ArticleACR open rheumatology2019
Gene Expression Meta-Analysis Reveals Concordance in Gene Activation, Pathway, and Cell-Type Enrichment in Dermatomyositis Target Tissues.
Article in ACR open rheumatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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
18 citing papers in PubMed, 24 citations in OpenAlex.
- Juvenile Myositis: Insights on Classification, Pathogenesis, and Therapies Over the Past 50 Years.Arthritis care & research · 2026Review
- Targeting interferon responses in juvenile dermatomyositis: Siglec-1 as an in vitro biomarker for JAK inhibitor efficacy.Rheumatology (Oxford, England) · 2025Article
- Article
- Juvenile Dermatomyositis: Updates in Pathogenesis and Biomarkers, Current Treatment, and Emerging Targeted Therapies.Paediatric drugs · 2025Review
- Neutrophil and mononuclear leukocyte pathways and upstream regulators revealed by serum proteomics of adult and juvenile dermatomyositis.Arthritis research & therapy · 2024Article
- Coordinated immune dysregulation in juvenile dermatomyositis revealed by single-cell genomics.JCI insight · 2024Article
- Coordinated immune dysregulation in Juvenile Dermatomyositis revealed by single-cell genomics.bioRxiv : the preprint server for biology · 2023Article
- Shared and Distinctive Transcriptomic and Proteomic Pathways in Adult and Juvenile Dermatomyositis.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Juvenile idiopathic inflammatory myositis: an update on pathophysiology and clinical care.Nature reviews. Rheumatology · 2023Review
- Single-cell profiling of peripheral blood and muscle cells reveals inflammatory features of juvenile dermatomyositis.Frontiers in cell and developmental biology · 2023Article
- Multi-Modal Single-Cell Sequencing Identifies Cellular Immunophenotypes Associated With Juvenile Dermatomyositis Disease Activity.Frontiers in immunology · 2022Article
- Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder.Translational psychiatry · 2021Article
- Analysis of human total antibody repertoires in TIF1γ autoantibody positive dermatomyositis.Communications biology · 2021Article
- Curation of over 10 000 transcriptomic studies to enable data reuse.Database : the journal of biological databases and curation · 2021Article
- Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis.Frontiers in immunology · 2021Article
- The Role of Cutaneous Type I IFNs in Autoimmune and Autoinflammatory Diseases.Journal of immunology (Baltimore, Md. : 1950) · 2020Review
- Article
- Advances Toward Precision Medicine in Juvenile Dermatomyositis.Current rheumatology reports · 2019Review
Corrections and comments
- Erratum issuedErratum.2020
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
objectiveWe conducted a comprehensive gene expression meta-analysis in dermatomyositis (DM) muscle and skin tissues to identify shared disease-relevant genes and pathways across tissues.
methodsSix publicly available data sets from DM muscle and two from skin were identified. Meta-analysis was performed by first processing data sets individually then cross-study normalization and merging creating tissue-specific gene expression matrices for subsequent analysis. Complementary single-gene and network analyses using Significance Analysis of Microarrays (SAM) and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identify genes significantly associated with DM. Cell-type enrichment was performed using xCell.
resultsThere were 544 differentially expressed genes (FC ≥ 1.3,
conclusionThere is striking similarity in gene expression across DM target tissues with enrichment of type I and II IFN pathways, MHC class I antigen-processing, T-cell activation, and antigen-presenting cells. These results suggest IFN-γ may contribute to the global IFN signature in DM, and altered auto-antigen presentation through the class I MHC pathway may be important in disease pathogenesis.
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.