Have you been Googling “do DNA diets work?”
If you have, you may have found an article written by Scientific American titled “Matching DNA to a Diet Does Not Work.”
This article is click bait, pure and simple.
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. The study relied on by Scientific American to declare the end of DNA diets (as the science of nutrigenmoics rapidly expands) looked at only 3 genes in the context of weight loss.
As I will get into in more detail shortly, a study by the same authors 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. So, on this narrow issue, the science is batting .500 and yet the headline is DNA diets don’t work.
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 over 100 SNPs.
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.
It is not a good idea to base dietary or supplement decisions on any one SNP. Many SNPs are common, 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) have the potential to be more reliable than the current study of one SNP at a time. 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.
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.
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.
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.
Can we conclude from the sampling of studies I’ve referenced above that DNA diets work uniformly across the board?
No, not based on the handful of genes studied to date.
Conversely, can we conclude that DNA diets don’t work?
We are just beginning to scratch the surface of nutrigenomics research. The studies to date have looked at a small sampling of SNPs – often just one or two. And yet, the human genome contains approximately 25,000 genes. The SA headline would have you believe the state of “the science” is settled, that factoring genetics into nutrition decisions is just another blood type diet, but actually the opposite is true. Personalized nutrition is not another diet fad, it’s an emerging body of science that grows by the day, and DNA, while not the only factor, plays a big role.
The Predict 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.
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.
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.
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.
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.