诊断学理论与实践

诊断学理论与实践 ›› 2025, Vol. 24 ›› Issue (01): 27-34.doi: 10.16150/j.1671-2870.2025.01.005

• 论著 • 上一篇    下一篇

细胞失巢相关基因PDK4与2型糖尿病发病相关——基于生物信息的研究

张珂, 张唯一, 孙海天, 曹铭峰, 张新焕()   

  1. 山东第一医科大学第二附属医院内分泌科，山东 泰安 271000
  • 收稿日期:2024-11-12 接受日期:2025-02-08 出版日期:2025-02-25 发布日期:2025-02-05
  • 通讯作者: 张新焕 E-mail：kathy0418@163.com
  • 基金资助:
    山东省医药卫生科技项目(202303060522)

Anoikis-related gene PDK4 and pathogenesis of type 2 diabetes mellitus： A bioinformatics-based study

ZHANG Ke, ZHANG Weiyi, SUN Haitian, CAO Mingfeng, ZHANG Xinhuan()   

  1. Department of Endocrinology, Second Affiliated Hospital of Shandong first medical university, Taian 271000, China
  • Received:2024-11-12 Accepted:2025-02-08 Published:2025-02-25 Online:2025-02-05

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摘要：

目的 采用生物信息学分析来确定胰岛组织中参与2型糖尿病（type 2 diabetes mellitus， T2DM）发病的失巢凋亡（anoikis）相关基因及免疫浸润情况。方法 从基因表达综合数据库（Gene Expression Omnibus， GEO）下载数据集GSE76894作为训练集，对训练集中T2DM和非糖尿病胰岛组织基因表达进行差异分析，并与失巢凋亡基因集取交集，得到失巢凋亡相关差异表达基因（differentially expressed genes， DEGs），后通过随机森林（randomforest， RF）和最小绝对收缩和选择算法（least absolute shrinkage and selection operator， LASSO）算法识别关键基因。绘制受试者操作特征（receiver operating characteristic，ROC）曲线，并计算曲线下面积（area under the curve，AUC），以评估筛选出的关键基因在胰岛组织中的表达水平与T2DM间的关联强度，并在验证集GSE76895中进行验证。接下来，对鉴定的关键基因进行蛋白互作网络（protein-protein interaction， PPI）和基因本体论（Gene Ontology， GO）富集分析。最后，利用CIBERSORT算法进行免疫浸润分析。结果 通过差异分析得到了8个失巢凋亡相关DEGs，其中6个基因上调，2个基因下调。后续通过2种机器学习算法确定了4个关键基因，分别是PDK4、BMF、ITGB1和SNAI2，ROC曲线显示，验证集GSE76895中，只有PDK4的表达显示出较强的区分能力（AUC = 0.721），提示PDK4的表达水平与T2DM存在较显著的关联。富集分析显示，这些基因主要富集在整合素介导的细胞黏附、脂质生物合成过程的调控、整合素复合物、胶质细胞突起等条目。免疫浸润分析表明，在T2DM与正常人胰岛组织中有多种免疫细胞存在差异表达，且PDK4表达与M0巨噬细胞呈负相关。结论 PDK4在T2DM患者胰岛组织中表达下调，且与M0巨噬细胞表达量成负相关，提示PDK4表达在一定程度上与T2DM的免疫失调所致发病相关，提示PDK4可能与T2DM免疫失调发病相关。

关键词: 2型糖尿病, 失巢凋亡, 生物信息学

Abstract:

Objective To identify anoikis-related genes and immune infiltration characteristics in pancreas islet tissues involved in the pathogenesis of type 2 diabetes mellitus (T2DM) using bioinformatic analysis. Methods The dataset GSE76894 was downloaded from the Gene Expression Omnibus (GEO) database as the training set. Diffe-rential gene expression analysis was conducted on T2DM and non-diabetic islet tissues within the training set, and intersected with the anoikis-related gene set to obtain anoikis-related differentially expressed genes (DEGs). Subsequently, key genes were identified using the random forest (RF) and least absolute shrinkage and selection operator (LASSO) algorithms. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to evaluate the association strength between the expression levels of the identified key genes in pancreas islet tissues and T2DM, followed by validation in the GSE76895 dataset. Protein-protein interaction (PPI) network analysis and gene ontology (GO) enrichment analysis were then performed on the identified key genes. The immune infiltration analysis was conducted using the CIBERSORT algorithm. Results Differential analysis identified 8 anoikis-related DEGs, with 6 upregulated and 2 downregulated genes. Subsequent application of two machine lear-ning algorithms identified 4 key genes: PDK4, BMF, ITGB1, and SNAI2. ROC analysis showed that in the validation set (GSE76895), only PDK4 expression had strong discriminatory power (AUC = 0.721), indicating a significant association with T2DM. Enrichment analysis demonstrated that these key genes were primarily enriched in terms related to integrin-mediated cell adhesion, regulation of lipid biosynthetic processes, integrin complex, and glial cell protrusions. Immune infiltration analysis indicated differential expression of various immune cells in the pancreas islet tissues of T2DM and healthy individuals. Furthermore, PDK4 expression was negatively correlated with that of M0 macrophages. Conclusions PDK4 is downregulated in T2DM islet tissues and negatively correlated with M0 macrophage expression levels, suggesting that the expression of PDK4 is related to the T2DM pathogenesis caused by immune dysregulation to some extent.

Key words: Type 2 diabetes mellitus, Anoikis, Bioinformatics

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