating nucleotide sequences into a set of consecutive, non-overlapping triplets, aka codons. Receptor: A structure that is able to respond to and bind specifically with something else, such as a molecule. Recessive traits / genes: Traits that require two gene copies — one from each parent, to express that trait. Reference genomes: A database of a “representative” genome of a species, used as an example or relative comparator for other genomes of the same species.

Retroviral sequences: A segment of genetic material that is an artifact of ancestral retroviral infections, but which is now incorporated into current DNA.

Ribosome: An organelle that is the site of protein synthesis within a cell. Ribosomal RNA (rRNA): See RNA.

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Ribose: A sugar that forms one of the components of DNA / RNA. In DNA, the molecule is deoxyribose; in RNA it’s ribose.

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Reverse transcription: Performing the normal steps of transcription in reverse order, going from RNA to DNA. This occurs in some RNA viruses.

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Relative risk: The risk of a given outcome as compared to another person or group (e.g., Disease X occurs 2 times more in Group Y than Group Z).

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RNA Messenger RNA (mRNA): A form of RNA that transmits genetic information to a ribosome. Ribosomal RNA (rRNA): An RNA enzyme that links amino acids together in the ribosome to make a polypeptide chain, and makes up some of the structure of ribosomes. Transfer RNA (tRNA): RNA molecules that carry specific amino acids to the ribosome. They match mRNA codons with their respective amino acid. Small nuclear RNA (snRNA): Short RNA segments that form small nuclear ribonucleoprotein particles (snRNPs), that then are part of RNA processing. MicroRNA (miRNA): A small segment of RNA involved in RNA silencing and regulation of gene expression. Small interfering RNA (siRNA): A short segment of RNA that can interfere with the expression of specific genes. RNA export: Exporting mRNA out of the cell’s nucleus. RNA processing: See RNA splicing. RNA splicing: “Stitching together” segments of RNA in a variety of ways by removing introns and joining exons. RNase: An enzyme that breaks down RNA.

Secalins: A type of protein found in rye, which may trigger an immune system response similar to gluten.

Selective sweep: A decrease in genetic variation, particularly near a specific mutation. Sequencing: Examining the genome to build a list of specific nucleotides, in order.

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Secosteroid: A type of steroid, or cholesterol-based hormone.

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Second messenger: A molecule that responds to a first messenger molecule in a signaling pathway.

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Sexual dimorphism: Having two biological sexes with distinct physiological characteristics within a species (e.g., male and female). Sexual orientation: Whom we prefer as sex partners. Signaling pathways: A series of interactions that trigger each other in a step-by-step process. Silencer: A part of the genome that prevents gene expression, particularly during certain stages of the cell cycle. Silent mutations: Mutations that don’t significantly alter the phenotype or health of the organism. Single nucleotide polymorphism (SNP): A variation in a single nucleotide (for instance, having a cytosine, or C, where there’s normally an adenine, or A). SNP genotyping arrays: Arrays that look at a series of predetermined locations on the genome (usually hundreds of thousands to millions) to look for SNP variations. Spindle nuclear transfer: A method of 3-parent artificial reproduction that is similar to pronuclear transfer, but occurs before fertilization. Substitution mutation: A type of mutation in which a single nucleotide is exchanged for another.

T Telomere: The structures on the ends of chromosomes that function much like the plastic end of a shoelace, preventing degradation of chromosomes. Terminal deletion: Removal of the end of a chromosome.

Thymine: One of the nucleotides that forms DNA, along with adenine, cytosine, and guanine. Often abbreviated as T. In base pairing, thymine pairs with adenine (A). In RNA, thymine is replaced by uracil (U).

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Thermogenesis: The production of heat (i.e., by the body).

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Terminator: A section of DNA that marks the end of a gene.

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T-helper cells: A type of immune system cell that assists other cells by releasing cytokines.

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Trait: A particular characteristic of an organism (such as eye color or hair texture) that is expressed by gene(s) as well as influenced by the environment. Transcription: Making RNA using the instructions from DNA. Transcription factor: A protein that controls the rate of transcription. Transfer RNA (tRNA): See RNA. Transgenic: Artificially introducing genetic material from one unrelated organism into another. Translation: Making protein using the instructions from RNA. Translesion synthesis (TLS): A type of DNA “damage control” that allows repair of genetic material to occur past damaged sites (aka lesions). Transmembrane protein: A protein that spans the membrane of cells, (e.g., to help transport materials from outside to inside of the cell, or to act as a receptor relaying information from outside to inside). Transposon: Segments of DNA that can move around within the genome. Triglyceride: The storage and transport form of fatty acids, formed with three fatty acids attached to a glycerol “backbone”. Type 1 diabetes (T1D): Often called early-onset diabetes, an autoimmune disorder where destruction of the pancreas leads to problems with insulin secretion. Type 2 diabetes (T2D): A disease in which the body cannot use insulin properly, and blood glucose (sugar) remains consistently high.

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Uracil: One of the nucleotides that forms RNA, along with adenine, cytosine, and guanine. Often abbreviated as U. In base pairing, uracil pairs with adenine (A). In DNA, uracil is replaced by thymine (T).

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V Variable number tandem repeat (or VNTR): Repetition of codons different numbers of times (e.g., the same codon may be repeated 3 times versus 5 times). Variant: A different version of the same gene. See also allele. Vitamin D receptor (VDR): A nuclear receptor that can bind to vitamin D and affect genetic expression.

W Whole-genome sequencing: “Reading” and analyzing an organism’s entire genome.

Don’t believe us? Want to learn more? Enjoy the hundreds of references we’ve collected.

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Now that you've learned more about genetic testing, or even gathered your own data, what should you do next?

References

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What does this mean for you?

CHAPTER 14

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CHAPTER 12

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References

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CHAPTER 13

Science is a collaborative endeavor. We are most grateful to all of those who contributed their data and expertise to help us write this book.

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Confused by codons? Mystified by mutations? No worries, we’ve got a handy glossary for all the technical terms we’ve used in this book.

Contributors and acknowledgments

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Zhu J, Loos RJF, Lu L, et al. Associations of genetic risk score with obesity and related traits and the modifying effect of physical activity in a Chinese Han population. Hsu Y-H, ed. PLoS ONE. 2014;9(3):e91442.

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CHAPTER 15

Contributors and acknowledgments

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Science is a collaborative endeavor. We are most grateful to all of those who contributed their data and expertise to help us write this book. Authors and Contributors

Dr. Krista Scott-Dixon Dr. Krista Scott-Dixon developed Precision Nutrition’s PN Coaching / ProCoach and PN Level 2 Master Class Certification curricula. She is also a co-author of the 3rd edition of the PN Level 1 Certification textbook, The Essentials of Sport and Exercise Nutrition. With a PhD from York University in Toronto and 10 years of university teaching, Krista has over 20 years of experience in research, adult education, curriculum design, and coaching and counselling. Krista is the author of several books, dozens of popular articles, and many academic publications.

Alaina Hardie Alaina Hardie is a programmer, maker, and biology enthusiast. She has worked in software development, data security, and network and systems engineering.

As PN’s original tech person and resident bioinformatician, she was responsible for a lot of the details in chapters 2 and 3, and for most of the computational analysis of the data we gathered for this book.

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After graduating in 2011 from Singularity University’s prestigious Graduate Studies Program, she studied molecular and computational biology. As the Chief Maker and director of the iLab at Singularity University, she is responsible for educating the current and upcoming generations of leaders on using exponential technologies to address humanity’s greatest challenges.

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Dr. Helen Kollias Dr. Helen Kollias is a researcher and regular content contributor for Precision Nutrition. She is also a co-author of the 3rd edition of the PN Level 1 Certification textbook, The Essentials of Sport and Exercise Nutrition as well as an advisor for the Precision Nutrition Level 1 Certification. As a regular content contributor to the blog, she uses her witty and articulate writing style to make complex science accessible and entertaining. Helen holds a PhD in Molecular Biology, specializing in the area of cell signaling in muscle development and regeneration, and a Master’s degree in Exercise Physiology and Biochemistry. She has also held research positions at some of the most prestigious institutions in the world, including John Hopkins University and Toronto’s Hospital for Sick Children. At Johns Hopkins, she researched muscle signaling of myostatin and IGF-1 in muscle. At the Hospital for Sick Children she researched the role of genetics in the emergence of brown fat.

Dr. John Berardi Dr. John Berardi is a co-founder of Precision Nutrition, the world’s largest online nutrition coaching and certification company.

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As an elite nutrition coach and exercise physiologist, JB has worked with over 50,000 clients in over 100 countries, including Olympic gold medalists, world champion UFC fighters, and professional sports teams. He is also an advisor to Apple, Equinox, Nike, and Titleist.

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JB has been recognized as one of the top exercise nutrition experts in the world. He earned a PhD in Exercise Physiology and Nutrient Biochemistry at the University of Western Ontario, Canada. His work has been published in numerous textbooks, peer-reviewed academic journals, and countless popular exercise and nutrition books and magazines.

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Judy Rubin Growing up, Judy was always trying to draw the bugs and creatures found in her backyard, and the cells seen under the microscope in her mother’s lab. This unusual childhood hobby later turned into a career. After receiving a BA in Biology from University of Maryland Baltimore County, she trained first as a fine artist at the Schuler School of Fine Arts and then as a medical illustrator at University of Toronto in the Biomedical Communications program. She hopes to continue creating accurate, effective, and beautiful visuals for a range biomedical and health topics. More examples of her work can be found at jrubinvisuals.com.

Reviewers, editors, and people who keep us honest Ryan Andrews Ryan Andrews is a world-leading educator in the fields of exercise science and nutrition. Ryan is a Registered Dietitian with two Master’s Degrees. He completed his education in exercise and nutrition at the University of Northern Colorado, Kent State University, and Johns Hopkins Medicine. A highly-respected coach who has been a part of the Precision Nutrition team since 2007, Ryan’s body of work includes an impressive number of articles, presentations, books, and certification manuals — most recently as a co-author on the 3rd edition of the PN Level 1 Certification textbook, The Essentials of Sport and Exercise Nutrition. PRECISION NUTRITION

A nationally-ranked competitive bodybuilder from 1996-2001, and now a certified yoga instructor, Ryan is also an active volunteer with non-profit organizations to help promote a sustainable future.

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Cam DePutter Camille DePutter is an author, speaker, and communications consultant with a rich portfolio of experience in marketing, public relations, and storytelling. Camille received her HBA in English from the University of Toronto and trained at the Humber School for Writers. She lends her communication expertise to Precision Nutrition publications, course materials and marketing content. As a consultant, Camille has helped dozens of top brands and business leaders refine their messaging and improve their customer relationships. Her work has been published extensively in popular websites, magazines and newspapers. Camille is a frequent contributor to the Precision Nutrition blog. She is also the author of the workbook Share Your Story, and self-publishes at camilledeputter.com.

Dr. Trevor Kashey Dr. Trevor Kashey, PhD is a biochemist who began his scientific career in high school where he dedicated to non-small cell lung cancer research at the Translational Genomics Research Institute in Phoenix, AZ. On top of setting some American strongman records of his own, he’s dedicated to improving the performance of all the other athletes he consults and makes a mean oatmeal cookie to boot.

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Trevor has worked with World’s Strongest Man competitors, 150-mile ultra marathon runners, and everything in between. Trevor blends anecdotal, academic, and clinical data, harmonizing it into practical dietary information for the general public. You can find him at trevorkashey.com.

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On top of regularly reviewing and publishing lay content, he contributes critical analysis of technical research data as a research reviewer for public and private institutions. He is a regular guest lecturer at local colleges and business seminars and is dedicated to the education and outreach in the field of sports nutrition and dietary supplements.

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Kenny Manson Kenny Manson is a performance coach and graduate of the PN Level 2 Master Class Certification. In addition to his PN qualifications, Kenny holds numerous international fitness certifications and is a PTA Global accredited coach, for whom he has co-presented at the mentorship level. Kenny has worked directly alongside wellness leaders such as OD on Movement, Human Fitness and Performance and The Kaizen Institute of Health, and is also qualified as a chartered and certified accountant. Kenny has applied his corporate experience in the fitness world in a variety of roles, from coaching clients and fellow fitness professionals to providing fitness business management solutions. Kenny is currently mentor to students of the PN Level 2 Master Class Certification and Digital Health Producer and presenter at Soulgenic.

Dr. Victor Peña Dr. Victor Peña has a decade of clinical and surgical experience in Ireland and the UK. He has published widely in international peer-reviewed medical journals, and continues to review the latest research in the fields of health, wellness, fitness, nutrition, and disease prevention on a daily basis to continue to bring the most reliable strategies to his clients. After deciding that he would like to prevent rather than treat the consequences of poor health, Victor changed careers from surgery to the field of lifestyle medicine.

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Victor is regularly interviewed on international radio to promote healthy lifestyle choices in Spanish-speaking communities in North America and beyond. You can find him at ElitePersonalizedHealth.com.

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His work is accredited by respected organizations such as the Harvard Medical School, Yale University School of Medicine, the American Medical Association and the George Washington University Medical School.

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Alex Picot-Annand Alex Picot-Annand is a holistic nutritionist and writer who studied psychology at Dalhousie University and nutrition at the Canadian School of Natural Nutrition. She is also Precision Nutrition Level 1 and Level 2 certified, and a key contributor to the Precision Nutrition Encyclopedia of Food. Although they did not earn her any degrees, she would also argue that she learned many textbooks worth of life wisdom by living in Ecuador for seven months, and by working on the frontline of the health industry for nearly a decade. Thankfully, neither Alex nor her husband carry the OR6A2 gene, so agree on loading their guacamole with cilantro. You can find her at alexpicotannand.com.

Jennifer Petrosino Jennifer Petrosino earned a BSc in Exercise Science from the University of Miami (FL) and an MSc in Kinesiology from The Ohio State University, while powerlifting for EliteFTS as a raw lifter in the 105-pound weight class. She is currently a PhD student in the Biomedical Sciences Program at The Ohio State University, where she studies post-transcriptional and translational control of protein synthesis in hypertrophying muscles.

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Dr. Jennifer Zantinge Dr. Jennifer Zantinge is a Molecular Cereal geneticist at the Field Crop Development Centre (FCDC) in Lacombe Alberta. Graduating with a PhD in molecular biology and genetics from the University of Guelph, Jennifer has had the opportunity to experience the rapid advancement of the field of genomics, along with its new technologies and practical applications. As lead scientist of the cereal biotechnology lab, her primary goals include the development and evaluation of molecular genetic based tools such as DNA marker panels to help plant breeders select genetically superior plants.

Additional thanks Dr. Ahmed el-Sohemy Dr. el-Sohemy is a pioneer in the field of nutrigenomics. His early research paved the way for our current understanding of how genetic and dietary factors interact to regulate various metabolic and biochemical pathways involved in the development of cardiometabolic disease, as well as athletic performance. Widely published, he is considered a leading researcher in the field of nutrigenomics / nutrigenetics.

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His genetic testing organization, Nutrigenomix, is a University of Toronto start-up biotechnology company. It is dedicated to empowering healthcare professionals and their clients with comprehensive, reliable, genomic information, with the ultimate goal of improving health through personalized nutrition.

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Dr. Mariane Héroux Dr. Mariane Héroux received her PhD in Kinesiology and Health Studies from Queen’s University, Canada where she was part of the physical activity epidemiology lab and studied the relationship between nutrition, physical activity, and obesity in children from different countries. Before this, she completed her MSc in Community Health Epidemiology, and studied the relationship between dietary patterns and chronic disease. Dr. Héroux has published her work in numerous scientific journals and has presented at several scientific conferences. Her interest in how nutrition and physical activity affect the body developed at an early age, when she started noticing that what she ate influenced her performance as a competitive gymnast. Dr. Héroux continues to explore the importance of nutrition and physical activity at Precision Nutrition where she contributes to research and analyses, and manages key projects.

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Singularity University Special thanks to Singularity University, its faculty, and facilities for their support of this project. Alaina would like to personally thank SU’s Chair of Digital Biology, Raymond McCauley, for checking on her the first day of the Graduate Studies Program, and providing countless opportunities to learn and teach the wonders of biology. Without Raymond’s inspiration and friendship, this book would not exist.

The PN team ΧΧTim Jones, for so freely sharing his genetic data and letting us tell his family secrets.

ΧΧJenny Brook, Ruby Giulioni, Holly Monster, and Lisanne Thomas, all of whom read and commented on earlier drafts of the manuscript.

The anonymous genetic data contributors You know who you are. Thanks for helping us science.

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Don’t believe us? Want to learn more? Enjoy the hundreds of references we’ve collected.

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References

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