Educational inequalities are associated with distinct metabolomic and gut microbiome patterns in adults

Educational attainment is a well-established determinant of health inequalities and non-communicable diseases. While social gradients in health are consistently observed, the biological mechanisms through which educational disadvantage becomes embedded in human physiology remain insufficiently understood. We analyzed baseline data from 1773 adults in the population-based Food Chain Plus (FoCus) cohort. Phenotype, lifestyle, and nutrition were integrated with non-targeted serum and urine metabolomics and 16S rRNA gut microbiome profiles. Educational attainment was categorized as low, medium, or high. Associations were assessed using confounder-adjusted regression models, differential abundance analyses, and mixed graphical models to explore cross-domain associations relevant to population health. Educational attainment was associated with an accumulation of adverse behavioral, clinical, and dietary factors, providing social context within which the omics findings are interpreted. MGM analyses identified three mechanistic bridges linking educational attainment to cardiometabolic and inflammatory risk, including sedentary behavior, adiposity and insulin resistance, and dietary quality and plant food intake. A panel of 15 education-associated metabolites across biofluids captures these patterns, clustering around dietary quality, glycemic markers, and adiposity. Gut microbiome composition differed modestly but significantly across educational groups (PERMANOVA R² < 0.003, p = 0.001), whereas α-diversity metrics did not differ. Twenty-four microbial genera were differentially abundant by educational attainment, including taxa related to short-chain fatty acid production and inflammation. These findings support the concept that social disadvantage is biologically embodied through three converging pathways connecting socially patterned behavior and diet to measurable metabolic and microbial signals. The MGM framework reveals the specific network positions through which these pathways operate, providing population-level, hypothesis-generating evidence relevant for understanding and addressing persistent health inequalities.