Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis
Jun Inamo, … , Deepak A. Rao, Fan Zhang
Jun Inamo, … , Deepak A. Rao, Fan Zhang
Published March 17, 2025
Citation Information: J Clin Invest. 2025;135(6):e185217. https://doi.org/10.1172/JCI185217.
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Research Article Autoimmunity Immunology

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease currently with no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in at-risk populations prior to clinical onset is crucial to establishing effective prevention strategies. Here, we applied multimodal single-cell technologies (mass cytometry and CITE-Seq) to characterize the immunophenotypes in blood from at-risk individuals (ARIs) identified through the presence of serum antibodies against citrullinated protein antigens (ACPAs) and/or first-degree relative (FDR) status, as compared with patients with established RA and people in a healthy control group. We identified significant cell expansions in ARIs compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5lo naive B cell population was expanded in ACPA-positive FDRs. Further, we uncovered the molecular phenotype of the CCR2+CD4+ T cells, expressing high levels of Th17- and Th22-related signature transcripts including CCR6, IL23R, KLRB1, CD96, and IL22. Our integrated study provides a promising approach to identify targets to improve prevention strategy development for RA.

Authors

Jun Inamo, Joshua Keegan, Alec Griffith, Tusharkanti Ghosh, Alice Horisberger, Kaitlyn Howard, John F. Pulford, Ekaterina Murzin, Brandon Hancock, Salina T. Dominguez, Miranda G. Gurra, Siddarth Gurajala, Anna Helena Jonsson, Jennifer A. Seifert, Marie L. Feser, Jill M. Norris, Ye Cao, William Apruzzese, S. Louis Bridges, Vivian P. Bykerk, Susan Goodman, Laura T. Donlin, Gary S. Firestein, Joan M. Bathon, Laura B. Hughes, Andrew Filer, Costantino Pitzalis, Jennifer H. Anolik, Larry Moreland, Nir Hacohen, Joel M. Guthridge, Judith A. James, Carla M. Cuda, Harris Perlman, Michael B. Brenner, Soumya Raychaudhuri, Jeffrey A. Sparks, The Accelerating Medicines Partnership RA/SLE Network, V. Michael Holers, Kevin D. Deane, James Lederer, Deepak A. Rao, Fan Zhang

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Figure 7

Validation using CITE-Seq data and molecular phenotype of CCR2+CD4+ T cells.

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Validation using CITE-Seq data and molecular phenotype of CCR2+CD4+ T ce...
(A) Composition and experimental design of CITE-Seq data, involving 69 participants with RA, 46 ARIs, and 25 controls. CITE-Seq includes single-cell RNA-Seq and antibody-derived tag (ADT) analysis to assess gene and protein expression. (B) Reference mapping assigned concordant cell clusters with mass cytometry data to CITE-Seq data. De novo cell clusters in CITE-Seq data are shown in the left UMAP plot. Through reference mapping using mass cytometry data as a reference, their cell cluster labels were transferred to the corresponding CITE-Seq clusters, effectively annotating the unidentified clusters with known cell types, as shown in the right plot. (C) UMAP plots of surface protein expression for key markers (CD3, CD4, CD8, CD56, CD20, CLEC12A) across PBMCs. Color intensity represents normalized expression levels of each marker, indicating presence and distribution of various cell populations. (D) UMAP plot of T cells from CITE-Seq data. CCR2+CD4+ T cells are labeled and colored in blue. Other colors correspond to cluster colors in Figure 2A. (E) UMAP plots depicting expression patterns of Th17- and Th22-related surface proteins. (F) Heatmap showing normalized expression levels of Th17- and Th22-related genes across helper T cell subsets. (G) UMAP colored by enrichment of Th22, Th17, and Tph gene signatures. (H) Associations of T cell neighborhoods with ARIs versus controls. For CNA-based association results, cells in UMAP are colored in red (expansion) or blue (depletion). (I) Distribution of cell type frequency for CCR2+CD4+ T cells. *P < 0.05, ***P < 0.001 by 2-sided Wilcoxon’s test. (J) UMAP plot of subclusters in CCR2+CD4+ T cells. (K) UMAP plots depicting expression of surface proteins for helper T cell subsets. (L) UMAP plots colored by enrichment of Th22, Th17, and Tph gene signatures. (M) Associations of CCR2+CD4+ T cell neighborhoods with ARIs versus controls. For all CNA-based association results, cells in UMAP are colored in red (expansion) or blue (depletion). (N) Distribution of cell type frequency for subclusters in CCR2+CD4+ T cells. **P < 0.01, ****P < 0.0001 by 2-sided Wilcoxon’s test. (O) Scatterplot showing correlation between ARI association obtained from CNA in H and mRNA expression level of CCR6.