Analysis of the gut microbiota in alopecia areata: identification of bacterial biomarkers

Abstract Background Alopecia areata is a T‐cell‐mediated autoimmune disease with an unknown etiopathogenesis. Gut microbiota has been revealed as a key modulator of systemic immunity. Objective To determine whether patients affected by alopecia universalis present differences in gut bacteria composition compared with healthy controls and investigate possible bacterial biomarkers of the disease. Methods We conducted a cross‐sectional study that involved 15 patients affected by alopecia universalis and 15 controls. Gut microbiome of the study subjects was analysed by sequencing the 16Sr RNA of stool samples. We searched for bacterial biomarkers of alopecia universalis using the linear discriminant analysis effect size ( LEF se) tool. Results In total, 30 study subjects (46.6% female; mean [ SD ] age, 40.1 [9.8] years) were enrolled. Neither alpha (Shannon diversity index 5.31 ± 0.43 vs. 5.03 ± 0.43, P 0.1) or beta diversity ( ADONIS P value: 0.35) of gut microbiota showed statistically significant differences between cases and controls. In patients affected with alopecia, we found an enriched presence ( LDA SCORE > 2) of Holdemania filiformis, Erysipelotrichacea, Lachnospiraceae, Parabacteroides johnsonii, Clostridiales vadin BB 60 group, Bacteroides eggerthii and Parabacteroides distasonis . A predictive model based on the number of bacterial counts of Parabacteroides distasonis and Clostridiales vadin BB 60 group correctly predicted disease status in 80% of patients ( AUC 0.804 (0.633–0.976), P 0.004). Conclusion Alopecia universalis does not seem to affect broadly gut microbiota structure. Bacterial biomarkers found associated with the disease ( Holdemania filiformis, Erysipelotrichacea, Lachnospiraceae, Parabacteroides johnsonii, Eggerthellaceae, Clostridiales vadin BB 60 group, Bacteroides eggerthii and Parabacteroides distasonis ) should be further studied as they could be involved in its pathophysiology or be used as diagnostic tools.