ArticleMolecular medicine reports2019
Identification of potential biomarkers for differential diagnosis between rheumatoid arthritis and osteoarthritis via integrative genome‑wide gene expression profiling analysis.
Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 33 citations in OpenAlex.
- Clinical predictors of response to methotrexate in patients with rheumatoid arthritis: a machine learning approach using clinical trial data.Arthritis research & therapy · 2022Trial
- Role of Total Body PET/CT in Inflammatory Disorders.Seminars in nuclear medicine · 2025Review
- Multicohort study testing the generalisability of the SASKit-ML stroke and PDAC prognostic model pipeline to other chronic diseases.BMJ open · 2024Article
- Identification and validation of immune-related genes in osteoarthritic synovial fibroblasts.Heliyon · 2024Article
- Multiple gene-drug prediction tool reveals Rosiglitazone based treatment pathway for non-segmental vitiligo.Inflammation · 2024Article
- Identification of diagnostic biomarkers for osteoarthritis through bioinformatics and machine learning.Heliyon · 2024Article
- Article
- Comparison of inflammatory molecular mechanisms between osteoarthritis and rheumatoid arthritis via gene microarrays.Molecular biology research communications · 2024Article
- EXPLORing Arthritis with Total-body Positron Emission Tomography.Seminars in musculoskeletal radiology · 2023Review
- TheJournal of inflammation research · 2023Article
- Identification of key candidate genes and biological pathways in the synovial tissue of patients with rheumatoid arthritis.Experimental and therapeutic medicine · 2022Article
- Non-Coding RNAs in Rheumatoid Arthritis: Implications for Biomarker Discovery.Non-coding RNA · 2022Article
- Potential biomarkers that discriminate rheumatoid arthritis and osteoarthritis based on the analysis and validation of datasets.BMC musculoskeletal disorders · 2022Article
- Gene Expression Microarray Data Identify Hub Genes Involved in Osteoarthritis.Frontiers in genetics · 2022Article
- Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs).Therapeutic advances in musculoskeletal disease · 2022Review
- Identification of SCRG1 as a Potential Therapeutic Target for Human Synovial Inflammation.Frontiers in immunology · 2022Article
- Potential clinical biomarkers in rheumatoid arthritis with an omic approach.Auto- immunity highlights · 2021Review
- Transthyretin and Receptor for Advanced Glycation End Product's Differential Levels Associated with the Pathogenesis of Rheumatoid Arthritis.Journal of inflammation research · 2021Article
- Identification of the Role of Wnt/β-Catenin Pathway Through Integrated Analyses and in vivo Experiments in Vitiligo.Clinical, cosmetic and investigational dermatology · 2021Article
- Antibiotic Treatment Prior to Injury Improves Post-Traumatic Osteoarthritis Outcomes in Mice.International journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to identify potential novel biomarkers in synovial tissue obtained from patients with Rheumatoid Arthritis (RA) and Osteoarthritis (OA) for differential diagnosis. The genome‑wide expression profiling datasets of synovial tissues from RA and OA cohorts, including GSE55235, GSE55457 and GSE55584 datasets, were retrieved and used to identify differentially expressed genes (DEGs; P<0.05; false discovery rate <0.05 and Fold Change >2) between RA and OA using R software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were performed to determine molecular and biochemical pathways associated with the identified DEGs, and a protein‑protein interaction (PPI) network of the DEGs was constructed using Cytoscape software. Significant modules in the PPI network and candidate driver genes were screened using the Molecular Complex Detection Algorithm. Potential biomarkers were evaluated by receiver operating characteristic and logistic regression analyses. Large numbers of DEGs were detected, including 273, 205 and 179 DEGs in the GSE55235, GSE55457 and GSE55584 datasets, respectively. Among them, 80 DEGs exhibited identical expression trends in all the three datasets, including 49 upregulated and 31 downregulated genes in patients with RA. DEGs in patients suffering from RA compared with patients suffering from OA were predominantly associated with the primary immunodeficiency pathway, including interleukin 7 receptor (IL7R) and signal transducer activator of transcription 1 (STAT1). The sensitivity of IL7R + STAT1 to differentiate RA from OA was 93.94% with a specificity of 80.77%. The results generated from analyses of the GSE36700 dataset were closely associated with results generated from analyses of GSE55235, GSE55457 and GSE55584 datasets, which further verified the reliability of the aforementioned results. The results of the present study suggested that increased expression of IL7R and STAT1 in synovial tissue as well as in the primary immunodeficiency may be associated with RA occurrence. These identified novel biomarkers may be used to predict disease occurrence and clinically differentiate RA from OA.
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