Human postprandial responses to food and potential for precision nutrition
June 11, 2020
Landmark Study Published in Nature Medicine and Presented at the American Society of Nutrition Shows Dietary Inflammation Varies Dramatically Among Healthy Adults, Pointing to the Need for Personalization in Eating
- The PREDICT Studies reveal multiple factors ranging from gut microbes, blood sugar, fat and insulin levels to exercise and sleep impact an individual’s ability to achieve optimal metabolic health.
- Even identical twins respond differently to the same food; identical twins share only a third of their gut microbes.
- This ongoing study has shown that dietary inflammation varies up to ten fold in healthy adults.
- Results point to the need for personalized eating plans to sustainably combat weight and health challenges, setting the stage for artificial intelligence (AI) to help people manage their health by choosing foods that work optimally with their biology.
- ZOE, the sponsor of the study, is launching a test kit using this science to help people achieve their healthiest weight, by profiling their unique gut microbes and inflammation after meals and using AI to create a personalized eating plan.
Boston, US and London, UK, 11 June 2020 – Health science company ZOE announced today the first published results from PREDICT, the largest ongoing nutritional study of its kind. The results, published in Nature Medicine and abstracts shared at the American Society of Nutrition show a wide range of inflammation responses after eating, even amongst apparently healthy people. Dietary inflammation is linked with increased risk for conditions such as heart disease, type 2 diabetes and obesity. The study suggests improved weight management and health could be achieved by eating food that are personalized to reduce dietary inflammation.
ZOE will launch a new test kit and app in July that uses AI to develop personalized eating plans based on a person’s unique gut microbes and dietary inflammation. They have launched today a waitlist for customers eager to access the new kit.
“When it comes to weight, we’ve traditionally put a huge emphasis on factors we have no control over, like genetics,” said Tim Spector, MD FRCP FRSB, scientific co-founder of ZOE, senior researcher of the PREDICT study and Professor of Genetic Epidemiology, King’s College London, UK. “The fact is, while genetics plays a role, there are many more important factors that impact an individual’s response to food and maintenance of a healthy metabolism. This study shows that achieving a healthy weight requires a scientific approach to eating that takes into account an individual’s unique biology.”
"Our data show that the time of the day when you eat a meal matters to how high your glucose will rise. And the same meals can have different effects on two people. The important thing is that we can now predict to a large extent this responses at least for blood sugar and therefore optimize the dietary advice" said Dr Ana Valdes from the University of Nottingham, one of the scientists involved in the project.
Led by Professor Tim Spector and his team at King’s College London and ZOE, in collaboration with researchers in the US, UK, Italy and Sweden,* the PREDICT-1 study recruited participants across the UK and the US. This consisted of 1,103 subjects including 660 identical and non-identical twins from the TwinsUK cohort. The study measured a wide range of markers from blood glucose, fat and insulin levels to exercise, sleep and gut bacteria (microbiome).
Every PREDICT participant attended a full hospital day at the start of the study for detailed blood measurements and testing of responses after eating set meals with carefully controlled calorie, fat, protein, carbohydrate and fiber content. They then carried out the rest of the study at home, eating a schedule of set meals and their own free choice of foods.
Participants wore a continuous glucose monitor and activity tracker throughout the duration of the study, took finger prick blood samples to monitor blood fat levels and collected stool samples for microbiome analysis.
Despite wide variation in nutritional responses between participants, results from identical meals eaten on different days showed that individual responses to the same foods were remarkably consistent for each person. Raised levels of blood sugar and blood fat can lead to inflammatory responses via oxidative stress and lipoprotein remodelling.
Sarah Berry, Senior Lecturer, Nutritional Sciences at King's College London said, "Our study has found that the increase in fat and glucose in our blood after eating a meal initiates an inflammatory response which differs hugely between individuals. This meal-induced inflammatory response is largely dependent on the rise in blood fat after the meal. Dietary and lifestyle strategies to reduce prolonged elevations in blood fat and glucose may, therefore, be a useful target to reduce low-grade inflammation in preventative health."
Christopher Gardner, Director of Nutrition Studies at the Stanford Prevention Research Center and an Associate Professor of Medicine at Stanford said, “We’ve known for a long time that the broad distinction of fats vs. carbs is relatively meaningless in comparison to differentiating food sources of healthy fats and healthy carbs from their less healthy counterparts. The PREDICT studies are taking this to the next level by demonstrating that the wide range of foods that are sources of healthy fats, and the wide range of foods that are sources of healthy carbs can have PREDICTably different metabolic effects on different individuals when put in the context of quantifiable individual factors such as microbiome, sleep and physical activity. An impressive step forward in personalized and precision nutrition.”
“When we looked at blood sugar and fat levels across participants who ate the same meal, we could see up to ten times difference in their bodies’ response,” said Andrew T. Chan, MD, MPH, lead researcher, Professor of Medicine, Harvard Medical School, Professor of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Chief of the Clinical and Translational Epidemiology Unit, CTEU Massachusetts General Hospital. “Many people who would traditionally be viewed as healthy, showed real signs of metabolic stress after eating certain foods. By using AI to predict responses to these meals, we’re able to identify a combination of foods for an individual that could reduce potentially harmful inflammatory processes that have been linked to obesity, heart disease, diabetes, fatty liver, and cancer.”
PREDICT study results showed:
- Genetics plays a minor role in determining personal nutritional response and even identical twins can respond very differently to the same foods. This suggests that tests offering personalized nutrition advice based only on genetic information are ineffective.
- Everyone is unique in the way their bodies respond to eating food (nutritional response), so there is no one “right” way to eat. Traditional standardized diets (e.g., low carb diet, low calorie diet, etc.) and meal plans therefore miss the mark.
- The optimal time to eat for nutritional health also depends on the individual rather than fixed “perfect” mealtimes. The researchers found that some people clearly metabolized food better at breakfast while others saw no difference. This is the subject of ongoing research.
- Optimal meal composition in terms of fat, carbohydrates, proteins and fiber (macronutrients) is also highly individual, so prescriptive diets based on fixed macronutrient ratios are too simplistic and will not work for everyone. For example, a sensitive glucose responder may need to reduce carbohydrates whereas someone else may be able to eat these freely.
- The relationship between the calories consumed in a meal and nutritional response is weak and the form a food is in (cooked, chopped, ground) will produce a drastically different result.
The ZOE plan: Harnessing AI for Better Health
Using this ongoing research, the ZOE team in partnership with scientists around the world has developed a new personalized eating plan that will help you hit your healthiest weight by reducing dietary inflammation and supporting your gut. This is not a diet or calorie restriction plan. The at home test kit is based on the novel tests developed for this study but easy to use and offers insights into your unique gut microbes and dietary inflammation. Once you’ve tested your body, you’ll be given your insights and a personalized program to reduce dietary inflammation and boost healthy gut microbes. ZOE’s AI powered app makes following the plan easy and offers personalized scores to a large number of foods, delicious recipes and insights that teach you clever ways to continue to eat the foods you love.
ZOE has recently launched their at-home test kit that can help anyone discover the best foods for their biology.
The company is also the creator of the COVID Symptom Study app, which uses AI and symptom data to predict the spread of COVID-19 in real-time. The app has 4 million users globally, with multiple scientific papers in journals such as Science and Nature Medicine. Data from the COVID Symptom Study app confirms that people who are obese are more likely to end up in hospital with COVID-19. People living with diabetes, cancer and heart disease are also at increased risk of hospitalisation. Public health efforts are increasingly focused on reducing the health impacts of many conditions associated with poor nutrition and being overweight, including COVID-19.
About the PREDICT Studies
The PREDICT (Personalized REsponses to Dietary Composition Trial) studies are the world’s largest ongoing program of nutrition research. This program of research exists to understand the role of personalized nutrition and the gut microbiome to solve complex, food related health issues including chronic disease and metabolic syndrome. The studies are led by ZOE in collaboration with researchers and scientists at Massachusetts General Hospital, Harvard T.H. Chan School of Public Health. Stanford Medicine, Tufts University and King’s College London.
PREDICT 1: The study included 1,103 U.K. and US participants including identical twins to understand the role of genetics and the microbiome in personal nutrition. Forthcoming scientific papers include findings on the factors that contribute to hunger and energy lulls, and post-meal fat response and its influence on dietary inflammation.
PREDICT 2: Studied 1,100 US participants and recently completed in March 2020. This study included complex microbiome profiling which has led to the discovery of a specific microbe that may determine your ability to metabolize food better. Initial findings will be published later in the year.
The next stage of the PREDICT studies will be announced soon.
ZOE is a health science company using data-driven research to tackle the world’s health issues. By using artificial intelligence combined with digital technologies like mobile phones, ZOE enables large-scale scientific studies to tackle issues like COVID-19, dietary inflammation and the impact of nutrition on health.
Located in London and Boston, ZOE was founded by Professor Tim Spector of King’s College London, machine learning leader Jonathan Wolf and entrepreneur George Hadjigeorgiou. ZOE has carried out the largest nutritional studies of their kind in the world, runs the COVID Symptom Study app with 4 million users around the world, and was named one of the Deloitte Fast 50 Rising Stars in 2019 for the company’s contribution to science enabled by technology and machine learning.
About Massachusetts General Hospital
Massachusetts General Hospital, founded in 1811, is the original and largest teaching hospital of Harvard Medical School. The Mass General Research Institute conducts the largest hospital-based research program in the nation, with annual research operations of more than $1 billion and comprises more than 9,500 researchers working across more than 30 institutes, centers and departments. In August 2019, Mass General was named #2 in the U.S. News & World Report list of "America’s Best Hospitals."
*Collaborators on the PREDICT-1 study are from:
- Ana Valdes, University of Nottingham
- Sarah Berry, Tim Spector, King’s College London
- Paul Franks, Lund University
- Andrew T. Chan & David Drew, Massachusetts General Hospital, Harvard T.H. Chan School of Public Health
- José Ordovás, Tufts University
- Christopher Gardner, Stanford University
- Nicola Segata, University of Trento