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<p>Tubular injury is a key driver of diabetic kidney disease (DKD) progression. However, the involvement and regulatory mechanisms of PANoptosis in diabetic tubular injury remain poorly defined. Utilizing transcriptomic datasets from DKD renal tubules, we identified differentially expressed genes (DEGs) through limma analysis and co-expression modules via weighted gene co-expression network analysis (WGCNA). These findings were intersected with a comprehensive PANoptosis-related gene set. Hub genes were further prioritized using machine learning algorithms, including LASSO regression and random forest. Validation was conducted through the Nephroseq database, single-cell RNA sequencing (scRNA-seq) analysis and experimental studies in high glucose-treated tubular cells, DKD mice, and human DKD biopsies. Furthermore, functional enrichment and immune infiltration analyses were performed to elucidate biological implications. We revealed 1,624 DEGs and two key WGCNA modules significantly associated with DKD. Among 31 PANoptosis-related DEGs, machine learning prioritized three hub genes (TAP1, CASP1, PRKX), all of which were significantly upregulated in DKD and exhibited negative correlations with glomerular filtration rate. Functional analyses linked these hub genes to inflammatory and immune responses and scRNA-seq data confirmed their overexpression in proximal tubular cells. Moreover, experimental validation consistently demonstrated TAP1 upregulation in tubular cells under high glucose conditions, kidney tissues from DKD mouse models and human DKD biopsy samples. Our integrated analysis identifies TAP1 as a crucial regulator of PANoptosis in injured renal tubules of DKD, providing novel mechanistic insights into the pathogenesis of tubular injury and a potential therapeutic target for future research.</p>

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Integrated Transcriptomic Analysis Identifies TAP1 as a Key Regulator of PANoptosis in Diabetic Kidney Disease Tubular Injury

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月22日

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  • Qingsong Chen,
  • Hongxuan He,
  • Gang Wang,
  • Lili Huang,
  • Jiakun Yang,
  • Yan Sun,
  • Zheng Zhang,
  • Xiaohui Liao

摘要

Tubular injury is a key driver of diabetic kidney disease (DKD) progression. However, the involvement and regulatory mechanisms of PANoptosis in diabetic tubular injury remain poorly defined. Utilizing transcriptomic datasets from DKD renal tubules, we identified differentially expressed genes (DEGs) through limma analysis and co-expression modules via weighted gene co-expression network analysis (WGCNA). These findings were intersected with a comprehensive PANoptosis-related gene set. Hub genes were further prioritized using machine learning algorithms, including LASSO regression and random forest. Validation was conducted through the Nephroseq database, single-cell RNA sequencing (scRNA-seq) analysis and experimental studies in high glucose-treated tubular cells, DKD mice, and human DKD biopsies. Furthermore, functional enrichment and immune infiltration analyses were performed to elucidate biological implications. We revealed 1,624 DEGs and two key WGCNA modules significantly associated with DKD. Among 31 PANoptosis-related DEGs, machine learning prioritized three hub genes (TAP1, CASP1, PRKX), all of which were significantly upregulated in DKD and exhibited negative correlations with glomerular filtration rate. Functional analyses linked these hub genes to inflammatory and immune responses and scRNA-seq data confirmed their overexpression in proximal tubular cells. Moreover, experimental validation consistently demonstrated TAP1 upregulation in tubular cells under high glucose conditions, kidney tissues from DKD mouse models and human DKD biopsy samples. Our integrated analysis identifies TAP1 as a crucial regulator of PANoptosis in injured renal tubules of DKD, providing novel mechanistic insights into the pathogenesis of tubular injury and a potential therapeutic target for future research.