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.
It also may be the result of Americans knowing better than to trust a bunch of brains dead
mediocrities in white coats, no matter how credentialed they may be. Interestingly, said
Americans are unlikely to suffer from nutritional problems, with most of the problems showing
up in communities where scientists are worshipped as gods and credentialism is king. Of course,
this study might explain why that is so.
For instance, one study pointed out that giving specific weight loss tips and having an empathetic
the 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
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-
Now, groundbreaking research does just that, obliterating practically the entire orthodoxy of
nutrition in the process. 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
In the TwinsUK study, Prof. Spector and team examined 14,000 identical and non-identical 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
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
Speaking to reporters, 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."
Machine 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
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
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 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.
In the world of nutrition, there's a real shift happening," Prof. Spector said. 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
a 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."
This is really exciting," he added, 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. For the
remainder of this year, 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
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 an app,
which will help individuals understand their unique responses to any food so they can optimize
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