Simon R Cox1, David Alexander Dickie2, Stuart J Ritchie2, Sherif Karama2, Alison Pattie2, Natalie A Royle2, Janie Corley2, Benjamin S Aribisala2, Maria Valdés Hernández2, Susana Muñoz Maniega2, John M Starr2, Mark E Bastin2, Alan C Evans2, Joanna M Wardlaw2, Ian J Deary2. 1. From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria. simon.cox@ed.ac.uk. 2. From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria.
Abstract
OBJECTIVE: To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11. METHODS: We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ. RESULTS: The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy. CONCLUSIONS: The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health.
OBJECTIVE: To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11. METHODS: We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ. RESULTS: The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy. CONCLUSIONS: The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health.
Authors: Jun Pyo Kim; Sang Won Seo; Hee Young Shin; Byoung Seok Ye; Jin-Ju Yang; Changsoo Kim; Mira Kang; Seun Jeon; Hee Jin Kim; Hanna Cho; Jung-Hyun Kim; Jong-Min Lee; Sung Tae Kim; Duk L Na; Eliseo Guallar Journal: Neurology Date: 2015-07-31 Impact factor: 9.910
Authors: Joanna M Wardlaw; Mark E Bastin; Maria C Valdés Hernández; Susana Muñoz Maniega; Natalie A Royle; Zoe Morris; Jonathan D Clayden; Elaine M Sandeman; Elizabeth Eadie; Catherine Murray; John M Starr; Ian J Deary Journal: Int J Stroke Date: 2011-12 Impact factor: 5.266
Authors: Stefan J Teipel; Thomas Meindl; Maximilian Wagner; Thomas Kohl; Katharina Bürger; Maximilian F Reiser; Sabine Herpertz; Hans-Jürgen Möller; Harald Hampel Journal: J Alzheimers Dis Date: 2009 Impact factor: 4.472
Authors: Stuart J Ritchie; Mark E Bastin; Elliot M Tucker-Drob; Susana Muñoz Maniega; Laura E Engelhardt; Simon R Cox; Natalie A Royle; Alan J Gow; Janie Corley; Alison Pattie; Adele M Taylor; Maria Del C Valdés Hernández; John M Starr; Joanna M Wardlaw; Ian J Deary Journal: J Neurosci Date: 2015-06-03 Impact factor: 6.167
Authors: Tian Ge; Chia-Yen Chen; Alysa E Doyle; Richard Vettermann; Lauri J Tuominen; Daphne J Holt; Mert R Sabuncu; Jordan W Smoller Journal: Cereb Cortex Date: 2019-07-22 Impact factor: 5.357
Authors: Susan D Shenkin; Cyril Pernet; Thomas E Nichols; Jean-Baptiste Poline; Paul M Matthews; Aad van der Lugt; Clare Mackay; Linda Lanyon; Bernard Mazoyer; James P Boardman; Paul M Thompson; Nick Fox; Daniel S Marcus; Aziz Sheikh; Simon R Cox; Devasuda Anblagan; Dominic E Job; David Alexander Dickie; David Rodriguez; Joanna M Wardlaw Journal: Neuroimage Date: 2017-02-14 Impact factor: 6.556
Authors: Simon R Cox; Mark E Bastin; Stuart J Ritchie; David Alexander Dickie; Dave C Liewald; Susana Muñoz Maniega; Paul Redmond; Natalie A Royle; Alison Pattie; Maria Valdés Hernández; Janie Corley; Benjamin S Aribisala; Andrew M McIntosh; Joanna M Wardlaw; Ian J Deary Journal: Brain Struct Funct Date: 2017-09-06 Impact factor: 3.270
Authors: Maria Del Carmen Valdés Hernández; Simon R Cox; Jaeil Kim; Natalie A Royle; Susana Muñoz Maniega; Alan J Gow; Devasuda Anblagan; Mark E Bastin; Jinah Park; John M Starr; Joanna M Wardlaw; Ian J Deary Journal: Neurobiol Aging Date: 2016-12-21 Impact factor: 4.673