Shim Unjin, Kim Han-Na, Lee Hyejin, Oh Jee-Young, Sung Yeon-Ah, Kim Hyung-Lae

Department of Internal Medicine, Seoul Seonam Hospital, Ewha Womans University Medical Center, Seoul, Korea.| Department of Biochemistry, Ewha Womans University School of Medicine, Seoul, Korea.| Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Korea.| Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Korea.| Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Korea.| Department of Biochemistry, Ewha Womans University School of Medicine, Seoul, Korea.

PLoS One. 2015 Aug 26;10(8):e0136609. doi: 10.1371/journal.pone.0136609.

BACKGROUND: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age, and it is affected by both environmental and genetic factors. Although the genetic component of PCOS is evident, studies aiming to identify susceptibility genes have shown controversial results. This study conducted a pathway-based analysis using a dataset obtained through a genome-wide association study (GWAS) to elucidate the biological pathways that contribute to PCOS susceptibility and the associated genes.
METHODS: We used GWAS data on 636,797 autosomal single nucleotide polymorphisms (SNPs) from 1,221 individuals (432 PCOS patients and 789 controls) for analysis. A pathway analysis was conducted using meta-analysis gene-set enrichment of variant associations (MAGENTA). Top-ranking pathways or gene sets associated with PCOS were identified, and significant genes within the pathways were analyzed.
RESULTS: The pathway analysis of the GWAS dataset identified significant pathways related to oocyte meiosis and the regulation of insulin secretion by acetylcholine and free fatty acids (all nominal gene-set enrichment analysis (GSEA) P-values < 0.05). In addition, INS, GNAQ, STXBP1, PLCB3, PLCB2, SMC3 and PLCZ1 were significant genes observed within the biological pathways (all gene P-values < 0.05).
CONCLUSIONS: By applying MAGENTA pathway analysis to PCOS GWAS data, we identified significant pathways and candidate genes involved in PCOS. Our findings may provide new leads for understanding the mechanisms underlying the development of PCOS.