Single-cell multi-omics analysis identifies two distinct phenotypes of newly-onset microscopic polyangiitis

Masayuki Nishide (), Kei Nishimura, Hiroaki Matsushita, Ryuya Edahiro, Sachi Inukai, Hiroshi Shimagami, Shoji Kawada, Yasuhiro Kato, Takahiro Kawasaki, Kohei Tsujimoto, Hokuto Kamon, Ryusuke Omiya, Yukinori Okada, Kunihiro Hattori, Masashi Narazaki and Atsushi Kumanogoh ()
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Masayuki Nishide: Osaka University
Kei Nishimura: Osaka University
Hiroaki Matsushita: Osaka University
Ryuya Edahiro: Osaka University
Sachi Inukai: Research Division, Chugai Pharmaceutical Co. Ltd
Hiroshi Shimagami: Osaka University
Shoji Kawada: Osaka University
Yasuhiro Kato: Osaka University
Takahiro Kawasaki: Osaka University
Kohei Tsujimoto: Osaka University
Hokuto Kamon: Osaka University
Ryusuke Omiya: Osaka University
Yukinori Okada: Osaka University
Kunihiro Hattori: Osaka University
Masashi Narazaki: Osaka University
Atsushi Kumanogoh: Osaka University

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract The immunological basis of the clinical heterogeneity in autoimmune vasculitis remains poorly understood. In this study, we conduct single-cell transcriptome analyses on peripheral blood mononuclear cells (PBMCs) from newly-onset patients with microscopic polyangiitis (MPA). Increased proportions of activated CD14+ monocytes and CD14+ monocytes expressing interferon signature genes (ISGs) are distinctive features of MPA. Patient-specific analysis further classifies MPA into two groups. The MPA-MONO group is characterized by a high proportion of activated CD14+ monocytes, which persist before and after immunosuppressive therapy. These patients are clinically defined by increased monocyte ratio in the total PBMC count and have a high relapse rate. The MPA-IFN group is characterized by a high proportion of ISG+ CD14+ monocytes. These patients are clinically defined by high serum interferon-alpha concentrations and show good response to immunosuppressive therapy. Our findings identify the immunological phenotypes of MPA and provide clinical insights for personalized treatment and accurate prognostic prediction.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41328-0

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DOI: 10.1038/s41467-023-41328-0

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