(P13-02-26) An Omics Signature Linking Body Composition to Cardiometabolic Risk

Objectives: Body composition is a critical driver of cardiometabolic risk, but the underlying molecular pathways linking body composition to cardiometabolic risk are not fully understood. We characterized a molecular phenotype signature reflecting overall body composition and examined its association with the risk of type 2 diabetes (T2D) and cardiovascular disease (CVD).

Methods: Participants included 4,750 women from the Swedish Mammography Cohort-Clinical. Untargeted metabolomics and proteomics profiles were analyzed in fasting plasma samples at baseline. Random forest models were performed to identify the combination of the most relevant metabolite and protein biomarkers related to baseline total and regional body fat (android and gynoid fat) and anthropometric indices (body mass index (BMI) and fat mass index (FMI)). A combined panel score of omics features (omics signature) was built using a combination of linear and elastic net models. Associations between body composition measures, the omics signature, and incident T2D and CVD were estimated using multivariate Cox proportional hazards models.

Results: The omics signature was calculated by including 19 metabolites and 24 proteins that were commonly associated with BMI, android fat, total fat, and FMI measurements (Q2 performance >0.60). Annotated metabolites included glycerophospholipids, sphingolipids, fatty acyls, glycerolipids, bile acids, and hexoses, while proteins were mainly involved in the inflammatory response, signal transduction, cholesterol homeostasis, and regulation of appetite and energy balance. There was a linear positive association between all body composition measurements and T2D and CVD risk. The omics signature was associated with higher risk of developing T2D (HR=1.68, 96%CI 1.56–1.80) and CVD (HR=1.14, 96%CI 1.08–1.20).

Conclusions: We identified an omics signature for overall body composition and demonstrated the association between the signature and T2D and CVD risk. The findings offer new insights into the underlying mechanisms of the obesity and cardiometabolic risk relationship, which is critical for improved cardiometabolic disease prevention.

Funding Sources: This study was supported by Instituto de Salud Carlos III and EU-JPI-HDHL. E.A.A. acknowledges funding from the EU Horizon 2020 research and innovation program under a Marie Skłodowska-Curie grant.