ADSP xQTL

Population-based genetic association studies have identified over 30 risk loci for Alzheimer’s disease (AD). However, such approaches do not directly reveal the true causal variants or unfold the functional mechanisms of the risk variants. To bridge these gaps, we need to investigate the functional impacts of genetic variants on molecular traits (e.g., mRNA, proteins, and epigenetic modifications) in disease-relevant tissues (e.g. brains) and cell types. We hypothesize that many of the SNPs influence multiple clinical and molecular features. By integrating the genetic associations with functional quantitative trait loci (QTLs), we aim to investigate the potential cascading causal effect of genetic variations in multiple layers of omics data in AD.

In this proposal, we plan to perform a multi-omic quantitative trait locus (xQTL) analyses to RNA-seq, proteomics, and DNA methylation data from the large number of postmortem brain tissues available from the AMP-AD project. This study will be part of NIH/NIA Alzheimer's Disease Sequencing Project (ADSP) Functional Genomics xQTL Consortium, a joint effort to generate a reference map of Alzheimer's-related quantitative loci (QTLs). Specifically, our team will be responsible for the xQTL analysis in the Mount Sinai Brain Bank (MSBB) cohort, which contains whole-genome sequencing (WGS), RNA-seq gene expression, proteomics, and DNA methylation data from over 300 AD and control brains. We will follow the unified xQTL calling pipelines developed by the xQTL Consortium to predict QTLs and conduct the subsequent fine mapping, causal inference, and functional annotation integration. We will validate the identified xQTLs in independent samples from the ROSMAP cohort. Through the AMP-AD portal, we already have access to the MSBB and ROSMAP sample meta data, RNA-seq raw read files, proteomics and DNA methylation data. However, the WGS genotype data in the AMP-AD portal were called based on the human hg19 genome, inconsistent with the hg38 genome-based genotype data for other studies in the xQTL consortium. Thus, we are applying for the access to the MSBB and ROSMAP WGS hg38 genome-based genotype data available in NIAGADS.

Numerous genetic loci have been identified to associate with when Alzheimer's disease (AD) occurs and how it progresses. However, the widely used genome-wide association studies (GWAS)-based approaches do not directly reveal the true causal variants or unfold the functional mechanisms of the risk variants. To bridge these gaps, we plan to study the functional impacts of genetic variants on molecular traits (e.g., mRNA, proteins, and epigenetic modifications) in postmortem brain tissues of large AD cohorts, including Mount Sinai Brain Bank and Religious Orders Study/Memory and Aging Project (ROSMAP). By integrating the genetic association signals with the functional quantitative trait loci, we aim to investigate the potential cascading causal effect of genetic variations in multiple layers of omics data in AD.