NRSN1 associated grey matter volume of the visual word form area reveals dyslexia before school

Literacy learning depends on the flexibility of the human brain to reconfigure itself in response to environmental influences. At the same time, literacy and disorders of literacy acquisition are heritable and thus to some degree genetically predetermined. Here we used a multivariate non-parametric genetic model to relate literacy-associated genetic variants to grey and white matter volumes derived by voxel-based morphometry in a cohort of 141 children. Subsequently, a sample of 34 children attending grades 4 to 8, and another sample of 20 children, longitudinally followed from kindergarten to first grade, were classified as dyslexics and controls using linear binary support vector machines. The NRSN1-associated grey matter volume of the ’visual word form area’ achieved a classification accuracy of ~ 73% in literacy-experienced students and distinguished between later dyslexic individuals and controls with an accuracy of 75% at kindergarten age. These findings suggest that the cortical plasticity of a region vital for literacy might be genetically modulated, thereby potentially preconstraining literacy outcome. Accordingly, these results could pave the way for identifying and treating the most common learning disorder before it manifests itself in school.   Literacy learning depends on the flexibility of the human brain to reconfigure itself in response to environmental influences. At the same time, literacy and disorders of literacy acquisition are heritable and thus to some degree genetically predetermined. Here we used a multivariate non-parametric genetic model to relate literacy-associated genetic variants to grey and white matter volumes derived by voxel-based morphometry in a cohort of 141 children. Subsequently, a sample of 34 children attending grades 4 to 8, and another sample of 20 children, longitudinally followed from kindergarten to first grade, were classified as dyslexics and controls using linear binary support vector machines. The NRSN1-associated grey matter volume of the ’visual word form area’ achieved a classification accuracy of ~ 73% in literacy-experienced students and distinguished between later dyslexic individuals and controls with an accuracy of 75% at kindergarten age. These findings suggest that the cortical plasticity of a region vital for literacy might be genetically modulated, thereby potentially preconstraining literacy outcome. Accordingly, these results could pave the way for identifying and treating the most common learning disorder before it manifests itself in school. //  Literacy learning depends on the flexibility of the human brain to reconfigure itself in response to environmental influences. At the same time, literacy and disorders of literacy acquisition are heritable and thus to some degree genetically predetermined. Here we used a multivariate non-parametric genetic model to relate literacy-associated genetic variants to grey and white matter volumes derived by voxel-based morphometry in a cohort of 141 children. Subsequently, a sample of 34 children attending grades 4 to 8, and another sample of 20 children, longitudinally followed from kindergarten to first grade, were classified as dyslexics and controls using linear binary support vector machines. The NRSN1-associated grey matter volume of the ’visual word form area’ achieved a classification accuracy of ~ 73% in literacy-experienced students and distinguished between later dyslexic individuals and controls with an accuracy of 75% at kindergarten age. These findings suggest that the cortical plasticity of a region vital for literacy might be genetically modulated, thereby potentially preconstraining literacy outcome. Accordingly, these results could pave the way for identifying and treating the most common learning disorder before it manifests itself in school.