Literature DB >> 30272126

The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology.

Tian Ge1,2,3,4, Chia-Yen Chen1,2,4,5, Alysa E Doyle1,2,4, Richard Vettermann2,3, Lauri J Tuominen2,3, Daphne J Holt2,3, Mert R Sabuncu6, Jordan W Smoller1,2,4.   

Abstract

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic, and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses relate the genetic overlap between cognitive ability and cortical thickness measurements to bilateral primary motor cortex as well as predominantly left superior temporal cortex and proximal regions. These findings extend our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  cognitive performance; cortical thickness; educational attainment; genetic correlation; heritability

Mesh:

Year:  2019        PMID: 30272126      PMCID: PMC6644848          DOI: 10.1093/cercor/bhy216

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  74 in total

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Journal:  J Neurosci       Date:  2006-10-04       Impact factor: 6.167

3.  Heritability analysis with repeat measurements and its application to resting-state functional connectivity.

Authors:  Tian Ge; Avram J Holmes; Randy L Buckner; Jordan W Smoller; Mert R Sabuncu
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-08       Impact factor: 11.205

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Authors:  Roberto Colom; Miguel Burgaleta; Francisco J Román; Sherif Karama; Juan Alvarez-Linera; Francisco J Abad; Kenia Martínez; Ma Ángeles Quiroga; Richard J Haier
Journal:  Neuroimage       Date:  2013-01-26       Impact factor: 6.556

5.  Assessing the significance of focal activations using their spatial extent.

Authors:  K J Friston; K J Worsley; R S Frackowiak; J C Mazziotta; A C Evans
Journal:  Hum Brain Mapp       Date:  1994       Impact factor: 5.038

6.  Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors.

Authors:  S F Witelson; H Beresh; D L Kigar
Journal:  Brain       Date:  2005-12-09       Impact factor: 13.501

7.  Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds.

Authors:  Karama S; Ad-Dab'bagh Y; Haier Rj; Deary Ij; Lyttelton Oc; Lepage C; Evans Ac
Journal:  Intelligence       Date:  2009-03

8.  High-expanding cortical regions in human development and evolution are related to higher intellectual abilities.

Authors:  Anders M Fjell; Lars T Westlye; Inge Amlien; Christian K Tamnes; Håkon Grydeland; Andreas Engvig; Thomas Espeseth; Ivar Reinvang; Astri J Lundervold; Arvid Lundervold; Kristine B Walhovd
Journal:  Cereb Cortex       Date:  2013-08-19       Impact factor: 5.357

9.  Associations between cortical thickness and general intelligence in children, adolescents and young adults.

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Journal:  Intelligence       Date:  2013-09

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Journal:  Nat Genet       Date:  2016-08-22       Impact factor: 38.330

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2.  Age and cognitive decline in the UK Biobank.

Authors:  Marilyn C Cornelis; Yamin Wang; Thomas Holland; Puja Agarwal; Sandra Weintraub; Martha Clare Morris
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