Bioinformatics probe reveals early onset ovarian insufficiency associated with impaired PEDF and VEGF balance

Abstract

Objective

To screen the key genes of patients with premature ovarian insufficiency (POI) by bioinformatics analysis, study the pathological mechanism of POI and predict the potential therapeutic targets.

Methods

The WGCNA algorithm was used to establish a weighted gene co-expression network, and the data downloaded from the GEO database was used to identify the relevant hub genes of premature ovarian insufficiency (GSE39501), and the relevant genes of premature ovarian insufficiency downloaded from the HMDD database were intersected to identify the key genes using Cytoscape and verified for their differential expression by QRT-PCR and Western Blot (WB) to verify their differential expression.

Results

A total of 20 expression modules were identified by WGCNA, and the Firebricks module was found to be highly correlated with premature ovarian insufficiency after correlation coefficient screening. 1666 up-regulated genes and 1617 down-regulated genes were screened by differential analysis in the GSE39501 dataset, and a total of 12 co-expressed genes were localized after taking the intersections with related genes in the POI of the HMD database, which were validated by QRT PCR and Western Blot (WB). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and found that they mainly affect the MAPK signaling pathway and VEGF signaling pathway. The top three key genes, VEGFB, PEDF and SERP1NF1, were then localized by Cytoscape, and finally the opposite expression trends of VEGF and PEDF were verified by WB and QRT-PCR experiments.

Conclusion

The key genes VEGFB, PEDF and SERP1NF1 may be the potential biological markers of POI, and the imbalance of PEDF and VEGF may lead to the development of POI, which needs to be verified by further experiments.