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Journal article
A Comprehensive Quantitative Genetic Analysis of Cerebral Surface Area in Youth
The Journal of neuroscience, v 39(16), pp 3028-3040
17 Apr 2019
PMID: 30833512
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The genetics of cortical arealization in youth is not well understood. In this study, we use a genetically informative sample of 677 typically developing children and adolescents (mean age 12.72 years), high-resolution MRI, and quantitative genetic methodology to address several fundamental questions on the genetics of cerebral surface area. We estimate that >85% of the phenotypic variance in total brain surface area in youth is attributable to additive genetic factors. We also observed pronounced regional variability in the genetic influences on surface area, with the most heritable areas seen in primary visual and visual association cortex. A shared global genetic factor strongly influenced large areas of the frontal and temporal cortex, mirroring regions that are the most evolutionarily novel in humans relative to other primates. In contrast to studies on older populations, we observed statistically significant genetic correlations between measures of surface area and cortical thickness (
r
G
= 0.63), suggestive of overlapping genetic influences between these endophenotypes early in life. Finally, we identified strong and highly asymmetric genetically mediated associations between Full-Scale Intelligence Quotient and left perisylvian surface area, particularly receptive language centers. Our findings suggest that spatially complex and temporally dynamic genetic factors are influencing cerebral surface area in our species.
SIGNIFICANCE STATEMENT
Over evolution, the human cortex has undergone massive expansion. In humans, patterns of neurodevelopmental expansion mirror evolutionary changes. However, there is a sparsity of information on how genetics impacts surface area maturation. Here, we present a systematic analysis of the genetics of cerebral surface area in youth. We confirm prior research that implicates genetics as the dominant force influencing individual differences in global surface area. We also find evidence that evolutionarily novel brain regions share common genetics, that overlapping genetic factors influence both area and thickness in youth, and the presence of strong genetically mediated associations between intelligence and surface area in language centers. These findings further elucidate the complex role that genetics plays in brain development and function.
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Details
- Title
- A Comprehensive Quantitative Genetic Analysis of Cerebral Surface Area in Youth
- Creators
- J. Eric Schmitt - Hospital of the University of PennsylvaniaMichael C. Neale - Virginia Commonwealth UniversityLiv S. Clasen - Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4D18, 10 Center Drive, Bethesda, MD 20892Siyuan Liu - Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4N242A, 10 Center Drive, Bethesda, MD 20892Jakob Seidlitz - Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4N242A, 10 Center Drive, Bethesda, MD 20892Joshua N. Pritikin - Virginia Commonwealth UniversityAlan Chu - Hospital of the University of PennsylvaniaGregory L. Wallace - George Washington UniversityNancy Raitano Lee - Drexel UniversityJay N. Giedd - University of California, San DiegoArmin Raznahan - Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4D18, 10 Center Drive, MSC 1367, Bethesda, MD 20892
- Publication Details
- The Journal of neuroscience, v 39(16), pp 3028-3040
- Publisher
- Society for Neuroscience
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000465040000005
- Scopus ID
- 2-s2.0-85065040714
- Other Identifier
- 991019167724604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neurosciences