Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging.

Bibliographic Collection: 
APE
Publication Type: Journal Article
Authors: Glahn, David C; Kent, Jack W; Sprooten, Emma; Diego, Vincent P; Winkler, Anderson M; Curran, Joanne E; McKay, D Reese; Knowles, Emma E; Carless, Melanie A; Göring, Harald H H; Dyer, Thomas D; Olvera, Rene L; Fox, Peter T; Almasy, Laura; Charlesworth, Jac; Kochunov, Peter; Duggirala, Ravi; Blangero, John
Year of Publication: 2013
Journal: Proc Natl Acad Sci U S A
Volume: 110
Issue: 47
Pagination: 19006-11
Date Published: 2013 Nov 19
Publication Language: eng
ISSN: 1091-6490
Keywords: Adult, Age Factors, Aged, Aged, 80 and over, Aging, Analysis of Variance, Anisotropy, Brain, Cognition, Diffusion tensor imaging, Humans, Memory disorders, Mexican Americans, Middle Aged, Nerve Fibers, Myelinated, Neuroimaging, Pedigree
Abstract:

Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.

DOI: 10.1073/pnas.1313735110
Alternate Journal: Proc. Natl. Acad. Sci. U.S.A.