SynthesisRheumatology (Oxford, England)2022
A genomic meta-analysis of clinical variables and their association with intrinsic molecular subsets in systemic sclerosis.
Synthesis 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 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The 2024 British Society for Rheumatology guideline for management of systemic sclerosis.Rheumatology (Oxford, England) · 2024Guideline
- Machine-learning classification identifies patients with early systemic sclerosis as abatacept responders via CD28 pathway modulation.JCI insight · 2022Trial
- Fibrotic Disease of the Skin and Lung: Shared Pathways, Environmental Drivers, and Therapeutic Opportunities in a Changing Climate.International journal of molecular sciences · 2025Review
- An international perspective on the future of systemic sclerosis research.Nature reviews. Rheumatology · 2025Review
- Single-cell analysis reveals key differences between early-stage and late-stage systemic sclerosis skin across autoantibody subgroups.Annals of the rheumatic diseases · 2023Article
- Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine.International journal of molecular sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
objectivesFour 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.
methodsPublicly 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.
resultsMales 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).
conclusionsWe 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.
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