132,000 meals. 28,000 blood tests. 2,000,000 blood sugar readings. 11,000 happiness ratings. And 32,000 standardized scientific muffins.
It all adds up to PREDICT 1 — the biggest nutritional study of its kind.
Led by ZOE’s scientific founder and Professor at King’s College London, Tim Spector — together with researchers at Massachusetts General Hospital (MGH) — PREDICT 1 measured how blood levels of markers such as sugar, insulin and fat change in response to specific meals.
The team also gathered data on activity, sleep, mood, hunger and gut bacteria (microbiome) in more than a thousand participants in the US and UK, mostly pairs of twins.
The biggest finding is that everyone has their own unique response to food — even identical twins. This means that everyone is different and there is no one right way to eat.
Why are we going to the trouble of running such a huge research project?
It’s all part of our mission to solve a seemingly simple but surprisingly hard question: what should I eat to be healthier?
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Go big or go home
Not only is it the largest study of its kind ever undertaken, what makes PREDICT 1 really special is how we used new technologies — like stick-on glucose monitors, at-home blood collection, food logging apps and machine learning — to measure, understand and predict what happens within the body when someone eats a meal (nutritional response).
In total, we captured millions of individual datapoints from more than a thousand participants as they munched their way through 32,000 standardized test muffins and a hundred thousand regular meals.
All this data gives us a vastly more detailed picture of individual nutritional responses to food than has ever been captured before. For example, we now have what is probably the largest database of blood fat and glucose responses in the world.
When it comes to food, we’re all different
We were expecting to see differences in personal nutritional responses. However, we were surprised to discover such a wide variation in responses to the same foods, even between identical twins who share all their genes and much of their environment.
Strikingly, we also discovered that identical twins shared just 37% of their gut microbes, only slightly higher than the 35% shared between two unrelated people.
The message is clear: when it comes to something as personal as food, we’re all different and there is no one right way to eat.
We’re now focused on taking this data and training our increasingly sophisticated machine learning algorithms to predict how someone will respond to any meal.
And we’re working with Professors Christopher Gardner at Stanford University and Andrew T. Chan at MGH to recruit participants for PREDICT 2 — an expanded, home-based study of 1,000 people across the US.
The PREDICT 1 results were presented by Tim Spector MD FRCP FRSB (Professor, King’s College London, UK) and Sarah Berry Ph.D (Senior Lecturer, King’s College London) and Paul Franks Ph.D. (Professor, Lund University, Sweden) at the American Diabetes Association (ADA) and American Society for Nutrition (ASN) meetings in San Francisco and Baltimore on 10th/11th June 2019. Presentation slide deck and White Paper available here: https://joinzoe.com/science