Over a decade ago, spurred by the success of the Human Genome Project and with the affordability of genetic sequencing, scientists began to open the door to the promise of “nutrigenomics.” Could personalized nutrition, informed by the understanding of an individual’s DNA, help prevent and even perhaps treat a diet-related diseases?
The results of some early studies from Stanford, Harvard and elsewhere were compelling to say the least: Genetic differences seemed to predispose individuals to lose totally different amounts of weight on different types of diets. A multimillion-dollar industry was born, premised on marketing DNA-based diets. However, subsequent research has failed to illustrate any statistically significant difference in the weight loss between overweight individuals who “eat right for their genotype” and the ones who do not.
In fact my friends, all the effect of genes on obesity has been very hard to tease out; various studies put the figure at anywhere from 35% to 85%. Nutritionists have long observed that absolutely no one weight-loss strategy will work for all people, also that individuals show striking differences in their responses to different diets. But, what then, explains the extremely large variation in individual metabolism?
Sarah Berry and Tim Spector in 2018, epidemiologists at King’s College, London, and Dr Andrew Chan, of Harvard School of Medical, began a progressive new search for the true answer. Their study, that was called Predict, is a comprehensive experiment to look at individual responses to different foods. The results, that was presented in June 2019 at the American Society for Nutrition’s annual conference, documented, for the very first time, with surprising variations in how well participants processed carbohydrates and fats, even among identical twins. How efficiently a person metabolized one macronutrient was absolutely predictor of how that person might respond to another.
We are indeed, getting closer to being able to provide the necessary guidance for each individual ideal diet should actually be, said Dr. Eric Topol, who is a geneticist at the Scripps Research Translational Institute in La Jolla, California, However, he was not affiliated with this study. For decades Dr. Spector has been exploring the causes of individual variation in disease risk, including diet-related ailments. In 1992, Spector set up TwinsUK, a research registry that now includes more than 12,000 identical and fraternal twins. Based on these twins, Spector concluded that our genes contributed 70 percent of an individual’s risk for obesity, on a oven all average.
Intrigued, Spector began a series of studies to tease out which factors influenced the remaining 30 percent. In 2014, he began the British Gut project, which was a crowdsourced effort to better understand the diversity of gut microbes, their response to different dietary interventions and their effect on weight. Among Spector registry of twins, he noticed, even the identical pairs shared only about 50% of their gut bacteria.
Dr Spector then started Predict to investigate how variations in people responses to carbohydrates and fats might contribute to obesity. Eating foods that contain carbohydrates and fats causes glucose, insulin and triglyceride levels in the blood to rise and fall; spikes that are way too high, too prolonged and too frequent are associated with inflammation, heart disease, weight gain and diabetes. This study included 700 identical twins, 100 U.S. volunteers and 300 British volunteers, and gathered data on almost everything that will affect metabolism: gut microbiota, exercise, sleep duration, body-fat composition and much more.
These initial results, however, analyzed only the rise and fall of glucose, insulin and triglyceride levels in the blood after all the participants had eaten standardized meals. The team came to the conclusion that genes play a limited role in how an individual processes carbohydrates and fats. 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% with regard to insulin and triglyceride response. The most important factors in metabolizing food, it seems are environmental: exercise, sleep, stress and the diversity of the gut microbiome.
This is actually very exciting for the scientists and individuals, said Dr. Berry. “It has shown us just how much is not genetic and is therefore modifiable.” Dr. Berry noted that the proportion of carbohydrates and fats in a meal explained less than 40% of an individual’s response to that food. This finding “reinforces the message that we need to focus on the whole lifestyle approaches instead of the individual foods and nutrients,” Dr, Berry said.
The full data set will take Dr, Spector and his colleagues, which is some 40 scientists around the globe-many years to analyze, even with the help of machine learning. However, it was already possible to glean individual insights, Dr. Spector said. After eating potato chips, one of the subject repeatedly experienced a triglyceride peak six times higher than that of the identical twin. That degree of awareness could help steer the chip-sensitive twin toward a snack with lower-fat, Dr. Spector said.
Jennie Brand-Miller, who is a professor of human nutrition at the University of Sydney in Australia, that was not involved with Predict, said that individualized nutrition advice, instead of the standard dietary guidelines that are based on population-wide averages, could significantly improve public health. “The one-size-fits-all nutrition guideline is antiquated,” Dr. Brand-Miller said. She noted that one in three individuals has a poor metabolic response to sugar; identifying those individuals, and then teaching them how to avoid the spikes in blood glucose, could indeed reduce their odds of later developing diabetes by as much as 40%.
The standard nutrition guidelines are usually built on the data from questionnaires, that ask people how frequently they had ate certain categories of foods in the past year. By using that approach, it provides useful data about the overall trends, however, it is also flawed: Respondents are notoriously bad at recalling their food choices, and unfortunately, the averaged data cannot offer personalized guidance. But, a more detailed view of our metabolic differences has come just recently, with the advent of affordable machine learning, wearable sensors and the genetic sequencing. This result has become a surge of overwhelming interest in the field.
In February 2019, another large-scale, multiyear personalized nutrition study was started at the Swiss Federal Institute of Technology, in Lausanne. The basic parameters of a healthy diet are without a doubt very well known: lots of whole grains, dark leafy greens and lots of other vegetables, healthy oils, and seafood, all the salmon that you can eat, preferably pink, and of course, very little red meat or refined carbohydrates. The problem is not that the guidelines are wrong or insufficiently personalized, said Tim Caulfield, who researches health law and policy in Canada, at the University of Alberta. The problem we have is that people are not following them. “It is a fantastically complex issue that has to do with our built environment, with socioeconomic, with our food environment, with marketing, and with our activity levels-so many things,” Caulfield said.
As a study, Predict is still in it early stages; whatever individualized recommendations it might provide, there is no real concrete evidence yet that they can improve an individual health any more than the standard dietary guidelines can. Nonetheless, my friends, its scope and rigor are novel. “It will require further validation, and it does not equate with preventing cancer or heart disease or any other outcome,” said Dr.Topl. “However, it is still important, if we’re ever going to get to the food as medicine ideal.”
Participating in the study can be grueling. The subjects are first put through an extensive battery of tests, that include blood draws hourly and scans of their body fat and bone mass, which is in a hospital setting. Then after that, for two weeks, they must consume a series of set meals, that includes a selection of muffins that, containing different combinations of fat, protein and carbohydrate, along with glucose drinks, fiber bars and protein shakes. Any other food or beverage that are consumed must be weighed and logged.
Each participant wears a continuous glucose monitor and an accelerometer to measure sleep and activity levels, and provides samples of saliva, feces, urine and blood-every thing except tears. With entrepreneurs, Dr. Spector also has started a for-profit company by the name of Zoe, with the hope of creating an app that will offer users individualized nutrition advice about how to eat correctly and ultimately, how their bodies could respond to foods that they have not yet tried.
However, for now Caulfield has low-tech advice for anyone that is in search of personalized nutrition: Look at your bathroom scale, That number is way more predictive of your future health than most of the so-call reliable information you can get from these direct-to-consumer companies, he said.
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