Background: Systemic sclerosis (SSc)-associated primary heart involvement (SSc-pHI) is one of the leading causes of death in SSc [1, 2]. The cellular and molecular pathogenesis of SSc-pHI is largely unknown.

Objectives: We aimed to characterize the fibroblast niche and its cellular networks in SSc-pHI compared with other myocardial diseases with chronic remodeling (postviral myocardial fibrosis (PVMF), hypertrophic cardiomyopathy (HCM), and ischemic cardiomyopathy (ICM)), or acute fibrotic remodeling (acute myocardial infarction (AMI)) by cyclic-in-situ-hybridization.

Methods: We employed the CosMx SMI platform from NanoString Technologies (now Bruker Spatial Biology, Inc) on FFPE myocardial biopsies from 15 SSc-pHI-, 10 PVMF-, 5 HCM-, 5 ICM-, and 3 AMI patients. Two areas of 1.8 mm ² were analyzed from each myocardial biopsy. The Human Universal Cell Characterization RNA Core Panel composed of 950 genes extended with 19 additional genes for the identification of fibroblast subsets was used [3]. Cell segmentation was performed on the CosMx SMI platform. The Banksy R package, which employs both the gene expression profile and spatial information, was used for the identification of cellular populations [4]. Dimensionality reduction was performed by principal component analysis (PCA) and Leiden clustering. The Delaunay triangulation method was used for the identification of cellular neighbors. The composition of neighboring cells was computed for each cell and K-means clustering was then applied to define cellular local microenvironments or cellular neighborhoods (CNs).

Results: We identified 11672 fibroblasts and 9826 immune cells. BANKSY-based spatially-informed clustering identified six fibroblast subpopulations: DCN/GSN+-, AP1+-, TIMP1+-, COL1A1/POSTN+-, NOTCH3+ fibroblasts, and myofibroblasts. We observed a significant upregulation of DCN/GSN+ fibroblasts in SSc-pHI and other forms of chronic fibrotic remodeling compared with AMI, with the most pronounced differences in SSc-pHI (90% in SSc-pHI vs. 5% in AMI from total fibroblasts). TIMP1+-, COL1A1/POSTN+-, and NOTCH3+ fibroblasts were significantly upregulated in AMI compared with chronic fibrotic remodeling. SPP1+ macrophages were the predominant macrophage subpopulation in acute myocardial remodeling, while C1q+ macrophages were the most abundant macrophage subset in SSc-pHI and other types of chronic fibrotic remodeling. Consistently, TIMP1+ fibroblast-, NOTCH3+ fibroblast/ COL1A1/POSTN+ fibroblast- and APOE+ macrophage CNs were significantly upregulated in acute remodeling, while DCN/GSN+ fibroblast- and C1q+ macrophage CNs were the most abundant CNs in SSc-pHI and other types of fibrotic chronic remodeling. The DCN/GSN+ fibroblast CN was enriched in C1q+ macrophages and plasma cells. Myofibroblasts were enriched in the C1q+ macrophage- and AP1+ fibroblast CNs. Cellular interaction analysis und ligand/ receptor analysis showed profound differences between SSc-pHI and other forms of chronic fibrotic remodeling and AMI.

Conclusion: We demonstrate profound changes in the cellular composition of fibroblasts in SSc-pHI, with altered cellular interaction and signaling in the local fibroblast niches. DCN/GSN+ fibroblasts are increased in SSc-pHI and in other forms of chronic myocardial remodeling, while TIMP1+-, COL1A1/POSTN+-, and NOTCH3+ fibroblasts are associated with acute fibrotic remodeling. These numeric changes are associated with profound reorganization of the local niches, alterations in cellular interactions and signaling. Our findings may provide new insights into the pathophysiology of fibrotic myocardial remodeling and offer opportunities for therapeutic intervention.

REFERENCES: [1] Elhai M, Meune C, Boubaya M, Avouac J, Hachulla E, Balbir-Gurman A, et al. Mapping and predicting mortality from systemic sclerosis. Ann Rheum Dis. 2017;76(11):1897-905.

[2] Györfi AH, Filla T, Polzin A, Tascila K, Buch M, Tröbs M, et al. Evaluation of systemic sclerosis primary heart involvement and chronic heart failure in the European Scleroderma Trials and Research (EUSTAR) cohort. JAHA. 2025.

[3] He S, Bhatt R, Brown C, Brown EA, Buhr DL, Chantranuvatana K, et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat Biotechnol. 2022;40(12):1794-806.

[4] Singhal V, Chou N, Lee J, Yue Y, Liu J, Chock WK, et al. BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis. Nat Genet. 2024;56(3):431-41.

Acknowledgements: NIL.

Disclosure of Interests: Alexandru Micu: None declared, Alexandru-Emil Matei: None declared, Yi-Nan Li: None declared, Ann-Christin Pecher: None declared, Tim Filla: None declared, Jörg Henes: None declared, Markus Eckstein: None declared, Karin Klingel: None declared, Jörg Distler Active Biotech, Anamar, ARXX, AstraZeneca, Bayer Pharma, Boehringer Ingelheim, Callidatas, Celgene, Galapagos, GSK, Inventiva, Janssen, Kyverna, Novartis, Pfizer, Quell Therapeutics and UCB, 4D Science, FibroCure, Active Biotech, Anamar, ARXX, AstraZeneca, Bayer Pharma, Boehringer Ingelheim, Callidatas, Celgene, Galapagos, GSK, Inventiva, Janssen, Kyverna, Novartis, Pfizer, Quell Therapeutics and UCB, Anamar, ARXX, BMS, Bayer Pharma, Boehringer Ingelheim, Cantargia, Celgene, CSL Behring, Exo Therapeutics, Galapagos, GSK, Incyte, Inventiva, Kiniksa, Kyverna, Lassen Therapeutics, Mestag, Sanofi-Aventis, RedX, UCB and ZenasBio, Andrea-Hermina Györfi Boehringer Ingelheim, Boehringer Ingelheim.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.