ArticleJCI insight2016
Integrated, multicohort analysis of systemic sclerosis identifies robust transcriptional signature of disease severity.
Article in JCI insight, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
52 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Comprehensive multi-cohort transcriptional meta-analysis of muscle diseases identifies a signature of disease severity.Scientific reports · 2022Pooled it
- Skin Transcriptomics Reveal Shared Molecular Mechanisms for Skin and Lung Involvement in Systemic Sclerosis.Arthritis & rheumatology (Hoboken, N.J.) · 2026Article
- Mechanical gating of tendon fibrogenic transcription in systemic sclerosis.Nature communications · 2026Article
- Multimodal analyses of early, untreated systemic sclerosis skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling.JCI insight · 2026Article
- Article
- Harnessing artificial intelligence to advance insights in systemic sclerosis skin and lung disease.Current opinion in rheumatology · 2025Review
- Multicohort Analysis of Bronchial Epithelial Cell Expression in Healthy Subjects and Patients with Asthma Reveals Four Clinically Distinct Clusters.American journal of respiratory cell and molecular biology · 2025Article
- Neural network analysis as a novel skin outcome in a trial of belumosudil in patients with systemic sclerosis.Arthritis research & therapy · 2025Article
- An international perspective on the future of systemic sclerosis research.Nature reviews. Rheumatology · 2025Review
- Skin Gene Expression Profiles in Systemic Sclerosis: From Clinical Stratification to Precision Medicine.International journal of molecular sciences · 2023Review
- Current Concepts on the Pathogenesis of Systemic Sclerosis.Clinical reviews in allergy & immunology · 2023Review
- Characterising the autoantibody repertoire in systemic sclerosis following myeloablative haematopoietic stem cell transplantation.Annals of the rheumatic diseases · 2023Article
- Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
- Three Distinct Transcriptional Profiles of Monocytes Associate with Disease Activity in Scleroderma Patients.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Loss of Protein Kinase D2 Activity Protects Against Bleomycin-Induced Dermal Fibrosis in Mice.Laboratory investigation; a journal of technical methods and pathology · 2023Article
- Epiregulin is a dendritic cell-derived EGFR ligand that maintains skin and lung fibrosis.Science immunology · 2022Article
- Tenascin-C in fibrosis in multiple organs: Translational implications.Seminars in cell & developmental biology · 2022Review
- Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets.Cancer biology & medicine · 2022Article
- A roadmap for translational cancer glycoimmunology at single cell resolution.Journal of experimental & clinical cancer research : CR · 2022Review
- Large-scale analysis of longitudinal skin gene expression in systemic sclerosis reveals relationships of immune cell and fibroblast activity with skin thickness and a trend towards normalisation over time.Annals of the rheumatic diseases · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 7 institutions in 2 countries.
Funding
Abstract
Systemic sclerosis (SSc) is a rare autoimmune disease with the highest case-fatality rate of all connective tissue diseases. Current efforts to determine patient response to a given treatment using the modified Rodnan skin score (mRSS) are complicated by interclinician variability, confounding, and the time required between sequential mRSS measurements to observe meaningful change. There is an unmet critical need for an objective metric of SSc disease severity. Here, we performed an integrated, multicohort analysis of SSc transcriptome data across 7 datasets from 6 centers composed of 515 samples. Using 158 skin samples from SSc patients and healthy controls recruited at 2 centers as a discovery cohort, we identified a 415-gene expression signature specific for SSc, and validated its ability to distinguish SSc patients from healthy controls in an additional 357 skin samples from 5 independent cohorts. Next, we defined the SSc skin severity score (4S). In every SSc cohort of skin biopsy samples analyzed in our study, 4S correlated significantly with mRSS, allowing objective quantification of SSc disease severity. Using transcriptome data from the largest longitudinal trial of SSc patients to date, we showed that 4S allowed us to objectively monitor individual SSc patients over time, as (a) the change in 4S of a patient is significantly correlated with change in the mRSS, and (b) the change in 4S at 12 months of treatment could predict the change in mRSS at 24 months. Our results suggest that 4S could be used to distinguish treatment responders from nonresponders prior to mRSS change. Our results demonstrate the potential clinical utility of a novel robust molecular signature and a computational approach to SSc disease severity quantification.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.