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已发表论文
通过转录组学和机器学习剖析系统性红斑狼疮相关冠状动脉损伤中的共享细胞毒性免疫特征
Authors Chen Y, Tso SM, Wu F, Xu Y, Cui L
Received 30 May 2025
Accepted for publication 22 October 2025
Published 4 November 2025 Volume 2025:14 Pages 1247—1266
DOI https://doi.org/10.2147/ITT.S539756
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Flavio Salazar-Onfray
Yongkang Chen,1,* Shuk Ming Tso,2,* Feng Wu,2 Yue Xu,3 Liyan Cui1
1Department of Laboratory Medicine, Peking University Third Hospital, Beijing, People’s Republic of China; 2Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA; 3Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Liyan Cui, Department of Laboratory Medicine, Peking University Third Hospital, Beijing, People’s Republic of China, Email cliyan@163.com
Purpose: This study investigated shared molecular pathways linking systemic lupus erythematosus (SLE) and coronary artery disease (CAD) to uncover mechanisms of coronary injury in SLE.
Patients and Methods: Bulk transcriptomic datasets (GSE45291 for SLE, GSE61145 for CAD) were analyzed to identify differentially expressed genes (DEGs), immune cell infiltration patterns, and co-expression networks. A diagnostic model was constructed and validated using external cohorts (GSE49454 for SLE, GSE179789 for CAD). Machine learning prioritized core genes, validated in both external cohorts and in SLE patients with coronary injury (GSE264125). Cellular localization and intercellular communication were explored by analyzing single-cell RNA-seq data (GSE135779). qPCR was used to validate the gene expression in peripheral blood mononuclear cells (PBMCs) from patients.
Results: We identified 146 common DEGs enriched in immune pathways related to cell toxicity, and found shared dysregulation in cytotoxic lymphocytes such as natural killer (NK) cells and CD8+ T cells. Through co-expression analysis and DEG intersection, we pinpointed 11 hub genes (eg, GZMK, KLRK1, GNLY). A diagnostic model based on these genes showed strong performance (SLE: AUC 0.881 training, 0.666 validation; CAD: AUC 0.897 training, 0.781 validation). Machine learning highlighted GZMK and KLRK1 as core genes, which were further validated for their combined diagnostic utility (AUC: 0.782– 1.000) in SLE-related coronary injury. Single-cell analysis revealed that these genes are primarily active in cytotoxic CD8+ T cells and NK cells, with GZMK linked to CLEC-mediated signaling and KLRK1 to HLA activation. Finally, we confirmed higher expression of these genes in blood cells from SLE patients with coronary artery disease using qPCR.
Conclusion: SLE and CAD share a cytotoxic lymphocyte-driven molecular axis, with GZMK/KLRK1-mediated immune dysregulation as a key contributor to coronary injury in SLE. GZMK and KLRK1 may represent promising biomarkers for early detection and risk stratification of SLE-associated coronary complications. Notably, the discrimination (AUC=1.000) was observed in a limited subgroup of SLE patients with coronary microvascular dysfunction (n=4), warranting further validation in expanded cohorts.
Keywords: systemic lupus erythematosus, coronary artery disease, diagnostic model, cytotoxic lymphocyte, cell interactions
1Department of Laboratory Medicine, Peking University Third Hospital, Beijing, People’s Republic of China; 2Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA; 3Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Liyan Cui, Department of Laboratory Medicine, Peking University Third Hospital, Beijing, People’s Republic of China, Email cliyan@163.com
Purpose: This study investigated shared molecular pathways linking systemic lupus erythematosus (SLE) and coronary artery disease (CAD) to uncover mechanisms of coronary injury in SLE.
Patients and Methods: Bulk transcriptomic datasets (GSE45291 for SLE, GSE61145 for CAD) were analyzed to identify differentially expressed genes (DEGs), immune cell infiltration patterns, and co-expression networks. A diagnostic model was constructed and validated using external cohorts (GSE49454 for SLE, GSE179789 for CAD). Machine learning prioritized core genes, validated in both external cohorts and in SLE patients with coronary injury (GSE264125). Cellular localization and intercellular communication were explored by analyzing single-cell RNA-seq data (GSE135779). qPCR was used to validate the gene expression in peripheral blood mononuclear cells (PBMCs) from patients.
Results: We identified 146 common DEGs enriched in immune pathways related to cell toxicity, and found shared dysregulation in cytotoxic lymphocytes such as natural killer (NK) cells and CD8+ T cells. Through co-expression analysis and DEG intersection, we pinpointed 11 hub genes (eg, GZMK, KLRK1, GNLY). A diagnostic model based on these genes showed strong performance (SLE: AUC 0.881 training, 0.666 validation; CAD: AUC 0.897 training, 0.781 validation). Machine learning highlighted GZMK and KLRK1 as core genes, which were further validated for their combined diagnostic utility (AUC: 0.782– 1.000) in SLE-related coronary injury. Single-cell analysis revealed that these genes are primarily active in cytotoxic CD8+ T cells and NK cells, with GZMK linked to CLEC-mediated signaling and KLRK1 to HLA activation. Finally, we confirmed higher expression of these genes in blood cells from SLE patients with coronary artery disease using qPCR.
Conclusion: SLE and CAD share a cytotoxic lymphocyte-driven molecular axis, with GZMK/KLRK1-mediated immune dysregulation as a key contributor to coronary injury in SLE. GZMK and KLRK1 may represent promising biomarkers for early detection and risk stratification of SLE-associated coronary complications. Notably, the discrimination (AUC=1.000) was observed in a limited subgroup of SLE patients with coronary microvascular dysfunction (n=4), warranting further validation in expanded cohorts.
Keywords: systemic lupus erythematosus, coronary artery disease, diagnostic model, cytotoxic lymphocyte, cell interactions