Genome-Wide Association Scan of Polycystic Ovary Syndrome Phenotypes

点击翻译按钮获取中文摘要

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder of premenopausal women, affecting ~7% of this population. It has major reproductive and metabolic morbidities across the lifespan, including markedly increased prevalence rates of obesity, type 2 diabetes (T2D), metabolic syndrome (MBS) and other cardiovascular disease (CVD) risk factors. It has been estimated that ~25% of premenopausal women with T2D have PCOS, making it perhaps the most common T2D subphenotype. The features of PCOS cluster within families providing evidence that genetic variation contributes to their pathogenesis. Indeed, male as well as female first-degree relatives have reproductive and metabolic phenotypes. Further, the cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the etiology of the associated metabolic abnormalities. Thus, although PCOS overlaps with obesity and T2D, its unique phenotypic features raise the fundamental question: Is PCOS a genetically distinct disorder or do the same obesity/T2D susceptibility genes interact with additional genetic or environmental factors resulting in the PCOS phenotype? We have already identified one PCOS susceptibility allele within a dinucleotide repeat (D19S884) in intron 55 of the fibrillin-3 gene on chromosome 19p13.2 that is linked and associated with hyperandrogenemia. This allele is also associated with metabolic phenotypes in affected women and their brothers. Fibrillin-3 has not been previously implicated as a T2D susceptibility gene suggesting that genetic analyses of PCOS may identify novel T2D genes. Genome-wide association studies (GWAS) should provide more power than linkage mapping studies for localizing PCOS susceptibility genes. We have assembled an investigative team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including GWAS. We have a large cohort of extensively and consistently phenotyped PCOS cases. We will employ GWAS to identify PCOS susceptibility alleles in ~1,200 PCOS cases and ~3,600 unselected population-based female controls. These control cohorts have phenotypes such as BMI available. Promising variants will be further investigated using replication studies of the 1536 most promising SNPs in an independent cohort of ~1,800 PCOS cases and ~5,400 unselected female controls. This project promises to identify not only susceptibility genes for PCOS, hyperandrogenemia and infertility but also novel risk loci for T2D, MBS and CVD. This information should lead to more effective and specific treatments as well as to disease prediction and prevention.