Despite repeated public awareness campaigns and official dietary recommendations, the obesity epidemic is a persistent problem in the United States, and obesity-related conditions such as metabolic syndrome are a growing concern.
The lack of personalized dietary advice may partly be the reason for this.
For instance, one study pointed out that giving specific weight loss tips and having an empathetic approach toward those trying to lose weight can be much more beneficial than simply telling someone to improve their diet.
Another intriguing study in mice pointed to genes as a key factor that may determine which diet works.
At the time, the researchers concluded that if they could replicate the same findings in humans, they would prove that “precision dietetics” may work a lot better than the standard “one-size-fits-all” approach.
Now, groundbreaking research does just that. Drawing from a large twin study, scientists have expanded the findings by conducting a nutritional response study with applied machine learning algorithms to show that one size really doesn’t fit all when it comes to a person’s diet. In fact, the new study reveals that even identical twins respond differently to food.
These findings are part of what is the largest ongoing scientific study of its kind, which researchers at King’s College London (KCL) in the United Kingdom and Massachusetts General Hospital in Boston — in collaboration with nutritional science company ZOE — carried out.
The team presented the first results of this ongoing research at both the American Society of Nutrition conference (which took place in Baltimore, MD) and the American Diabetes Association conference (which took place in San Francisco, CA).
Tim Spector, a professor of genetic epidemiology at KCL, led the TwinsUK Study, which provided the foundation for this large new project. Prof. Spector is also the scientific founder of ZOE.
Studying people’s responses to food
In the TwinsUK study, Prof. Spector and team examined 14,000 identical and nonidentical twins in an effort to understand the causes of various chronic conditions and distinguish between what may be genetic or environmental triggers.
Secondly, as part of the large-scale new research project called “PREDICT 1,” Prof. Spector and colleagues expanded on the TwinsUK findings by examining the biological responses that 1,100 participants had to certain foods over a period of 14 days. Around 60% of these participants were twins.
The researchers measured markers such as blood sugar levels, triglycerides, insulin resistance, levels of physical activity, and the health of their gut microbiome.
The participants registered factors including their food intake and hunger levels using an app. The researchers also intensively monitored their sleep and exercise activities and took their blood samples.
Speaking to Medical News Today, Prof. Spector shared additional details about how the team conducted the study. “The study uses an app specially designed to collect the most detailed and robust dietary data ever collected before at this scale,” he said.
“Uniquely, the app combines dietary assessment technology with real-time support from a team of nutritionists, ensuring that the best quality detailed dietary data [are] collected.”
“[M]achine learning allows us to combine all [these] data to predict an individual’s personalized responses to food,” Prof. Spector added. “The more people who participate, the better those predictions become.”
Identical twins respond differently to food
The results showed that people’s biological responses to the same meals varied widely. This was true regardless of whether the meals contained carbohydrates or fat.
For instance, some people had spikes in blood sugar and insulin levels — both of which are implicated in weight gain and diabetes.
Others showed spikes in triglycerides that lasted for hours after a meal. Some research has linked triglycerides with heart disease.
Importantly, genes did not fully explain these variations. In fact, less than 50% of the variation in blood sugar, less than 30% of the variation in insulin, and less than 20% of the variation in triglycerides were down to genes.
Also, the scientists “found out that identical twins shared 37% of the bacteria in their gut — only slightly higher than the 35% shared between two unrelated individuals,” Prof. Spector told MNT. Despite having the same genes and exposure to similar environments, identical twins often had very different glucose responses to set meals, whether they were high in carbs, fiber, fat, or sugar.
Surprisingly, the research also revealed that the information on the foods’ nutritional labels — such as fat, protein, and carb content — accounted for less than 40% of the difference between people’s biological responses to foods with a similar calorie content.
These results, the team explains, suggest that factors including individual differences in people’s metabolism, gut microbiome, schedules, meal timings, and physical activity levels are just as important as the nutritional content of the food.
A ‘shift’ in the world of nutrition
“In the world of nutrition, there’s a real shift happening,” Prof. Spector told MNT. “People are finally starting to reject the notion that if everyone just follows the general guidelines (five servings of vegetables, counting calories, reducing fat) they’ll be healthy forever.”
“There’s also a lack of clarity around the impact of food choices on health and disease, or the best nutritional plan that each individual should follow to optimize their health and control weight.”
“This research shows us for the first time just how much our responses to food can be modified; that it’s not all determined by our genes or the nutrient composition of the meal.”
Prof. Tim Spector
“This is really exciting,” he said, “as this means we have the power as individuals to change how we respond to food and to choose the food that is best for us as individuals.”
He also shared with us his team’s future plans. “For the remainder of this year,” he said, “we are expanding ZOE’s PREDICT study in collaboration with Stanford University and Massachusetts General Hospital, and we are enrolling 1,000 volunteers across the U.S. to participate from home.”
“We will continue to collect a wide dataset from as many people as possible to develop better research and help even more people understand their responses to food so they can make their own decisions.”
“In 2020, we are planning to launch the home test and app, which will help individuals understand their unique responses to any food so they can optimize their metabolism.”