Leveraging omics data to understand sleep health and its consequences among diverse Hispanics/Latinos - 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 cardiovascular risk factors, 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 from multiple Latino backgrounds (Mexican, South American, Central American, Cuban, Dominican, and Puerto Rican). We oversaw the collection and analysis of sleep measures during its baseline exam. Along with our colleagues, we identified a high prevalence of sleep disorders which varied in frequency by social and behavioral factors and Latino background, and associated with incident DM, HTN, and cognitive decline and impairment. In this project we will apply an integrative and multi-disciplinary research to study biological mechanisms that result in sleep health-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 will link some of them to modifiable lifestyle and sociocultural measures. Second, we will develop metabolomics and methylation biomarkers of sleep by combining information across multiple makers. We will study the association 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 development of public health interventions at the community level (e.g., addressing strategies to improve sleep health) and at the personal level: by identifying individuals who will benefit most from improving their sleep, for example, according to their genetics or metabolomics profile.
