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<p>Idiopathic inflammatory myopathies (IIMs) are systemic autoimmune disorders with unknown etiology. Despite the established link between gut microbes and immunity, the roles of gut bacteriome, mycobiome, and virome in IIM are unexplored. We performed shotgun metagenomic sequencing on fecal samples from 34 IIM patients and 37 healthy controls to profile gut microbiota. Taxonomic, functional, network, and machine-learning analyses revealed microbial dysbiosis and its potential for discriminating IIM. All three microbial kingdoms were significantly altered in IIM. Several inflammation-associated bacterial taxa (e.g., <i>Rothia mucilaginosa</i>, <i>Streptococcus parasanguinis</i>, <i>Trueperella pyogenes</i>) and opportunistic fungi (e.g., <i>Aspergillus</i> spp.) were enriched in IIM, while SCFA-producing bacteria and fungi were depleted. Virome analysis revealed substantial shifts, with higher abundance of <i>Siphoviridae</i> in IIM. Altered viral functional gene profiles suggesting enhanced phage-mediated genome integration, recombination, and bacterial stress adaptation. Multi-kingdom network analysis showed extensive rewiring in IIM, characterized by increased network connectivity and a shift toward fungi-centered ecological hubs, contrasting with bacteria/virus-dominated networks in controls. In machine-learning models, the virome demonstrated the strongest discriminatory power, and viral signatures dominated the combined multi-kingdom classifier (AUC = 0.997). This first comprehensive multi-kingdom gut microbiota analysis in IIM provides a foundation for developing diagnostic and therapeutic strategies.</p>

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Multi-kingdom gut microbiota characterization in Chinese patients with idiopathic inflammatory myopathies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月7日

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  • Changyan Liu,
  • Yida Xing,
  • Jinwen Su,
  • Yiping Liu,
  • Yuemeng Dou,
  • Zheng Wang,
  • Shanshan Sha,
  • Qiulong Yan,
  • Mingxi Xu,
  • Lin Zhao,
  • Yi Tian,
  • Guorui Xing,
  • Shenghui Li,
  • Jian Kang,
  • Xiaodan Kong

摘要

Idiopathic inflammatory myopathies (IIMs) are systemic autoimmune disorders with unknown etiology. Despite the established link between gut microbes and immunity, the roles of gut bacteriome, mycobiome, and virome in IIM are unexplored. We performed shotgun metagenomic sequencing on fecal samples from 34 IIM patients and 37 healthy controls to profile gut microbiota. Taxonomic, functional, network, and machine-learning analyses revealed microbial dysbiosis and its potential for discriminating IIM. All three microbial kingdoms were significantly altered in IIM. Several inflammation-associated bacterial taxa (e.g., Rothia mucilaginosa, Streptococcus parasanguinis, Trueperella pyogenes) and opportunistic fungi (e.g., Aspergillus spp.) were enriched in IIM, while SCFA-producing bacteria and fungi were depleted. Virome analysis revealed substantial shifts, with higher abundance of Siphoviridae in IIM. Altered viral functional gene profiles suggesting enhanced phage-mediated genome integration, recombination, and bacterial stress adaptation. Multi-kingdom network analysis showed extensive rewiring in IIM, characterized by increased network connectivity and a shift toward fungi-centered ecological hubs, contrasting with bacteria/virus-dominated networks in controls. In machine-learning models, the virome demonstrated the strongest discriminatory power, and viral signatures dominated the combined multi-kingdom classifier (AUC = 0.997). This first comprehensive multi-kingdom gut microbiota analysis in IIM provides a foundation for developing diagnostic and therapeutic strategies.