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<p>Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with challenging early diagnosis. Aberrant programmed cell death (PCD) is critical in SLE pathogenesis. This study aimed to identify key PCD genes for SLE diagnosis and disease activity assessment. Integrated bioinformatics analysis was conducted on three whole-blood transcriptomic datasets (GSE65391, GSE110174, GSE154851) from GEO. Machine learning algorithms (LASSO, SVM-RFE) identified hub genes across 18 PCD types. ssGSEA and logistic regression determined the predominant PCD pathway. Immune infiltration and correlation analyses evaluated clinical relevance. Necroptosis was identified as the most discriminative PCD pathway (AUC = 0.950, 95% CI: 0.921–0.979). Seven necroptosis-related genes (STAT1, STAT2, ZBP1, CASP1, TNFSF10, RIPK3, IL1B) were validated as key diagnostic biomarkers. A multivariate logistic regression model demonstrated robust performance across training and external validation cohorts, confirmed by internal validation (20 SLE patients and 16 healthy controls). The seven genes correlated significantly with dysregulated immune cells and were positively associated with SLEDAI, dsDNA levels, and neutrophil percentages. Necroptosis is a critical PCD pathway in SLE. The seven necroptosis-related genes represent promising diagnostic biomarkers and therapeutic targets.</p>

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Identification of key programmed cell death genes—necroptosis-related genes in systemic lupus erythematosus

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月19日

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  • Lu Wang,
  • Yuanyuan Li,
  • Xinyi Liu,
  • Shichang Song,
  • Yichen Han,
  • Lingfei Mo,
  • Hanchao Li,
  • Xiaohao Wang,
  • Ying Pan,
  • Jian Sun,
  • Jing Wang

摘要

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with challenging early diagnosis. Aberrant programmed cell death (PCD) is critical in SLE pathogenesis. This study aimed to identify key PCD genes for SLE diagnosis and disease activity assessment. Integrated bioinformatics analysis was conducted on three whole-blood transcriptomic datasets (GSE65391, GSE110174, GSE154851) from GEO. Machine learning algorithms (LASSO, SVM-RFE) identified hub genes across 18 PCD types. ssGSEA and logistic regression determined the predominant PCD pathway. Immune infiltration and correlation analyses evaluated clinical relevance. Necroptosis was identified as the most discriminative PCD pathway (AUC = 0.950, 95% CI: 0.921–0.979). Seven necroptosis-related genes (STAT1, STAT2, ZBP1, CASP1, TNFSF10, RIPK3, IL1B) were validated as key diagnostic biomarkers. A multivariate logistic regression model demonstrated robust performance across training and external validation cohorts, confirmed by internal validation (20 SLE patients and 16 healthy controls). The seven genes correlated significantly with dysregulated immune cells and were positively associated with SLEDAI, dsDNA levels, and neutrophil percentages. Necroptosis is a critical PCD pathway in SLE. The seven necroptosis-related genes represent promising diagnostic biomarkers and therapeutic targets.