Discovery and Validation of Gut Microbiome and Circulating Metabolites Associated with Dietary Patterns and Cardiometabolic Diseases
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2025-07-02
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Abstract
Diet plays an important role in the development and progression of cardiometabolic diseases (CMD); however, the underlying biological mechanisms are not yet well understood. To address this gap, we integrated fecal metagenomics and blood metabolomics to identify and validate gut microbiome and circulating metabolites associated with different dietary patterns–Healthy Eating Index (HEI), Dietary Approaches to Stop Hypertension (DASH), Empirical Dietary Inflammatory Potential (EDIP), Empirical Dietary Index for Hyperinsulinemia (EDIH), and Ultra-Processed Foods (UPF)–and CMD. Microbiome analyses included 514 Black/African American participants from the Southern Community Cohort Study (SCCS) for discovery and 2,133 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) for validation. Metabolomics analyses were conducted in the SCCS (N=1688) for discovery and in the HCHS/SOL (N=5,164) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N=2,315) for validation. Associations of five dietary patterns with microbiome abundance and circulating metabolites were assessed using linear regression after data transformation and adjusting for sociodemographics, lifestyles, and history of major chronic diseases. Logistic or Cox regression was used to further evaluate the associations of diet-related bacteria and metabolites with CMD. We identified and validated inverse associations between healthy dietary patterns (i.e., HEI and DASH) and abundance of Collinsella and C. aerofaciens, which were further linked to risk of obesity. Additionally, we validated a broad spectrum of metabolites across key biochemical pathways (e.g., amino acids, lipids, cofactors and vitamins, and xenobiotics) for those dietary patterns–HEI (n=89), DASH (n=52), EDIP (n=11), EDIH (n=60), and UPF (n=38); several of these diet-related metabolites were further linked to major health outcomes, including incident coronary heart disease (n=7), cardiovascular disease mortality (n=2), and total mortality (n=52). Importantly, we developed a metabolite signature for each dietary pattern, which demonstrated strong associations with disease outcomes and explained a significant proportion (>60%) of the diet-disease associations. These findings underscore the potential of multi-omics approaches to elucidate the complex interplay between diet and CMD, offering more precise insights for tailored dietary interventions.
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Keywords
Dietary patterns, Gut microbiome, Blood metabolomics, Cardiometabolic diseases