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In Frontiers in microbiology

Autoimmune diseases are increasingly linked to aberrant gut microbiome and relevant metabolites. However, the association between vitiligo and the gut microbiome remains to be elucidated. Thus, we conducted a case-control study through 16S rRNA sequencing and serum untargeted-metabolomic profiling based on 30 vitiligo patients and 30 matched healthy controls. In vitiligo patients, the microbial composition was distinct from that of healthy controls according to the analysis on α- and β-diversity (P < 0.05), with a characteristic decreased Bacteroidetes: Firmicutes ratio. Meanwhile, the levels of 23 serum metabolites (including taurochenodeoxycholate and L-NG-monomethyl-arginine) in the vitiligo patients were different from those in the healthy individuals and showed significant correlations with some microbial markers. We found that Corynebacterium 1, Ruminococcus 2, Jeotgalibaca and Psychrobacter were correlated significantly with disease duration and serum IL-1β level in vitiligo patients. And Psychrobacter was identified as the most predictive features for vitiligo by machine learning analysis ("importance" = 0.0236). Finally, combining multi-omics data and joint prediction models with accuracies up to 0.929 were established with dominant contribution of Corynebacterium 1 and Psychrobacter. Our findings replenished the previously unknown relationship between gut dysbiosis and vitiligo circulating metabolome and enrolled the gut-skin axis into the understanding of vitiligo pathogenesis.

Ni Qingrong, Ye Zhubiao, Wang Yinghan, Chen Jianru, Zhang Weigang, Ma Cuiling, Li Kai, Liu Yu, Liu Ling, Han Zheyi, Gao Tianwen, Jian Zhe, Li Shuli, Li Chunying


16S rRNA sequence, gut microbiome, gut-skin axis, serum metabolomic, vitiligo