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.
Marie Binvignat, Brenda Y. Miao, Camilla Wibrand, Monica M. Yang, Dmitry Rychkov, Emily Flynn, Joanne Nititham, Whitney Tamaki, Umair Khan, Alexander Carvidi, Melissa Krueger, Erene C. Niemi, Yang Sun, Gabriela K. Fragiadakis, Jérémie Sellam, Encarnita Mariotti-Ferrandiz, David Klatzmann, Andrew J. Gross, Chun Jimmie Ye, Atul J. Butte, Lindsey A. Criswell, Mary C. Nakamura, Marina Sirota
Usage data is cumulative from July 2024 through July 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 1,167 | 0 |
268 | 0 | |
Supplemental data | 44 | 0 |
Citation downloads | 21 | 0 |
Totals | 1,500 | 0 |
Total Views | 1,500 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.