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The Peter Attia Drive
#392 - Genetic testing: when it's valuable, how to choose the right test, and what to do with the results
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Hey everyone.
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Welcome to the Drive Podcast. I'm your host Peter Attia. This podcast, my website and my weekly newsletter all focus on the goal of translating the science of longevity into something accessible for everyone. Our goal is to provide the best content in health and wellness and we've established a great team of analysts to make this happen. It is extremely important important to me to provide all of this content without relying on paid ads to do this. Our work is made entirely possible by our members and in return we offer exclusive member only content and benefits above and beyond what is available for free. If you want to take your knowledge of this space to the next level, it's our goal to ensure members get back much more than the price of a subscription. If you want to learn more about the benefits of our premium membership, head over to peterattiamd.com subscribe
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welcome to today's episode of the Drive.
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Few areas in medicine generate as much
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fascination and as much confusion as genetic testing. The basic intuition here is sound.
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If DNA contributes so strongly to our biological machinery, then sequencing it should in principle help us understand health and disease more clearly. It's true that some genetic tests can
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be genuinely life changing, but it's equally
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true that others are barely more useful than a horoscope.
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Most fall somewhere in between, in a
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gray zone that is far more nuanced
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than either the hype or the skepticism would suggest.
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So today I want to build a practical framework for thinking clearly about genetic testing. Through this, I'll discuss what genetic tests
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can and can't do, why most genetic
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tests are probabilistic rather than deterministic, and why directly measuring the phenotype is often more useful than inferring risk from DNA alone.
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I'll also walk through where genetics can
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be most informative across the major disease categories, the Four Horsemen, and where it is much more limited than people assume. Finally, I'll talk about how to choose the right test or type of test,
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how to interpret the results, and how
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to avoid the very common mistake of
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getting more information without getting more clarity.
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So without further delay, I hope you
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enjoy this episode of the Drive. Recently, a patient asked me a question that I hear all the time, Should I be doing genetic testing? It sounds like a simple question, but in reality it doesn't tell me very much because the question can mean a lot of different things. You know, it could mean I'm worried about my risk of Alzheimer's disease. Should we test for APOE genotype? It could mean my mother died of breast cancer. Should I find out whether or Not I carry a BRCA mutation. It could mean, will genetic testing help determine the best medication to address my lipids? Or more commonly, it means something much broader. What diseases am I most likely to get? And that last question is really what most people have in mind. And I, of course, understand why. The notion that your DNA might serve as the kind of blueprint for your future health, that if you could read it closely enough, it would tell you what problems are coming and what to do about them. That is an extraordinarily compelling idea. If we truly had a test that could reliably tell you which diseases you were most likely to develop and exactly how to prevent them, that would be a genuine game changer for medicine. And that promise, or at least some version of that promise, is what many companies have tried to sell. Genetic testing has been marketed as a way to tell you everything from what diet you should eat to how you should exercise, to which supplements you need, to how well your body handles things like detoxification or methylation. But this is where we have to slow down and be much more precise, because that's not quite the reality we live in. Genetic testing can absolutely be useful. In some cases, it can be very useful, even life altering. There are situations where it can meaningfully change screening, influence treatment decisions, clarify risk, or provide critical information for family members. But there are also many situations where it adds very little, where it's oversold, or where the better answers come not from genetics at all, but from directly measuring the phenotype through blood work, imaging, family history, or other clinical evaluation. So the real question is not simply, should I do genetic testing? The real questions are, what exactly am I trying to learn? And is genetic testing the best tool to answer that? If so, what kind of test is actually appropriate? And if I get an answer, will it change anything meaningful about what I do next? That's how I'd like to approach this discussion today. Before getting into where genetic testing is useful and where it's not, I think it's worth stepping back for a moment and talking a bit about the history. Because many of the assumptions people still carry about what genetic testing can deliver are leftovers from an earlier era. We now live in a world where sequencing a human genome feels almost routine. It's far less expensive than it used to be, increasingly accessible, and technically much easier to obtain. But that normalization obscures how recent this capability actually is. The first draft of the human genome was published in 2001, and the human Genome Project was declared essentially complete in 2003. So we are only a little more than two decades removed from the first time we we had a comprehensive map of human DNA. At the time, expectations were extraordinarily high. And to be fair, understandably so. If you suddenly gained the ability to read the full genetic code of a human being, it was not unreasonable to think that many of medicine's biggest problems Would become much easier to understand. Cancer, cardiovascular disease, neurodegeneration, psychiatric illnesses. These all seemed like conditions that might become far more tractable Once their genetic basis was decoded. This is not exactly what happened. Now, that does not mean the human genome project failed. It was an extraordinary scientific achievement, and it created real value, Especially in rare monogenic diseases, in some aspects of oncology and in pharmacogenetics. But it did not deliver on the broadest version of the promises attached to it. The assumption was that once we knew this sequence, we would quickly understand function, that reading the code would tell us more or less directly how disease worked and how to prevent or treat it. Part of the reason that expectation ran into trouble Is the sheer scale and complexity of the human genome. It contains roughly 20,000 genes and about 6 billion total base pairs. Each of us differs from one another at millions of places across the genome, including roughly 5 million single nucleotide variants, plus many other insertions, deletions, and structural changes. Some of these variants affect physical traits, Some affect our risk for disease, and many appear to do absolutely nothing. And even this description understates the complexity, because when people hear genesis, they often think only about the part of DNA that codes directly for proteins. But those protein coding regions of DNA make up only 1.5% of the genome. The vast majority is non coding. What used to be dismissed as so called junk DNA. We now know that much of it plays a critical regulatory role, Controlling when genes are turned on or off, where and how strongly proteins are expressed. So the challenge isn't just identifying variations in the coding regions. Variation in the non coding genome may matter enormously, Even when we don't yet fully understand what it means. In hindsight, the $2.7 billion task of sequencing the genome May have actually been the easier part. Accurately interpreting that sequence and what we should do with it Is the far bigger challenge. To understand why it helps to have a working mental model of how genetic variants actually produce disease. DNA is essentially a set of instructions. Those instructions get transcribed into rna, which is then translated into proteins, the molecular machines that carry out virtually every biological function in the body. A change in those instructions is called a gene variant, or more Colloquially a mutation, though these things mean the same thing. Often the change is inconsequential, but sometimes it results in a protein that doesn't fold correctly, doesn't function as intended, or isn't produced at all. And it is that dysfunctional protein that ultimately shapes the phenotype, the observable, measurable output of the body, from a lab value to a symptom to a disease. This is the central dogma of molecular biology, meaning information flows in one direction, from DNA to rna, RNA to protein, and protein to phenotype. For a small number of diseases, there is a relatively direct line from gene to dysfunctional protein to disease. But for the conditions that matter most, the story is much more complex. Even diseases where genetics matter a great deal tend to arise from countless interactions among many genes and environmental triggers. Before we dig into specific diseases or tests, it's important that we calibrate our expectations. Genetic testing can be useful, sometimes very useful, but it is not a perfect blueprint for health, and it does not replace phenotypic data. Put another way, for genetic testing to be useful, we need to have some confidence that learning the genetic variant will actually inform something clinically. So with this in mind, let's discuss the major limitations we need to consider. The first limitation, and really the most important one, is that most things we talk about in genetics are probabilities, not guarantees. Part of the problem is that most of us were introduced to to genetics through a very simplified model. In high school biology class, genetics is taught through Mendelian inheritance. We learned about dominant traits, recessive traits, sometimes called semi dominant traits. We drew punnett squares. We crossed a white flower with a red flower and got a white, red or pink flower. The logic is clean, the outcomes are discrete, and the relationship between genotype and phenotype appears relatively straightforward. And for a small number of traits and diseases, that framework is actually useful. There are cases where a single mutation has a large and fairly predictable effect, what we call high penetrance mutations. And those cases are part of what makes genetics seem so promising in the first place. Huntington's disease is probably the most extreme example. The HTT gene normally contains a stretch of repeated CAG sequences. Those are just the base pairs and shorthand. In Huntington's disease, this CAG repeat is abnormally expanded. When the expanded gene is translated into protein, it produces a mutant Huntington protein that is toxic to neurons, particularly in the striatum and the cortex. If you carry this expansion above the pathologic neuron threshold, you will develop Huntington's disease, full stop. There Is essentially no version of that story where the mutation is present and the disease doesn't follow. But that's the exception, not the rule, for the vast majority of conditions that people care about. Heart disease, cancer, diabetes, most psychiatric illnessesthat is simply not how genetics work. These are not one gene, one disease problems. They are shaped by the combined effects of many genes, each often contributing only a small amount of risk, layered on top of environment, behavior, aging, and chance. Which means you can carry a variant associated with increased risk and never develop the disease. And you can lack any known high risk variant and still develop the disease anyway. The genetics shift the probability distribution. It doesn't write the ending. People without a BRCA mutation get breast cancer, and people with two copies of APOE 4 never develop Alzheimer's disease. The genes matter, but they are almost always operating alongside other genes and other inputs that our tests will likely never fully capture. The second limitation is that our ability to generate genetic data has moved faster than our ability to interpret it. This is especially true as tests get broader. The more of the genome you look at, the more likely you are to find something. But finding something is not the same as finding something useful. And even when a lab does a good job limiting what it reports, Broader testing still increases the amount of information that has to be interpreted. We can now sequence a genome for a few hundred dollars, but there are simply too many variants, too many interactions, and too many things we still do not understand. So one of the real paradoxes of genetic testing is that broader testing doesn't always produce more clarity. Sometimes it just produces more ambiguity. You get more data, but not necessarily more understanding. The third limitation is that genetic information is often less informative than directly measuring the phenotype. If the thing you care about can be measured directly, that is usually a better place to start than a genetic proxy for it. If I want to know someone's risk for a heart attack, I can measure their cholesterol and image their coronary arteries. I can take their blood pressure and ask whether or not they're smoking. The phenotype tells me something that is happening right now, Something integrated across all the contributing factors. Genetic environment, behavior, age, everything. It's a real time readout that can be acted upon. Genetic testing is something different. It's reading the source code without necessarily knowing how the program will run. The source code matters, but the program is shaped by a thousand other inputs that the sequence alone doesn't capture. And finally, one of the most under appreciated aspects of genetic testing, the potential psychological weight of the information I Have had patients who found out they did not inherit the same mutation carried by their parents, Suffered from a debilitating disease, and who were so overwhelmed with relief that they literally started to cry on a call. The results of a genetic test gave them clarity around something they had been dreading for years. That's a real value, even if it doesn't show up in an outcome study. But I've also had patients who received a result indicating an elevated risk for a disease and were consumed by anxiety about didn't make them more proactive, it just made them more frightened in a way that affected their quality of life for years. This matters because information is not automatically useful just because it's true. A result that is likely to produce fear or confusion without changing screening, treatment, or planning in a constructive way has real costs. And those costs need to be a part of the calculation before you ever work order a test. Okay, so the obvious question then is if genetic testing has all of these limitations, how should we think about whether it's worth doing at all? I think it boils down to a few important questions. One, what exactly are you trying to learn? The more specific the question, the better. Two, is genetic testing the best tool for this question, or is it easier and more informative to measure phenotype, the actual biological output, directly? Three, if you get an answer, what will you do differently? In other words, how will this test change your behavior? And four, are you mentally prepared for the answer, Whether positive or negative? Genetics should be empowering and informative. So if the results are likely to just scare you, maybe it's not the right choice, at least for you. There aren't necessarily right or wrong answers here, but these are the questions I think people should be thinking about when they consider genetic testing layered on top. I think there's one other consideration to help you determine how useful a genetic test is likely to be, and that is how large is the effect of the genetic signal you're looking for? Is this something that nudges the disease risk by 5%? Or is it something that changes the risk by 10 to 20 fold? And so, with this framework in mind, we can now turn to the practical question. Across the major disease categories, where is genetic testing actually useful? And for what kinds of questions? If we start with the biggest threats to lifespan, the first place to go is atherosclerotic cardiovascular disease and metabolic disease. And here in general, I think the case for routine genetic testing is relatively weak. This is not because genetics don't matter in these conditions. Lipids, blood pressure, insulin Resistance and obesity are very clearly influenced by genetics. But the clinical question is not whether genes play a role, but whether knowing the genotype gives you something more useful than simply measuring the phenotype directly. And most of the time, it does not take lp. It is almost entirely genetically determined, driven largely by the LPA gene. In fact, it is the most common hereditary driver of cardiovascular disease. But knowing someone carries a variant that influences LP doesn't actually tell me what I need to know. I'm still going to measure it directly because the measurement gives me more precise, actionable information than the genotype does. The same logic applies across the board. If I want to know whether someone has hypertension, I measure their blood pressure. If I want to assess insulin resistance, I have direct tools to do that. And of course, if I want to know their LDL cholesterol or APOB concentration, both things that are highly influenced by genetics, I can simply measure those things and measure their response to therapy. For most of the major drivers of cardiovascular and metabolic disease, we already have access to the things that matter most, and those things are far more actionable than a genetic estimate of predisposition. Now, that does not mean there are no exceptions. Familial hypercholesterolemia is an obvious one. If someone presents with a markedly elevated LDL and a family history suggesting a monogenic lipid disorder. Genetic confirmation can be genuinely useful, not necessarily because it changes the initial treatment, but because it can solidify the diagnosis and potentially trigger cascading screenings in relatives who may be affected without knowing it. There's also the rarer situations where specific variants change how we interpret the phenotype altogether. ScarB1 mutations, for example, can cause HDL cholesterol to appear elevated in a way that looks falsely reassuring, when in reality, the patient's cardiovascular risk is substantially higher than their lipid panel implies. I actually had a friend that I was able to catch this diagnosis in who had spent years believing that his HDL cholesterol of 100 milligrams per deciliter and his LDL cholesterol of 80 milligrams per deciliter meant he was free and clear of risk, when in reality, a calcium score revealed that he was riddled with disease. These mutations are rare, but they do illustrate where the genotype is actually telling you something that is not immediately obvious from a lipid panel and prompt additional testing. And then there is another category that I think is worth acknowledging. Cases where genetic information shifts behavior rather than truly changing clinical care. I've seen patients agree to start lipid lowering medication that they'd been resistant to after seeing genetic data that confirmed their risk. I've seen patients who struggled with obesity for years find it meaningful, even relieving, to learn that they carry multiple genetic risk variants for weight gain. Not because it changed the treatment plan, but because it reframed the problem in a way that felt less like a personal failure. That psychological shift is real, and I don't dismiss it, but it is different from saying the test revealed something the phenotype could not. In most of these cases, the clinical information was already there. The genetics just changed how the patient related to it. So the conclusion for this category is fairly straightforward. Genetics matter a lot, but for most people it is not the right first tool. Measure the phenotype if something in the clinical picture raises a specific question, a family history that doesn't add up, an unusually extreme lab value, a presentation that suggests a monogenic disorder, then consider whether genetic testing adds something. But as a routine starting point, the phenotype almost always beats the genotype here. Now, once you move outside of ASCVD into inherited cardiac conditions, the question changes a bit. This is where genetic testing can become more compelling, because there are real inherited syndromes involving arrhythmia, cardiomyopathy and structural heart disease where where genotype may reveal risk that is not obvious from routine labs or standard cardiovascular risk markers. Of course, these are also conditions we can test for, but may not do so nearly as regularly. For individuals with no obvious risk factors or symptoms. We may not perform an ekg, or we may run these tests once and then never run them again if everything appears normal. Conditions like atrial fibrillation, however, can arise later in life. So a normal EKG earlier in life is doesn't necessarily preclude a future problem. Knowing about genetic risk may also prompt more regular testing that can catch a potential life threatening condition earlier on. So the options here are to run these somewhat more complex tests on everyone, or find a way to determine who should get regular testing. Family history can be helpful Patients with a family history of sudden cardiac death or known cardiac issues are are probably good candidates for routine screening, but family history alone may not give us the whole picture. Some mutations are incompletely penetrant, meaning some but not all of the carriers are affected. So it's entirely possible to have a genetic risk factor without a family history. Further, a vague family history of heart disease could mean any number of different conditions, and not all patients are able to provide a complete detailed history that would inform more advanced tests. So in this domain Genetic testing can sometimes uncover a more specific inherited risk that may change what tests you order and when. This does not mean everybody should go out looking for every conceivable arrhythmia or cardiomyopathy gene. But compared with ascvd, this is clearly a category where genetics can provide more incremental value. So I would kind of put this in the middle category. Not an area for broad routine testing in everyone, but clearly more defensible when the personal or family history points in that direction. Cancer is where the conversation becomes much more nuanced, because cancer is, after all, a genetic disease. But most cancer is not due to inherited DNA. The vast majority of cancers arise from what are called somatic mutations, as opposed to germline mutations. These are acquired mutations, not the inherited ones, and they won't appear on standard genetic tests. In fact, by most estimates, only about 5% of cancers are attributable to inherited germline mutations. Put another way, most people who have cancer would not find anything unusual in their inherited genetics. So the absence of cancer predisposing mutations certainly does not rule out the possibility of developing cancer later in life. But 5% matters because the cancers that fall into this category tend to involve highly penetrant mutations that carry substantial elevated lifetime risk, and because knowing about them changes management in meaningful ways. The clearest examples, which I've already mentioned, are BRCA1 and BRCA2. Women who carry BRCA mutations face drastically elevated lifetime risks of breast and ovarian cancer high enough that enhanced screening, chemo prevention, and even prophylactic surgery can be appropriate. But these are not the only breast and ovarian cancer genes. They are also associated with an increased risk of cancers such as pancreatic and prostate cancer, which broadens both the clinical implications and the family history clues that matter. Similarly, lynch syndrome, caused by mutations in mismatch repair genesis, dramatically increase the risk for colorectal cancer and several other cancers. And knowing your status changes screening intensity and frequency in ways that saves lives. These types of conditions also have implications for family members. A father who carries a mutation in BR I P1 that predisposes to ovarian cancer is not going to be concerned about his risk for cancer in an organ that he does not have. But knowing that he carries this variant is a very good reason for his daughters to get tested. Just as importantly, an apparent lack of family history does not entirely rule out the risk for having one of these mutations. While not the norm, there are certainly cases of patients carrying potent cancer predisposing mutations with an unremarkable family history. So does this mean everyone needs genetic testing for cancer? Not necessarily. For someone with no meaningful family or personal history of cancer, the pretest probability of finding a high penetrance cancer mutation is low enough that it's hard to justify routine testing on a population basis. That said, I do think cancer is one area where an individual may opt for testing without notable family history because unlike cardiovascular disease, there is no biomarker we can assess and the relative impact of these mutations tends to be quite high. Now, to be clear, most people will have a negative result here, and while that negative result can be reassuring, it's important that we don't lose sight of the fact that 95% of cancers that arise are still somatic mutations. There is one important technical point I want to make here because it's one of the most common sources of false reassurance I encounter. Consumer genetic tests oftentimes only test a few different cancer predisposing mutations. The original 23andMe test, for example, assessed only three pathogenic mutations in BRCA1 and BRCA2, but there are thousands of known pathogenic variants in these genes. So if a patient tells me that their 23andMe results came back negative for BRCA, that does not really tell me that they don't have an important cancer mutation. It just tells me that they don't have one of the three more well studied ones. For meaningful cancer genetic risk assessment, you need clinical grade panel testing, not a consumer genotype product. So cancer is one of the clearest areas where germline genetic testing can be very useful, but only when it is used to answer the right question with a very clear understanding of what the test is and is not. Covering neurodegenerative disease is a very different category, because here the balance between understanding risk and actionability is much shakier. And for obvious reasons, these diseases tend to be the most emotionally complex for patients to deal with. The most familiar example is of course, apoe, something we've talked about a lot on this podcast over the years. APOE 4 is the strongest common genetic risk factor for Alzheimer's disease, and it can shift risk in a meaningful way. Individuals with two copies of APOE 4 may have a risk of Alzheimer's disease up to 15 times higher than someone who does not have the mutation, but it is still not destiny. Not everyone who is homozygous for ApoE4, meaning has two copies develops Alzheimer's disease, and roughly 50% of people with Alzheimer's disease do not carry even a single APOE gene at all, let alone two copies. That said, I think that knowing APOE status can be useful for a few reasons. There are emerging therapeutic strategies such as opacetrapib, which we've also covered on this podcast being studied, that specifically show promise in APOE4 carriers. Based on the hypothesis that APOE4 affects lipid metabolism in both the brain and periphery. The data are still early, but it's a plausible example of where genetic information could begin to inform therapeutic decisions in a more personalized way, even for diseases as ravaging as Alzheimer's. It may also make us more aggressive about managing other modifiable Alzheimer's disease risk factors such as lipids and metabolic health, if we know the patient is starting from a higher baseline risk. For some patients, particularly those with a family history of dementia, knowing their APOE status is less about medicine and more about planning. It is far easier to discuss finances and long term care preferences many years before a crisis than during one. Beyond apoe, there are rare but highly penetrant mutations that drive early onset or familial forms of severe neur degenerative disease, including Alzheimer's disease, Parkinson's disease, Huntington's disease, as I mentioned earlier, and als. Diseases such as Parkinson's disease and ALS do not have one clear common genetic risk factor. Instead, only about 10% of cases are due to known genetic mutations. And so for someone with a parent or sibling affected, especially at an unusually young age, genetic testing may be an appropriate option. But broad population screening rarely makes sense in this category. The prevalence of these mutations are low, and unlike hereditary cancer mutations, the results don't yet really map onto established interventions. So testing here is almost always a personal decision driven by a specific family circumstance. More than any other type of disease, the value of testing here depends on the question being asked. Are you trying to estimate Alzheimer's disease risk for curiosity's sake, are you trying to determine whether or not you carry the mutation for a devastating familial syndrome? Are you trying to make treatment decisions or prevention decisions? Or are you really asking a planning question, gaining information that may help inform long term financial, career or even care decisions? All of these are valid questions, but ones that should be very carefully considered before testing. This is also the category where the psychological dimension of testing matters most. Here the question is not just whether the information is true, but whether it is likely to be useful for that particular person. There are no universal right answers, it is deeply patient specific, and it requires an honest conversation before the test is ever ordered. Once you move into diseases outside of the four Horsemen, areas like mental health and complex chronic conditions. The same themes we saw in ASCVD return Genetics clearly matter, but that does not mean that the current genetic testing changes care in a meaningful way. The genetic influences on mood disorders, stress reactivity and substance use are real, but the variants identified so far explain only a modest fraction of overall risk, and they do not yet guide treatment in a way that outperforms standard clinical care. Now, of course that may change in the future, but we are just not there yet. And that makes this space particularly vulnerable to the hype that outruns the science, especially the functional medicine style panels that test common variants and then build a story around detoxification, methylation, inflammation or neurotransmitter balance. The leap from this variant plays some role in this pathway to therefore this is the supplement protocol you need is almost always much larger than the evidence justifies. MTHFR is a prime example of this. Variants in this gene are real and they do alter folate metabolism to some degree. But the thing that often gets left out is just how common these variants are. Up to 40% of the population carries one or two copies of some of these variants. Think about what that means for a moment. If MTHFR variants were driving meaningful disease, we would expect to see it clearly in population level data. But of course we don't. The fact that these variants are so prevalent is itself strong evidence that their average effect is is small because natural selection tends to weed out variants that cause serious harm. And yet MTHFR has become one of the most over ordered and over interpreted findings in functional medicine. Patients are routinely told that their fatigue or brain fog or anxiety or a dozen other non specific symptoms are caused by MTHFR and they are placed on aggressive methylation protocols and based on a variant that for the vast majority of people is clinically irrelevant. The mere presence of an MTHFR variant is not a diagnosis or an explanation for mysterious symptoms or reason to spend a fortune on specialized just for you supplement stacks. A mutation can be biologically interesting without being clinically actionable. MTHFR is perhaps the clearest illustration of that distinction in all of clinical genetics, but it is far from the only one. In fact, once you know what to look for, a pattern emerges. Find a common variant with at least some science, inflate its importance, and then use it to justify a supplement protocol. Oftentimes these variants are explained in a way that is akin to personality tests or astrological signs. The description is just broad enough that practically Everyone can read it and say, wow, that describes me perfectly without realizing that the information applies to everyone. COMT and other neurotransmitter related genes are another favorite for this playbook. A common COMT variant is often used to tell people that they are a fast or slow metabolizer of dopamine, that it explains their personality, their stress response, and yet again, which supplements they should take. There is real biology here. Many of these gene variants do affect dopamine metabolism, but the jump from a common context dependent variant to a bespoke personality profile or supplement protocol is wildly overconfident. Then there are the so called detox panels. Tests that assess common variants in cytochrome P450 enzymes and related pathways and present them as a window into your liver's ability to, quote, handle toxins. The premise sounds scientific and the results often come back with color coded charts implying that your detox pathways are somehow compromised and in need of, wait for it, supplemental support. What these reports usually leave out is that the liver's detoxification machinery is extraordinarily redundant. When one pathway is less active, others often compensate. There is no recognized clinical syndrome of poor detox in otherwise healthy people based on common variants in these genes. The body has been solving this problem for a very long time without personalized supplement stacks, nutrigenomic tests that are marketed as a way to identify your perfect diet based on your DNA function. Similarly, there are some studies linking mutations in genes like FTO to better outcomes from certain diets. But these DNA specific diets often only perform as well as, if not worse than, conventional wisdom. You don't need a fancy genetic test to tell you to eat fruits and vegetables and get regular exercise. For these functional tests, we should be very skeptical not of genetics itself, but but of the claim that current testing can turn common variants into recommendations that are more specific, more reliable or more effective than good clinical care. In many of these settings, it simply cannot. One final area worth mentioning is pharmacogenetics. Unlike the kinds of functional medicine tests that I just described, pharmacogenetics is a very real and potentially very impactful way to utilize genetic information. Rather than asking about risk for disease, these tests address something that is far more practical. How might I respond to a medication, and could that help guide which one I choose? This is a very different kind of question, and genetics tend to perform much better when the question is that specific. This is especially relevant in areas where treatment is often trial and error, where side effects may be severe, or where metabolism varies meaningfully from one person to another. If someone has already struggled with medication tolerability, or if there are several reasonable treatment options and no obvious reason to choose one over the other, pharmacogenetic information may help refine the decision. For example, Plavix is one of the most commonly prescribed antiplatelet medications. In order for this drug to work, it needs to be activated by a specific enzyme called CYP2C19. About 10% of the population have gene variants that make this enzyme completely non functional, meaning their body can't convert Plavix into a usable compound. For someone who needs reliable platelet inhibition after a stent or another vascular event and carries one of these loss of function mutations, they can instead be prescribed a different drug that does not require CYP2C19. A very different example is HLA B58 and the drug very commonly used to treat uric acid called Allopurinol. Here the issue is not whether the drug will work, but whether it's safe to give the drug at all. Patients who carry HLA B58 are at a substantially increased risk of developing a potentially life threatening hypersensitivity reaction to the drug. In fact, the effect of this is so clear that testing for this gene prior to giving allopurinol has become standard of care for us in our practice and hopefully for any other physician out there. Listening other genes can help guide decisions about dosages or determine whether an entire class of drugs, as opposed to one particular medication, may be contraindicated. Pharmacogenetics does not necessarily dictate the answer, but it can help inform it. This is a more modest claim than what is often promised in the broader genetic marketplace, but it is also a much more defensible one. So if there's one place where inherited genetic testing may be most clinically useful for otherwise common conditions, it may be here. Not in trying to predict disease in a broad abstract way, but in helping optimize a specific treatment decision. Okay, now that we've gone through the major disease categories, I think it's helpful to zoom out and see how they could compare side by side. We've put a summary table in the show notes, and I'd encourage you to take a look. But let me walk you through the important takeaways. There are really two axes that matter. How large is the effect of the genetic variant? Meaning does it have a dramatic change on risk or only nudge it slightly? And how much does knowing about it actually change what you do clinically? When you lay things out this way, Hereditary cancer panels covering things like BRCA and Lynch syndrome sit squarely in the upper right quadrant. High effect size and high actionability on the opposite end. Consumer variant or SNP tests for things like MTHFR or COMT sit in the lower left of this 2x2 low effect and virtually no response clinically to the intervention. And most other categories fall somewhere in between. Pharmacogenetics, for example, has a moderate effect size but a relatively high actionability. It may not tell you whether or not you get a disease, but it can meaningfully change how a disease is treated. APOE is interesting because the effect size is real, but actionability remains somewhat limited, or at least it does for now. The main point is that these two dimensions don't always move together. A variant can have a large biological effect but still not change what you do. And a variant with a more modest effect can still be highly useful if it shifts specific clinical decisions. So let's say you've worked through this framework and you have a specific question, and you've determined that genetics is actually the right tool to answer it. You've thought through what you want to do with the results, and you're mentally prepared for whatever comes back. The next question is which test? And this is where a lot of people and a lot of clinicians get tripped up. Because one of the biggest mistakes people make is assuming that all genetic tests are more or less interchangeable, as though getting genetic testing is a single thing. But it isn't. There are many different kinds of genetic tests, and they differ enormously in what they measure, how much of the genome they cover, how reliable they are for a given question, and how clinically useful the results are likely to be. The key principle then is that the type of test you choose should be determined by the question you are trying to answer. More specifically, it should be determined by how much of the genome you actually need to look at to answer the question reliably. And in general, you want the test that captures what you need without unnecessary additional data. That is likely to generate confusion rather than clarity. There's a natural temptation here to assume that more is better. And for some people, in some cases, a comprehensive sequencing based test may in fact be a good option. But for many of us, that much data is overwhelming. The human genome, as we discussed, is enormous. The data files used to meaningfully interpret that sequence can exceed 100 gigabytes. Collecting more of it does not automatically mean we will get more insight. Sometimes it just generates more noise. With that in mind, let's walk through the main categories, from narrowest to broadest. Single gene or single mutation tests sit at one end of the spectrum. They look for a specific variant, usually because clinical presentation or family history already points towards it. If your mother carries a known BRCA1 mutation and you want to know whether you inherited it, that is a very specific question, and a targeted test is the right choice. It's precise, relatively inexpensive, and gives you a clean answer. This is genetics at its best. Narrow question, specific test, interpretable result. The limitation, of course, is that it only answers the question you asked. If the question is too narrow, you may miss something important that lies just outside of the test's scope. Genotyping arrays are the technology underlying most direct to consumer products. They scan for hundreds of thousands of common single nucleotide polymorphisms or SNPs, known positions in the genome where people commonly differ from one another. These tests can be useful for ancestry and physical traits, but because they only look at common variants, they will miss rarer but far more clinically significant mutations. A negative result on a consumer SNP test can create false reassurances because these tests capture only a narrow slice of the variants that may matter clinically. A related but distinct concept worth addressing here are polygenic risk scores. Rather than reporting individual SNPs, a polygenic risk score aggregates the effects of thousands of common variants across the genome into a single composite score meant to reflect overall genetic predisposition to a given disease relative to the population. The appeal here is obvious. It sounds like it should be more information than any single variant, and at the population level these scores can capture real signal. But at the individual level, the evidence is quite underwhelming. This is an active and genuinely interesting area, but it is still very early stage. When paired with other tests or analyses, such as in the Myriad myrisk test, they may help to further stratify risk. But for now I don't find these tests particularly useful on their own. Gene panels are up next. Rather than scanning the whole genome for common variants, a panel sequence is a defined set of genes known to be relevant to a specific condition or disease category. A hereditary cancer panel, for example, might include BRCA1, BRCA2, PAL B2, CHEK2, lynch syndrome genes, and dozens of others, all sequenced with enough depth to to detect rare high impact variants, not just the common ones. Pharmacogenetic panels work similarly, covering the key metabolic genes relevant to drug response. Panels tend to be the right tool when you have a specific clinical question and a defined set of genes that are well established as relevant to that question. They are more expensive than SNP tests, but often covered by insurance when there is a clinical indication and the results are far more meaningful for health decisions. Whole exome sequencing and whole genome sequencing sit at the broadest end of the spectrum. Whole exome sequencing covers all protein coding regions of the genome, roughly 1.5% of total DNA, but the region where the majority of known disease causing mutations occur. Whole genome sequencing covers everything, including the non coding regions, though our ability to interpret variants in those regions remains quite limited. Both generate enormous amounts of data and interpretation is highly dependent on the quality of the sequencing analysis. These tests are most appropriate for unexplained or complex presentations, a patient with a rare disease that hasn't been characterized, or a situation where a panel has come back negative. But clinical suspicion remains high. For most routine health questions, sequencing can likely answer the question, but it may provide more information than is needed. It can generate incidental findings and create more questions than answers. We've also put a comparison table in the show Notes that lays out each of these test types, what they measure and where they're most appropriate. Let me highlight where I think the most important distinctions lie. The biggest mistake I see people making is treating a consumer SNP test as though it were a clinical grade gene panel. These are fundamentally different tools. A SNP test is scanning for common variants. It's good for ancestry, it's fun, but it's not designed to answer clinical questions about disease risk. A gene panel, by contrast, is sequencing specific genes in depth, looking for rare, high impact mutations that the SNP test will miss entirely. That's why a negative BRCA result on a consumer test is not the same as a negative result from a hereditary cancer panel. On the other end, whole exome and whole genome sequencing gives you the most amount of data, but that doesn't automatically make them the best choice. More data means more incidental findings, more variants of uncertain significance, and more interpretive complexity. For most people with a defined clinical question, a well chosen panel is going to give you a cleaner, more interpretable answer than sequencing everything and hoping the signal emerges from the noise. One practical point that can be confusing is that these categories are not completely mutually exclusive in what they can find. The same pathogenic variant might be detectable on a targeted test, a disease specific panel, or a whole genome or exome sequence. So the choice is not simply about whether a variant is theoretically on the test, it's about whether the test is designed and validated to answer your specific question reliably and whether you only want to answer that question or that answer plus a larger amount of additional information. In other words, broad tests can often include the narrow answer, but they also bring more data beyond the scope of your question. For any genetic test that will inform a meaningful medical decision, I would strongly encourage using a CLIA certified laboratory with demonstrated expertise in the relevant area. The Clinical Laboratory Improvements Amendments or CLIA regulations set a minimum standard for laboratory quality, which at least tells you the labor completing the tests has been inspected and approved for human samples. Beyond that, you also want a lab that has deep experience in the specific domain. A lab that specializes in hereditary cancer genetics is going to give you a more reliable and better contextualized result than a general purpose sequencing facility. And before you order anything, look carefully at the data privacy policies. Genetic data is uniquely sensitive. It is permanent. It is shared with biological relatives who may or may not consent to data sharing, and the downstream implications of how it is stored and used are worth understanding before you hand it over. And finally, make sure you understand exactly what a test does and does not cover, not at a general level, but specifically for that test. What mutations does it detect? What does it miss? What will a negative test actually mean? These are questions worth asking explicitly and ideally working through with a clinician or genetic counselor before the test is ordered, not after the results come back. Now, of course, ordering the test is actually the easy part. Once the results come back, the real question is what to actually do with them. A genetic result is not like most other lab values. You cannot simply glance at it in the portal and move on. The more consequential the test, the more deliberate the follow up needs to be. And ideally you have already thought through the major possibilities before the test was ever ordered. One thing worth noting up front, a negative result is not always a clean bill of health. It means no pathologic variant was found on this specific test ordered, which is useful and sometimes very useful. But it does not override a strong phenotype or family history, and it does not mean something wasn't missed simply because it wasn't tested for a negative result deserves the same careful interpretation as a positive one. With that in mind, I find it useful to sort genetic findings into a few broad categories. The first is a result that confirms something already suspected. If a lab test or family history suggests a genetic condition, such as familial hypercholesterolemia, genetic testing can confirm its presence or absence. This may not change clinical management, but it can increase confidence in the diagnosis, solidify the plan and inform testing for other family members in addition to provide coverage for medication. The second and most valuable is a result that identifies a novel but actionable risk, something that wasn't necessarily on the radar before the test, but that points to a clear next step that may not have otherwise been considered. These can be from a test that was performed specifically to answer this question, such as someone who doesn't have a strong family history of cancer but opts to complete a hereditary cancer panel or an incidental finding from a broader test. For these results, knowledge of risk can inform more advanced cancer screening and a clear action plan can be made. The third category is a result that adds context but not necessarily new action. A variant associated with a structural cardiac condition in a patient who already had a normal echocardiogram, for example, or a metabolic risk factor that is already being tracked through phenotype. Not every finding demands a new intervention. The fourth and most difficult is a result that points to a risk with no RCT level action plan available. I think dementia risk in patients is probably one of the most common examples we see here. We don't really have validated screening tests or even well established preventive strategies. Of course, there are many things that we think there are compelling and suggestive data for, but it's not quite at the same level of cancer screening for a woman with a BRCA mutation. The value here is less about established medical action and potentially more about being on the front edge of of what prevention looks like and considering more planning or even perspective. That does not make the result less helpful, but it does shift what useful might look like. Every result in any of these categories should ultimately come back to a question. What now? Do we confirm a diagnosis? Do we increase our screening? Do we change treatments? Do we inform family members? Or do we simply document the finding without changing the management? If it's the last of these, I would call into question the purpose altogether. The test is just the information gathering step. The clinical value comes entirely from what happens next. So if I had to compress all of this into a single answer to the question should I be doing genetic testing? My obvious response now would be it depends. Some patients want all available information about their health full stop, and for them comprehensive testing may be worth it, even knowing its limitations. Others have a specific clinical question where more constraint testing is the right tool and some are perfectly content to leave it alone. All of those positions are reasonable, but regardless of where you land, the framework is still the same. Start with the question. Determine whether genetics is the right tool to answer it, choose the test that matches the question and think through what you'll do with the results before they arrive. To make this more concrete, I think there are a few buckets we can use to think through genetics. The best use case by far is for something like brca. These mutations are highly penetrant with clear actionability. Most people do not have these mutations, but for those who do, learning about them can be life saving. Genetics at its worst are the direct to consumer style tests that are marketed for health purposes. The tests that look at common low effect variants like COMT and MTHFR and treat them as gospel for justifying supplement protocols that evidence simply doesn't support. Most aspects of health are going to sit somewhere in the middle where genetic testing can be informative but but may not be quite as clearly actionable or with as much supporting evidence. For patients with questions about risk that can't be answered with lab testing such as predicted medication response, genetic testing can sometimes offer insight. I think APOE deserves its own place within this category. It isn't highly actionable in the traditional sense, but that certainly doesn't make it useless for patients with APOE4. We may be more aggressive in reducing other risk factors for Alzheimer's disease, such as aggressive managing of lipids, promoting greater insulin sensitivity and early adoption of treatments like GLP1 agonists. Or it may serve as the behavioral lever to help keep a person motivated and stick with a lifestyle intervention. We may not use this information the same way we would use pharmacogenetics, but it can matter for stratifying risk and long term planning. Beyond these categories, the clinical utility for genetics is less clear. Seeking out genetic information purely out of curiosity is not an illegitimate reason to test, provided you recognize that you may not get more clarity from the tests. Genetic testing is a tool, and like every tool we have in medicine, it has real strengths and real limitations, and its value depends almost entirely on how thoughtfully it is used. It is not a blueprint, it does not tell you everything, and it will sometimes raise more questions than it answers. But when the question is clear, the test matches the question and the answer changes something meaningful. That is when genetic testing earns its place. That is when it stops being just an interesting data point and starts being genuinely useful. The principle I'd leave you with is simple. Test with intention. Know what you're looking for, know what you'll do when you find it out, and know what you will do if you don't. Everything else follows from that.
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Thank you for listening to this week's episode of the Drive. Head over to Peteratti md.com shownotes if you want to dig deeper into this episode, you can also find me on YouTube, Instagram and Twitter, all with the handle Peteratti MD. You can also leave us review on Apple Podcasts or whatever podcast player you use. This podcast is for general informational purposes only and does not constitute the practice of medicine, nursing or other professional healthcare services, including the giving of medical advice. No doctor patient relationship is formed. The use of this information and the materials linked to this podcast is at the user's own risk. The content on this podcast is not intended to be a substitute for professional medical advice, diagnosis or treatment. Users should not disregard or delay in obtaining medical advice from any medical condition they have, and they should seek the assistance of their healthcare professionals for any such conditions. Finally, I take all conflicts of interest very seriously. For all of my disclosures and the companies I invest in or advise, please visit Peter Attia and where I keep an up to date and active list of all disclosures.