Identification of immune-related biomarkers linked to systemic lupus erythematosus and dilated cardiomyopathy through integrated bioinformatics analysis and multiple machine learning algorithms

列线图 扩张型心肌病 基因 免疫系统 基因表达谱 计算生物学 小桶 炎症 医学 心肌病 生物信息学 基因表达 免疫学 生物 内科学 心力衰竭 转录组 遗传学
作者
Gaijie Li,Liwen Lin,Shushu Wang,Kachun Lu,KaMan Szeto,Guiting Zhou,Xianwen Tang,Chuanjin Luo
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:16
标识
DOI:10.3389/fimmu.2025.1606920
摘要

Background Epidemiological evidence indicates that up to 50% of systemic lupus erythematosus (SLE) patients exhibit cardiac involvement, suggesting a potential strong association between SLE and dilated cardiomyopathy (DCM). This study aims to identify SLE-related genes that may contribute to DCM development and to discover potential biomarkers for early DCM diagnosis in SLE patients. Methods We obtained expression profile datasets for dilated cardiomyopathy DCM and SLE from the Gene Expression Omnibus (GEO) database. Through differential expression analysis and weighted gene co-expression network analysis (WGCNA), we screened for candidate biomarkers shared between DCM and SLE and constructed a diagnostic nomogram. The diagnostic performance and effectiveness of the nomogram were evaluated using external datasets and qPCR. Additionally, we performed single-gene set enrichment analysis (GSEA) on key genes to elucidate their potential roles in SLE-related DCM. Finally, we applied the CIBERSORT algorithm to assess immune cell infiltration in both DCM and SLE patients. Results Through DEG and WGCNA in the DCM and SLE datasets, we identified a total of 141 key module genes and 24 commonly expressed differentially expressed genes. Enrichment analysis revealed that these 24 genes were primarily involved in inflammation, cell apoptosis, and immune regulation. Through machine learning algorithms and dataset validation, we further identified the HERC6 and IFI44L genes as important diagnostic markers for SLE-related DCM. Experimental validation supports the key role of HERC6, IFI44L, and RSAD2 in SLE-related cardiac dysfunction. Additionally, we developed a nomogram for DCM based on these two genes, and the results showed that both genes exhibited AUC values greater than 0.84. Simultaneously, single-GSEA and immune infiltration analysis indicated immune dysfunction in both DCM and SLE, with both HERC6 and IFI44L significantly associated with immune cell infiltration. Furthermore, connectivity map (cMAP) analysis identified α-linolenic acid as a potential therapeutic agent for treating DCM. Conclusion Our study identifies HERC6 and IFI44L as diagnostic markers for DCM in SLE and suggests α-linolenic acid as a potential therapeutic agent.
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