Leveraging Correlated Traits to Identify Genetic Associations with Sleep Disordered Breathing

项目摘要/摘要 睡眠呼吸紊乱(SDB)是一种复杂的疾病，在人群中很常见，并与 有严重的不良健康后果。尽管有相当大的遗传性，但对遗传病的遗传基础的阐明 这种疾病仅限于相对较小的样本--由于诊断不足和报告不足 以及缺乏对SDB性状的隔夜测量--以及潜在的异质性。鉴于SDB是 在生理和新陈代谢上与其他特征相关，有机会增加 利用相关的大关联研究对SDB性状进行相对较小的遗传关联研究 特征。使用相关性状也将有助于识别由这些性状捕获的SDB机制，如 在遗传水平上解释SDB异质性的第一步。因此，我们建议利用 与SDB相关的性状的遗传关联以剖析SDB的遗传决定机制， 它们可归因于不同的分子/生理途径，并被不同的性状捕获。 我们将采取两种方法。首先，我们将研究多个基因之间的相关性 夜间测量的最大队列中的心肺和代谢特征以及SDB特征 SDB特征，拉美裔社区健康研究/拉美裔研究。基于这些关联，我们将 从之前与相关性状相关的那些基因座中找出与SDB相关的遗传位点。 第二，我们将研究和实施基于多基因风险分数(PRSS)的方法， 不同的NHLBI队列。我们将使用以前已知的关联来为检测到的 相关性状，并研究它们与SDB性状的关系。我们将使用以下工具实现因果分析 最近提出的孟德尔随机化方法论在多效性存在的情况下研究是否 体重指数、血压、血脂异常和胰岛素抵抗等特征与SDB有因果关系。 这些分析将揭示SDB的特定遗传决定机制，为 最终目标是确定疾病的亚型，从而开发个性化治疗

PROJECT SUMMARY/ABSTRACT Sleep Disordered Breathing (SDB) is a complex disorder that is common in the population and is associated with significant adverse health outcomes. Despite considerable heritability, elucidation of the genetic basis of this disorder has been limited by relatively small samples - due to under diagnosis and under reporting of SDB, and paucity of overnight measurements of SDB traits - and potential heterogeneity. Given that SDB is physiologically and metabolically related to other traits, there is an opportunity to increase power in the relatively-small genetic association studies of SDB traits by leveraging large association studies in correlated traits. Using correlated traits will also be useful for identifying SDB mechanisms captured by these traits, as a first step in explaining, at the genetic level, the heterogeneity of SDB. Therefore, we propose to utilize genetic associations for traits that correlate with SDB to dissect genetically-determined mechanisms of SDB, that are attributable to different molecular/physiological pathways, and are captured by different traits. We will take two approaches. First, we will study the genetic correlations between multiple cardiopulmonary and metabolic traits and SDB traits in the largest cohort with overnight measurements of SDB traits, the Hispanic Community Health Study/Study of Latinos. Based on these correlations, we will identify genetic loci associated with SDB from those that were previously implicated with the correlated traits. Second, we will study and implement approaches based on Polygenic Risk Scores (PRSs) in multiple, diverse, NHLBI cohorts. We will use previously known associations to construct PRSs for the detected correlated traits, and study their association with SDB traits. We will implement causal analyses using recently proposed methodologies of Mendelian Randomization in the presence of pleiotropy to study whether traits such as BMI, blood pressure, dyslipidemia, and insulin resistance are causally associated with SDB. These analyses will reveal specific genetically-determined mechanisms of SDB, setting the foundation for the ultimate goal of identifying subtypes of the disorder and consequently developing personalized therapies