Identification of a distinctive gene signature in granulomatous myositis
Pinal Fernandez, Iago (Johns Hopkins University School of Medicine)
Ruffer, Nikolas (University Medical Center Hamburg-Eppendorf)
Casal-Dominguez, Maria (Johns Hopkins University School of Medicine)
Pak, Katherine (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Kleefeld, Felix (Charité-Universitätsmedizin Berlin)
Preusse, Corinna (Charité-Universitätsmedizin Berlin)
Kirou, Raphael A. (State University of New York Downstate Health Sciences University)
Kinder, Travis B (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Del Orso, Stefania (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Naz, Faiza (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Islam, Shamima (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Gutierrez-Cruz, Gustavo (National Institute of Arthritis and Musculoskeletal and Skin Diseases)
Selva O'Callaghan, Albert (Universitat Autònoma de Barcelona. Departament de Medicina)
Milisenda, José César (Hospital Clínic i Provincial de Barcelona)
Schneider, Udo (Charité-Universitätsmedizin Berlin)
Liewluck, Teerin (Mayo Clinic (Rochester, Estats Units d'Amèrica))
Stenzel, Werner (Charité-Universitätsmedizin Berlin)
Mammen, Andrew L. (Johns Hopkins University School of Medicine)

Data:	2025
Resum:	Granulomatous myositis (GM) is defined by focal collections of activated macrophages that fuse to form multinucleated cells that aggregate into granulomas within skeletal muscle. This study aimed to elucidate the pathophysiology of GM by defining its specific transcriptomic profile. Bulk RNA sequencing was performed on 722 muscle biopsies, including 38 from patients with GM, other myopathies, and healthy comparators. Spatial transcriptomics and immunohistochemistry assays were used to identify the location of specific transcripts and proteins within the tissue. The transcriptomic signature of GM muscle biopsies was characterized by high levels of IFNγ, IFNγ-inducible genes, and proinflammatory cytokine genes including IL1B, TNF, and TGFB1. The expression levels of 1293 specifically upregulated and 256 specifically downregulated genes were highly correlated with transcriptomic markers of disease activity. Support vector machine models using this gene set identified GM with an AUC of 99. 6% (99. 0%-99. 9%) and an accuracy of 98. 6% (98. 2%-98. 9%). Expression of CHIT1, the most significantly upregulated gene, strongly correlated with disease severity and was detected at the RNA and protein level in granulomas and giant cells. GM is transcriptomically characterized by a strong IFNγ signature and overexpression of proinflammatory cytokines, including IL1B, TNF, and TGFB1. Additionally, it exhibits a unique transcriptomic profile, including CHIT1, which correlates with disease activity.
Drets:	Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets.
Llengua:	Anglès
Document:	Article ; recerca ; Versió sotmesa a revisió
Matèria:	Myositis ; Polymyositis ; Sarcoid ; RNA-sequencing ; Muscle Biopsy ; Granulomatous diseases
Publicat a:	medRxiv, January 2025

DOI: 10.1101/2024.12.27.24319708
PMID: 40568658

Preprint 27 p, 11.4 MB

El registre apareix a les col·leccions:
Articles > Articles de recerca
Articles > Articles publicats