| Literature DB >> 29511103 |
Marco Lorenzi1,2, Andre Altmann3, Boris Gutman4, Selina Wray5, Charles Arber5, Derrek P Hibar4, Neda Jahanshad4, Jonathan M Schott6, Daniel C Alexander7, Paul M Thompson4, Sebastien Ourselin3.
Abstract
The joint modeling of brain imaging information and genetic data is a promising research avenue to highlight the functional role of genes in determining the pathophysiological mechanisms of Alzheimer's disease (AD). However, since genome-wide association (GWA) studies are essentially limited to the exploration of statistical correlations between genetic variants and phenotype, the validation and interpretation of the findings are usually nontrivial and prone to false positives. To address this issue, in this work, we investigate the functional genetic mechanisms underlying brain atrophy in AD by studying the involvement of candidate variants in known genetic regulatory functions. This approach, here termed functional prioritization, aims at testing the sets of gene variants identified by high-dimensional multivariate statistical modeling with respect to known biological processes to introduce a biology-driven validation scheme. When applied to the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, the functional prioritization allowed for identifying a link between tribbles pseudokinase 3 (TRIB3) and the stereotypical pattern of gray matter loss in AD, which was confirmed in an independent validation sample, and that provides evidence about the relation between this gene and known mechanisms of neurodegeneration.Entities:
Keywords: Alzheimer’s disease; TRIB3; brain atrophy; imaging–genetics; neuroimaging
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Year: 2018 PMID: 29511103 PMCID: PMC5866534 DOI: 10.1073/pnas.1706100115
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205