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ABSTRACT: Introduction
Primary Sjögren's syndrome (pSS) is an autoimmune disease characterized by inflammatory infiltration, and dysfunction of the salivary and lacrimal glands. This research aimed to explore the disease pathogenesis and improve the diagnosis and treatment of pSS by mining inflammation-associated biomarkers.Methods
Five pSS-related datasets were retrieved from the Gene Expression Omnibus (GEO) database. Inflammation-associated biomarkers were determined by the least absolute shrinkage and selection operator (LASSO) and support vector machines recursive feature elimination (SVM-RFE). Single sample gene set enrichment analysis (ssGSEA) was implemented to profile the infiltration levels of immune cells. Real-time quantitative PCR (RT-qPCR) verified the expression of bio
SUBMITTER: Liu X
PROVIDER: S-EPMC10944815 | biostudies-literature | 2024 Apr
REPOSITORIES: biostudies-literature