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Abstract Number: 2233

Spatial Multi-omics Demonstrates Shared Immune States Across Autoimmune Diseases and Target Tissues in the Accelerating Medicines Partnership: Autoimmune and Immune-Mediated Diseases Network (AMP AIM)

Caleb Marlin1, Roopa Madhu2, Erin Theisen3, Liz Bradshaw4, Ce Gao5, Thomas Eisenhaure6, Nicolas Sugiarto7, Accelerating Medicines Partnertship: Autoimmune and Immune Mediated Diseases8, Jill Buyon9, Michelle Petri10, Brad Rovin11, Victoria Werth12, Ellen M. Gravallese13, Jennifer Anolik14, Larry Moreland15, Laura Donlin16, Christopher Ritchlin17, Jose Scher18, Johann Gudjonsson19, Wilson Liao20, Alexis Ogdie21, Caroline Shiboski22, A. Darise Farris1, Alan Baer23, Blake M. Warner24, Jose Clemente25, Adriana Heguy26, Michael Brenner27, Nir Hacohen28, Joel Guthridge1, Judith James1, Soumya Raychaudhuri29, Lam Tsoi19, Xiang Zhou30, Joshua Welch30, Rachael Clark3, ilya Korsunsky29, Christopher Lessard1 and Kevin Wei31, 1Oklahoma Medical Research Foundation, Oklahoma City, OK, 2Brigham and Women's Hospital, Brookline, MA, 3Brigham and Women's Hospital, Boston, 4Oklahoma Medical Research Foundation, Oklahoma City, 5Division of Rheumatology, Inflammation and Immunity, DOM, BWH; Harvard Medical School, Boston, MA, 6Broad Institute, Cambridge, MA, 7Broad Institute, Boston, 8Multiple Institutions, Oklahoma City, 9NYU Grossman School of Medicine, New York, NY, 10Johns Hopkins University School of Medicine, Timonium, MD, 11The Ohio State University, Columbus, OH, 12University of Pennsylvania, Wynnewood, PA, 13Brigham and Women's Hospital, Harvard Medical School, Chestnut Hill, MA, 14University of Rochester Medical Center, Rochester, NY, 15University of Colorado, Denver, CO, 16Hospital for Special Surgery, New York, NY, 17University of Rochester Medical Center, Canandaigua, NY, 18New York University School of Medicine, New York, NY, 19University of Michigan, Ann Arbor, MI, 20UCSF, San Francisco, CA, 21Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Wilmington, DE, 22University of California San Francisco, San Francisco, CA, 23Johns Hopkins University School of Medicine, Baltimore, MD, 24National Institutes of Health, Bethesda, MD, 25Icahn School of Medicine at Mount Sinai, New York, NY, 26NYU Grossman School of Medicine, New York, 27Brigham and Women's Hospital, Harvard Medical School, Newton, MA, 28Broad Institute of MIT Harvard, Cambridge, MA, 29Brigham and Women's Hospital, Boston, MA, 30University of Michigan, Ann Arbor, 31Brigham and Women's Hospital at Harvard Medical School, Boston, MA

Meeting: ACR Convergence 2025

Keywords: autoimmune diseases, Psoriatic arthritis, rheumatoid arthritis, Sjögren's syndrome, Systemic lupus erythematosus (SLE)

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Session Information

Date: Tuesday, October 28, 2025

Title: (2227–2264) Rheumatoid Arthritis – Diagnosis, Manifestations, and Outcomes Poster III

Session Type: Poster Session C

Session Time: 10:30AM-12:30PM

Background/Purpose: Autoimmune diseases affect more than 23.5 million Americans involving nearly every organ system of the human body. To identify shared, unique, and novel pathways underlying the pathogenesis of common autoimmune diseases, The Accelerating Medicines Partnership: Autoimmune and Immune-Mediated Diseases Network (AMP AIM) was launched to investigate Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus (SLE), Psoriatic Disease (PsD), and Sjogren’s Disease (SD) using single-cell and spatial technologies.

Methods: The Disease Teams, Technology Cores, System Biology Groups, Tissue Research Center, and Research Management Units collaborated on pilot projects to evaluate spatial and single-cell technologies for their feasibility, sensitivity, and scalability. These assessments aimed to inform the selection of omics approaches that would provide the greatest utility and reproducibility across the network’s diverse research settings.

Results: Following two years of focused investigation, the AMP AIM network developed a standard operating procedure which enables a multi-institutional, spatial multi-omics workflow of deep phenotyping of study participants. This protocol leverages centrally collected, FFPE-preserved target tissues (e.g., synovium, skin, salivary gland, and kidney) and integrates spatial transcriptomics (ST) using Xenium (10x Genomics), histological evaluation via H&E staining, and protein-level spatial profiling with Imaging Mass Cytometry (IMC) on the Hyperion platform (Standard BioTools), all on the same slide.1. Successful implementation of combined spatial transcriptomics and proteomics. With the network selecting Xenium as the preferred ST platform and post-run H&E stain, we developed a workflow which integrates Xenium and IMC from the same tissue section. This results in a unified dataset comprising ~5,000 spatially resolved transcripts, 40 protein markers, and histological context, enabling single-cell level correlation of gene and protein expression within intact tissue architecture (Fig 1).2. Defining shared immune cell states in target tissues across RA, SLE, PSD, and SD. To identify shared immune cell states across autoimmune diseases and target tissues, we implemented a computational pipeline for robust cell type and state annotation in spatial transcriptomic datasets. To evaluate the generalizability of this pipeline, we used a unified scRNA-seq reference to annotate T and NK cell states across spatially profiled tissues. This approach identified 9 distinct T cell states (Fig 2A), each exhibiting comparable transcriptional signatures across RA, SLE, PSD, and SD.

Conclusion: This integrated spatial multi-omics platform is being applied across disease-specific (e.g., RA, SLE, PSD, and SD) and cross-disease studies to uncover shared and distinct cellular programs in autoimmune pathogenesis. Through robust, high-resolution, single cell analyses within the tissue context, our approach lays the foundation for discovering common and unique mechanisms and advancing targeted therapeutics across autoimmune diseases.

Supporting image 1Figure 1: Spatial Characterization of Target Tissues. Representative images from all four target tissues (Synovium, Kidney, Salivary Gland, and Skin) processed and imaged on the Xenium spatial transcriptomics (10X Genomics), stained and whole slide imaged for H&E, and then stained and imaged for ~40 surface proteins via Imaging Mass Cytometry (Standard Biotools), all on the same tissue section and slide. Similar cell types (IMC) or transcripts (Xenium) are highlighted in the example projections to demonstrate agreement across technologies.

Supporting image 2Figure 2: Assessment of Spatial Transcriptomics Technologies demonstrates shared T-cell states across tissues. (A) Median abundance of T-cell states, shown as the proportion relative to the number of T-cells within each tissue. (B-E) Spatial localization of T-cell states within selected regions of interest. in: (B) skin, (C) salivary gland, (D) synovium, and (E) kidney tissues. T-cells are colored by their state, and non-T-cells are colored in grey.


Disclosures: C. Marlin: None; R. Madhu: None; E. Theisen: None; L. Bradshaw: None; C. Gao: None; T. Eisenhaure: None; N. Sugiarto: None; A. Autoimmune and Immune Mediated Diseases: None; J. Buyon: Artiva Biotherapeutics, 2, Biogen, 2, Bristol-Myers Squibb(BMS), 2, Celgene, 2, CLIMB Bio Operating, 2, GlaxoSmithKlein(GSK), 2, Janssen, 2, Related Sciences, 2, UCB, 2; M. Petri: Amgen, 2, AnaptysBio, 2, Annexon Bio, 2, AstraZeneca, 2, 5, Atara Biosciences, 2, Aurinia, 2, 5, Autolus, 2, Bain Capital, 2, Baobab Therapeutics, 2, Biocryst, 2, Biogen, 2, Boxer Capital, 2, Cabaletto Bio, 2, Caribou Biosciences, 2, CTI Clinical Trial and Consulting Services, 2, CVS Health, 2, Dualitybio, 2, Eli Lilly, 2, 5, EMD Serono, 2, Emergent, 2, Escient Pharmaceuticals, 2, Exagen, 5, Exo Therapeutics, 2, Gentibio, 2, GlaxoSmithKlein(GSK), 2, 5, iCell Gene Therapeutics, 2, Innovaderm Research, 2, IQVIA, 2, Janssen, 5, Kezar Life Sciences, 2, Kira Pharmaceuticals, 2, Nexstone Immunology, 2, Nimbus Lakshmi, 2, Novartis, 2, Ono Pharma, 2, PPD Development, 2, Proviant, 2, Regeneron, 2, Seismic Therapeutic, 2, Senti Biosciences, 2, Sinomab Biosciences, 2, Steritas, 2, Takeda, 2, Tenet Medicines, 2, TG Therapeutics, 2, UCB, 2, Variant Bio, 2, Worldwide Clinical Trials, 2, Zydus, 2; B. Rovin: Alexion, 2, Artiva, 2, 11, AstraZeneca, 2, Aurinia, 2, 5, Biogen, 2, 5, Bristol Myers Squibb, 2, Cabelleta, 2, Century, 2, F. Hoffman-La Roche Ltd/Genentech, Inc., 2, GlaxoSmithKlein(GSK), 2, Novartis, 2; V. Werth: AbbVie/Abbott, 2, Amgen, 2, 5, Anaptysbio, 2, Argenx, 2, 5, AstraZeneca, 2, 5, Biogen, 2, 5, Boehringer-Ingelheim, 2, Bristol-Myers Squibb(BMS), 2, Cabaletta Bio, 2, Calyx, 2, CSL Behring, 5, Cugene, 2, Eli Lilly, 2, EMD Serona, 2, 2, Evommune, 2, Gilead, 2, 5, GlaxoSmithKlein(GSK), 2, Horizon, 5, Immunovant, 2, Janssen, 2, Kwoya Kirin, 2, Merck/MSD, 2, Novartis, 2, Nuvig, 2, Pfizer, 2, 5, Regeneron, 2, 5, Roche, 2, Rome Pharmaceuticals, 5, Sanofi, 2, Takeda, 2, UCB, 2, 2, Ventus, 2, Viela, 5; E. Gravallese: Beam Therapeutics, 11, CRISPR Therapeutics, 11, Editas Medicine, 11, Elsevier, 9, Ginkgo Bioworks, 11, Intellia Therapeutics, 11, New England Journal of Medicine, 1, UpToDate, 9; J. Anolik: None; L. Moreland: None; L. Donlin: Bristol-Myers Squibb (BMS), 2, Karius, Inc., 5, Stryker, 2; C. Ritchlin: AbbVie, 2, Amgen, 2, Bristol-Myers Squibb(BMS), 2, Eli Lilly, 2, Janssen, 2, 5, MoonLake Pharma, 2, Novartis, 2, 5, Solara, 2, UCB, 2; J. Scher: Bristol-Myers Squibb(BMS), 2, Johnson & Johnson, 2, 5, Novartis, 2, Pfizer, 2, 5, UCB, 2; J. Gudjonsson: None; W. Liao: None; A. Ogdie: AbbVie, 5, Amgen, 5, 11, Bristol Myers Squibb, 5, Celgene, 5, CorEvitas, 2, Eli Lilly, 5, Novartis, 5, 11, Pfizer, 5, 11; C. Shiboski: None; A. Farris: Johnson & Johnson Innovative Medicine, 5; A. Baer: Bristol-Myers Squibb(BMS), 2; B. Warner: Mitobridge, subsidiary of Astellas Bio, 5, Pfizer, Inc., 5; J. Clemente: None; A. Heguy: None; M. Brenner: AbbVie/Abbott, 2, Johnson & Johnson, 5, Mestag Therapeutics, 2, 8, Moderna, 2, Ono Pharma, 5, Simcere, 2; N. Hacohen: Calico Biosciences, 5, Cytoreason, 1, 11, Danger Bio, 1, 11, Moderna, 5, Repertoire Immune Medicines, 1, 11, Takeda, 5; J. Guthridge: None; J. James: GlaxoSmithKlein(GSK), 2, Progentec, 5; S. Raychaudhuri: Bonito, 1, Bristol-Myers Squibb(BMS), 1, Janssen, 1, Mestag, 1, 8, Nimbus, 2, Pfizer, 1, Sonoma, 1, 8, Visterra, 6; L. Tsoi: Galderma, 5, Janssen, 5; X. Zhou: None; J. Welch: None; R. Clark: None; i. Korsunsky: Mestag therapeutics, 2; C. Lessard: Janssen Global Services, 2, Johnson & Johnson Innovative Medicine, 2, 5; K. Wei: 10X Genomics, 5, anaptysbio, 2, Gilead, 5, Merck/MSD, 5, Mestag, 2, Pfizer, 2.

To cite this abstract in AMA style:

Marlin C, Madhu R, Theisen E, Bradshaw L, Gao C, Eisenhaure T, Sugiarto N, Autoimmune and Immune Mediated Diseases A, Buyon J, Petri M, Rovin B, Werth V, Gravallese E, Anolik J, Moreland L, Donlin L, Ritchlin C, Scher J, Gudjonsson J, Liao W, Ogdie A, Shiboski C, Farris A, Baer A, Warner B, Clemente J, Heguy A, Brenner M, Hacohen N, Guthridge J, James J, Raychaudhuri S, Tsoi L, Zhou X, Welch J, Clark R, Korsunsky i, Lessard C, Wei K. Spatial Multi-omics Demonstrates Shared Immune States Across Autoimmune Diseases and Target Tissues in the Accelerating Medicines Partnership: Autoimmune and Immune-Mediated Diseases Network (AMP AIM) [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/spatial-multi-omics-demonstrates-shared-immune-states-across-autoimmune-diseases-and-target-tissues-in-the-accelerating-medicines-partnership-autoimmune-and-immune-mediated-diseases-network-amp-aim/. Accessed .
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