Uncovering potential new biomarkers and immune infiltration characteristics in primary Sjögren's syndrome by integrated bioinformatics analysis.

Primary Sjögren's syndrome (pSS) is known as autoimmune disease characterized by damage to endocrine glands, such as the salivary and lacrimal glands. This study aimed to identify potential biomarkers for pSS using integrated bioinformatics analysis and explore the relationship between differentially expressed genes (DEGs) and immune infiltration. Three pSS datasets (GSE7451, GSE23117, and GSE40611) from the gene expression omnibus database were integrated.

Bioinformatics analysis identified immune infiltration, risk and drug prediction models of copper-induced death genes involved in salivary glands damage of primary Sjögren's syndrome.

This study aimed to identify copper-induced death genes in primary Sjögren's syndrome (pSS) and explore immune infiltration, risk and drug prediction models for salivary glands (SGs) damage. The 3 datasets, including GSE40611, GSE23117, and GSE7451 from the Gene Expression Omnibus database were downloaded. The datasets were processed using the affy in R (version 4.