Deep learning for microbiome-informed precision nutrition

Nutrition science, over the past several centuries, has evolved from focusing on the isolation and synthesis of individual nutrients to a more sophisticated understanding of the intricate biological impacts of food and dietary patterns.Particularly in the last century, varied dietary patterns have spurred extensive scientific inquiry linked to chronic diseases.For instance, studies have consistently affirmed the efficacy of the Mediterranean diet in mitigating cardiovascular disease risk and reducing overall mortality 1 .Nowadays, a multi-omics approach is frequently invoked to formulate strategies for precision nutrition.The National Institutes of Health defines Precision Nutrition as an encompassing framework that integrates diverse elements, including genetics, dietary habits, circadian rhythms, health status, and socioeconomic and psychosocial factors, alongside food environments, physical activity, and microbiome composition.This paradigm acknowledges the intrinsic individual differences among humans, suggesting that when, why, and how we eat are as critical as what we eat.