In Defense of DNA Diet Tests (They Can and Do Work)
Contents
The problem with some DNA diet studies
The first thing you need to know about “DNA dieting” is there is no one DNA diet. Studies which use a concert of genes to help improve a given health outcome are rare, and usually look at 1-3 genes instead. The study relied on by Scientific American to declare the end of DNA diets (as the science of nutrigenomics progresses everyday) looked at only 3 genes in the context of weight loss. 3 genes. Total. According to the Human Genome Project, the human genome has between 20,000 – 25,000 genes. One of the problems with “DNA diet” studies, as well as the reporting on them, is the failure to differentiate between the use of a single SNP vs. the use of an algorithm which factors in hundreds of SNPs.DNA diet commentary ignores the Black community
Another glaring issue ignored by Scientific American is the racial makeup of the DNA diet study they use to dismiss the efficacy of DNA diets. African Americans makeup 13% of the general population, yet the group studied by Stanford and cited by Scientific American was only 3% Black. 3 genes, and 3% Black participation. Not good enough.DNA diet studies cited by Scientific American conflict
As I will get into in more detail shortly, a previous study by the same researchers cited by Scientific American saw a major increase in weight loss of 33% when these three genetic markers were used to help participants lose weight. The subsequent study failed to see a benefit. Now that we’ve established the obvious error of dismissing DNA diets based on the reporting of Scientific American, let’s dive in and look at what successful DNA diets might look like.SNP Testing vs. Genetic risk scoring
A single nucleotide polymorphism, or “SNP,” is the most common type of genetic “mutation” found in people. We all have variants in shared genes which cause small changes in enzyme activity, or in the case of rare genetic disorders, the loss of function altogether. As a general rule, it is not a good idea to base dietary or supplement decisions on any one SNP. Many SNPs, such as MTHFR, are common in some populations, and hyper-focusing on a mechanism out of context leads to error. However, this doesn’t mean that SNPs aren’t important. For example, this Harvard study, which found a significant increase in weight loss when participants with a specific FTO gene variation were given a higher protein diet. These types of studies, while not dispositive of all health outcomes, are far more helpful than the current one-size fits all diet debates which leave many of us confused and sick. Just as we aim to diversify our stock portfolios, we should also take a pluralistic approach to SNPs and DNA diets. Genetic risk scores (GRS), which are also called polygenic risk scores, have the potential to be more reliable than the current study of one SNP at a time. On its page about polygenic risk scores, The National Human Genome Institute does a fantastic job of explaining the difference between single gene vs. complex diseases. Most nutrigenomic markers standing alone don’t determine health outcomes in the same way that a single gene disease, like cystic fibrosis unfolds. Rather than looking at just one SNP, algorithms like the one we have at Gene Food aggregate information from multiple risk related SNPs and assign a comprehensive score for a given macronutrient. The use of GRS will be a part of the future of personalized medicine and nutrition and studies are already showing that GRS has greater efficacy than just placing people on one size fits all diets like Keto. With that background out of the way, let’s dive into a deeper analysis of some of the DNA diet studies out there. For those who are interested, we also keep a table of some of our favorite studies on our Science page.BMC Nutrition nutrigenomics study
Researchers in the UK compared a ketogenic diet vs. a DNA tailored diet for maximum nutrition. Although weight loss wasn’t the goal at the outset, body weight, total cholesterol, HDL, and fasting blood sugar were all measured. The 114 subjects were monitored in two stages: a 24 week initial stage and then an 18 month follow up. The follow up after 18 months was put in place because it’s extremely difficult to lose weight and to keep it off. Many people who struggle with weight can follow a crash diet for a short period of time and have success, but long term the weight comes back. This was the pattern researchers found in this study. Initially, members of the ketogenic diet group lost on average about 2.5 more kg than the nutrigenomic group, who were placed on a low glycemic index DNA diet similar to our Forager diet. However, the results after the 18 month follow up period were stunning. After a year and a half, the weight loss for the DNA diet group was significantly higher than the ketogenic diet group, who saw significant weight gain after the 24 week sprint. After 18 months, the DNA diet group had lost on average 8 kg more than the ketogenic diet group. Further, the DNA diet group had significantly better results in lowering total cholesterol and fasting glucose, and in raising HDL. The nutrigenomic group had better adherence than the ketogenic diet group and were given an exercise program tailored to their genetics as well. By contrast to the JAMA study cited by Scientific American which looked at only 3 SNPs, the BMC study evaluated 28 SNPs and 22 genes. We are familiar with the genes used in the BMC study because we use them in our algorithm and include them in our Guide to Nutrigenomics. Notably, the BMC study increased dietary folate intake for those with MTHFR SNPs and gave them a B complex supplement with 400 mcg of folate (unclear whether methylfolate was given). The use of 28 SNPs to form a polygenic risk score, as opposed to trying to gauge outcomes from a single SNP, is a step in the right direction, and inevitably contributed to the success seen by the DNA diet group. However, the BMC study again has the fatal flaw of a lack of diversity. All the participants here were European Caucasian. This is one of the most exciting nutrigenomics studies to be released to date, and the fact that it was published by BMC Nutrition, one of the best peer reviewed journals in the world, makes it all that much better.The JAMA DNA diet study
The sole study Scientific American cites to support this proposition was performed on a total of 609 people and looked at only 3 genes in the context of weight loss. Subjects were assigned one of two “healthy” diets – a low fat diet and a low carbohydrate diet. Both groups lost weight. The low fat dieters saw a drop in LDL-C (average 5%) and the low carb dieters saw a drop in triglycerides (15%). The study authors then looked at data from subjects who had been assigned to a diet that didn’t suit their DNA (roughly half of the subjects in either group were on the wrong DNA based diet). People on a diet that was thought to be optimal for their genetics didn’t lose more weight than the subjects eating a diet that wasn’t right for their DNA. Since both groups in the study lost weight on their assigned diet, and because the group eating the genetically tailored diet didn’t lose more weight, Scientific American (SA) went with the “DNA diets don’t work” headline. However, authors of the JAMA study, researchers from Stanford, conducted a similar study in 2010 (based on the same 3 genes evaluated in JAMA) and found the opposite – that the group assigned to eat according to their DNA lost a lot more weight than the group eating against the grain of their DNA. The JAMA study was a missed attempt to replicate the success of this previous study where those matched to a DNA diet lost 13 pounds in a year while those eating without “genetic guidance” lost only 4 pounds on average.Journal Circulation Study
Furthermore, there are many other studies out there which show promise for the role of DNA in choosing diet, often based on only one polymorphism. For example, this study, which appeared in the Journal Circulation, a publication under the auspices of the American Heart Association, found that variants in the IRS1 genes (specifically IRS1 rs2943641 CC genotype) can benefit from a higher carbohydrate and lower fat diet to combat insulin resistance. The Circulation study evaluated 738 subjects over 2 years and saw improvements in both insulin levels and weight loss for those assigned to a DNA diet protocol. For me, the Circulation study was particularly interesting because it may shed light on which genotypes can utilize plant based diet protocols to combat high blood sugar, and conversely, which people might do better using a lower carb approach to insulin resistance and type 2 diabetes. For those of us following the “diet wars,” this issue is on the front lines. Plant based doctors say the problem is always fat and low carb enthusiasts blame the carbs and sugar. Expansion of nutrigenomics research could help us better answer these questions for individuals, rather than operating under the current fiction that everyone can follow one diet.The Predict-1 Study
One of the more ambitious evaluations of the role DNA can play in tailoring an individual’s diet was initiated by Doctor Tim Spector and Sarah Berry, epidemiologists at King’s College, London. Called Predict, Dr. Spector, aided by a prestigious team that includes Dr. Andrew Chan, of Harvard Medical School, set out to compile data on why certain individual’s respond so differently to different diets. Because identical twins carry the exact same genes, Dr. Spector included 700 identical twins in the study. The earliest data his team released looked at how different people metabolize fats and carbohydrates immediately after a meal, in what us called the “post-prandial” period. Although long term markers of blood sugar control, like HbA1c, get most of the attention, we now know that what happens to blood sugar immediately after a meal can actually be a larger driver of inflammation. In the Predict study, glucose, insulin, and triglyceride were measured after eating using continuous blood glucose monitors and finger prick tests. What I can’t understand is why the press billed the early results as a blow to nutrigenomics. The NY Times reported the results this way:The team concluded that genes play a limited role in how a person processes fats and carbohydrates. Among identical twins, only about half of the amount and duration of an individual’s post-meal blood glucose level could be attributed to genetic influence — and less than 30 percent with regard to insulin and triglyceride response.Half of the post-meal blood glucose response being attributable to genetics is remarkable. How is 50% a limited role for genetics? Dr. Spector’s findings are consistent with the way we use DNA in shaping dietary choices at Gene Food – as one piece of the puzzle, not the entire picture. Also, lost in the conversation about what the Predict study showed about the efficacy of DNA diets is the fact that Dr. Spector is a major player in a startup that hopes to sell you a personalized diet based on the state of your microbiome.
DNA diets and ketosis
Keto, and high fat diets, are all the rage these days. The big benefit of ketogenic diets are the ketones themselves, 1 which can be viewed as another “endogenous antioxidant” such as glutathione or superoxide dismutase. So, yes, a state of ketosis can be beneficial for some people. But here’s the problem – not everyone achieves a state of ketosis under the same conditions. Some go on a high fat, ketogenic diet, measure ketone levels, and find they cannot achieve a state of ketosis at all, thereby missing the protective effect of the ketogenic diet altogether. Why? Genetics. Changes in the PPAR-alpha genes make it very difficult for some people to achieve a state of ketosis. 2 Despite mountains of marketing for “keto” friendly products and meal plans, carriers of certain variants in the PPAR-alpha genes will find their best diet is certainly not a ketogenic diet as they are not in a position to take advantage of the metabolic benefits. After evaluating the body of research behind PPAR-alpha, authors of this article, which appeared in the Advances in Nutrition Journal, concluded PPARa status could impact on nutrition decisions:The interactions between genetic PPARα variants and the response to dietary factors will help to identify individuals or populations who can benefit from specific dietary recommendations.Huh, so the Advances in Nutrition Journal, a journal with hundreds of citations on PubMed, is concluding that PPAR alpha has promise as a future marker that can help people tailor diet to…genetics. Additionally, PPAR-alpha status also changes the way the body metabolizes polyunsaturated fatty acids (“PUFA”). In studies, the G allele was associated with greater plasma concentrations of triglycerides (“TG”) and apoC3 (a protein that increases the lifespan of LDL particles making them more dangerous for heart health) in subjects consuming a diet low in PUFAs (<6% of energy). By contrast, when PUFA intake was high, carriers of the G allele had lower TG and apoC3, indicating a significant dose-response relationship between PUFA intake and serum TG concentrations depending on the genotype . A good DNA diet scoring system will never focus on just one genetic marker, however, just based on this one PPAR-alpha gene variant, we could steer some people away from a high saturated fat ketogenic diet. In these subjects, a marker that usually goes down on keto, TG levels, could spike to unhealthy levels with resulting dangerous expression of apoc3, a protein that is viewed as very atherogenic in lipid circles.
DNA diets for heart health
The debate over dietary cholesterol, perhaps the single biggest point of contention in the diet wars. One side tells you eating an egg will kill you. The other side says eggs are a super food that can be eaten at every meal. Who are we to believe? Much of the debate comes down to cholesterol absorption. In many people, cholesterol levels in the body are tightly regulated. To the extent we absorb dietary cholesterol (or the recirculating pool in bile acids), the body simply makes less. 3 This is the rule of “cholesterol homeostasis” is the basis for the American Heart Association dropping its previous recommended upper limit of 300mg a day of dietary cholesterol per day. The changing of cholesterol guidelines was based on new and emerging science. In other words, science doesn’t stay static, it evolves. And that is exactly where nutrigenomics comes into play, as a new body of science that helps shine a light on why two people may respond differently to the same nutritional inputs. However, the general rule of cholesterol homeostasis does come with exceptions, many of which can be explained by genetic variability. For example, a recent evaluation by world renowned lipid expert Dr. Tom Dayspring and colleagues of over 600,000 blood samples from a laboratory in Virginia found that ApoE4 carriers were far more likely to be hyper absorbers of cholesterol. I had the opportunity to interview Dr. Dayspring on the Gene Food Podcast. His episode can be viewed, here. You can take things a step further by testing for the polymorphisms in the ABCG5 and ABCG8 regions that affect sterol absorption and cholesterol efflux. In other words, companies like ours can analyze the SNPs relevant to cholesterol absorption and score a customer to predict the likelihood that they will absorb more of the cholesterol they eat. Why would we do this? Because almost no one has access to the blood work necessary to get a full sterol absorption panel done. Only a small handful of labs measure for sitosterol, choletsanol, and camposterol, the sterols used as proxy markers for cholesterol absorption. Being clued in from a genetics test that you are much more likely to be a hyper absorber of cholesterol can be life changing information for some people, information that can help them craft a diet that decreases the risk they will develop heart disease early in life.Harvard and new frontiers for DNA diets
If there is one takeaway message here, it’s that DNA diets show promise, but more research is needed. The evidence we do have points towards ideas for future research with the potential to answer questions like “how much protein should I be eating?” In the case of evaluating the role of genetics in tailoring diet to specific protocols, analyzing extreme cases of total “loss of function” can be instructive. In the sterol example above, total loss of function for the ABCG8 genes results in a condition known as sitosterolemia. We are learning that the function of different systems in the body exist on a spectrum, with some exhibiting excllent function, some with total loss of function, and likely, many cases in between. For example, this Harvard health blog discussing the urea cycle, a complex biochemical process involved in the breakdown of protein waste products, that is driven by genes such as CPS1. The article discusses children born with zero urea cycle function. In these cases, ammonia, a waste product of protein metabolism immediately pools in the system, causing hyperammonemia. These cases of hyperammonemia due to loss of urea cycle function are easy to spot since children with the condition have a significant gene mutation that slows the urea cycle to a crawl. But is the urea cycle black and white? Not according to Harvard. Consider this quote:Urea cycle disorders are viewed as rare and primarily pediatric conditions, but there might be a whole range of unrecognized, genetically determined problems with protein metabolism experienced by adults. Some people may have mild mutations that compromise a gene’s function and cause slight symptoms. This may explain why one person eschews meat while another loves nothing more than a steak meal. Defects in protein metabolism may also explain why some people have bad reactions to high-protein diets like the Atkins diet.
DNA diets are not uniform
As you continue researching DNA diets, keep these issues in mind. First, there is no one uniform DNA diet. The studies on efficacy are mixed and they almost exclusively look at weight loss rather than say cholesterol absorption. Most of these studies focus on only 2-3 genes. A fair conclusion based on the scientific evidence available to us would be to say that DNA diets require more research. But, as we all know, that type of headline doesn’t drive clicks and ad revenue. Saying DNA diets “don’t work” is like saying the election polling industry doesn’t work, or that there is no reason to test biomarkers like LDL-C because not everyone with elevated LDL-C will die of a heart attack, or that meteorology doesn’t work because the weather woman is occasionally wrong about when that nasty rain storm will hit. DNA diets do work and their coverage in the clickbait science journalism world has been, well, unscientific. Just as election polling models, like Nate Silver developed at FiveThirtyEight, predict likely election outcomes, and just as LDL-C is a predictor of increased heart disease risk, and just as the weather woman uses meteorological tools to predict the weather, DNA diets, at least the good ones, are predictive tools that evaluate predispositions for a particular response to particular diet. As the BMC study cited above demonstrates, any good DNA diet scoring system takes into account multiple SNPs and then scores people based on the latest research. The resulting score isn’t your fate, it’s a path towards lifestyle changes that can help avoid potential pitfalls based on genetic predispositions.
