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Single-cell RNA-seq analysis reveals cell subsets and gene signatures associated with Rheumatoid Arthritis Disease Activity.
Binvignat, Marie; Miao, Brenda Y; Wibrand, Camilla; Yang, Monica M; Rychkov, Dmitry; Flynn, Emily; Nititham, Joanne; Tamaki, Whitney; Khan, Umair; Carvidi, Alexander; Krueger, Melissa; Niemi, Erene C; Sun, Yang; Fragiadakis, Gabriela K; Sellam, Jérémie; Mariotti-Ferrandiz, Encarnita; Klatzmann, David; Gross, Andrew J; Ye, Chun Jimmie; Butte, Atul J; Criswell, Lindsey A; Nakamura, Mary C; Sirota, Marina.
Afiliação
  • Binvignat M; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Miao BY; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Wibrand C; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Yang MM; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Rychkov D; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Flynn E; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Nititham J; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Tamaki W; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Khan U; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Carvidi A; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Krueger M; Department of Medicine, Oregon Health & Science University, Portland, United States of America.
  • Niemi EC; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Sun Y; Human Genetics, UCSF, San Francisco, United States of America.
  • Fragiadakis GK; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Sellam J; Department of Rheumatology, Research Center Saint Antoine, APHP Saint Antoine Hospital and Sorbonne Université, Paris, France.
  • Mariotti-Ferrandiz E; Immunology Immunopathology Immunotherapy, Pitie Salpetriere Hospital UMRS 959, Sorbonne Université, Paris, France.
  • Klatzmann D; Immunology Immunopathology Immunotherapy, Pitie Salpetriere Hospital UMRS 959, Sorbonne Université, Paris, France.
  • Gross AJ; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Ye CJ; Human Genetics, UCSF, San Francisco, United States of America.
  • Butte AJ; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
  • Criswell LA; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Nakamura MC; Division of Rheumatology, Department of Medicine, UCSF, San Francisco, United States of America.
  • Sirota M; Bakar Computational Health Sciences Institute, UCSF, San Francisco, United States of America.
JCI Insight ; 2024 Jul 02.
Article em En | MEDLINE | ID: mdl-38954480
ABSTRACT
Rheumatoid arthritis (RA) management lean toward achieving remission or low-disease activity. In this study, we conducted single-cell RNA sequencing (scRNAseq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 RA patients and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type-specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFITM3 overexpressing Interferon-activated (IFN-activated) monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate to high disease activity (DAS28-CRP ≥ 3.2), and a decrease in non-classical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of pro-inflammatory genes in the gamma-delta T cells subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and non-classical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of pro-inflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, G0S2, and downregulation of genes including HLA-DQB1, HLA-DRB5, TNFSF13B. Notably, cell-cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JCI Insight Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JCI Insight Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos