Genome-wide meta-analysis of polycystic ovary syndrome using GSA

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder in females of reproductive age. It is characterized by hyperandrogenism (HA), ovulatory dysfunction (OD) and polycystic ovary morphology (PCOM). PCOS is diagnosed based on two different sets of diagnostic criteria, resulting in a heterogeneous population. Using the diagnostic Rotterdam criteria, four different phenotypes can be identified: (A) OD, HA and PCOM; (B) OD and HA; (C) OD and PCOM; and (D) HA and PCOM. Of these four phenotypes, phenotype A and B are considered the most severe phenotypes, presenting with more pronounced menstrual dysfunction and the highest risk for metabolic syndrome. 
Genetic predisposition and environmental exposure are thought to play a major role in the pathophysiology of PCOS. Familial clustering of PCOS and its associated symptoms have been well established and its heritability was estimated as ~65%. Yet, the exact pathophysiological mechanisms remain to be unraveled. Recently published genetic studies have identified several PCOS-associated polymorphisms located in coding and non-coding regions in regulatory regions of genes associated with reproduction. This suggests a different regulation of these genes in patients with PCOS. Moreover, as being part of the international PCOS consortium, we participated in a large-scale genome wide association study analyzing ~10,000 PCOS cases and ~100,000 controls from seven different cohorts. This study identified novel loci associated with PCOS across all phenotypic criteria. However, the exact mechanisms of the different gene regulatory networks between PCOS patients and normo-ovulatory women remain to be unraveled. Therefore, the current research project aims to identify novel PCOS-specific loci across different genotypes. This research project is a follow-up study from the previously published large-scale meta-analysis including a larger sample of PCOS cases and controls.