Observational studyBioscience reports2020
Identification of biomarkers associated with synovitis in rheumatoid arthritis by bioinformatics analyses.
Observational study in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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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.
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Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- MAPK Pathway Activation Patterns in the Synovium Reveal ERK1/2 and EGFR as Key Players in Osteoarthritis.Biomedicines · 2025Article
- Selection of Common Genes Associated with Rheumatoid Arthritis and Cardiovascular Disease via a Network- and Pathway-Based Approach.Anatolian journal of cardiology · 2025Article
- Investigation of the Mechanism of Siweixizangmaoru Decoction in Improving CIA-Induced Arthritis in Rats Based on Network Pharmacology and Experimental Verification.Combinatorial chemistry & high throughput screening · 2025Article
- Carvone-loaded chitosan nanoparticles alleviate joint destruction by downregulating the expression of pro, inflammatory cytokines and MMP-13 in adjuvant-induced rat model.Inflammopharmacology · 2025Article
- Article
- [Identification of potential biomarkers and immunoregulatory mechanisms of rheumatoid arthritis based on multichip co-analysis of GEO database].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Machine learning and weighted gene co-expression network analysis identify a three-gene signature to diagnose rheumatoid arthritis.Frontiers in immunology · 2024Article
- The effect of food on the pharmacokinetics of WXFL10203614, a potential selective JAK1 inhibitor, in healthy Chinese subjects.Frontiers in pharmacology · 2022Article
- Safety, tolerability and pharmacokinetics of WXFL10203614 in healthy Chinese subjects: A randomized, double-blind, placebo-controlled phase Ⅰ study.Frontiers in pharmacology · 2022Article
- RNA-seq and Network Analysis Reveal Unique Chemokine Activity Signatures in the Synovial Tissue of Patients With Rheumatoid Arthritis.Frontiers in medicine · 2022Article
- Identification and validation of potential hub genes in rheumatoid arthritis by bioinformatics analysis.American journal of translational research · 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
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesRheumatoid arthritis (RA) is the most common inflammatory arthritis in the world, but its underlying mechanism is still unclear. The present study aims to screen and verify the potential biomarkers of RA.
methodsWe searched the Gene Expression Omnibus (GEO) database for synovial expression profiling from different RA microarray studies to perform a systematic analysis. Functional annotation of differentially expressed genes (DEGs) was conducted, including GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The protein-protein interaction (PPI) networks of the DEGs were constructed based on data from the STRING database. The expression levels of the hub genes in normal membranes and RA synovium were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot system.
resultsA total of 444 differential expression genes were identified, including 172 up-regulated and 272 down-regulated genes in RA synovium compared with normal controls. The top ten hub genes; protein tyrosine phosphatase receptor type C (PTPRC), LCK proto-oncogene (LCK), cell division cycle 20 (CDC20), Jun proto-oncogene (JUN), cyclin-dependent kinase 1 (CDK1), kinesin family member 11 (KIF11), epidermal growth factor receptor (epidermal growth factor receptor (EGFR), vascular endothelial growth factor A (VEGFA), mitotic arrest deficient 2 like 1 (MAD2L1), and signal transducer and activator of transcription 1 (STAT1) were identified from the PPI network, and the expression level of VEGFA and EGFR was significantly increased in RA membranes (P<0.05).
conclusionOur results indicate that the hub genes VEGFA and EGFR may have essential effects during the development of RA and can be used as potential biomarkers of RA.
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