Metagenomic sequencing reveals altered gut microbial compositions and gene functions in patients with non-segmental vitiligo

宏基因组测序揭示非节段型白癜风患者肠道微生物组成和基因功能改变

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Abstract

BACKGROUND: Vitiligo has been correlated with an abnormal gut microbiota. We aimed to systematically identify characteristics of the gut microbial compositions, genetic functions, and potential metabolic features in patients with non-segmental vitiligo. METHODS: Twenty-five patients with non-segmental vitiligo and 25 matched healthy controls (HCs) were enrolled. Metagenomic sequencing and bioinformatic analysis were performed to determine the gut microbiota profiles. Differences in gut microbiota diversity and composition between patients with vitiligo and HCs were analyzed. Gene functions and gut metabolic modules were predicted with the Kyoto Encyclopedia of Gene and Genomes (KEGG) and MetaCyc databases. RESULTS: Compared with HCs, alpha diversity of intestinal microbiome in vitiligo patients was significantly reduced. At the species level, the relative abundance of Staphylococcus thermophiles was decreased, and that of Bacteroides fragilis was increased in patients with vitiligo compared with those of the HCs. Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed representative microbial markers of Lachnospiraceae_bacterium_BX3, Massilioclostridium_coli, TM7_phylum_sp_oral_taxon_348 and Bacteroides_fragilis for patients with vitiligo. KEGG gene function analysis showed that the NOD-like receptor signaling pathway was significantly enriched in patients with vitiligo. Gut metabolic modules (GMMs) analysis showed that cysteine degradation was significantly down-regulated, and galactose degradation was up-regulated in patients with vitiligo. A panel of 28 microbial features was constructed to distinguish patients with vitiligo from HCs. CONCLUSIONS: The gut microbial profiles and genetic functions of patients with vitiligo were distinct from those of the HCs. The identified gut microbial markers may potentially be used for earlier diagnosis and treatment targets.

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