A vegan diet signature from a multi-omics study on different European populations is related to favorable metabolic outcomes

Vegan and omnivorous diets differ markedly in composition, but their effects on the gut microbiome, metabolome, and lipidome across populations remain insufficiently characterized. While both diet and country of origin influence these molecular layers, the relative contribution of diet versus country-specific factors has not yet been systematically evaluated within a multi-omics framework.In this cross-sectional, bicentric, observational study, we profiled healthy vegans (<i>n</i> = 100) and omnivores (<i>n</i> = 73) from the Czech Republic and Italy using integrated microbiome, metabolome, and lipidome analyses. Findings were subsequently validated in an independent cohort (<i>n</i> = 142).Significant differences across all omics layers were observed for both country and diet. The predictive models confirmed diet-associated separation, with validation cohort AUCs of 0.99 (lipidome), 0.89 (metabolome), and 0.87 (microbiome). Functional metagenome analysis revealed enrichment of amino acid biosynthesis, inositol degradation, and the pentose phosphate pathway in vegans, while omnivores presented greater potential for amino acid fermentation, fatty acid biosynthesis, and propanoate metabolism. Linear models identified a robust, country-independent "vegan signature" consisting of 27 lipid metabolites, five non-lipid metabolites, and 11 bacterial species. Several lipid features associated with an omnivorous diet were inversely related to the duration of vegan diet adherence. Some of the vegan-associated metabolites and bacteria have been previously linked to favorable cardiometabolic profiles, although causality remains to be established.These findings demonstrate that vegan diets are associated with reproducible, country-independent molecular and microbial signatures. Our results highlight diet-driven shifts in host-microbiota interactions and provide a framework for understanding how dietary patterns relate to host-microbiota interactions.