A genomic meta-analysis of clinical variables and their association with intrinsic molecular subsets in systemic sclerosis

Author:

Franks Jennifer M12ORCID,Toledo Diana M2,Martyanov Viktor12,Wang Yue12,Huang Suiyuan3,Wood Tammara A12,Spino Cathie3,Chung Lorinda4,Denton Christopher P5ORCID,Derrett-Smith Emma5,Gordon Jessica K6,Spiera Robert6,Domsic Robyn7ORCID,Hinchcliff Monique8ORCID,Khanna Dinesh39ORCID,Whitfield Michael L12ORCID

Affiliation:

1. Department of Biomedical Data Science

2. Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth , Lebanon, NH

3. Department of Biostatistics, University of Michigan , Ann Arbor, MI

4. Palo Alto Health Care System , Palo Alto, Stanford, CA, USA

5. Division of Medicine, University College London , London, UK

6. Hospital for Special Surgery , New York, NY

7. University of Pittsburgh , Pittsburgh, PA

8. Yale University , New Haven, CT

9. Division of Rheumatology, Department of Medicine, University of Michigan , Ann Arbor, MI, USA

Abstract

Abstract Objectives Four intrinsic molecular subsets (inflammatory, fibroproliferative, limited, normal-like) have previously been identified in SSc and are characterized by unique gene expression signatures and pathways. The intrinsic subsets have been linked to improvement with specific therapies. Here, we investigated associations between baseline demographics and intrinsic molecular subsets in a meta-analysis of published datasets. Methods Publicly available gene expression data from skin biopsies of 311 SSc patients measured by DNA microarray were classified into the intrinsic molecular subsets. RNA-sequencing data from 84 participants from the ASSET trial were used as a validation cohort. Baseline clinical demographics and intrinsic molecular subsets were tested for statistically significant associations. Results Males were more likely to be classified in the fibroproliferative subset (P = 0.0046). SSc patients who identified as African American/Black were 2.5 times more likely to be classified as fibroproliferative compared with White/Caucasian patients (P = 0.0378). ASSET participants sera positive for anti-RNA pol I and RNA pol III autoantibodies were enriched in the inflammatory subset (P = 5.8 × 10−5, P = 9.3 × 10−5, respectively), while anti-Scl-70 was enriched in the fibroproliferative subset. Mean modified Rodnan Skin Score (mRSS) was statistically higher in the inflammatory and fibroproliferative subsets compared with normal-like (P = 0.0027). The average disease duration for inflammatory subset was less than fibroproliferative and normal-like intrinsic subsets (P = 8.8 × 10−4). Conclusions We identified multiple statistically significant differences in baseline demographics between the intrinsic subsets that may represent underlying features of disease pathogenesis (e.g. chronological stages of fibrosis) and have implications for treatments that are more likely to work in certain SSc populations.

Funder

National Institutes of Health

National Institute of Allergy and Infectious Diseases Clinical and Autoimmunity Center of Excellence

National Institute of Arthritis and Musculoskeletal and Skin Diseases

Scleroderma Research Foundation

Burroughs-Wellcome PUP Big Data in the Life Sciences Training Program

Marian Falk Medical Research Trust

Publisher

Oxford University Press (OUP)

Subject

Pharmacology (medical),Rheumatology

Reference26 articles.

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