Human skin microbiota and postpartum depression: A bidirectional Mendelian randomization study

Postpartum depression (PPD) is a common mental health disorder after childbirth. Although microbiome research in PPD has mainly focused on the gut, the role of skin microbiota remains unclear. We used Mendelian randomization (MR) to assess potential causal associations between skin microbiota and PPD. A bidirectional 2-sample MR analysis used genome-wide association study (GWAS) summary statistics. Genetic instruments for skin microbial features were obtained from a published skin microbiota GWAS, and PPD data were derived from 67,205 mothers (7604 cases, 59,601 controls). Instruments were selected at P <1 × 10-5, linkage disequilibrium-clumped, harmonized, and filtered for weak instruments (F statistic <10). Because this microbiome threshold is exploratory, Benjamini-Hochberg false discovery rate correction was applied within taxonomic levels. The inverse-variance weighted method was primary, complemented by weighted median and mode-based methods. Heterogeneity, pleiotropy, and outliers were assessed using Cochran Q, MR-Egger intercept, and MR-PRESSO. Three skin microbial taxa showed nominal associations with PPD. Higher genetically predicted Acinetobacter on the dorsal forearm (dry skin; 9 single nucleotide polymorphisms [SNPs]; mean F = 22.12) and Proteobacteria in the antecubital fossa (moist skin; 6 SNPs; mean F = 23.44) were associated with increased PPD risk, whereas Betaproteobacteria in the antecubital fossa (11 SNPs; mean F = 21.54) was associated with decreased risk. Associations were directionally consistent, with no substantial heterogeneity or horizontal pleiotropy. After multiple-testing assessment, the findings were exploratory rather than definitive. Reverse MR did not support an effect of PPD on the identified skin microbiota. This MR study provides exploratory genetic evidence linking specific skin microbial features to PPD risk. The findings extend microbiota-related hypotheses beyond the gut microbiome but require validation in larger microbiome GWAS datasets, longitudinal cohorts, and mechanistic studies before clinical or causal conclusions are drawn.