Eur Rev Med Pharmacol Sci 2023; 27 (8): 3255-3269

DOI: 10.26355/eurrev_202304_32097

J. Zhang, F.-J. Zhang, L. Zhang, D.-X. Xian, S.-A. Wang, M. Peng, Y. Liu

Department of Pediatrics, Shandong Second Provincial General Hospital, Jinan, China. liuyuanly0429@126.com

OBJECTIVE: Type 2 diabetes mellitus (T2DM) and polycystic ovary syndrome (PCOS) are highly prevalent endocrine system diseases. However, studies on the molecular mechanisms of T2DM and PCOS at the transcriptomic level are still few. Thus, we aimed to reveal the potential common genetic and molecular pathways between T2DM and PCOS via bioinformatics analyses.

MATERIALS AND METHODS: We downloaded the GSE10946 and GSE18732 datasets for T2DM and PCOS, respectively, from the National Center for Biotechnology Information’s Gene Expression Omnibus (GEO) database. These datasets were subjected to integrated differential and weighted gene co-expression network analyses (WGCNA) to screen common genes. Thereafter, functional enrichment and disease gene association analyses were performed, transcription factor (TF)-gene and TF-miRNA-gene regulatory networks were constructed, and finally, the relevant target drugs were identified.

RESULTS: We identified common genes (BIRC3, DEPTOR, TNNL3, ADRA2A) in T2DM and PCOS. Pathway enrichment analysis depicted that the common genes were enriched in smooth muscle contraction, channel inhibitor activity, apoptosis, and tumor necrosis factor (TNF) signaling pathways. TFs such as SP7, KLF8, HCFC1, IRF1, and MLLT1 played key roles in TF regulatory networks. Orlistat was indicated to be an important gene-targeting drug.

CONCLUSIONS: This study is the first study to explore four diagnostic biomarkers and gene regulatory networks for T2DM and PCOS. The findings of our study provide novel insights into the diagnosis and treatment of T2DM and PCOS.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

J. Zhang, F.-J. Zhang, L. Zhang, D.-X. Xian, S.-A. Wang, M. Peng, Y. Liu
Identification of key genes and molecular pathways in type 2 diabetes mellitus and polycystic ovary syndrome via bioinformatics analyses

Eur Rev Med Pharmacol Sci
Year: 2023
Vol. 27 - N. 8
Pages: 3255-3269
DOI: 10.26355/eurrev_202304_32097