SynthesisPloS one2015
Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases.
Synthesis in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Biosemantics guided gene expression profiling of Sjögren's syndrome: a comparative analysis with systemic lupus erythematosus and rheumatoid arthritis.Arthritis research & therapy · 2017Pooled it
- Exploration of the Regulatory Network of Programmed Cell Death Genes in Rheumatoid Arthritis Based on Blood-Derived circRNA Transcriptome Information and Single-Cell Multi-omics Data.Biochemical genetics · 2025Article
- Analysis of immune cell infiltration landscape and identification of diagnostic biomarkers in ankylosing spondylitis.APL bioengineering · 2025Article
- An Immunosenescent CD8+ T Cell Subset in Patients with Axial Spondyloarthritis and Psoriatic Arthritis Links Spontaneous Motility to Telomere Shortening and Dysfunction.Arthritis & rheumatology (Hoboken, N.J.) · 2025Article
- Identification of Key Biomarkers in Systemic Lupus Erythematosus by a Multi-Cohort Analysis.Frontiers in immunology · 2022Article
- Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis.Frontiers in immunology · 2021Article
- Article
- The Role of Long Non-coding RNAs in the Pathogenesis of RA, SLE, and SS.Frontiers in medicine · 2018Article
- Cell-type-specific gene expression patterns in the knee cartilage in an osteoarthritis rat model.Functional & integrative genomics · 2018Article
- The clinical utility of gene expression examination in rheumatology.Mediterranean journal of rheumatology · 2017Review
- Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles.Oncotarget · 2017Article
- Long noncoding RNA expression profile of infantile hemangioma identified by microarray analysis.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveRheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested.
methodsWe collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis.
resultsWe identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation.
conclusionThe findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases.
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