ArticleScientific reports2026
Identification of molecular diagnostic markers and potential therapeutic drugs for Sjögren's syndrome.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Sjögren's Syndrome (SS) is a long-term autoimmune disorder marked by damage to exocrine glands and irregularities in the immune system. Currently, there is a significant lack of effective diagnostic biomarkers and targeted therapeutic options for this disorder. This research aimed to identify molecular biomarkers that could be used for SS diagnosis and to explore therapeutic candidates that could address current clinical needs. Multiple public datasets (GSE84844, GSE40611, GSE7451, GSE208260) were retrieved from the Gene Expression Omnibus (GEO) database, including samples of salivary glands, saliva, salivary ducts, and blood from both SS patients and healthy individuals. The GEO2R tool was used to identify Differentially Expressed Genes (DEGs). Five machine learning algorithms-Decision Tree, XGBoost, Random Forest, Lasso Regression, and Gradient Boosting Machines (GBM)-were applied to screen key diagnostic biomarkers. RT-PCR in PBMCs and IHC in salivary gland tissues were used to validate the expression levels of the candidate genes. Furthermore, CIBERSORT was employed to analyze immune cell infiltration in the blood of SS patients. Network pharmacology and molecular docking using CB-Dock2 were performed to explore paeoniflorin's therapeutic potential against SS. Eight common DEGs were identified, among which EPSTI1, IFI44, and IFIT1 were core biomarkers. These genes were significantly upregulated in SS patients (P < 0.05) and exhibited high diagnostic efficacy (AUC: 0.89, 0.90, 0.88, respectively). Blood samples from SS patients showed increased proportions of memory B cells and activated dendritic cells, as well as decreased CD4 naive T cells and γδ T cells (P < 0.05)-changes that correlated with the expression of the three core genes. Paeoniflorin shared 110 common targets with SS (enriched in immune and inflammatory pathways) and bound stably to the three biomarkers (Vina scores: -7.6, -8.7, -7.7). EPSTI1, IFI44, and IFIT1 are promising candidate diagnostic biomarkers for SS, with potential links to immune dysregulation. Paeoniflorin may exert immunomodulatory effects by targeting these genes, but this remains a hypothesis requiring experimental validation. This study provides preliminary insights into SS biomarkers and therapeutic candidates, but prospective clinical validation, functional experiments, and in vivo studies are essential before translation into practice.
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