The Early‐Onset Alzheimer's Disease Whole‐Genome Sequencing Project: Study design and methodology

Abstract

INTRODUCTIONSequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late‐onset AD although early‐onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology.METHODSWhole‐genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries.RESULTSA publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local‐ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits.DISCUSSIONThis novel resource complements over 50,000 control and late‐onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range.Highlights Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late‐onset AD although early‐onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early‐Onset Alzheimer's Disease Whole‐genome Sequencing Project is a collaborative initiative to generate a large‐scale genomics resource for early‐onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local‐ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.