2105: Cohort-wide Immuno-phenotype Deconvolute Immunological and Clinical Heterogeneity Across Autoimmune Rheumatic Diseases

Tuesday, November 14, 2023

9:00 AM - 11:00 AM PT

Location: Poster Hall

Abstract Poster Presenter(s)

Yukinori Okada, MD, PhD

The University of Tokyo / Osaka University / RIKEN
Tokyo, Japan

Disclosure(s): No financial relationships with ineligible companies to disclose

Hiroaki Tanaka¹, Yukinori Okada², Shingo Nakayamada¹, Yusuke Miyazaki³, Kyuto Sonehara⁴, Shinichi Namba⁵, Suguru Honda⁶, Yuya Shirai⁷, Kenichi Yamamoto⁵, Katsunori Ikari⁸, Masayoshi Harigai⁹, KOSHIRO SONOMOTO¹⁰ and Yoshiya Tanaka¹, ¹University of Occupational and Environmental Health, Kitakyushu, Japan, ²University of Tokyo / Osaka University / RIKEN, Tokyo, Japan, ³The First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kiakyusyu Fukuoka, Japan, ⁴University of Tokyo, Tokyo, Japan, ⁵Osaka University, Osaka, Japan, ⁶Tokyo Women's Medical University, Tokyo, Japan, ⁷Osaka University, Suita, Japan, ⁸Tokyo Women's Medical University School of Medicine, Tokyo, Japan, ⁹Tokyo Women's Medical University, Division of Rheumatology, Department of Internal Medicine, Tokyo, Japan, ¹⁰University of Occupational and Environmental Health, Beppu, Japan

Background/Purpose: Autoimmune rheumatic diseases (AIRDs) are systemic but heterogeneous diseases characterized by orchestration of disrupted self-tolerance of immune systems. We face a challenge in characterizing clinical immune features and selecting best treatment strategy of the AIRD patients. Deconvolution of immunological and clinical heterogeneity within and across AIRDs is an essential step towards implementation of personalized medicine. Immuno-phenotypes, immune-related cell types in peripheral blood mononuclear cells quantified by flow-cytometry analysis, can less invasively describe immune profiles of individuals and is considered as a promising technique.

Methods: We conducted large-scale and cohort-wide immuno-phenotyping of 46 peripheral immune cells using the Human Immunology Protocol of comprehensive 8-color flow cytometric analysis. The dataset consisted of >1,000 Japanese patients of 11 AIRDs and controls with deep clinical information registered at the FLOW study, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE),systemic sclerosis (SSc), ANCA related vasculitis (AAV), idiopathic inflammatory myopathy (IIM), psoriasis, IgG4 related disease (IgG4RD), mixed connective tissue disease (MCTD), ankylosing spondylitis (AS), Sjogren's syndrome (SjS), and giant cell aortitis (GCA). In depth and longitudinal clinical analysis was conducted for the identified RA patient clusters registered at the FIRST registry. Inborn human genetics represented by genome-wide polygenic risk score (PRS) were estimated for the RA patients.

Results: Multimodal clustering of immuno-phenotypes deciphered underlying disease-cell type network, providing immune cell type specificity shared or distinct across AIRDs (Figure 1), such as close immunological network of MCTD with SLE rather than with SSc. Individual patient-level clustering deconvoluted the AIRD patients into several clusters with different immunological features (Figure 2). Of these, RA- or SLE-like clusters were exclusively dominant, showing immunological polarization between RA and SLE across AIRDs (the patient clusters 4-6 and 1-3 for RA and SLE, respectively). In depth and longitudinal clinical analysis of RA revealed that such patient clusters differentially defined clinical heterogeneity in disease activity and treatment responses, which were supported by immune cell-type specificity (e.g., decreased regulatory T cells associated with treatment resistance in the RA patients with SLE-like immuno-phenotypes). PRS based on RA case-control genome-wide association study (GWAS) and within-case stratified RA GWAS were associated with patient characteristics, disease activity, and immuno-phenotypes of the RA patients, such as dendritic cells for RA-interstitial lung disease (Figure 3).

Conclusion: Our study demonstrated a value of cohort-wide and cross-disease immuno-phenotyping to elucidate clinically heterogenous patient subtypes existing within the single disease in an immune cell type-specific manner.

Figure 1 Immune-phenotype network across AIRDs and immune cell types.
AIRD-immune cell type associations based on backward-forward stepwise logistic regression adjusted by sex were visualized as a network plot.

Figure 2. Patient-level clustering of the 11 AIRDs based on the cohort-wide immuno-phenotypes.
(A) Unsupervised clustering of individual AIRD patients according to the immuno-phenotypes of the 46 peripheral immune cells. (B) Pie charts showing proportions of the AIRDs within each cluster, and those of the clusters within RA and SLE (left). A co-plot of the fractions of the RA and SLE patients within each cluster (right).

Figure 3. Associations of PRS with clinical and immunological information
Associations of the PRS based on RA case-control GWAS and within RA case GWAS for RA-ILD with clinical information and immune-phenotypes of the cell types are indicated.

H. Tanaka: None; Y. Okada: None; S. Nakayamada: None; Y. Miyazaki: None; K. Sonehara: None; S. Namba: None; S. Honda: None; Y. Shirai: None; K. Yamamoto: None; K. Ikari: AbbVie/Abbott, 6, Asahi Kasei, 6, Astellas Pharma, 6, Ayumi Parmaceutical, 6, Bristol-Myers Squibb(BMS), 6, Chugai Parmaceutical, 6, Eisai, 6, Eli Lilly, 6, Janssen, 6, Kaken Pharmaceutical, 6, Mitsubishi Tanabe Pharma, 6, Pfizer, 6, Takeda Pharmaceutical, 6, Teijin Pharma, 6, UCB, 6; M. Harigai: Astellas Pharma, 6, AstraZeneca, 6, GlaxoSmithKlein(GSK), 6, 12, Post marketing surveillence, Novartis, 5; K. SONOMOTO: AbbVie/Abbott, 6, Eli Lilly, 6, UCB, 5; Y. Tanaka: AbbVie, 6, AstraZeneca, 6, BMS, 6, Boehringer-Ingelheim, 6, Chugai, 5, 6, Eisai, 5, 6, Eli Lilly, 6, Gilead, 6, GSK, 6, Mitsubishi-Tanabe, 5, Pfizer, 6, Taiho, 6, Taisho, 5, 6.