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Background: Previous single-cell transcriptomic and proteomic studies identified several subpopulations of fibroblasts in systemic sclerosis (SSc) skin. Furthermore, our group demonstrated that distinct fibroblast subsets have unique spatial localizations and composition of their niches [1, 2]. Previous studies showed that fibroblasts undergo metabolic reprogramming upon activation, to which tissue hypoxia and release of free oxygen radicals contribute. However, metabolic phenotyping of fibroblasts and of cells in their niche with single-cell and spatial resolution has not been achieved thus far in SSc.
Objectives: We aimed to perform single-cell metabolic phenotyping of fibroblasts, macrophages and endothelial cells, as well as of their cellular niches, and their association with progression of skin fibrosis in SSc, using imaging mass cytometry (IMC), a spatial proteomics technique.
Methods: Skin biopsies from nine SSc patients and seven controls were obtained and sections were prepared. An IMC panel of 38 metal-labelled antibodies, of which 22 antibodies targeting key enzymes and signalling molecules in several metabolic pathways was designed and validated in human skin. Data analysis was performed as described previously [1, 3-5]. Previous publications demonstrated a robust correlation between the glycolysis or OxPhos/ETC scores calculated with a similar mass cytometry-based approach and the respective pathway activities determined by functional assays [6].
Results: We analyzed the expression of key regulators of metabolic pathways such as glycolysis, oxidative phosphorylation (OxPhos), electron transport chain (ETC), fatty acid oxidation and synthesis, amino acid internalization, pentose phosphate pathway, hypoxia, reactive oxygen species production as well as of regulators of mitochondrial dynamics, collectively termed as metabolic regulome, in SSc and control skin. We identified a remarkably distinct metabolic regulome in dermal cells of SSc patients with progressive skin fibrosis compared with patients with stable skin fibrosis and to controls, with upregulation of computed glycolysis and OxPhos/ETC scores. Unbiased clustering of fibroblasts based on the metabolic markers identified eight distinct fibroblasts subsets defined by their metabolic regulome. Of these, a subpopulation of fibroblasts with a high expression of glycolysis and OxPhos/ETC enzymes (termed Met hi Fib) was upregulated in SSc patients with progressive skin fibrosis, and expressed high levels of markers of activated fibroblasts, such as αSMA and FAP. In contrast, a subpopulation of fibroblasts with low expression of glycolysis and OxPhos/ETC enzymes (termed Met low Fib), was downregulated in SSc patients with progressive skin fibrosis. The fibroblast subsets defined by their metabolic regulome formed niches with endothelial cells and macrophages with similar levels of metabolic pathway activities, e.g. the Met hi fibroblasts were located in spatial proximity to endothelial cells and macrophages that expressed high levels of glycolysis and OxPhos/ETC enzymes.
Conclusion: Using an IMC-based spatial proteomics approach, we identified distinct subsets of fibroblasts defined by their metabolic profiles in SSc and control skin, with a switch from resting fibroblasts with low metabolic activity to metabolically highly active fibroblasts in progressive skin fibrosis. These fibroblasts with high metabolic activity were expressing myofibroblast markers and were forming niches with other cell types with a similar metabolic profile. Thus, metabolic phenotyping of fibroblasts and their niches by IMC-based spatial proteomics might identify SSc patients at risk for progression of skin fibrosis.
REFERENCES: [1] Rius Rigau A, Liang M, Devakumar V, Neelagar R, Matei AE, Gyorfi AH, et al. Imaging mass cytometry-based characterisation of fibroblast subsets and their cellular niches in systemic sclerosis. Ann Rheum Dis. 2024.
[2] Li Y-N, Filla T, Györfi A-H, Liang M, Devakumar V, Micu A, et al. Spatially informed phenotyping by cyclic-in-situ-hybridization identifies novel fibroblast populations and their pathogenic niches in systemic sclerosis. bioRxiv. 2024:2024.12.28.630505.
[3] Rius Rigau A, Li YN, Matei AE, Gyorfi AH, Bruch PM, Koziel S, et al. Characterization of Vascular Niche in Systemic Sclerosis by Spatial Proteomics. Circ Res. 2024;134(7):875-91.
[4] Gronberg C, Rattik S, Tran-Manh C, Zhou X, Rius Rigau A, Li YN, et al. Combined inhibition of IL-1, IL-33 and IL-36 signalling by targeting IL1RAP ameliorates skin and lung fibrosis in preclinical models of systemic sclerosis. Ann Rheum Dis. 2024;83(9):1156-68.
[5] Gyorfi AH, Matei AE, Fuchs M, Liang C, Rigau AR, Hong X, et al. Engrailed 1 coordinates cytoskeletal reorganization to induce myofibroblast differentiation. J Exp Med. 2021;218(9).
[6] Hartmann FJ, Mrdjen D, McCaffrey E, Glass DR, Greenwald NF, Bharadwaj A, et al. Single-cell metabolic profiling of human cytotoxic T cells. Nat Biotechnol. 2021;39(2):186-97.
Acknowledgements: NIL.
Disclosure of Interests: Veda Devakumar: None declared, Yi-Nan Li: None declared, Tim Filla: None declared, Aleix Rius Rigau: None declared, Andrea-Hermina Györfi Boehringer Ingelheim, Bilgesu Safak Tuemerdem: None declared, Ranjana Neelagar: None declared, Christina Bergmann: None declared, Minrui Liang: None declared, Georg Schett: None declared, Jörg Distler CEO of 4D Science and scientific lead of FibroCure, Active Biotech, Anamar, ARXX, AstraZeneca, Bayer Pharma, Boehringer Ingelheim, Callidatas, Celgene, Galapagos, GSK, Inventiva, Janssen, Kyverna, Novartis, Pfizer, Quell Therapeutics, 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, ZenasBio, Alexandru-Emil Matei: None declared.
© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (