ArticleRheumatology (Oxford, England)2022
Transcriptome analysis reveals key genes modulated by ALK5 inhibition in a bleomycin model of systemic sclerosis.
Article in Rheumatology (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Immunomodulatory functions of growth differentiation factor 15 in skin aging and inflammatory dermatoses.Frontiers in immunology · 2026Review
- Characterization of a pathogenic nonmigratory fibroblast population in systemic sclerosis skin.JCI insight · 2025Article
- Single-Walled vs. Multi-Walled Carbon Nanotubes: Influence of Physico-Chemical Properties on Toxicogenomics Responses in Mouse Lungs.Nanomaterials (Basel, Switzerland) · 2023Article
- Scleroderma-like Impairment in the Network of Telocytes/CD34International journal of molecular sciences · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSSc is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for SSc.
methodsIn this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analysing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis.
resultsWe observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1 and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-β pathway inhibition via oral ALK5 (TGF-β receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin. We also implemented a machine learning algorithm that showed promise at predicting lung function using transcriptome data from both skin and lung biopsies.
conclusionThis study provides the most comprehensive look at the gene expression dynamics of an animal model of SSc to date, provides a rich dataset for future comparative fibrotic disease research, and helps refine our understanding of pathways at work during SSc pathogenesis and intervention.
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