Department of Endocrinology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China.
Department of Nephrology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China.
Acta Diabetol. 2024 Aug;61(8):1053-1068. doi: 10.1007/s00592-024-02278-1. Epub 2024 May 1.
AIMS: Accumulating evidences indicate that abnormalities in tubular lipid metabolism play a crucial role in the development of diabetic kidney disease (DKD). We aim to identify novel lipid metabolism-related genes associated with tubular injury in DKD by utilizing bioinformatics approaches. METHODS: Differentially expressed genes (DEGs) between control and DKD tubular tissue samples were screened from the Gene Expression Omnibus (GEO) database, and then were intersected with lipid metabolism-related genes. Hub genes were further determined by combined weighted gene correlation network analysis (WGCNA) and protein-protein interaction (PPI) network. We performed enrichment analysis, immune analysis, clustering analysis, and constructed networks between hub genes and miRNAs, transcription factors and small molecule drugs. Receiver operating characteristic (ROC) curves were employed to evaluate the diagnostic efficacy of hub genes. We validated the relationships between hub genes and DKD with external datasets and our own clinical samples. RESULTS: There were 5 of 37 lipid metabolism-related DEGs identified as hub genes. Enrichment analysis demonstrated that lipid metabolism-related DEGs were enriched in pathways such as peroxisome proliferator-activated receptors (PPAR) signaling and pyruvate metabolism. Hub genes had potential regulatory relationships with a variety of miRNAs, transcription factors and small molecule drugs, and had high diagnostic efficacy. Immune infiltration analysis revealed that 13 immune cells were altered in DKD, and hub genes exhibited significant correlations with a variety of immune cells. Through clustering analysis, DKD patients could be classified into 3 immune subtypes and 2 lipid metabolism subtypes, respectively. The tubular expression of hub genes in DKD was further verified by other external datasets, and immunohistochemistry (IHC) staining showed that except ACACB, the other 4 hub genes (LPL, AHR, ME1 and ALOX5) exhibited the same results as the bioinformatics analysis. CONCLUSION: Our study identified several key lipid metabolism-related genes (LPL, AHR, ME1 and ALOX5) that might be involved in tubular injury in DKD, which provide new insights and perspectives for exploring the pathogenesis and potential therapeutic targets of DKD.
目的：越来越多的证据表明，管状脂质代谢异常在糖尿病肾病（DKD）的发展中起着关键作用。我们旨在通过生物信息学方法鉴定与 DKD 管状损伤相关的新型脂质代谢相关基因。
方法：从基因表达综合数据库（GEO）中筛选出对照和 DKD 管状组织样本之间的差异表达基因（DEGs），然后与脂质代谢相关基因进行交集。通过联合加权基因相关网络分析（WGCNA）和蛋白质-蛋白质相互作用（PPI）网络进一步确定枢纽基因。我们进行了富集分析、免疫分析、聚类分析，并构建了枢纽基因与 miRNA、转录因子和小分子药物之间的网络。接收器操作特征（ROC）曲线用于评估枢纽基因的诊断效能。我们使用外部数据集和我们自己的临床样本验证了枢纽基因与 DKD 之间的关系。
结果：在 37 个脂质代谢相关 DEGs 中，有 5 个被鉴定为枢纽基因。富集分析表明，脂质代谢相关 DEGs 富集在过氧化物酶体增殖物激活受体（PPAR）信号和丙酮酸代谢等途径中。枢纽基因与多种 miRNA、转录因子和小分子药物具有潜在的调控关系，且具有较高的诊断效能。免疫浸润分析表明，在 DKD 中，有 13 种免疫细胞发生改变，枢纽基因与多种免疫细胞存在显著相关性。通过聚类分析，分别将 DKD 患者分为 3 种免疫亚型和 2 种脂质代谢亚型。通过其他外部数据集进一步验证了枢纽基因在 DKD 中的管状表达，免疫组织化学（IHC）染色显示，除 ACACB 外，其他 4 个枢纽基因（LPL、AHR、ME1 和 ALOX5）与生物信息学分析结果一致。
结论：本研究鉴定了几个关键的脂质代谢相关基因（LPL、AHR、ME1 和 ALOX5），它们可能参与了 DKD 中的管状损伤，为探索 DKD 的发病机制和潜在治疗靶点提供了新的见解和视角。
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