Causal Relationship Between Gut Microbiota and Androgenic Alopecia: A Mendelian Randomization Analysis

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Abstract

Background: Androgenic alopecia (AGA) is a common condition influenced by genetic and hormonal factors, with emerging evidence linking it to gut microbiota. Dysbiosis may affect AGA through immune regulation, androgen metabolism, and systemic pathways. Using Mendelian randomization (MR), this study investigates the causal relationship between gut microbiota and AGA, aiming to uncover potential mechanisms and therapeutic targets. Methods: The study selected six types of gut microbiota-related genetic loci associated with GM from summary data of genome-wide association studies (GWAS), which served as instrumental variables. MR analysis was conducted utilizing inverse variance weighting (IVW), MR-Egger regression, and weighted median approaches. Sensitivity analyses were performed through heterogeneity tests, pleiotropy tests, and leave-one-out analyses, while odds ratios and 95% confidence intervals were used to assess the potential causal relationship between GM and AGA. Results: The IVW analysis revealed that several taxa may serve as protective factors against AGA, including the Oxalobacteraceae (OR=0.957, 95% CI 0.919-0.996, P=0.033), Paraprevotella (OR=0.953, 95% CI 0.909-0.999, P=0.047), Eubacteriumventriosumgroup (OR=0.931, 95%CI 0.869-0.997, P=0.043), LachnospiraceaeUCG008 (OR=0.937, 95%CI 0.892-0.985, P=0.011), and Clostridiales (OR=0.917, 95%CI 0.853-0.986, P=0.019). Conversely, the Coriobacteriaceae (OR=1.103, 95%CI 1.003-1.213, P=0.041) may be a potential risk factor for AGA. Heterogeneity testing indicated no significant heterogeneity in results (P>0.05), and the intercept term from MR-Egger regression ruled out the presence of horizontal pleiotropy. The leave-one-out test results consistently fell on one side of the null line, indicating good robustness in MR analysis. Funnel plot analysis demonstrated that the distribution of all SNPs was approximately symmetrical, elucidating that potential confounding factors have relatively small impact on causality. Conclusion: This study suggests a potential causal relationship between gut microbiota and AGA, highlighting potential pathways and opening opportunities for microbiota-based therapeutic strategies.

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