Here we propose a comprehensive program to dissect the underlying disease-causing mechanisms of PCOS and associated comorbidities. We will investigate how the different layers of biological information (ranging from DNA variant genotyping, to RNA sequencing and proteomics), and clinical characteristics are correlated with each other and how this affects PCOS in fat tissue derived cells, as well as ovarian tissue and tissue derived cells by using a combination of big data analysis, a range of -omics technologies, of both in-house generated and publicly available data, paired with state of the art statistical and bioinformatics analysis. Out of these mechanisms and pathways we will identify druggable targets for proposals for detailed functional follow up with an aim of development of novel therapeutic options for PCOS.
This is a prospective observational study that aims to identify the underlying mechanisms of PolyCystic Ovarian Syndrome (PCOS) and associated comorbidities such as subfertility, miscarriage; and pregnancy complications such as gestational diabetes mellitus and Intrahepatic cholestasis of pregnancy (ICP). This will be achieved through cross-sectional observation and laboratory analyses.