Leveraging omics data to understand sleep health and its consequences among diverse Hispanics/Latinos

项目总结 拉美裔/拉丁裔是美国增长最快的人口群体，预计将占美国人口的24% 到2060年人口增长。拉美裔人的健康差距很大，包括糖尿病的沉重负担 糖尿病(DM)、失控高血压(HTN)、肥胖、阿尔茨海默病和血管性痴呆。 西班牙裔社区健康研究/拉丁裔社区健康研究(HCHS/SOL)是一项纵向队列研究 2004年，在来自四个地理区域和多种拉丁裔背景的约16,500名美国拉丁裔之后(墨西哥， 南美洲、中美洲、古巴、多米尼加和波多黎各)。我们监督了收藏品的收集 HCHS/SOL基线检查期间的睡眠测量分析。与我们的同事们一起，我们确定了一个 睡眠障碍患病率高，因社会和行为因素以及拉丁裔背景而异，以及 与糖尿病、HTN、认知功能减退和损害有关。 该项目将应用综合和多学科的研究方法来研究 导致与睡眠相关的糖尿病、HTN和不同拉丁裔人认知能力下降的风险。首先，我们将确定 甲基化和代谢组学测量与睡眠表型相关，并从生物学角度对其进行表征。 我们进一步确定了这些组学措施中与可改变的生活方式和社会文化相关的子集 措施。第二，我们将开发睡眠的代谢组学和甲基化生物标记物 跨多个标记的信息。我们将研究这些生物标志物与事件结果的关联。 (DM、HTN、认知功能减退和功能障碍)。第三，我们将评估睡眠表型对 使用与睡眠相关的基因交互分析修改糖尿病、HTN和认知结果的遗传风险 每种结局的多基因风险评分。我们还将进行多组学分析，合成多个组学 了解生物途径的措施。最后，我们将应用因果分析来量化潜在的 潜在干预措施可降低糖尿病、HTN以及认知功能减退和损害的风险 睡眠表型，假设代谢组学和遗传途径可以被阻断。我们会 估计这些影响的总和和整个拉丁裔背景。我们的工作将导致 社区公共卫生干预--(例如，在墨西哥裔拉美人中)和病人一级，通过确定 将从改进中获益最多的个人(例如，基于特定的遗传或代谢特征) 他们的睡眠。

PROJECT SUMMARY Hispanics/Latinos are the fastest growing demographic group in the U.S., expected to comprise 24% of the US population by 2060. Latinos experience high rates of health disparities, including a high burden of diabetes mellitus (DM), uncontrolled hypertension (HTN), obesity, and Alzheimer's Disease and vascular dementias. The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a longitudinal cohort study established in 2004, following ~16,500 US Latinos from four geographic areas and multiple Latino backgrounds (Mexican, South American, Central American, Cuban, Dominican, and Puerto Rican). We oversaw the collection and analysis of sleep measures during the HCHS/SOL baseline exam. Along with our colleagues, we identified a high prevalence of sleep disorders which varied by social and behavioral factors and Latino background, and were associated with incident DM, HTN, and cognitive decline and impairment. This project will apply integrative and multi-disciplinary research methods to study biological mechanisms that result in the sleep-related risk of DM, HTN, and cognitive decline across diverse Latinos. First, we will identify methylation and metabolomics measures associated with sleep phenotypes and characterize them biologically. We further identify a subset of these omics measures that are linked to modifiable lifestyle and sociocultural measures. Second, we will develop metabolomics and methylation biomarkers of sleep by combining information across multiple markers. We will study the association of such biomarkers with incident outcomes (DM, HTN, cognitive decline and impairment). Third, we will estimate the effect of sleep phenotypes on modifying genetic risks for DM, HTN, and cognitive outcomes using a gene-by-sleep interaction analysis with polygenic risk scores for each outcome. We will also perform multi-omics analyses synthesizing multiple omics measures to understand biological pathways. Finally, we will apply causal analysis to quantify the potential reduction in risks of incident DM, HTN, and cognitive decline and impairment following potential intervention on sleep phenotypes, under the assumption that metabolomics and genetic pathways can be blocked. We will estimate these effects in aggregate and across Latino backgrounds. Our work will lead to the development of public health interventions at the community-(e.g., in Latinos of Mexican origin) and patient-level by identifying individuals (e.g., based on specific genetic or metabolomic profiles) who would benefit most from improving their sleep.