ArticleJournal of inflammation research2021
Bioinformatics Analysis for Identification of Key Genes in Salivary Gland and the Potential of a Combination of Biomarkers for the Diagnosis of SS.
Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- CCR1Journal of advanced research · 2026Article
- Integrative Bioinformatics and Machine Learning Identify Novel Diagnostic Biomarkers and Molecular Mechanisms in Sjögren's Syndrome.International journal of genomics · 2026Article
- Transcriptomic Analysis Reveals C-C Motif Chemokine Receptor 1 as a Critical Pathogenic Hub Linking Sjögren's Syndrome and Periodontitis.Current issues in molecular biology · 2025Article
- MNDA, a PYHIN factor involved in transcriptional regulation and apoptosis control in leukocytes.Frontiers in immunology · 2024Review
- Identification of Key Genes for Pyroptosis-Induced Salivary Gland Inflammation in Sjogren's Syndrome Based on Microarray Data and Immunohistochemistry Analysis.Journal of inflammation research · 2023Article
- Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells.Frontiers in immunology · 2023Article
- IRF9 and XAF1 as Diagnostic Markers of Primary Sjogren Syndrome.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSjögren's syndrome (SS) is a systemic autoimmune disease mainly characterized by dysfunction of exocrine glands. Studies on diagnosis models specific for SS patients are very limited. We aimed to use gene expression datasets from salivary glands to identify aberrant differentially expressed genes (DEGs) and pathways by bioinformatics and validate candidate genes by clinical minor labial gland biopsy (MSGB) samples, and finally build a combined gene quantitative diagnosis model of SS. PATIENTS AND
methodsOriginal datasets GSE23117, GSE7451, and GSE127952 were obtained from the Gene Expression Omnibus database (GEO) and integrated and analyzed for differentially expressed genes in SS salivary glands. ClueGO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of upregulated and downregulated DEGs were performed, and protein-protein interaction (PPI) networks were constructed using the STRING and Cytoscape database. H&E staining and immunohistochemistry were used to validate the expression levels of four hub genes in salivary glands. Finally, a receiver operating characteristic (ROC) curve of the combined diagnosis of four hub genes was analyzed in SS patients and non-SS patients in order to explore the diagnostic efficacy of these genes compared with conventional FS in SS.
resultsFifty-three upregulated genes and fifteen downregulated genes were identified. We analyzed the expression and function of four hub genes via H&E, immunohistochemistry, and ROC analysis. We then evaluated and verified the diagnosis value of four hub genes,
conclusionThe expression of
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