Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA pannus tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting distinct etiologies that warrant specific targeted therapy. Thus, cost-effective alternatives to clinical pathology phenotyping are needed for research and disparate healthcare. To this end, we developed automated multi-scale computational pathotyping (AMSCP) with two distinct components that can be leveraged together or independently: 1) segmentation of different tissue types to characterize tissue-level changes, and 2) cell type classification within each tissue compartment that assesses change across disease states. Initial training and validation were completed on 264 knee histology sections from mice with TNF-transgenic (n=233) and injected zymosan induced (n=32) inflammatory arthritis. Peak tissue segmentation performance was 0.94 +/- 0.01 frequency weight mean intersection over union and peak cell classification was 0.83 +/- 0.12 F1. We then leveraged these models and adapted them to analyze RA pannus tissue clinically phenotyped as pauci-immune (n=5), diffuse (n=28) and lymphoid (n=27), achieving peak cell classification of 0.81 +/- 0.06 F1. Regression analysis demonstrated a highly significant correlation between AMSCP of lymphocyte counts and average Krenn Inflammation Score (rho = 0.88; p<0.0001). While a simple threshold of 1.1% of plasma cells demonstrated the phenotyping potential of our automated approach vs. a clinical pathologist with a sensitivity and specificity of 0.81 and 0.73. Taken together, we find AMSCP to be a valuable cost-effective method for research. Follow up studies to assess its clinical utility are warranted.

The authors have declared no competing interest.

This work was supported by the Accelerating Medicines Partnership (AMP) in Rheumatoid Arthritis and Lupus Network. AMP is a public-private partnership (AbbVie Inc., Arthritis Foundation, Bristol-Myers Squibb Company, Foundation for the National Institutes of Health, GlaxoSmithKline, Janssen Research and Development, LLC, Lupus Foundation of America, Lupus Research Alliance, Merck Sharp & Dohme Corp., National Institute of Allergy and Infectious Diseases, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Pfizer Inc., Rheumatology Research Foundation, Sanofi and Takeda Pharmaceuticals International, Inc.) created to develop new ways of identifying and validating promising biological targets for diagnostics and drug development. Funding was provided through grants from the National Institutes of Health (UH2-AR067676, UH2-AR067677, UH2-AR067679, UH2-AR067681, UH2-AR067685, UH2- AR067688, UH2-AR067689, UH2-AR067690, UH2-AR067691, UH2- AR067694, and UM2- AR067678). Accelerating Medicines Partnership and AMP are registered service marks of the U.S. Department of Health and Human Services.

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The human data was acquired from the Accelerating Medicines Partnership (AMP) Network for RA and SLE constructed a cross-sectional cohort - samples were collected from 13 clinical sites across the United States and sites in the United Kingdom. The collection occurred over the course of a 45-month period from October 2016 to February of 2020. The study was performed in accordance with protocols approved by the institutional review board. The mouse work was approved by the University of Rochester Medical Centers UCAR and the Hospital for Special Surgeries IACUC.

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