Zhu Yidong, Liu Jun, Wang Bo
Department of Traditional Chinese Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, People's Republic of China.
Department of Endocrinology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, 200090, People's Republic of China.
Diabetes Metab Syndr Obes. 2025 Jan 31;18:267-282. doi: 10.2147/DMSO.S503449. eCollection 2025.
Type 2 diabetes mellitus (T2DM) is associated with an increased risk of non-Hodgkin lymphoma (NHL), but the underlying mechanisms remain unclear. This study aimed to identify potential biomarkers and elucidate the molecular mechanisms underlying the co-pathogenesis of T2DM and NHL.
Microarray datasets of T2DM and NHL were downloaded from the Gene Expression Omnibus database. Subsequently, a protein-protein interaction network was constructed based on the common differentially expressed genes (DEGs) between T2DM and NHL to explore regulatory interactions. Functional analyses were performed to explore underlying mechanisms. Topological analysis and machine learning algorithms were applied to refine hub gene selection. Finally, quantitative real-time polymerase chain reaction was performed to validate hub genes in clinical samples.
Intersection analysis of DEGs from the T2DM and NHL datasets identified 81 shared genes. Functional analyses suggested that immune-related pathways played a significant role in the co-pathogenesis of T2DM and NHL. Topological analysis and machine learning identified three hub genes: , and . Correlation analysis revealed significant correlations between these hub genes and immune cells, underscoring the importance of immune dysregulation in shared pathogenesis. The expression of these genes was successfully validated in clinical samples.
This study suggested the pivotal role of immune dysregulation in the co-pathogenesis of T2DM and NHL and identified and validated three hub genes as key contributors. These findings provide insight into the complex interplay between T2DM and NHL.
2型糖尿病(T2DM)与非霍奇金淋巴瘤(NHL)风险增加相关,但潜在机制仍不清楚。本研究旨在识别潜在生物标志物,并阐明T2DM和NHL共同发病机制的分子机制。
从基因表达综合数据库下载T2DM和NHL的微阵列数据集。随后,基于T2DM和NHL之间的共同差异表达基因(DEG)构建蛋白质-蛋白质相互作用网络,以探索调控相互作用。进行功能分析以探索潜在机制。应用拓扑分析和机器学习算法优化枢纽基因选择。最后,进行定量实时聚合酶链反应以验证临床样本中的枢纽基因。
T2DM和NHL数据集的DEG交叉分析确定了81个共享基因。功能分析表明,免疫相关途径在T2DM和NHL的共同发病机制中起重要作用。拓扑分析和机器学习确定了三个枢纽基因: 、 和 。相关性分析揭示了这些枢纽基因与免疫细胞之间的显著相关性,强调了免疫失调在共同发病机制中的重要性。这些基因的表达在临床样本中得到成功验证。
本研究表明免疫失调在T2DM和NHL共同发病机制中起关键作用,并确定并验证了三个枢纽基因作为关键因素。这些发现为T2DM和NHL之间的复杂相互作用提供了见解。