Metabolomic signature of ultra-processed foods and cardiovascular morbidity and mortality

BACKGROUND & AIMS: High intake of ultra-processed foods (UPFs) increases cardiovascular disease (CVD) risk, but the underlying mechanisms are unclear. Leveraging untargeted blood metabolomics in three prospective cohorts, we aimed to identify and validate circulating metabolites associated with UPF intake and CVD risk and mortality. METHODS: This two-stage metabolomics study involved a discovery stage conducted in the Southern Community Cohort Study (SCCS; N = 1688) and a validation stage performed in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO; N = 2315) and the Atherosclerosis Risk in Communities Study (ARIC; N = 3682). UPF intake (classified by Nova) was quantified as weight percentage or servings per day based on food frequency questionnaires administered at cohort baseline. Untargeted profiling of baseline blood metabolites was performed in selected participants without cancer or CVD. For discovery, linear regression was used to evaluate UPF intake in association with 1100 metabolites, and conditional logistic and Cox regression models were used to further examine the associations of UPF-related metabolites and metabolite signature (MetSig) with incident coronary heart disease (CHD), CVD mortality, and total mortality. Significant findings (FDR