Gut Microbes (May 2020)

Altered gut microbiome composition in patients with Vogt-Koyanagi-Harada disease

  • Zi Ye,
  • Chunyan Wu,
  • Ni Zhang,
  • Liping Du,
  • Qingfeng Cao,
  • Xinyue Huang,
  • Jihong Tang,
  • Qingfeng Wang,
  • Fuzhen Li,
  • Chunjiang Zhou,
  • Qian Xu,
  • Xiao Xiong,
  • Aize Kijlstra,
  • Nan Qin,
  • Peizeng Yang

DOI
https://doi.org/10.1080/19490976.2019.1700754
Journal volume & issue
Vol. 11, no. 3
pp. 539 – 555

Abstract

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Background Vogt-Koyanagi-Harada (VKH) disease is a multisystemic autoimmune disorder characterized by granulomatous panuveitis. Gut microbiome has been considered to play a role in the pathogenesis of this disease but whether the alternation of gut microbiome was involved is unclear. This study was set up to identify abnormalities of gut microbiome composition in VKH disease. Results Depleted butyrate-producing bacteria, lactate-producing bacteria and methanogens as well as enriched Gram-negative bacteria were identified in the active VKH patients, as well as in VKH patients of Mix enterotype and Bacteroides enterotype. Changes of gut microbiome in the VKH patients were partially restored after an immunosuppressive treatment. The disease susceptibility genotype HLA-DRA was associated with Bacteroides sp.2.1.33B, Paraprevotella clara, Alistipes finegoldii and Eubacterium eligens. A microbial marker profile including 40 disease-associated species was established to differentiate patients from controls. Another microbial marker profile including 37 species was found to be associated with the response to treatment. An animal experiment showed that transfer of gut microbiome from VKH patients could significantly exacerbate disease activity clinically and pathologically in the recipient mice. Conclusion Our results revealed a distinct gut microbiome signature in VKH patients and showed an exacerbating effect of this gut microbiome on experimental autoimmune uveitis (EAU). We also developed two microbial marker profiles in differentiating VKH patients from healthy controls as well as predicting the effectiveness of treatment.

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