Bioinformatics Analysis for Identification of Key Genes in Salivary Gland and the Potential of a Combination of Biomarkers for the Diagnosis of SS.

ABSTRACT:

Purpose

Sjögren'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 methods

Original 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 en

SUBMITTER: Chen L 

PROVIDER: S-EPMC8405838 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature