369 Serum bile acid and gut microbiome composition in heterogeneous individuals

Objectives/Goals: Colorectal cancer risk varies across populations. Bile acid (BA) composition and the gut microbiome can impact CRC risk, but their differences across populations is poorly understood. We characterized serum BA and gut microbiome profiles in non-Hispanic Black and White Americans and examined associations with diet and social determinants of health. Methods/Study Population: To characterize BA composition, participants from the Chicago Multiethnic Prevention and Surveillance Study with a banked serum sample (n=100) were selected, with a subset of participants having completed a diet recall survey (ASA24; n=23). Sixty-two BA (primary, secondary, and glyco/tauro-conjugated BA) from serum samples were analyzed using liquid chromatography-mass spectrometry. For microbiome profiling, normal colonic biopsy samples from non-cancer participants were obtained from the Digestive Disease Research Core Center’s Integrative Clinical and Biospecimens Core (University of Chicago; n=109). Following DNA extraction, the mucosally adherent microbial community was assessed by 16S rRNA sequencing. Results/Anticipated Results: Of the BA detected in over 80% of the samples, glycochenodeoxycholic acid (GCDCA) and deoxycholic (DCA) had the highest median concentrations (56.7 and 55.0 µg/mL, respectively). Moderate positive correlations between DCA/isoDCA and calories, fat, and cholesterol were observed. The linear regression model employed to understand the relationship between log-transformed DCA and race, age, sex, and area deprivation index highlighted age as a key predictor of DCA level when controlling for other covariates. Microbiome analysis revealed that diversity was not different when comparing sexes, races, or colonic anatomic locations. At the phylum level, taxa belonging to the Bacillota and Bacteroidota phyla were common across samples. Discussion/Significance of Impact: These data and subsequent analysis, including additional BA analysis, improvement of the regression model, and deeper analysis of microbiome community related to BA metabolism, will provide additional context to the role of social and biological factors in better understanding differences in CRC risk and pathogenesis across human populations.