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      The correlation between reading and mathematics ability at age twelve has a substantial genetic component

      a , 1 , 2 , 31 , 3 , 31 , 3 , 31 , 2 , 4 , 5 , 6 , 7 , 2 , 2 , 2 , 2 , 3 , 3 , 3 , 3 , 3 , 3 , 8 , 8 , 8 , 8 , 8 , 8 , 8 , 8 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 3 , 24 , 22 , 25 , 26 , 8 , 8 , 27 , 28 , 2 , 2 , 2 , 29 The Wellcome Trust Case Control Consortium 3 , 30 , 2 , 32 , b , 3 , 32

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          Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.


          Understanding the genetic basis of cognitive traits could aid the development of numeracy and literacy skills in children. Here the authors show that reading and mathematics have a large overlapping genetic component and suggest that a child's learning environment has a key role in creating differences between them.

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          Most cited references 37

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          The mystery of missing heritability: Genetic interactions create phantom heritability.

          Human genetics has been haunted by the mystery of "missing heritability" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator--that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating "phantom heritability." Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.
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            GWAS of 126,559 individuals identifies genetic variants associated with educational attainment.

            A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
              • Record: found
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              Genome-wide association studies establish that human intelligence is highly heritable and polygenic

              General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan 1,2 . Data from twin and family studies are consistent with a high heritability of intelligence 3 , but this inference has been controversial. We conducted a genome-wide analysis of 3511 unrelated adults with data on 549 692 SNPs and detailed phenotypes on cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just SNP data we predicted approximately 1% of the variance of crystallized and fluid cognitive phenotypes in an independent sample (P = 0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.

                Author and article information

                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                08 July 2014
                : 5
                [1 ]Department of Genetics, Evolution and Environment, UCL Genetics Institute, University College London , London WC1E 6BT, UK
                [2 ]King’s College London, Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry , London SE5 8AF, UK
                [3 ]Wellcome Trust Centre for Human Genetics, University of Oxford , Oxford OX3 7BN, UK
                [4 ]Department of Psychology, University of Warwick , Coventry CV4 7AL, UK
                [5 ]Department of Psychological Sciences, Birkbeck, University of London , London WC1E 7HX, UK
                [6 ]Department of Psychology, Goldsmiths, University of London , London SE14 6NW, UK
                [7 ]Department of Psychology and Neuroscience, University of Colorado Boulder , Boulder, Colorado 80309-0345, USA
                [8 ]Wellcome Trust Sanger Institute , Cambridge CB10 1SA, UK
                [9 ]Telethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia , Crawley, Western Australia, Australia
                [10 ]Cambridge Institute for Medical Research, University of Cambridge School of Clinical Medicine , Cambridge CB2 0XY, UK
                [11 ]UCL Institute of Cognitive Neuroscience, University College London , London WC1N 3AR, UK
                [12 ]UCL Mental Health Sciences Unit, University College London , London W1W 7EJ, UK
                [13 ]University of Queensland Diamantia Institute, Translational Research Institute, Princess Alexandra Hospital, University of Queensland , Brisbane, Queensland QLD 4102, Australia
                [14 ]Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine , London WC1E 7HT, UK
                [15 ]Department of Epidemiology and Public Health, University College London , London WC1E 6BT, UK
                [16 ]Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin , Dublin 2, Ireland
                [17 ]Molecular and Physiological Sciences, The Wellcome Trust , London NW1 2BE, UK
                [18 ]Centre for Digestive Diseases, Blizard Institute, Queen Mary University of London , London E1 2AT, UK
                [19 ]Wolfson College , Linton Road, Oxford OX2 6UD, UK
                [20 ]Peninsula School of Medicine and Dentistry, Associate Deans Office, John Bull Building , Plymouth PL6 8BU, UK
                [21 ]Clinical Neurosciences, Saint George's University of London , London SW17 0RE, UK
                [22 ]Department of Medical and Molecular Genetics, King’s College London, King’s Health Partners Guy’s Hospital , London SE1 9RT, UK
                [23 ]Biomedical Research Centre, Ninewells Hospital and Medical School , Dundee DD1 9SY, UK
                [24 ]Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital , Cambridge CB2 2QQ, UK
                [25 ]NIHR Biomedical Research Centre at Moorfields Eye Hospital NHSFT and UCL Institute of Ophthalmology , London EC1V 2PD, UK
                [26 ]Department of Molecular Neuroscience, Institute of Neurology, University College London , London WC1N 3BG, UK
                [27 ]Department of Speech and Hearing Sciences, University of New Mexico , Albuquerque, New Mexico 87131, USA
                [28 ]Department of Family Science, Institute for Population Research, The Ohio State University , Columbus, Ohio 43210, USA
                [29 ]Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine , Philadelphia, Pennsylvania 19104-5158, USA
                [30 ]Department of Statistics, University of Oxford , Oxford OX1 3TG, UK
                [31 ]These authors contributed equally to this work
                [32 ]These authors jointly supervised this work
                Author notes
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

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