Presentation summary

Introduction :
Polycystic ovary syndrome (PCOS) is one of the most prevalent endocrine disorder, also knownas Stein–Leventhal syndrome. This heterogeneous disorder is typically characterized by anovulation, infertility,obesity, insulin resistance, and polycystic ovaries, which after those vary depend on patient’s symptomphenotypes. Our study aims to design newly network medicine by focusing on symptoms rather than diseasefor PCOS.

Method :
A curated list of PCOS-specific symptom-associated genes was collected from GeneCards opendatabase and analyzed with the network centrality metrics such as degree, betweenness, closeness, andedged and linked eigenvector. The overlapped top 5% scored core genes were found and validated using theGEO dataset GSE48301, which analyzes ‘Polycystic ovary syndrome: proliferative phase endometrial celltypes’. Apart from that, molecular targeting gene, protein and enzymes of Food and Drug Administration (FDA)-approved drugs for PCOS were identified between the core genes to evaluate therapeutic proximity. Then,topologically central core genes were further subjected to enrichment analysis.

Results :
The genes, which were found based on the network centrality from disease-related symptom,exhibited differential expression in PCOS patient samples. Apparently, some of them were significantly up-regulated, while some were down-regulated in the PCOS group. In addition, the enrichment analysis of a set of11 key associated genes showed regulation of programmed cell death, epithelial cell proliferation, oocytemeiosis and ovarian steroidogenesis. The target genes derived from FDA-approved drugs were highlyconnected within the symptom-related gene network.

Conclusion :
This study suggests an integrating network pharmacology with gene expression analysis identifiedthe core network of disease-related symptoms in PCOS. Through those approach, the central hub gene couldprovide a framework for development of network medicine.