Decoding Gut Microbiome Dysbiosis as a Non-Invasive Diagnostic Biomarker for Alopecia Areata

This study investigates the gut microbiota composition in alopecia areata (AA) patients to evaluate its potential as a diagnostic biomarker. Fecal samples from AA patients and healthy controls were analyzed using 16S rRNA sequencing. The results showed distinct microbial signatures in AA, with an increase in pro-inflammatory genera and a decrease in immunoregulatory commensals. Network analyses indicated more complex microbial interactions in AA. A Random Forest model achieved 92% accuracy in distinguishing AA from controls. These findings suggest that gut dysbiosis may contribute to AA pathogenesis and could serve as a basis for diagnostic biomarkers and microbiota-targeted therapies.