Abstract MP26: Dietary Patterns, Metabolome Profile and Risk of Type 2 Diabetes

Background: Plasma metabolites have been associated with type 2 diabetes (T2D) risk and may reflect metabolic homeostasis as a result of the interplay among diet, genetics, and the gut microbiome. Hypothesis: We hypothesized that specific multi-metabolite signatures can characterize the adherence and metabolic response to various dietary patterns and are associated with incident T2D. Methods: We analyzed 20578 participants in the Nurses’ Health studies and Health Professional Follow-up Study (NHS/HPFS), Hispanic Community Health Study/Study of Latinos, and Women’s Health Initiative, whose blood metabolome were profiled by liquid chromatography-mass spectrometry. We applied elastic net regression to develop (n=1206 in a NHS/HPFS lifestyle sub-study) and validate (in the remaining samples) metabolic signatures for 3 dietary recommendation-based diets (a Mediterranean diet - AMED, a healthy eating index - AHEI, and an anti-hypertensive diet - DASH), 3 plant-based diets (PDIs), and 2 mechanism-based diets (proinflammatory [EDIP] and insulinemic [EDIH] diets). We tested associations between the dietary metabolic signatures and incident T2D in 14060 initially T2D-free participants (1832 cases in up to 22 years of follow-up). In sub-samples, we further examined genetic and microbial factors (shotgun sequencing) associated with metabolic signatures. Results: We identified 8 metabolic signatures, each consisted of 37-66 metabolites and was robustly correlated with the corresponding dietary pattern index in all validation cohorts ( r =0.11-0.38; P < 8.06 х10 -9 ). We noted shared and distinct metabolites cross metabolic signatures of various dietary patterns. In multivariable-analyses, metabolic signatures of healthful diets (i.e., AMED, AHEI, DASH, healthful PDI) were associated with a lower T2D risk (hazard ratio [HR]: 0.82-0.90; P < 3х10 -6 ), whereas metabolic signatures of unhealthful diets (e.g., EDIP and EDIH) were associated with a higher T2D risk (HR: 1.23-1.26; P < 2х10 -15 ). The metabolic signatures mediated 26%-56% of the associations between their corresponding dietary patterns and T2D risk ( P < 0.01). Further, a proportion of variation in the dietary metabolic signatures was explained by genetic variants (9.9% for EDIP to 34.5% for PDI) and gut microbial diversity (0.2% for PDI to 14.9% for EDIP). Dietary metabolic signatures were associated with 7 genetic loci including those involved in fatty acid and energy metabolism (e.g., FADS1/2 and CERS4 , P < 5х10 -8 ), and the abundance of 39 gut bacterial species (FDR <0.05). Conclusions: We identified metabolic signatures that characterized the adherence and metabolic responses (related to genetics and gut microbiome) to various dietary patterns, and were associated with T2D risk, in ethnically diverse populations. Metabolomic profiling may facilitate personalized nutritional interventions for T2D prevention.