Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease with unclear etiology. T cell exhaustion (TEX) suppresses the immune response and can be a potential therapeutic strategy for autoimmune diseases. Therefore, this study primarily investigated the mechanism by which TEX influences...

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Main Authors: Yiqing Zheng, Hejun Li, Yanqing Wang, Lixin Huang, Ling Chen, Shunping Lin, Shuhuan Lin
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Immunology
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Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1476575/full
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author Yiqing Zheng
Hejun Li
Yanqing Wang
Lixin Huang
Ling Chen
Shunping Lin
Shuhuan Lin
author_facet Yiqing Zheng
Hejun Li
Yanqing Wang
Lixin Huang
Ling Chen
Shunping Lin
Shuhuan Lin
author_sort Yiqing Zheng
collection DOAJ
description BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease with unclear etiology. T cell exhaustion (TEX) suppresses the immune response and can be a potential therapeutic strategy for autoimmune diseases. Therefore, this study primarily investigated the mechanism by which TEX influences SLE, offering a novel target for its treatment.MethodsGSE72326 and GSE81622 were utilized in this study. TEX related genes (TEX-RGs) were obtained from the published literature. Differentially expressed genes (DEGs) were obtained through differential expression analysis. Subsequently, candidate genes were selected by overlapping DEGs and TEX-RGs. These candidate genes underwent protein-protein interactions (PPIs) analysis for further screening. Machine learning was applied to identify candidate key genes from the PPI-identified genes. The candidate key genes exhibiting an area under the receiver operating characteristic (ROC) curve (AUC) greater than 0.7, along with consistent expression trends and significant differences in GSE72326 and GSE81622 were defined as biomarkers. Additionally, enrichment analysis, immune infiltration analysis, chemical compounds prediction and molecular docking were carried out. Importantly, the biomarkers were validated for expression by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).ResultsThe biomarkers MX1, LY6E, IFI44 and OASL were screened by overlapping 327 DEGs and 1,408 TEX-RGs. Gene set enrichment analysis (GSEA) showed that there was a significant positive correlation between the expression of these biomarkers and immune-related pathways, such as the NOD-like receptor signaling pathway, Toll-like receptor signaling pathway and RIG-I-like receptor signaling pathway significant positive correlation. The immune infiltration of 8 types of immune cells differed significantly in SLE. Naive B cells, resting memory CD4 T cells and resting NK cells were significantly down-regulated in the SLE group. 4 biomarkers showed the highest correlation with resting memory CD4 T cells. Bisphenol A targeted OASL and LY6E, whereas acetaminophen targeted IFI44 and MX1.The binding activity between the biomarkers and the chemical compounds targeting them was very strong. Finally, RT-qPCR expression of MX1, LY6E, IFI44 and OASL was consistent with the results of the dataset.ConclusionMX1, LY6E, IFI44 and OASL were identified as biomarkers related to TEX in SLE. These biomarkers could be detected in the blood for early diagnosis of the disease or to monitor the efficacy of the disease treatment, thus providing a new target for the management of SLE.
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spelling doaj-art-53e166b0998b4d699ed9a8b0d1190a182025-08-20T02:40:48ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-03-011610.3389/fimmu.2025.14765751476575Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosusYiqing ZhengHejun LiYanqing WangLixin HuangLing ChenShunping LinShuhuan LinBackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease with unclear etiology. T cell exhaustion (TEX) suppresses the immune response and can be a potential therapeutic strategy for autoimmune diseases. Therefore, this study primarily investigated the mechanism by which TEX influences SLE, offering a novel target for its treatment.MethodsGSE72326 and GSE81622 were utilized in this study. TEX related genes (TEX-RGs) were obtained from the published literature. Differentially expressed genes (DEGs) were obtained through differential expression analysis. Subsequently, candidate genes were selected by overlapping DEGs and TEX-RGs. These candidate genes underwent protein-protein interactions (PPIs) analysis for further screening. Machine learning was applied to identify candidate key genes from the PPI-identified genes. The candidate key genes exhibiting an area under the receiver operating characteristic (ROC) curve (AUC) greater than 0.7, along with consistent expression trends and significant differences in GSE72326 and GSE81622 were defined as biomarkers. Additionally, enrichment analysis, immune infiltration analysis, chemical compounds prediction and molecular docking were carried out. Importantly, the biomarkers were validated for expression by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).ResultsThe biomarkers MX1, LY6E, IFI44 and OASL were screened by overlapping 327 DEGs and 1,408 TEX-RGs. Gene set enrichment analysis (GSEA) showed that there was a significant positive correlation between the expression of these biomarkers and immune-related pathways, such as the NOD-like receptor signaling pathway, Toll-like receptor signaling pathway and RIG-I-like receptor signaling pathway significant positive correlation. The immune infiltration of 8 types of immune cells differed significantly in SLE. Naive B cells, resting memory CD4 T cells and resting NK cells were significantly down-regulated in the SLE group. 4 biomarkers showed the highest correlation with resting memory CD4 T cells. Bisphenol A targeted OASL and LY6E, whereas acetaminophen targeted IFI44 and MX1.The binding activity between the biomarkers and the chemical compounds targeting them was very strong. Finally, RT-qPCR expression of MX1, LY6E, IFI44 and OASL was consistent with the results of the dataset.ConclusionMX1, LY6E, IFI44 and OASL were identified as biomarkers related to TEX in SLE. These biomarkers could be detected in the blood for early diagnosis of the disease or to monitor the efficacy of the disease treatment, thus providing a new target for the management of SLE.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1476575/fullsystemic lupus erythematosusT cell exhaustionbiomarkerstype I interferonchemical compounds
spellingShingle Yiqing Zheng
Hejun Li
Yanqing Wang
Lixin Huang
Ling Chen
Shunping Lin
Shuhuan Lin
Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
Frontiers in Immunology
systemic lupus erythematosus
T cell exhaustion
biomarkers
type I interferon
chemical compounds
title Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
title_full Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
title_fullStr Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
title_full_unstemmed Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
title_short Identification and immunoassay of biomarkers associated with T cell exhaustion in systemic lupus erythematosus
title_sort identification and immunoassay of biomarkers associated with t cell exhaustion in systemic lupus erythematosus
topic systemic lupus erythematosus
T cell exhaustion
biomarkers
type I interferon
chemical compounds
url https://www.frontiersin.org/articles/10.3389/fimmu.2025.1476575/full
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