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With rates of obesity and associated diseases continuing to rise across the globe, we are constantly bombarded with new diet strategies to help us shed the excess pounds. One approach that has been gaining increasing interest in recent years is the use of genetics to create personalized diets to optimize metabolic responses to food intake. These so-called “DNA diets” are based on the concept of nutrigenetics, which describes how genetic variation influences responses to certain foods across individuals. But is there any evidence that such “genetically validated” diets truly provide a benefit for weight loss? A recent randomized clinical trial by Höchsmann and colleagues sought to address this question.
Genetics impact food processing
We know that many genes alter our experience with food (e.g., some people possess mutations that make cilantro taste like soap), and we know that certain gene variants influence our ability to process foods (think: lactose intolerance, caused by variants in the LCT gene), so it is not unreasonable to think that we might be able to use genetically determined variation in nutrient absorption and metabolism to determine which foods an individual responds to in such a way that promotes greater energy expenditure or a reduction in overall appetite.
Genes of particular interest in this capacity would include those involved in metabolism of carbohydrates and fats, as genetics could then be used to inform an individual’s optimal ratio of these two macronutrients for promoting weight loss and metabolic health. One such gene could be AMY1, which encodes amylase, the enzyme found in saliva that is responsible for breaking down carbohydrates. Some individuals possess multiple replicates of this gene on the same chromosome, and greater copy numbers of AMY1 are thought to result in more efficient/effective digestion of carbohydrates, conferring higher “carb-tolerance” to these individuals. Fat processing, meanwhile, may be influenced by variants in genes encoding fatty acid desaturase enzymes, including FADS1 and FADS2, which are involved in fat metabolism and have been linked with weight gain.
The fact that genes influence our processing of certain macronutrients motivated Höchsmann et al. to test the notion that individual genetic profiles might be leveraged to aid in weight loss.
About The Study
In their 12-week randomized trial among subjects with overweight or obesity, the investigators first tested participants for variants (i.e., single nucleotide polymorphisms, or SNPs) in ten genes thought to be associated with metabolic responses to dietary carbohydrate or fat. For each of these SNPs, an individual could have one of three genotypes (i.e., homozygous for one variant, homozygous for the alternative variant, or heterozygous – that is, one copy of each variant), so each was scored as a 0-2 for “high fat/low-carbohydrate” and “high carbohydrate/low-fat” responsiveness, and scores were aggregated. Participants were determined to be “fat-responders” (meaning they were expected to lose weight more easily with a diet high in fat) if they scored ≥4 for a potential high-fat response and <7 for a potential high-carbohydrate response, and they were determined to be “carbohydrate responders” (expected to lose weight more easily with a diet high in carbohydrates) if they scored <4 for a potential high-fat response and ≥7 for a potential high-carbohydrate response.
From the original pool of 275 eligible participants who underwent genetic testing, 106 were excluded because they were determined to be responsive to neither dietary pattern or to both. “Fat responder” and “carbohydrate responder” groups were then subdivided to receive a diet either aligned with their genotype (genotype-concordant) or at odds with their genotype (genotype-discordant), resulting in four total groups: (1) fat-responders on high-fat diet (n=44); (2) fat-responders on high-carbohydrate diet (n=41); (3) carbohydrate-responders on high-fat diet (n=21), and (4) carbohydrate-responders on high-carbohydrate diet (n=16).
The high-fat diet consisted of 40% calories from fat and 45% calories from carbohydrates, while the high-carbohydrate diet consisted of 20% calories from fat and 65% calories from carbohydrates. Protein accounted for the remaining 15% of calories in both diets. Though food itself was not provided, participants were given detailed diet-specific meal plans. Additionally, these meal plans were designed to impose a calorie deficit for each participant of approximately 750 kcal/day.
By the end of the 12-week diet intervention, all four groups showed reductions in both body fat percentage and total body weight. However, the authors observed no statistically significant differences between any groups in either metric, regardless of whether the participants were on a genotype-concordant diet or a genotype-discordant diet, and apart from minor differences in self-reported cravings between groups, they also saw no differences in other outcomes assessed, including blood pressure, HOMA-IR (a measure of insulin resistance), and insulin levels. Though the genetically concordant groups trended slightly and non-significantly toward greater improvements in weight loss (-5.3 kg for genetic-concordant diet vs. -4.8 kg for genetic discordant diet) and body fat percentage reduction (-1.3% for genetic-concordant diet vs. -0.8% for genetic discordant diet), ultimately, this study found that genetically concordant and discordant diets produced the same results, indicating that the intervention that they had in common – namely, the 750 kcal/day caloric deficit – had a far greater impact on body weight and body fat than whether the diet was in line with genetic predispositions.
Those on discordant versus concordant diets within each macronutrient response group did not differ even in measures of diet preference, intervention satisfaction, restraint changes, or overall hunger. Thus, it seems likely that even in the case of a longer-term but less severe caloric deficit, adherence would likely not differ in genotype concordant versus genotype discordant groups.
Why Nutrigenetics (Currently) Doesn’t Impact Weight Loss
As explained above, the logic of genetics-based diets is theoretically reasonable, so why did it fail in practice in this randomized trial? The most likely explanation is that, at present, nutrigenetics simply lacks the fidelity necessary to herald an era of “precision nutrition.”
One aspect of this problem is in segregating individuals into diet patterns based on genetics. The Höchsmann et al. study utilized just two very broad categories of diets – differentiated only by the variable of carbohydrate to fat ratio – but used several genes to determine whether a given individual fell into one category or the other. This redundancy ought to increase the accuracy of each participant’s classification, while the broad diet categories ought to maximize the likelihood that a given individual can meet the definitions for either class. Yet even still, over half of eligible participants (106 of 275) did not fit cleanly into either dietary pattern (either because they were responsive to both or neither dietary pattern).
Sure, these 106 participants might just need to adopt an intermediate balance of fats and carbohydrates, but the large exclusion rate highlights a bigger problem. Genetically informed diets are not an efficient way of determining one’s response to any single dietary variable. To find out whether you control weight better on a high-fat or high-carbohydrate diet, trying each diet for yourself will provide an answer that is far more reliable, cost-effective, and efficient than getting a genetic test. The real hope for nutrigenetics is in creating more finely tailored diets – taking into account genetic variation in responses to micronutrients, optimal meal times, types of carbohydrates and fats, and countless other variables. But for each additional variable introduced, the likelihood that genetics can be used to accurately and cleanly assign an individual to an “optimal” dietary pattern becomes statistically lower and lower.
But the concept of genetically informed diets for weight loss also faces a more inherent problem. Though observational data have shown that some of the genes chosen for this study are associated with obesity, many factors outside of macronutrient-specific digestion also influence body weight. Indeed, the vast majority of obesity-associated genes are expressed primarily in the brain and are thought to exert their effects through their roles in nutrient sensing, food reward signaling, and other processes not directly related to digestion. Many of these processes may be completely unaffected by diet composition, or if diet composition does play a part, the connections are less obvious than with macronutrient-specific digestion pathways, so it’s unclear exactly how to design an optimal diet based on these genetic variants. Finally, there are many, many environmental factors that influence the interaction between obesity-associated genes and diet, adding further complexity and uncertainty.
Indeed, even if DNA-informed diet personalization becomes feasible and reliable, at no point will this approach ever provide anyone with a static, life-long action plan for eating. New information will constantly come to light, necessitating revisions to previous algorithms. Other aspects of an individual’s health will change over time, necessitating dietary changes to achieve a new “optimal.” Even foods themselves change, as new options appear or nutrient compositions vary and evolve.
Is there a future for nutrigenetics?
The field of nutrigenetics has too many unknowns to offer substantial utility in weight loss at present, but it’s important to note that our understanding of both genetics and energy homeostasis has come a long way in a relatively short time, and as knowledge continues to build, it’s possible that a genetic approach to dieting could be a viable option in the future. But as we see from the failure of even the simple, proof-of-principle genetics-based diets used by Höchsmann et al., that future is still a long distance away. To realize it will likely require far more than advances in genetics alone; we will need proteomics, metabolomics, neuroscience, microbiome characterization, and many more fields to come together and form a cohesive picture – one that will nevertheless be subject to change as additional information comes to light.
Unfortunately, there is currently no biohacking magic solution when it comes to weight loss. As this current study shows, even the wealth of genetic information now available to us does not yet offer us a way around the two tried-and-true requirements for weight loss: some form of caloric restriction, and maintaining it over time.
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