Susceptibility of brain atrophy to TRIB3 in Alzheimer’s disease, evidence from functional prioritization in imaging genetics

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 115; no. 12; pp. 3162 - 3167
• Main Authors: Lorenzi, Marco, Altmann, Andre, Gutman, Boris, Wray, Selina, Arber, Charles, Hibar, Derrek P., Jahanshad, Neda, Schott, Jonathan M., Alexander, Daniel C., Thompson, Paul M., Ourselin, Sebastien
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 20.03.2018
• Subjects: Aged; Alzheimer Disease - diagnostic imaging; Alzheimer Disease - genetics; Alzheimer Disease - pathology; Alzheimer's disease; Atrophy; Atrophy - diagnostic imaging; Atrophy - genetics; Atrophy - metabolism; Bioinformatics; Biological activity; Biological Sciences; Brain; Brain - diagnostic imaging; Brain - pathology; Cell Cycle Proteins - genetics; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - genetics; Cognitive Dysfunction - pathology; Cohort Studies; Computer Science; Correlation analysis; Disease control; Female; Genes; Genetic diversity; Genetic Predisposition to Disease; Genetic variance; Genetics; Genomes; Human genetics; Human health and pathology; Humans; Life Sciences; Magnetic Resonance Imaging; Male; Mathematical models; Modelling; Multivariate Analysis; Neurobiology; Neurodegeneration; Neuroimaging; Neurology; Neurons and Cognition; Phenotypes; Physical Sciences; Polymorphism, Single Nucleotide; Protein-Serine-Threonine Kinases - antagonists & inhibitors; Protein-Serine-Threonine Kinases - genetics; Quantitative Methods; Repressor Proteins - genetics; Statistical models; Substantia grisea; Tissues and Organs; imaging–genetics; TRIB3; Alzheimer’s disease; brain atrophy; neuroimaging; phenotype; GWA; Alzheimer's disease; bioinformatics; imaging-genetics; genotype
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.1706100115

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.