Integrative Genomic Approaches for Understanding Sex Differences in Alzheimer's Disease

项目总结

Project Summary Women make up nearly two-thirds of all Alzheimer's disease (AD) cases in the United States and these differences are likely due to contributions from differential genetic and environmental effects between the sexes. While several candidate gene studies have identified sex-specific associations, no large-scale, genome- wide, sex-specific association analysis of AD has been conducted. Furthermore, the functional underpinnings of sex-specific genetic associations and how they relate to expression and epigenetic variations, are still largely unknown. We hypothesize that multiple genetic, epigenetic and gene-expression changes operate in a sex-specific manner to explain at least part of the sex disparity in AD prevalence. To this end, we propose new strategies for integrative analysis of DNA variants, gene expression, splicing and DNA methylation in a sex- aware framework, which will allow us to prioritize variants with the most regulatory potential and provide additional insight into the biological mechanisms of sex differences in AD. To accomplish these goals we will leverage existing large-scale genetic data from several consortia studies in AD, as well as expression and methylation data from brain tissue of AD cases and healthy individuals. We propose the following specific aims: 1) Evaluate the sex-specific genetic architecture of AD through association and genetic correlation analysis; 2) Conduct transcriptome-wide association analyses to identify sex-specific changes relevant to AD; 3) Conduct region-centric analysis to identify sex-specific DNA methylation changes that contribute to AD; and 4) Prioritize sex-specific loci and develop sex-specific polygenic risk scores for AD through integrative analysis. Successful completion of this project will deliver the first large scale sex-specific genome-wide analysis of AD. It will also provide a paradigm for comprehensive and integrative analysis of genomic and epigenomic datasets in a sex-aware framework. By focusing on integrative analysis of multiple types of `omics data, our study will provide a more complete understanding of the genetic and epigenetic programs underlying sex differences in AD, which will lead to better prevention, diagnosis and individualized treatment strategies.