Dataset Information

Heritable changes in regional cortical thickness with age.

ABSTRACT: It is now well established that regional indices of brain structure such as cortical thickness, surface area or grey matter volume exhibit spatially variable patterns of heritability. However, a recent study found these patterns to change with age during development, a result supported by gene expression studies. Changes in heritability have not been investigated in adulthood so far and could have important implications in the study of heritability and genetic correlations in the brain as well as in the discovery of specific genes explaining them. Herein, we tested for genotype by age (G ×A) interactions, an extension of genotype by environment interactions, through adulthood and healthy aging in 902 subjects from the Genetics of Brain Structure (GOBS) study. A "jackknife" based method for the analysis of stable cortical thickness clusters (JASC) and scale selection is also introduced. Although additive genetic variance remained constant throughout adulthood, we found evidence for incomplete pleiotropy across age in the cortical thickness of paralimbic and parieto-temporal areas. This suggests that different genetic factors account for cortical thickness heritability at different ages in these regions.

SUBMITTER: Chouinard-Decorte F

PROVIDER: S-EPMC4205107 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Heritable changes in regional cortical thickness with age.

Chouinard-Decorte Francois F McKay D Reese DR Reid Andrew A Khundrakpam Budhachandra B Zhao Lu L Karama Sherif S Rioux Pierre P Sprooten Emma E Knowles Emma E Kent Jack W JW Curran Joanne E JE Göring Harald H H HH Dyer Thomas D TD Olvera Rene L RL Kochunov Peter P Duggirala Ravi R Fox Peter T PT Almasy Laura L Blangero John J Bellec Pierre P Evans Alan C AC Glahn David C DC

Brain imaging and behavior 20140422 2

It is now well established that regional indices of brain structure such as cortical thickness, surface area or grey matter volume exhibit spatially variable patterns of heritability. However, a recent study found these patterns to change with age during development, a result supported by gene expression studies. Changes in heritability have not been investigated in adulthood so far and could have important implications in the study of heritability and genetic correlations in the brain as well a ...[more]

PMID: 24752552

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Project description:Recent longitudinal neuroimaging and neurophysiological studies have shown that tracking relative age-related changes in neural signals, rather than a static snapshot of a neural measure, could offer higher sensitivity for discriminating typically developing (TD) individuals from those with autism spectrum disorder (ASD). It is not clear, however, which aspects of age-related changes (trajectories) would be optimal for identifying atypical brain development in ASD. Using a large cross-sectional data set (Autism Brain Imaging Data Exchange [ABIDE] repository; releases I and II), we aimed to explore age-related changes in cortical thickness (CT) in TD and ASD populations (age range 6-30 years old). Cortical thickness was estimated from T1-weighted MRI images at three scales of spatial coarseness (three parcellations with different numbers of regions of interest). For each parcellation, three polynomial models of age-related changes in CT were tested. Specifically, to characterize alterations in CT trajectories, we compared the linear slope, curvature, and aberrancy of CT trajectories across experimental groups, which was estimated using linear, quadratic, and cubic polynomial models, respectively. Also, we explored associations between age-related changes with ASD symptomatology quantified as the Autism Diagnostic Observation Schedule (ADOS) scores. While no overall group differences in cortical thickness were observed across the entire age range, ASD and TD populations were different in terms of age-related changes, which were located primarily in frontal and tempo-parietal areas. These atypical age-related changes were also associated with ADOS scores in the ASD group and used to predict ASD from TD development. These results indicate that the curvature is the most reliable feature for localizing brain areas developmentally atypical in ASD with a more pronounced effect with symptomatology and is the most sensitive in predicting ASD development.

Dataset Information

Heritable changes in regional cortical thickness with age.

Publications

Heritable changes in regional cortical thickness with age.

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