Big data, multi-omics key to accurate precision nutrition - freetxp

Big data, multi-omics key to accurate precision nutrition

November 05, 2021

2 min read


Source/Disclosures

Source:

Berry S. Precision nutrition — fact or fiction? Presented at: ObesityWeek; Nov. 1-5, 2021 (virtual meeting).


Disclosures: Berry reports receiving consultant fees from ZOE Global.


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Advances in big data collection and multi-omics technology can provide the depth and precision needed to better determine individual responses to food, allowing researchers to personalize diets for optimal success, according to a speaker.

Moving from population-based nutrition guidelines to so-called precision nutrition is challenging because of the complexity of food and individual human responses to food, which vary widely, Sarah Berry, PhD, associate professor in the department of nutritional sciences at King’s College London, said during a virtual presentation at the ObesityWeek annual meeting. Novel technologies that leverage genomic, metabolomic, metagenomic and meal-context information to predict individual metabolic responses to food can help researchers to begin to untangle the huge variability observed between people, Berry said.


Berry is an associate professor in the department of nutritional sciences at King’s College London.

“We all respond differently to food — what we eat, how we eat and who we are shape those responses,” Berry told Healio. “The small contribution that genetics plays for most of us in shaping our responses to food and the relative impact of easily modifiable factors might be surprising to some; However, basic healthy eating principles still apply to everyone. Eat less processed food, more fiber rich foods, a greater diversity of unprocessed plant foods and enjoy your food.”

Berry said a paradigm shift is occurring in nutrition research and how it is conducted, thanks to the evolution of digital devices, like continuous glucose monitoring, the arrival of at-home DNA and microbiome tests, and the emergence of citizen science.

“By collecting these data, using remote and novel technologies and sharing it with nutrition researchers, we can push the fast-forward button on nutrition research to get the kind of data that we need to make precision nutrition a reality.”

Berry is collaborating with leading scientists for the PREDICT program, a series of studies designed to predict personalized food responses based on individual characteristics, like gut microbiome makeup. PREDICT is the largest ongoing nutrition research program.

For the PREDICT 1 study, researchers analyzed postprandial metabolic responses in a controlled clinical setting and during a 2-week at-home phase for 1,002 twins and unrelated healthy adults in the UK and 100 people in the US During a remote, at-home phase of the study, participants consumed standardized meals and wore CGMs and activity trackers and provided blood samples while also using a study app. Nutritionists monitored data in real time. In-depth clinical testing was also conducted involving deep phenotyping at an scale and depth, Berry said.

“We were able to use this huge amount of data to start to unravel how much variability there is in response to food, and what factors determine this variability,” Berry said.

In findings published in October 2020 in Nature Medicine, the researchers reported large, interindividual variability in postprandial responses of triglyceride levels (103%), glucose (68%) and insulin (59%) after identical. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6% and 15.4%, respectively).

“This is important, because for precision nutrition to be valuable, we need to look between but also within individuals,” said Berry, also the lead nutritional scientist for the PREDICT program. “Because we gave all of our test meals in duplicate, we were able to look at intraindividual variability, and we found it to be a lot less than interindividual variability.”

Data showed genetic variants had only a modest impact on predictions, Berry said. Instead, a combination of determinants, including food type, meal timing and sequence, exercise and sleep habits, and factors like age and sex, influence responses to food outcomes.

“We have seen from our research that everyone is unique in how we respond to food,” Berry said. “We need to look at these multiple factors to make precision nutrition a fact and not just fiction.”

Reference:

Berry SE, et al. Nat Med. 2021;doi:10.1038/s41591-020-0934-0.

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