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

Abstract

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. All the datasets were processed in R (version 4.0.3). A total of 16 immune cells and 13 immune functions were obtained. The top immune cell and immune function were “activated” dendritic cells and major histocompatibility complex class I. Correlation analysis showed the top correlation among 16 immune cells were B cells and tumor infiltrating lymphocytes, check-point and T cell co-stimulation, respectively. In comparisons of immune score, “activated” dendritic cells (.657 vs 594, P < .001), B cells (.492 vs 434, P = .004), macrophages (.631 vs 601, P = .010), inflammation-promoting (.545 vs 478, P < .001), Type I interferon Reponse (.728 vs 625, P < .001) and so on were higher in pSS than control group. In correlation analysis, the up-regulation of interferon induced protein with tetratricopeptide repeats 1 gene was strongly correlated with Type I interferon response with a correlation coefficient of .87. The receiver operating characteristic curve of 5 genes showed that the area under curve was.891. In the verification model, the area under curve was.881. In addition, disease ontology analysis supported the association between DEGs and pSS. In summary, pSS has a variety of DEGs in immune infiltration, which is worthy of the attention from clinicians.