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Updated: Feb 18, 2026

Author Spotlight: Exploring the Role of Inflammation in the Co-occurrence of Primary Sjogren's Syndrome and Lung Adenocarcinoma
Published on: September 20, 2024
Expression of TLR7, TLR9, JAK2, and STAT3 genes in peripheral blood mononuclear cells from patients with systemic
Miša Vreća1, Ana Zeković2, Nemanja Damjanov2,3
1Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Vojvode Stepe 444a, Belgrade, 11000, Serbia.
Abstract:
Systemic sclerosis (SSc) is a rare, chronic, multisystem autoimmune disease clinically characterized by progressive fibrosis of the skin and internal organs. The basic mechanism appears to involve endothelial cell injury, overproduction of extracellular matrix proteins, and aberrant immune activation. So far, there have been a few attempts to find genetic biomarkers for monitoring disease activity or for correlation with certain symptoms. In order to reveal reliable biomarkers, we analyzed the expression of four genes representing three important signaling pathways, TLR7, TLR9, and JAK2-STAT3. Using RT-qPCR technique, we analyzed the expression of TLR7, TLR9, JAK2, and STAT3 genes in peripheral blood mononuclear cells of 50 SSc patients and 13 healthy individuals. We detected significant upregulation of TLR7 gene expression in a group of SSc patients compared to non-SSc group. Receiver operating characteristic (ROC) analysis showed that TLR7 expression efficiently discriminates SSc cases from healthy individuals. High TLR7 expression positively correlated with the late form of disease, active SSc, and the presence of digital ulcers. Decreased levels of TLR9 and JAK2 mRNA were found in the patient's cohort in comparison to non-SSc individuals, but showed no correlation with specific clinical outcomes. The expression level of the STAT3 gene did not differ between the analyzed groups. This is the first study on the expression of TLR7, TLR9, and STAT3 genes in SSc patients. Our results show that TLR7, TLR9, and JAK2 genes are potential biomarkers for SSc. The results obtained in this study could contribute to better classification, monitoring, and outcome prediction of patients with SSc based on genetics.
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