Dai Yuheng, Lu Sha, Hu Wensheng
Department of Obstetrics Hangzhou Women's Hospital (Hangzhou Maternity and Child Health Care Hospital) Hangzhou People's Republic of China.
Department of Obstetrics, Women's Hospital, School of Medicine Zhejiang University Hangzhou People's Republic of China.
Health Sci Rep. 2024 Oct 7;7(10):e70115. doi: 10.1002/hsr2.70115. eCollection 2024 Oct.
Gestational diabetes mellitus (GDM) is characterized by glucose intolerance that occurs during pregnancy. This study aimed to identify key ubiquitination-related genes associated with GDM pathogenesis.
Microarray data from GSE154377 was analyzed to identify differentially expressed genes (DEGs) in GDM vs normal pregnancy samples. Weighted gene co-expression network analysis was performed on ubiquitination-related genes. Functional enrichment, protein-protein interaction network, and TF-mRNA-miRNA interaction network analyses were conducted on differentially expressed ubiquitination-related genes (DE-URGs).
We identified 2337 DEGs and 65 DE-URGs in GDM. Functional enrichment analysis of the 65 DE-URGs revealed involvement in protein ubiquitination and ubiquitin-dependent catabolic processes. Protein-protein interaction network analysis identified 8 hub genes, including MAP1LC3C, USP26, USP6, UBE2U, USP2, USP43, UCHL1, and USP44. ROC curve analysis showed these hub genes have high diagnostic accuracy for GDM (AUC > 0.6). The TF-mRNA-miRNA interaction network suggested USP2 and UCHL1 may be key ubiquitination genes in GDM.
In conclusion, this study contributes to our understanding of the molecular landscape of GDM by uncovering key ubiquitination-related genes. These findings may serve as a foundation for further investigations, offering potential biomarkers and therapeutic targets for clinical applications in GDM management.
妊娠期糖尿病(GDM)的特征是孕期出现糖耐量异常。本研究旨在鉴定与GDM发病机制相关的关键泛素化相关基因。
分析来自GSE154377的微阵列数据,以鉴定GDM与正常妊娠样本中的差异表达基因(DEG)。对泛素化相关基因进行加权基因共表达网络分析。对差异表达的泛素化相关基因(DE-URG)进行功能富集、蛋白质-蛋白质相互作用网络和TF-mRNA-miRNA相互作用网络分析。
我们在GDM中鉴定出2337个DEG和65个DE-URG。对65个DE-URG的功能富集分析显示其参与蛋白质泛素化和泛素依赖性分解代谢过程。蛋白质-蛋白质相互作用网络分析鉴定出8个枢纽基因,包括MAP1LC3C、USP26、USP6、UBE2U、USP2、USP43、UCHL1和USP44。ROC曲线分析表明,这些枢纽基因对GDM具有较高的诊断准确性(AUC > 0.6)。TF-mRNA-miRNA相互作用网络表明USP2和UCHL1可能是GDM中的关键泛素化基因。
总之,本研究通过揭示关键的泛素化相关基因,有助于我们了解GDM的分子格局。这些发现可为进一步研究提供基础,为GDM管理的临床应用提供潜在的生物标志物和治疗靶点。