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Updated: Sep 23, 2025
Author Spotlight: Exploring the Role of Inflammation in the Co-occurrence of Primary Sjogren's Syndrome and Lung Adenocarcinoma
Published on: September 20, 2024
Identification of immune-related diagnostic markers in primary Sjögren's syndrome based on bioinformatics analysis
Qingle Zeng1, Jing Wen1, Leting Zheng1
1Department of Rheumatology and Immunology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Background:
Primary Sjögren's syndrome (pSS) is a relatively common diffuse connective tissue disease that often invades exocrine glands, such as the lacrimal and salivary glands, and manifests as dry eyes and dry mouth. At present, the molecular mechanism of pSS is not clear. This study was designed to explore the internal mechanism of pSS from the gene level and screen out the immune-related diagnostic markers of pSS.
Methods:
The gene expression profiles GSE84844, GSE7451, and GSE40611 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified with R software. Then, the DEGs were intersected with the immune genes obtained from the ImmPort database to acquire differentially expressed immune-related genes (DEIRGs), and functional enrichment analyses were performed. The DEIRGs were screened through the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm to obtain the optimal immune-related genes (IRGs). Expression levels of the optimal IRGs were verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to obtain the key genes. Next, gene chips GSE7451 and GSE40611, from other tissues, were selected as the training sets to verify the sensitivity and specificity of the diagnosis of the key genes by receiver operating characteristic (ROC) analysis.
Results:
A total of 54 DEIRGs were obtained. The functional enrichment analysis results showed that they play an important role in immune and inflammatory responses. Nine optimal IRGs were screened from the DEIRGs by the LASSO logistic regression algorithm. After qRT-PCR verification, eight out of nine optimal IRGs (IL-18, JAK2, TBK1, EED, TNFSF10, TNFSF13B, CYSLTR1, and ICOS) were significantly highly expressed in pSS patients and were defined as key genes. ROC analysis identified that TNFSF13B and CYSLTR1 had high sensitivity and specificity. Finally, the lack of previous research on EED and CYSLTR1 in pSS suggests that these IRGs may be regarded as new gateways to explore the diagnosis and pathogenesis of pSS.
Conclusions:
The key DEIRGs play a decisive role during the occurrence and development of pSS.
