Deep Immunophenotyping Reveals Circulating Activated Lymphocytes in Individuals at Risk for Rheumatoid Arthritis

Jun Inamo¹, Joshua Keegan², Alec Griffith², Tusharkanti Ghosh³, Alice Horisberger², Kaitlyn Howard², John Pulford², Ekaterina Murzin², Brandon Hancock², The Accelerating Medicines Partnership SLE/RA⁴, Marie Feser⁴, Jill Norri⁵, Anna Helena Jonsson⁶, Ye Cao⁷, William Apruzzese⁸, S. Louis Bridges⁹, Vivian Bykerk¹⁰, Susan Goodman⁹, Laura Donlin⁹, Gary S Firestein¹¹, Harris Perlman¹², Joan Bathon¹³, Laura Hughes¹⁴, Darren Tabechian¹⁵, Andrew Filer¹⁶, Costantino Pitzalis¹⁷, Jennifer Anolik¹⁵, Larry Moreland¹⁸, Joel Guthridge¹⁹, Judith James¹⁹, Michael Brenner², Soumya Raychaudhuri⁶, Jeffrey Sparks²⁰, Jennifer Seifert²¹, Michael Holer⁴, Kevin Deane⁴, James Lederer², Deepak Rao⁶ and Fan Zhang²², ¹University of Colorado School of Medicine, Aurora, CO, ²Brigham and Women's Hospital and Harvard Medical School, Boston, MA, ³School of Public Health, University of Colorado, Anschutz Medical Campus, Aurora, CO, ⁴University of Colorado Anschutz Medical Campus, Aurora, CO, ⁵Colorado School of Public Health, Denver, CO, ⁶Brigham and Women's Hospital, Boston, MA, ⁷Brigham and Women's Hospital, Boston, MA, ⁸Accelerating Medicines Partnership® Program: Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP® RA/SLE) Network, Boston, MA, ⁹Hospital for Special Surgery, New York, NY, ¹⁰Department of Rheumatology, Hospital for Special Surgery, New York, NY, ¹¹Department of Medicine, University of California San Diego, La Jolla, CA, ¹²Northwestern University, Chicago, IL, ¹³Columbia University, New York, NY, ¹⁴University of Alabama at Birmingham Medicine, Birmingham, AL, ¹⁵University of Rochester Medical Center, Rochester, NY, ¹⁶University of Birmingham, Birmingham, United Kingdom, ¹⁷Queen Mary University of London, London, United Kingdom, ¹⁸University of Colorado, Denver, CO, ¹⁹Oklahoma Medical Research Foundation, Oklahoma City, OK, ²⁰Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, ²¹The Accelerating Medicines Partnership RA/SLE Network, ²²University of Colorado, Aurora, CO

Meeting: ACR Convergence 2023

Keywords: proteomics, rheumatoid arthritis

Session Information

Date: Sunday, November 12, 2023

Title: Abstracts: Genetics, Genomics & Proteomics

Session Type: Abstract Session

Session Time: 2:00PM-3:30PM

Background/Purpose: Rheumatoid arthritis (RA) is a systemic autoimmune disease with currently no effective prevention strategies. Single-cell technologies have been used to investigate established RA heterogeneity (1), but it is unknown if the immune populations identified from RA tissues play important roles in blood during the preclinical phase of disease. Thus, identifying pathogenic immune phenotypes in individuals who are at risk for future RA, designated “At-Risk RA”, is crucial to establishing prevention strategies.

Methods: We applied mass cytometry to deeply characterize immunophenotypes in PBMCs (peripheral blood mononuclear cells) from At-Risk individuals based on the presence of antibodies to citrullinated protein antigens (ACPA) and/or first-degree relative (FDR) status (n=52), established RA (n=67), and healthy controls (n=48) (Figure 1). We performed co-varying neighborhood analysis to characterize immunophenotypes in At-Risk individuals and identify phenotypical changes between At-Risk subpopulations accounting for batch effect, age, sex, and inter-individual variation. We further developed an “RA immunophenotype score” for cross-phenotype classification using mixed-effect modeling and logistic regression.

Results: We quantified the immune populations and uncovered significant cell expansions in At-Risk individuals compared with controls (p = 6e-3), including CCR2+CD4+ effector memory T cells (TEM) (OR = 1.47), T peripheral helper cells (Tph) (OR = 1.30), type 1 T helper cells (OR = 1.31), and CXCR5+CD8+ T cells (OR = 3.33) (Figure 2A-B). We further confirmed the expansions of these T cell phenotypes in the At-Risk individuals using our validation cohort with 57 At-Risk and 23 healthy individuals. In addition, we found that CD15+ classical monocytes were especially expanded in ACPA-negative At-Risk individuals who had FDR (p = 1e-3, OR = 1.30), and an activated PAX5low naïve B cell population expanded in ACPA-positive individuals who also had an FDR with RA (p = 9e-3, OR = 1.35). Further, we demonstrated that our “RA immunophenotype score” classification method built based on the degree of enrichment and the abundance of cell states relative to established RA (adjusted p < 0.05) (Figure 3A) is able to significantly distinguish At-Risk individuals from the control (p = 0.039, AUC >0.6) (Figure 3B-C).

Conclusion: We systematically characterized altered circulating immune phenotypes in At-Risk individuals, along with immunophenotypical differences among ACPA+ and FDR At-Risk subpopulations. Our classification model may provide a promising approach for understanding the pathogenesis of preclinical RA with the goal to develop preventive strategies and novel therapeutic targets.

References:
1. Zhang, F. et al. Cellular deconstruction of inflamed synovium defines diverse inflammatory phenotypes in rheumatoid arthritis. bioRxiv (2022) doi: https://doi.org/10.1101/2022.02.25.481990

Fig.1: Overview of mass cytometry analytical strategy, clustering, and classifications for At-Risk RA and established RA individuals.

Fig.2: Identifications of specific T cell populations that were associated with At-Risk. A. Cells in UMAP are colored in red (expansion) or blue (depletion) and p-value is shown as well. B. Distributions of cell neighborhood correlations and odds ratio. Error bars represent 95% confidence intervals.

Fig.3: Classifications for At-Risk individuals and established RA individuals. A. RA immunophenotype score utilizing RA-specific cell type abundances to quantify and distinguish At-Risk individuals from control. For each cell type, all p-values from the covarying neighborhood analysis test were p = 1e_3. We incorporated clusters that are significantly associated with RA (adjusted p < 0.05) to model the RA immunophenotype score. We calculated RA immunophenotype score based on cell type abundances multiplied by corresponding major cell type proportions and enrichment scores for each cell type, B. Distribution of RA immunophenotype score across individual samples from RA, At-Risk, and controls; **** p < 0.0001, * p < 0.05, C. Receiver operating characteristic (ROC) analysis to evaluate the classification performance of RA immunophenotype score in distinguishing At-Risk from control. Areas under the curve (AUC) with 95% confidence intervals were described. All the analyses are adjusted for age and sex.

Disclosures: J. Inamo: None; J. Keegan: None; A. Griffith: None; T. Ghosh: None; A. Horisberger: None; K. Howard: None; J. Pulford: None; E. Murzin: None; B. Hancock: None; J. Seifert: None; M. Feser: None; J. Norri: None; A. Jonsson: None; Y. Cao: None; W. Apruzzese: Pfizer, 3; S. Bridges: None; V. Bykerk: AbbVie, 2, Bristol Myers Squibb, 1, 2, 5, Pfizer, 1, 2; S. Goodman: NIH, 5, Novartis, 5; L. Donlin: Bristol-Myers Squibb(BMS), 2, Stryker, 2; G. Firestein: Eli Lilly, 5; H. Perlman: None; J. Bathon: None; L. Hughes: None; D. Tabechian: amgen, 12, share holder; A. Filer: Bristol-Myers Squibb(BMS), 5, GlaxoSmithKlein(GSK), 5, Janssen, 5, Nascient, 5, Sonoma Biotherapeutics, 2; C. Pitzalis: None; J. Anolik: None; L. Moreland: Boehringer-Ingelheim, 12, member of independent Data Safety Monitoring Board, Celltrion, 12, member of independent Data Safety Monitoring Board; J. Guthridge: None; J. James: Bristol-Myers Squibb(BMS), 5, GlaxoSmithKlein(GSK), 2, Novartis, 2, Progentec Biosciences, 5; M. Brenner: 4FO Ventures, 2, GlaxoSmithKlein(GSK), 2, Mestag Therapeutics, 2, 8, Third Rock Ventures, 2; S. Raychaudhuri: AbbVie, 6, Janssen, 1, Mestag, Inc, 2, 8, Pfizer, 1, Sanofi, 1, Sonoma, 1, 8; J. Sparks: AbbVie, 2, Amgen, 2, Boehringer Ingelheim, 2, Bristol-Myers Squibb, 2, 5, Gilead, 2, Inova Diagnostics, 2, Janssen, 2, Optum, 2, Pfizer, 2, ReCor, 2; T. RA/SLE Network: None; M. Holer: None; K. Deane: Bristol-Myers Squibb(BMS), 1, Gilead, 5, Janssen, 5, Werfen, 1, 12, Biomarker kits; J. Lederer: None; D. Rao: AstraZeneca, 2, Bristol-Myers Squibb, 2, 5, GlaxoSmithKlein(GSK), 2, Hifibio, 2, Janssen, 5, Merck, 5, Scipher Medicine, 2; F. Zhang: None.

To cite this abstract in AMA style:

Inamo J, Keegan J, Griffith A, Ghosh T, Horisberger A, Howard K, Pulford J, Murzin E, Hancock B, Seifert J, Feser M, Norri J, Jonsson A, Cao Y, Apruzzese W, Bridges S, Bykerk V, Goodman S, Donlin L, Firestein G, Perlman H, Bathon J, Hughes L, Tabechian D, Filer A, Pitzalis C, Anolik J, Moreland L, Guthridge J, James J, Brenner M, Raychaudhuri S, Sparks J, RA/SLE Network T, Holer M, Deane K, Lederer J, Rao D, Zhang F. Deep Immunophenotyping Reveals Circulating Activated Lymphocytes in Individuals at Risk for Rheumatoid Arthritis [abstract]. Arthritis Rheumatol. 2023; 75 (suppl 9). https://acrabstracts.org/abstract/deep-immunophenotyping-reveals-circulating-activated-lymphocytes-in-individuals-at-risk-for-rheumatoid-arthritis/. Accessed .

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