Integration of Socio-Spatial Data for Neighborhoods with Multi-omic profiles to Identify and Mitigate Factors Affecting Risk of ALzheimer's Disease

点击翻译按钮获取中文摘要

Alzheimer’s disease (AD) affects a higher proportion of Hispanics - the fastest growing group of older adults in the U.S. - than Caucasians, and at younger ages. The causes of these differences are unknown, partly due to underrepresentation of Hispanics in AD research. Uncovering the reasons for this disparity may provide insight into the causes of AD and help to develop solutions and is this project's goal. Robust findings have linked the social and physical characteristics of neighborhoods to cognitive health, and the neighborhood - el barrio - is known to be important to Hispanic populations. However, identifying specific contextual and individual factors that affect risk of AD is a complex problem. This project aims to determine the effects of neighborhood factors on AD-like cognitive trajectories in Hispanic Americans, by a novel approach that integrates 1) individual differences revealed by high-dimensional multi-omics (genetic and metabolic molecular markers) and 2) mediation/moderation by family and neighborhood dynamics. Our access to a Mexican American cohort - the San Antonio Mexican American Family Study (SAFS) - will enable us to test if variations in AD-like cognitive trajectories across neighborhoods are explained exclusively by individual characteristics, or depend at least partly on social and physical elements of neighborhoods. SAFS participants have been deeply characterized for almost 30 years, including clinical (cardiometabolic and cognitive trajectories), structural neuroimaging, and environmental data; whole-genome sequencing (WGS), and other -omics (e.g., metabolic profiles, epigenomics, protein and RNA expression patterns). The specific aims of this project are to 1) determine if familism provides protection from AD-like cognitive decline compared to non-AD like cognitive decline in Mexican Americans; 2) analyze the associations between social and built environments of different neighborhoods and AD-like cognitive trajectories, by using online street imagery analysis of 17 neighborhoods within each of which at least 30 SAFS participants reside; 3) detect environmental (social and spatial) signals at neighborhood and family levels, reflected in any high-dimensional metabolomic/lipidomic, epigenomic, and transcriptomic biomarkers we find correlated with risk of AD-like cognitive decline; and 4) exploit the results to provide guidance for neighborhood-based projects aimed at decreasing the risk of AD-like cognitive decline, by developing a strategic communication toolkit, and convening a forum that will engage diverse stakeholders, particularly neighborhood designers and city planners. Overall, the results will elucidate pathways through which neighborhood-specific factors contribute to AD-like cognitive decline in Hispanics, offering new approaches to mitigation of AD.