Machine learning analysis of sex and menopausal differences in the gut microbiome in the HELIUS study

Sex differences in the gut microbiome have been examined previously, but results are inconsistent, often due to small sample sizes. We investigated sex and menopausal differences in the gut microbiome in a large multi-ethnic population cohort study, including 5166 participants. Using machine learning models, we revealed modest associations between sex and menopausal status, and gut microbiota composition (AUC 0.61–0.63). After adjustments for age, cardiovascular risk factors, and diet, a part of the associations of the highest-ranked gut microbes with sex were attenuated, but most associations remained significant. In contrast, most associations with menopausal status were driven by age and lost significance after adjustment. Using pathway analyses on metagenomic data, we identified sex differences in vitamin B6 synthesis and stachyose degradation pathways. Since some of sex differences in gut microbiome composition and function could not be explained by covariates, we recommend sex stratification in future microbiome studies.