Research Project
10300830
Abstract Alzheimer's disease (AD) is a highly heterogeneous multifactorial disease. Genetic influences on AD are strong as shown by several pathogenic genes and over 50 AD loci identified through genome-wide association studies (GWAS). There are also clear sex differences in AD risk and progression. Women are at a higher risk of developing AD and present faster progression. A recent GTEx study also highlights sex differences in the genetic regulation of gene expression. Despite these established sex differences, sex-specific molecular findings in AD are still limited. The objective of this study is therefore to generate detailed sex-specific multi- tissue molecular profiles of AD and decipher the genetic architecture that underlies AD. We propose to identify sex-specific functional mechanisms underlying the genetic architecture of AD. We will generate multiple layers of -omics data, including DNA methylation, gene expression, proteomics, metabolomics, and lipidomics, from several large and well characterized studies. A series of well-powered sex-specific omics characterization across multiple tissues can help identify novel drug targets and provide critical insights for clinically translatable interventions for prevention and treatment. We will then map additional GWAS loci by performing sex-specific multi-omic quantitative trait loci and co-localization for each -omic layers. We will identify the causal genes, proteins, and additional -omic analytes by performing Mendelian randomization. Analyzing such omics data will elucidate a causal path from sex-specific genetic variation to AD risk, onset and progression. The human multi- omic data will finally be combined with induced pluripotent stem cell (iPSC) models to identify novel sex- specific FDA-approved therapeutics. We have assembled a very productive and interdisciplinary research team with expertise in all the aspect of the proposal. All aims in this proposal will be conducted and reported in compliance with NIH guidance on scientific rigor and reproducibility. Our preliminary data already identified several genes and proteins that are associated with AD risk and cerebrospinal fluid biomarkers in a sex- specific manner. All the raw data will be shared via NIA-approved mechanism (including AD Knowledge Portal, NIAGADS). This rich resource will benefit the field for additional analyses beyond the ones proposed here.
