Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approaches

Objective: Utilize ADSP data sets to identify genes & specific genetic variants that confer risk for or protection from Alzheimer disease.
Aim 1: Using combined WGS/WES across the ADSP Discovery, Disc-Ext, and FUS Phases, including single nucleotide variants, small insertion/deletions, and structural variants. We will:
Aim 1a. Perform whole genome single variant and rare variant case/control association analyses of AD using ADSP and other available data;
Aim 1b. Target protective variant identification via association analysis using selected controls within the ADSP data and performing meta analysis across association results based on selected controls from non-ADSP data sets.
Aim 1c. Perform endophenotype analyses including cognitive function measures, hippocampal volume and circulation beta-amyloid ADSP data in subjects for which these measures are available. Meta analysis will be conducted across ADSP and non-ADSP analysis results.
Aim 2: To leverage ethnically-diverse and admixed populations to identify AD variants we will:
Aim 2a. Estimate and account for global and local ancestry in all analyses;
Aim 2b. Perform admixture mapping in samples of admixed ancestry; and
Aim 2c. Perform ethnicity-specific and trans-ethnic meta-analyses.
Aim 3: To identify putative therapeutic targets through functional characterization of genes and networks via bioinformatics, integrative omics analyses. We will:
Aim 3a. Annotate variants with their functional consequences using bioinformatic tools and publicly available “omics” data.
Aim 3b. Prioritize results, group variants with shared function, and identify key genes functionally related to AD via weighted association analyses and network approaches.
Analyses will be performed in coordination with the following PIs. Coordination will involve sharing expertise, analysis plans or analysis results. No individual level data will be shared across institutions. Philip De Jager, Columbia University; Eric Boerwinkle & Myriam Fornage, UT Health Science Center at Houston; Sudha Seshadri, UT Health Science Center at San Antonio; Ellen Wijsman, University of Washington; William Salerno, Baylor College of Medicine.

This proposal seeks to analyze existing genetic sequencing data generated as part of the Alzheimer’s Disease Sequencing Project (ADSP) including the ADSP Follow-up Study (FUS) with the goal of identifying genes and specific changes within those genes that either confer risk for Alzheimer’s disease or provide protection from Alzheimer’s disease. Analytic challenges include analysis of whole genome sequencing data, appropriately accounting for population structure across European ancestry, Hispanic, and African American participants, and interpreting results in the context of other genomic data available.