GWAS of Hormone Treatment and CVD and Metabolic Outcomes in the WHI

描述（由申请人提供）：早期终止的WHI激素试验（WHI- ht）的结果导致绝经后妇女在试验终止后的5年内激素使用量显著减少50%。然而，争议仍在继续，几个重要的临床和科学问题仍未解决。已知个体对药物治疗和其他干预措施的反应有很大差异，无论是在治疗效果的大小还是在不良事件的风险方面。这种药物反应的变化大多被假设为具有遗传基础。基于动物模型、观察性人体研究的先前数据，以及WHI-HT积累的候选基因、血浆生物标志物和蛋白质组学数据，雌激素和孕激素对动脉粥样硬化和代谢特征具有多因素影响。然而，控制激素治疗后血管和代谢紊乱总体风险的具体遗传因素在很大程度上是未知的。因为它需要较少的先验假设，全基因组方法可能增加识别风险变异的可能性，并可能揭示新的机制。此外，在目前的100万个SNP全基因组平台上，基因组连锁不平衡覆盖的广度和深度允许基于先前的生物学假设对候选基因进行更集中的分析和随访。因此，使用当前一代全基因组关联（GWA）技术对snp进行综合评估是筛选易感人群的下一个合乎逻辑的步骤。因此，通过本提案增加GWA基因分型研究，将大大增加使用现有流行病学数据和来自大型人群随机激素试验的生物标本的价值。我们假设，在绝经后妇女暴露于雌激素（含或不含黄体酮）后，有可能识别出可重复改变血管事件（冠心病、中风和静脉血栓栓塞）和糖尿病风险的常见变异。

DESCRIPTION (provided by applicant): The results of the early-terminated WHI hormone trials (WHI-HT) led to a dramatic 50% reduction in hormone use by post-menopausal women in the ensuing 5 years since the trial was terminated. Yet, controversy persists, and several important clinical and scientific questions remain unresolved. Individuals are known to vary considerably in response to drug therapy and other interventions, both in magnitude of treatment effect and in risk of adverse events. Much of this variation in drug response has been hypothesized to have a genetic basis. Based on previous data from animal models, observational human studies, and accruing candidate gene and plasma biomarker and proteomic data from WHI-HT, estrogen and progesterone have multi-factorial effects on atherosclerotic and metabolic traits. Nonetheless, the specific genetic factors that govern the overall risk of vascular and metabolic disorders in response to hormone therapy are largely unknown. Because it requires fewer a priori assumptions, a genome-wide approach may increase the likelihood of identifying risk variants and may reveal novel mechanisms. Moreover, the breadth and depth of genomic linkage disequilibrium coverage on current 1 million SNP whole-genome platforms allow for more focused analysis and follow-up of candidate genes based on prior biologic hypotheses. Therefore, a comprehensive evaluation of SNPs using current generation genome-wide association (GWA) technology is the next logical step to screening susceptible populations. As such, the value of using existing epidemiologic data and biologic specimens from the large, population-based randomized hormone trials of WHI will be substantially increased by the addition of GWA genotyping studies through this proposal. We hypothesize that it is possible to identify common variants that reproducibly alter risk of vascular events (CHD, stroke, and VTE) and diabetes after exposure to estrogen with or without progestin in postmenopausal women. Public Health Relevance: Information generated from this study will be critical to determine the health impact of genetic variants on the balance of benefits and risks associated with hormone therapy in post-menopausal women. Findings may also provide valuable insights into disease pathways and mechanisms, and identify novel targets for disease screening, prevention, and treatment of cardiovascular events and diabetes in women.