P3‐021: Identification and Characterization of Polymorphic Structural Variants Associated With Alzheimer's Disease and Diseases of Aging
Year: 2014
Type: article
Abstract: Genome-wide association studies (GWAS) based on meta-analysis of large pooled studies have produced extensive lists of variants associated with late-onset Alzheimer's disease (LOAD) and diseases of aging. However, translation of this data into new clinical applications, or biochemical targets with defined mechanisms that are appropriate drug intervention points, lags behind. Most GWAS-identified variants for LOAD with the exception of APOE have a relatively weak association with disease (OR 0.9 - 1.2), and the biological function of the variants is unclear. This presentation builds on previous work to identify structural variants in the TOMM40 gene that involve noncoding variants associated with tissue-specific modulation of APOE and TOMM40. It extends the work to other loci tagged by GWAS and to other diseases of aging. Two published bioinformatics methods (preferential linkage disequilibrium and localization of a minimal region containing a causal variant) developed to prioritize causal variants based on published GWAS data and a novel database of structural variation were used to interrogate specific genomic regions associated with LOAD and human longevity. The Alzheimer's Disease Neuroimaging Initiative (ADNI) database was used to provide a cohort of LOAD cases and controls for these analytical methods. The GWAS tracks for an extended 1 megabase region of chromosome 19 were congruent for the LOAD and aging data. Variants in this region were scored for likelihood of causality. Highly polymorphic structural variants in the region were identified. This analysis was repeated for LOAD susceptibility loci (in APOE, TOMM40, CR1, CLU, PICALM, BIN1, EPHA1, MS4A, CD33, CD2AP and ABCA7) reported in 2011 and the 11 LOAD-risk loci reported by IGAP in 2013. This presentation describes the application of innovative bioinformatics tools to identify and prioritize regulatory genetic variants associated with LOAD and other diseases of aging. It is highly likely that variants in non-coding RNA, promoters and distal regulatory elements are associated with these complex phenotypes. Application of these methods has the potential to elucidate the biochemical basis for disease-gene associations, the identification of genetic biomarkers for clinical application, and analysis of biochemical pathways associated with LOAD.
Source: Alzheimer s & Dementia
Authors: Michael W. Lutz, Robert Saul, Daniel Burns, Ann Saunders, Allen Roses
Institutions: Duke University, Duke Medical Center
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2157633856