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Likhanov M, Zakharov I, Awofala A, Ogundele O, Selita F, Kovas Y, Chapman R. Attitudes towards genetic testing: The role of genetic literacy, motivated cognition, and socio-demographic characteristics. PLoS One 2023; 18:e0293187. [PMID: 37967060 PMCID: PMC10651000 DOI: 10.1371/journal.pone.0293187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 09/26/2023] [Indexed: 11/17/2023] Open
Abstract
Understanding reasons for why people choose to have or not to have a genetic test is essential given the ever-increasing use of genetic technologies in everyday life. The present study explored the multiple drivers of people's attitudes towards genetic testing. Using the International Genetic Literacy and Attitudes Survey (iGLAS), we collected data on: (1) willingness to undergo testing; (2) genetic literacy; (3) motivated cognition; and (4) demographic and cultural characteristics. The 37 variables were explored in the largest to-date sample of 4311 participants from diverse demographic and cultural backgrounds. The results showed that 82% of participants were willing to undergo genetic testing for improved treatment; and over 73%-for research. The 35 predictor variables together explained only a small proportion of variance: 7%-in the willingness to test for Treatment; and 6%-for Research. The strongest predictors of willingness to undergo genetic testing were genetic knowledge and deterministic beliefs. Concerns about data misuse and about finding out unwanted health-related information were weakly negatively associated with willingness to undergo genetic testing. We also found some differences in factors linked to attitudes towards genetic testing across the countries included in this study. Our study demonstrates that decision-making regarding genetic testing is influenced by a large number of potentially interacting factors. Further research into these factors may help consumers to make decisions regarding genetic testing that are right for their specific circumstances.
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Affiliation(s)
- Maxim Likhanov
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ilya Zakharov
- Ural Federal University Named after the First President of Russia B. N. Yeltsin, Yekaterinburg, Russia
- Psychological Institute of Russian Academy of Education, Moscow, Russia
| | - Adeyemi Awofala
- Department of Biological Sciences, Tai Solarin University of Education, Ijebu-Ode, Nigeria
| | - Olusegun Ogundele
- Department of Biological Sciences, Tai Solarin University of Education, Ijebu-Ode, Nigeria
| | - Fatos Selita
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
| | - Yulia Kovas
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
| | - Robert Chapman
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
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Wagner RK, Moxley J, Schatschneider C, Zirps FA. A Bayesian Probabilistic Framework for Identification of Individuals with Dyslexia. SCIENTIFIC STUDIES OF READING : THE OFFICIAL JOURNAL OF THE SOCIETY FOR THE SCIENTIFIC STUDY OF READING 2022; 27:67-81. [PMID: 36685047 PMCID: PMC9851422 DOI: 10.1080/10888438.2022.2118057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Purpose Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia. Method Model-based meta-analysis was used to create a composite correlation matrix that included common predictors of dyslexia such as decoding, phonological awareness, oral language, but also included response to intervention (RTI) and family risk for dyslexia. Bayesian logistic regression models were used to predict poor reading comprehension, unexpectedly poor reading comprehension, poor decoding, and unexpectedly poor decoding, all at two levels of severity. Results Most predictors made independent and substantial contributions to prediction, supporting models of dyslexia that rely on multiple rather than single indicators. RTI was the strongest predictor of poor reading comprehension and unexpectedly poor reading comprehension. Phonological awareness was the strongest predictor of poor decoding and unexpectedly poor decoding, followed closely by family risk. Conclusion Bayesian-based models are a promising tool for implementing multiple-indicator models of identification. Ideas for improving prediction and implications for theory and practice are discussed.
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Affiliation(s)
- Richard K. Wagner
- Department of Psychology and Florida Center for Reading Research, Florida State University
| | | | - Chris Schatschneider
- Department of Psychology and Florida Center for Reading Research, Florida State University
| | - Fotena A. Zirps
- Department of Psychology and Florida Center for Reading Research, Florida State University
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Mitchell BL, Hansell NK, McAloney K, Martin NG, Wright MJ, Renteria ME, Grasby KL. Polygenic influences associated with adolescent cognitive skills. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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4
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Kim K, Joo YY, Ahn G, Wang HH, Moon SY, Kim H, Ahn WY, Cha J. The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children. Hum Brain Mapp 2022; 43:3857-3872. [PMID: 35471639 PMCID: PMC9294341 DOI: 10.1002/hbm.25888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 11/06/2022] Open
Abstract
Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (pfdr < .001, η p 2 $$ {\eta}_p^2 $$ < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.
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Affiliation(s)
- Kakyeong Kim
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | | | - Gun Ahn
- Interdisciplinary Program of Bioengineering, College of Engineering, Seoul National University, Seoul, South Korea
| | - Hee-Hwan Wang
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Seo-Yoon Moon
- College of Liberal Studies, Seoul National University, Seoul, South Korea
| | - Hyeonjin Kim
- Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea
| | - Woo-Young Ahn
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
| | - Jiook Cha
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, South Korea.,Department of Psychology, College of Social Sciences, Seoul National University, Seoul, South Korea.,AI Institute, Seoul National University, Seoul, South Korea
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5
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Austerberry C, Fearon P, Ronald A, Leve LD, Ganiban JM, Natsuaki MN, Shaw DS, Neiderhiser JM, Reiss D. Early manifestations of intellectual performance: Evidence that genetic effects on later academic test performance are mediated through verbal performance in early childhood. Child Dev 2022; 93:e188-e206. [PMID: 34783370 PMCID: PMC10861934 DOI: 10.1111/cdev.13706] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Intellectual performance is highly heritable and robustly predicts lifelong health and success but the earliest manifestations of genetic effects on this asset are not well understood. This study examined whether early executive function (EF) or verbal performance mediate genetic influences on subsequent intellectual performance, in 561 U.S.-based adoptees (57% male) and their birth and adoptive parents (70% and 92% White, 13% and 4% African American, 7% and 2% Latinx, respectively), administered measures in 2003-2017. Genetic influences on children's academic performance at 7 years were mediated by verbal performance at 4.5 years (β = .22, 95% CI [0.08, 0.35], p = .002) and not via EF, indicating that verbal performance is an early manifestation of genetic propensity for intellectual performance.
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Affiliation(s)
- Chloe Austerberry
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Pasco Fearon
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Angelica Ronald
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Leslie D. Leve
- Prevention Science Institute, University of Oregon, Eugene, Oregon, USA
| | - Jody M. Ganiban
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia, USA
| | - Misaki N. Natsuaki
- Department of Psychology, University of California, Riverside, California, USA
| | - Daniel S. Shaw
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jenae M. Neiderhiser
- Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - David Reiss
- Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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6
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Erbeli F, Rice M, Paracchini S. Insights into Dyslexia Genetics Research from the Last Two Decades. Brain Sci 2021; 12:27. [PMID: 35053771 PMCID: PMC8773624 DOI: 10.3390/brainsci12010027] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/21/2021] [Accepted: 12/23/2021] [Indexed: 12/14/2022] Open
Abstract
Dyslexia, a specific reading disability, is a common (up to 10% of children) and highly heritable (~70%) neurodevelopmental disorder. Behavioral and molecular genetic approaches are aimed towards dissecting its significant genetic component. In the proposed review, we will summarize advances in twin and molecular genetic research from the past 20 years. First, we will briefly outline the clinical and educational presentation and epidemiology of dyslexia. Next, we will summarize results from twin studies, followed by molecular genetic research (e.g., genome-wide association studies (GWASs)). In particular, we will highlight converging key insights from genetic research. (1) Dyslexia is a highly polygenic neurodevelopmental disorder with a complex genetic architecture. (2) Dyslexia categories share a large proportion of genetics with continuously distributed measures of reading skills, with shared genetic risks also seen across development. (3) Dyslexia genetic risks are shared with those implicated in many other neurodevelopmental disorders (e.g., developmental language disorder and dyscalculia). Finally, we will discuss the implications and future directions. As the diversity of genetic studies continues to increase through international collaborate efforts, we will highlight the challenges in advances of genetics discoveries in this field.
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Affiliation(s)
- Florina Erbeli
- Department of Educational Psychology, Texas A&M University, College Station, TX 77843, USA;
| | - Marianne Rice
- Department of Educational Psychology, Texas A&M University, College Station, TX 77843, USA;
| | - Silvia Paracchini
- School of Medicine, University of St Andrews, St Andrews KY16 9AJ, UK;
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Abstract
Around the world, about 10% people prefer using their left-hand. What leads to this fixed proportion across populations and what determines left versus right preference at an individual level is far from being established. Genetic studies are a tool to answer these questions. Analysis in twins and family show that about 25% of handedness variance is due to genetics. In spite of very large cohorts, only a small fraction of this genetic component can be pinpoint to specific genes. Some of the genetic associations identified so far provide evidence for shared biology contributing to both handedness and cerebral asymmetries. In addition, they demonstrate that handedness is a highly polygenic trait. Typically, handedness is measured as the preferred hand for writing. This is a very convenient measure, especially to reach large sample sizes, but quantitative measures might capture different handedness dimensions and be better suited for genetic analyses. This paper reviews the latest findings from molecular genetic studies as well as the implications of using different ways of assessing handedness.
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8
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Gialluisi A, Andlauer TFM, Mirza-Schreiber N, Moll K, Becker J, Hoffmann P, Ludwig KU, Czamara D, Pourcain BS, Honbolygó F, Tóth D, Csépe V, Huguet G, Chaix Y, Iannuzzi S, Demonet JF, Morris AP, Hulslander J, Willcutt EG, DeFries JC, Olson RK, Smith SD, Pennington BF, Vaessen A, Maurer U, Lyytinen H, Peyrard-Janvid M, Leppänen PHT, Brandeis D, Bonte M, Stein JF, Talcott JB, Fauchereau F, Wilcke A, Kirsten H, Müller B, Francks C, Bourgeron T, Monaco AP, Ramus F, Landerl K, Kere J, Scerri TS, Paracchini S, Fisher SE, Schumacher J, Nöthen MM, Müller-Myhsok B, Schulte-Körne G. Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia. Mol Psychiatry 2021; 26:3004-3017. [PMID: 33057169 PMCID: PMC8505236 DOI: 10.1038/s41380-020-00898-x] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 07/26/2020] [Accepted: 09/18/2020] [Indexed: 02/06/2023]
Abstract
Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10-6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10-13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10-43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10-22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10-12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10-4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10-7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10-29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.
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Affiliation(s)
- Alessandro Gialluisi
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy
| | - Till F M Andlauer
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Nazanin Mirza-Schreiber
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Kristina Moll
- Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilians University, Munich, Germany
| | - Jessica Becker
- Department of Genomics, Life and Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Per Hoffmann
- Department of Genomics, Life and Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Kerstin U Ludwig
- Department of Genomics, Life and Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics and Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Ferenc Honbolygó
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Dénes Tóth
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Valéria Csépe
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Guillaume Huguet
- Human Genetics and Cognitive Functions Unit, Institut Pasteur and University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Yves Chaix
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
- Children's Hospital, Purpan University Hospital, Toulouse, France
| | | | - Jean-Francois Demonet
- Leenaards Memory Centre, Department of Clinical Neurosciences Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Jacqueline Hulslander
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Erik G Willcutt
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - John C DeFries
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Richard K Olson
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Shelley D Smith
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE, USA
| | - Bruce F Pennington
- Developmental Neuropsychology Lab and Clinic, Department of Psychology, University of Denver, Denver, CO, USA
| | - Anniek Vaessen
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience and Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, The Netherlands
| | - Urs Maurer
- Department of Psychology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
| | - Heikki Lyytinen
- Centre for Research on Learning and Teaching, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | | | - Paavo H T Leppänen
- Centre for Research on Learning and Teaching, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich and ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Milene Bonte
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience and Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, The Netherlands
| | - John F Stein
- Department of Physiology, University of Oxford, Oxford, UK
| | - Joel B Talcott
- School of Life and Health Sciences, Aston University, Birmingham, UK
| | - Fabien Fauchereau
- Human Genetics and Cognitive Functions Unit, Institut Pasteur and University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Arndt Wilcke
- Cognitive Genetics Unit, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Holger Kirsten
- Cognitive Genetics Unit, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
- Institute for Medical Informatics, Statistics and Epidemiology and LIFE-Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Bent Müller
- Cognitive Genetics Unit, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics and Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur and University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Anthony P Monaco
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Tufts University, Medford, MA, USA
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Ecole Normale Supérieure, CNRS, EHESS, PSL University, Paris, France
| | - Karin Landerl
- Institute of Psychology, University of Graz and BioTechMed, Graz, Austria
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
- Stem Cells and Metabolism Research Program, Biomedicum, Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
| | - Thomas S Scerri
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- The Walter and Eliza Hall Institute of Medical Research, Melbourne University, Melbourne, VIC, Australia
| | | | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics and Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Johannes Schumacher
- Department of Genomics, Life and Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Markus M Nöthen
- Department of Genomics, Life and Brain Center, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
| | - Gerd Schulte-Körne
- Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilians University, Munich, Germany.
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Shero J, van Dijk W, Edwards A, Schatschneider C, Solari EJ, Hart SA. The practical utility of genetic screening in school settings. NPJ SCIENCE OF LEARNING 2021; 6:12. [PMID: 34075049 PMCID: PMC8169884 DOI: 10.1038/s41539-021-00090-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
Can genetic screening be used to personalize education for students? Genome-wide association studies (GWAS) screen an individual's DNA for specific variations in their genome, and how said variations relate to specific traits. The variations can then be assigned a corresponding weight and summed to produce polygenic scores (PGS) for given traits. Though first developed for disease risk, PGS is now used to predict educational achievement. Using a novel simulation method, this paper examines if PGS could advance screening in schools, a goal of personalized education. Results show limited potential benefits for using PGS to personalize education for individual students. However, further analysis shows PGS can be effectively used alongside progress monitoring measures to screen for learning disability risk. Altogether, PGS is not useful in personalizing education for every child but has potential utility when used simultaneously with additional screening tools to help determine which children may struggle academically.
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Affiliation(s)
- J Shero
- Department of Psychology, Florida State University, Tallahassee, FL, USA.
| | - W van Dijk
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
| | - A Edwards
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - C Schatschneider
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
| | - E J Solari
- Department of Curriculum Instruction and Education, University of Virginia, Charlottesville, VA, USA
| | - S A Hart
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
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10
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The Polygenic Nature and Complex Genetic Architecture of Specific Learning Disorder. Brain Sci 2021; 11:brainsci11050631. [PMID: 34068951 PMCID: PMC8156942 DOI: 10.3390/brainsci11050631] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 05/11/2021] [Accepted: 05/12/2021] [Indexed: 12/16/2022] Open
Abstract
Specific Learning Disorder (SLD) is a multifactorial, neurodevelopmental disorder which may involve persistent difficulties in reading (dyslexia), written expression and/or mathematics. Dyslexia is characterized by difficulties with speed and accuracy of word reading, deficient decoding abilities, and poor spelling. Several studies from different, but complementary, scientific disciplines have investigated possible causal/risk factors for SLD. Biological, neurological, hereditary, cognitive, linguistic-phonological, developmental and environmental factors have been incriminated. Despite worldwide agreement that SLD is highly heritable, its exact biological basis remains elusive. We herein present: (a) an update of studies that have shaped our current knowledge on the disorder’s genetic architecture; (b) a discussion on whether this genetic architecture is ‘unique’ to SLD or, alternatively, whether there is an underlying common genetic background with other neurodevelopmental disorders; and, (c) a brief discussion on whether we are at a position of generating meaningful correlations between genetic findings and anatomical data from neuroimaging studies or specific molecular/cellular pathways. We conclude with open research questions that could drive future research directions.
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11
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Snowling MJ, Hulme C. Annual Research Review: Reading disorders revisited - the critical importance of oral language. J Child Psychol Psychiatry 2021; 62:635-653. [PMID: 32956509 DOI: 10.1111/jcpp.13324] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/24/2020] [Accepted: 08/11/2020] [Indexed: 02/06/2023]
Abstract
This paper discusses research on reading disorders during the period since their classification within the overarching category of neurodevelopmental disorders (Journal of Child Psychology and Psychiatry, 53, 2012, 593). Following a review of the predictors of learning to read across languages, and the role of language skills as critical foundations for literacy, profiles of reading disorders are discussed and putative causal risk factors at the cognitive, biological, and environmental levels of explanation considered. Reading disorders are highly heritable and highly comorbid with disorders of language, attention, and other learning disorders, notably mathematics disorders. The home literacy environment, reflecting gene-environment correlation, is one of several factors that promote reading development and highlight an important target for intervention. The multiple deficit view of dyslexia (Cognition, 101, 2006, 385) suggests that risks accumulate to a diagnostic threshold although categorical diagnoses tend to be unstable. Implications for assessment and intervention are discussed.
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Affiliation(s)
- Margaret J Snowling
- Department of Experimental Psychology, University of Oxford, Oxford, UK.,St John's College, University of Oxford, Oxford, UK
| | - Charles Hulme
- Department of Education, University of Oxford, Oxford, UK
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12
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Hart SA, Little C, van Bergen E. Nurture might be nature: cautionary tales and proposed solutions. NPJ SCIENCE OF LEARNING 2021; 6:2. [PMID: 33420086 PMCID: PMC7794571 DOI: 10.1038/s41539-020-00079-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 11/12/2020] [Indexed: 05/27/2023]
Abstract
Across a wide range of studies, researchers often conclude that the home environment and children's outcomes are causally linked. In contrast, behavioral genetic studies show that parents influence their children by providing them with both environment and genes, meaning the environment that parents provide should not be considered in the absence of genetic influences, because that can lead to erroneous conclusions on causation. This article seeks to provide behavioral scientists with a synopsis of numerous methods to estimate the direct effect of the environment, controlling for the potential of genetic confounding. Ideally, using genetically sensitive designs can fully disentangle this genetic confound, but these require specialized samples. In the near future, researchers will likely have access to measured DNA variants (summarized in a polygenic scores), which could serve as a partial genetic control, but that is currently not an option that is ideal or widely available. We also propose a work around for when genetically sensitive data are not readily available: the Familial Control Method. In this method, one measures the same trait in the parents as the child, and the parents' trait is then used as a covariate (e.g., a genetic proxy). When these options are all not possible, we plead with our colleagues to clearly mention genetic confound as a limitation, and to be cautious with any environmental causal statements which could lead to unnecessary parent blaming.
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Affiliation(s)
- Sara A Hart
- Department of Psychology, Florida State University, Tallahassee, FL, USA.
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA.
| | - Callie Little
- Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA
- Department of Psychology, University of New England, Armidale, NSW, Australia
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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13
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Petscher Y, Cabell SQ, Catts HW, Compton DL, Foorman BR, Hart SA, Lonigan CJ, Phillips BM, Schatschneider C, Steacy LM, Terry NP, Wagner RK. How the Science of Reading Informs 21st-Century Education. READING RESEARCH QUARTERLY 2020; 55:S267-S282. [PMID: 34007089 PMCID: PMC8128160 DOI: 10.1002/rrq.352] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 07/06/2020] [Indexed: 05/15/2023]
Abstract
The science of reading should be informed by an evolving evidence base built upon the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of at-risk readers. The recent resurfacing of questions about what constitutes the science of reading is leading to misinformation in the public space that may be viewed by educational stakeholders as merely differences of opinion among scientists. Our goals in this paper are to revisit the science of reading through an epistemological lens to clarify what constitutes evidence in the science of reading and to offer a critical evaluation of the evidence provided by the science of reading. To this end, we summarize those things that we believe have compelling evidence, promising evidence, or a lack of compelling evidence. We conclude with a discussion of areas of focus that we believe will advance the science of reading to meet the needs of all children in the 21st century.
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Affiliation(s)
- Yaacov Petscher
- Florida Center for Reading Research, Florida State University
| | - Sonia Q. Cabell
- Florida Center for Reading Research, Florida State University
| | - Hugh W. Catts
- Florida Center for Reading Research, Florida State University
| | | | | | - Sara A. Hart
- Florida Center for Reading Research, Florida State University
| | | | | | | | - Laura M. Steacy
- Florida Center for Reading Research, Florida State University
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14
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Smith-Woolley E, Selzam S, Plomin R. Polygenic score for educational attainment captures DNA variants shared between personality traits and educational achievement. J Pers Soc Psychol 2019; 117:1145-1163. [PMID: 30920283 PMCID: PMC6902055 DOI: 10.1037/pspp0000241] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Genome-wide polygenic scores (GPS) can be used to predict individual genetic risk and resilience. For example, a GPS for years of education (EduYears) explains substantial variance in cognitive traits such as general cognitive ability and educational achievement. Personality traits are also known to contribute to individual differences in educational achievement. However, the association between EduYears GPS and personality traits remains largely unexplored. Here, we test the relation between GPS for EduYears, neuroticism, and well-being, and 6 personality and motivation domains: Academic Motivation, Extraversion, Openness, Conscientiousness, Neuroticism, and Agreeableness. The sample was drawn from a U.K.-representative sample of up to 8,322 individuals assessed at age 16. We find that EduYears GPS was positively associated with Openness, Conscientiousness, Agreeableness, and Academic Motivation, predicting between 0.6% and 3% of the variance. In addition, we find that EduYears GPS explains between 8% and 16% of the association between personality domains and educational achievement at the end of compulsory education. In contrast, both the neuroticism and well-being GPS significantly accounted for between 0.3% and 0.7% of the variance in a subset of personality domains. Furthermore, they did not significantly account for any of the covariance between the personality domains and achievement, with the exception of the neuroticism GPS explaining 5% of the covariance between Neuroticism and achievement. These results demonstrate that the genetic effects of educational attainment relate to personality traits, highlighting the multifaceted nature of EduYears GPS. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
- Emily Smith-Woolley
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London. SE5 8AF, UK
| | - Saskia Selzam
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London. SE5 8AF, UK
| | - Robert Plomin
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London. SE5 8AF, UK
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15
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McGrath LM, Stoodley CJ. Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies. J Neurodev Disord 2019; 11:31. [PMID: 31752659 PMCID: PMC6873566 DOI: 10.1186/s11689-019-9287-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 10/04/2019] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Dyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders (estimates of 25-40% bidirectional comorbidity). Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders. METHODS We conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia (15 studies; 417 cases, 416 controls) or ADHD (22 studies; 898 cases, 763 controls) were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (p < .001, k = 50) and more lenient (p < .005, k = 50) thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls (false discovery rate [FDR] p < .05, k = 50, 5000 permutations). RESULTS Results showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity. CONCLUSIONS The current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis.
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Affiliation(s)
- Lauren M. McGrath
- Department of Psychology, University of Denver, Frontier Hall, 2155 S. Race St., Denver, CO 80208 USA
| | - Catherine J. Stoodley
- Department of Psychology and Center for Behavioral Neuroscience, American University, Washington, DC USA
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16
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Peters L, Ansari D. Are specific learning disorders truly specific, and are they disorders? Trends Neurosci Educ 2019; 17:100115. [PMID: 31685130 DOI: 10.1016/j.tine.2019.100115] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 05/30/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022]
Abstract
Specific learning disorders, such as dyslexia and dyscalculia, are frequently studied to inform our understanding of cognitive development, genetic mechanisms and brain function. In this Opinion Paper, we discuss limitations of this research approach, including the use of arbitrary criteria to select groups of children, heterogeneity within groups and overlap between domains of learning. By drawing on evidence from cognitive science, neuroscience and genetics, we propose an alternative, dimensional framework. We argue that we need to overcome the problems associated with a categorical approach by taking into account interacting factors at multiple levels of analysis that are associated with overlapping rather than entirely distinct domains of learning. We conclude that this research strategy will allow for a richer understanding of learning and development.
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Affiliation(s)
- Lien Peters
- Numerical Cognition Laboratory, Department of Psychology, Faculty of Education & Brain and Mind Institute, University of Western Ontario, Western Interdisciplinary Research Building, 1151 Richmond Street North, London, ON N6A 5B7, Canada.
| | - Daniel Ansari
- Numerical Cognition Laboratory, Department of Psychology, Faculty of Education & Brain and Mind Institute, University of Western Ontario, Western Interdisciplinary Research Building, 1151 Richmond Street North, London, ON N6A 5B7, Canada
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17
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Choi SW, O'Reilly PF. PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience 2019; 8:giz082. [PMID: 31307061 PMCID: PMC6629542 DOI: 10.1093/gigascience/giz082] [Citation(s) in RCA: 770] [Impact Index Per Article: 154.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 03/13/2019] [Accepted: 06/11/2019] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Polygenic risk score (PRS) analyses have become an integral part of biomedical research, exploited to gain insights into shared aetiology among traits, to control for genomic profile in experimental studies, and to strengthen causal inference, among a range of applications. Substantial efforts are now devoted to biobank projects to collect large genetic and phenotypic data, providing unprecedented opportunity for genetic discovery and applications. To process the large-scale data provided by such biobank resources, highly efficient and scalable methods and software are required. RESULTS Here we introduce PRSice-2, an efficient and scalable software program for automating and simplifying PRS analyses on large-scale data. PRSice-2 handles both genotyped and imputed data, provides empirical association P-values free from inflation due to overfitting, supports different inheritance models, and can evaluate multiple continuous and binary target traits simultaneously. We demonstrate that PRSice-2 is dramatically faster and more memory-efficient than PRSice-1 and alternative PRS software, LDpred and lassosum, while having comparable predictive power. CONCLUSION PRSice-2's combination of efficiency and power will be increasingly important as data sizes grow and as the applications of PRS become more sophisticated, e.g., when incorporated into high-dimensional or gene set-based analyses. PRSice-2 is written in C++, with an R script for plotting, and is freely available for download from http://PRSice.info.
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Affiliation(s)
- Shing Wan Choi
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London, UK, SE5 8AF
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, 1 Gustave L. Levy Pl, New York City, NY 10029, USA
| | - Paul F O'Reilly
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London, UK, SE5 8AF
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, 1 Gustave L. Levy Pl, New York City, NY 10029, USA
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18
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Gialluisi A, Andlauer TFM, Mirza-Schreiber N, Moll K, Becker J, Hoffmann P, Ludwig KU, Czamara D, St Pourcain B, Brandler W, Honbolygó F, Tóth D, Csépe V, Huguet G, Morris AP, Hulslander J, Willcutt EG, DeFries JC, Olson RK, Smith SD, Pennington BF, Vaessen A, Maurer U, Lyytinen H, Peyrard-Janvid M, Leppänen PHT, Brandeis D, Bonte M, Stein JF, Talcott JB, Fauchereau F, Wilcke A, Francks C, Bourgeron T, Monaco AP, Ramus F, Landerl K, Kere J, Scerri TS, Paracchini S, Fisher SE, Schumacher J, Nöthen MM, Müller-Myhsok B, Schulte-Körne G. Genome-wide association scan identifies new variants associated with a cognitive predictor of dyslexia. Transl Psychiatry 2019; 9:77. [PMID: 30741946 PMCID: PMC6370792 DOI: 10.1038/s41398-019-0402-0] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 01/02/2019] [Indexed: 12/12/2022] Open
Abstract
Developmental dyslexia (DD) is one of the most prevalent learning disorders, with high impact on school and psychosocial development and high comorbidity with conditions like attention-deficit hyperactivity disorder (ADHD), depression, and anxiety. DD is characterized by deficits in different cognitive skills, including word reading, spelling, rapid naming, and phonology. To investigate the genetic basis of DD, we conducted a genome-wide association study (GWAS) of these skills within one of the largest studies available, including nine cohorts of reading-impaired and typically developing children of European ancestry (N = 2562-3468). We observed a genome-wide significant effect (p < 1 × 10-8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2, within MIR924HG (micro-RNA 924 host gene; rs17663182 p = 4.73 × 10-9), and a suggestive association on 8q12.3 within NKAIN3 (encoding a cation transporter; rs16928927, p = 2.25 × 10-8). rs17663182 (18q12.2) also showed genome-wide significant multivariate associations with RAN measures (p = 1.15 × 10-8) and with all the cognitive traits tested (p = 3.07 × 10-8), suggesting (relational) pleiotropic effects of this variant. A polygenic risk score (PRS) analysis revealed significant genetic overlaps of some of the DD-related traits with educational attainment (EDUyears) and ADHD. Reading and spelling abilities were positively associated with EDUyears (p ~ [10-5-10-7]) and negatively associated with ADHD PRS (p ~ [10-8-10-17]). This corroborates a long-standing hypothesis on the partly shared genetic etiology of DD and ADHD, at the genome-wide level. Our findings suggest new candidate DD susceptibility genes and provide new insights into the genetics of dyslexia and its comorbities.
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Affiliation(s)
- Alessandro Gialluisi
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (Sypartially), Munich, Germany
- Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy
| | - Till F M Andlauer
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (Sypartially), Munich, Germany
| | - Nazanin Mirza-Schreiber
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Kristina Moll
- Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilians University, Munich, Germany
| | - Jessica Becker
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Kerstin U Ludwig
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - William Brandler
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
| | - Ferenc Honbolygó
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Dénes Tóth
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Valéria Csépe
- Brain Imaging Centre, Research Centre of Natural Sciences of the Hungarian Academy of Sciences, Budapest, Hungary
| | - Guillaume Huguet
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France
- University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Andrew P Morris
- Department of Biostatistics, Universiy of Liverpool, Liverpool, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Jacqueline Hulslander
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Erik G Willcutt
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - John C DeFries
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Richard K Olson
- Institute for Behavioral Genetics and Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Shelley D Smith
- Developmental Neuroscience Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE, USA
| | - Bruce F Pennington
- Developmental Neuropsychology Lab & Clinic, Department of Psychology, University of Denver, Denver, CO, USA
| | - Anniek Vaessen
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience & Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, Netherlands
| | - Urs Maurer
- Department of Psychology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
| | - Heikki Lyytinen
- Centre for Research on Learning and Teaching, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | | | - Paavo H T Leppänen
- Centre for Research on Learning and Teaching, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP), Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Milene Bonte
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience & Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, Netherlands
| | - John F Stein
- Department of Physiology, University of Oxford, Oxford, UK
| | - Joel B Talcott
- School of Life and Health Sciences, Aston University, Birmingham, UK
| | - Fabien Fauchereau
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France
- University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Arndt Wilcke
- Cognitive Genetics Unit, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France
- University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Anthony P Monaco
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Tufts University, Medford, MA, USA
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Ecole Normale Supérieure, CNRS, EHESS, PSL Research University, Paris, France
| | - Karin Landerl
- Institute of Psychology, University of Graz, Graz, Austria and BioTechMed, Graz, Austria
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
- Molecular Medicine Program, Biomedicum, University of Helsinki, and Folkhälsan Institute of Genetics, Helsinki, Finland
- School of Basic and Medical Biosciences, King's College London, London, UK
| | - Thomas S Scerri
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- The Walter and Eliza Hall Institute of Medical Research & Melbourne University, Melbourne, Australia
| | | | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Johannes Schumacher
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany.
- Munich Cluster for Systems Neurology (Sypartially), Munich, Germany.
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
| | - Gerd Schulte-Körne
- Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilians University, Munich, Germany.
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19
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Verhoef E, Demontis D, Burgess S, Shapland CY, Dale PS, Okbay A, Neale BM, Faraone SV, Stergiakouli E, Davey Smith G, Fisher SE, Børglum AD, St Pourcain B. Disentangling polygenic associations between attention-deficit/hyperactivity disorder, educational attainment, literacy and language. Transl Psychiatry 2019; 9:35. [PMID: 30679418 PMCID: PMC6345874 DOI: 10.1038/s41398-018-0324-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 11/13/2018] [Indexed: 01/08/2023] Open
Abstract
Interpreting polygenic overlap between ADHD and both literacy-related and language-related impairments is challenging as genetic associations might be influenced by indirectly shared genetic factors. Here, we investigate genetic overlap between polygenic ADHD risk and multiple literacy-related and/or language-related abilities (LRAs), as assessed in UK children (N ≤ 5919), accounting for genetically predictable educational attainment (EA). Genome-wide summary statistics on clinical ADHD and years of schooling were obtained from large consortia (N ≤ 326,041). Our findings show that ADHD-polygenic scores (ADHD-PGS) were inversely associated with LRAs in ALSPAC, most consistently with reading-related abilities, and explained ≤1.6% phenotypic variation. These polygenic links were then dissected into both ADHD effects shared with and independent of EA, using multivariable regressions (MVR). Conditional on EA, polygenic ADHD risk remained associated with multiple reading and/or spelling abilities, phonemic awareness and verbal intelligence, but not listening comprehension and non-word repetition. Using conservative ADHD-instruments (P-threshold < 5 × 10-8), this corresponded, for example, to a 0.35 SD decrease in pooled reading performance per log-odds in ADHD-liability (P = 9.2 × 10-5). Using subthreshold ADHD-instruments (P-threshold < 0.0015), these effects became smaller, with a 0.03 SD decrease per log-odds in ADHD risk (P = 1.4 × 10-6), although the predictive accuracy increased. However, polygenic ADHD-effects shared with EA were of equal strength and at least equal magnitude compared to those independent of EA, for all LRAs studied, and detectable using subthreshold instruments. Thus, ADHD-related polygenic links with LRAs are to a large extent due to shared genetic effects with EA, although there is evidence for an ADHD-specific association profile, independent of EA, that primarily involves literacy-related impairments.
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Affiliation(s)
- Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- International Max Planck Research School for Language Sciences, Nijmegen, The Netherlands.
| | - Ditte Demontis
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Chin Yang Shapland
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Philip S Dale
- Speech and Hearing Sciences, University of New Mexico, Albuquerque, USA
| | - Aysu Okbay
- Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, The Netherlands
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and Neuroscience and Physiology, SUNY Upstate Medical University, New York, USA
| | - Evie Stergiakouli
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
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20
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Li M, Malins JG, DeMille MMC, Lovett MW, Truong DT, Epstein K, Lacadie C, Mehta C, Bosson-Heenan J, Gruen JR, Frijters JC. A molecular-genetic and imaging-genetic approach to specific comprehension difficulties in children. NPJ SCIENCE OF LEARNING 2018; 3:20. [PMID: 30631481 PMCID: PMC6249284 DOI: 10.1038/s41539-018-0034-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 08/08/2018] [Accepted: 08/21/2018] [Indexed: 06/09/2023]
Abstract
Children with poor reading comprehension despite typical word reading skills were examined using neuropsychological, genetic, and neuroimaging data collected from the Genes, Reading and Dyslexia Study of 1432 Hispanic American and African American children. This unexpected poor comprehension was associated with profound deficits in vocabulary, when compared to children with comprehension skills consistent with their word reading. Those with specific comprehension difficulties were also more likely to have RU2Short alleles of READ1 regulatory variants of DCDC2, strongly associated with reading and language difficulties. Subjects with RU2Short alleles showed stronger resting state functional connectivity between the right insula/inferior frontal gyrus and the right supramarginal gyrus, even after controlling for potentially confounding variables including genetic ancestry and socioeconomic status. This multi-disciplinary approach advances the current understanding of specific reading comprehension difficulties, and suggests the need for interventions that are more appropriately tailored to the specific comprehension deficits of this group of children.
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Affiliation(s)
- Miao Li
- Department of Curriculum and Instruction, College of Education, University of Houston, Houston, TX USA
- Graduate School of Education, Harvard University, Cambridge, MA USA
| | - Jeffrey G. Malins
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
- Haskins Laboratories, New Haven, CT USA
| | | | - Maureen W. Lovett
- Neurosciences and Mental Health Program, Learning Disabilities Research Program, The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
| | - Dongnhu T. Truong
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
| | - Katherine Epstein
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
| | - Cheryl Lacadie
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT USA
| | - Chintan Mehta
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
| | - Joan Bosson-Heenan
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
| | - Jeffrey R. Gruen
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT USA
- Department of Genetics and the Investigative Medicine Program, Yale University School of Medicine, New Haven, CT USA
| | - Jan C. Frijters
- Faculty of Social Sciences, Department of Child and Youth Studies, Brock University, St. Catharines, ON Canada
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21
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Melchior M, Hebebrand J. Unraveling genetic factors involved in intelligence, educational attainment and socioeconomic standing: what are the implications for childhood mental health care professionals? Eur Child Adolesc Psychiatry 2018. [PMID: 29516195 DOI: 10.1007/s00787-018-1142-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Maria Melchior
- Department of Social Epidemiology, INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, 75012, Paris, France.
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Wickenburgstr. 21, 45147, Essen, Germany.
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22
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Crosswaite M, Asbury K. Teacher beliefs about the aetiology of individual differences in cognitive ability, and the relevance of behavioural genetics to education. BRITISH JOURNAL OF EDUCATIONAL PSYCHOLOGY 2018; 89:95-110. [PMID: 29700829 DOI: 10.1111/bjep.12224] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 03/19/2018] [Indexed: 11/26/2022]
Abstract
BACKGROUND Despite a large body of research that has explored the influence of genetic and environmental factors on educationally relevant traits, few studies have explored teachers' beliefs about, or knowledge of, developments in behavioural genetics related to education. AIMS This study aimed to describe the beliefs and knowledge of UK teachers about behavioural genetics and its relevance to education, and to test for differences between groups of teachers based on factors including years of experience and age of children taught. SAMPLE Data were gathered from n = 402 teachers from a representative sample of UK schools. Teachers from primary and secondary schools, and from across the state and independent sectors, were recruited. METHODS An online questionnaire was used to gather demographic data (gender, age, years of experience, age of children taught, and state vs. independent) and also data on beliefs about the relative influence of nature and nurture on cognitive ability; knowledge of behavioural genetics; openness to genetic research in education; and mindset. Data were analysed using descriptive statistics, ANOVA, correlations, and multiple regression. RESULTS Teachers perceived genetic and environmental factors as equally important influences on cognitive ability and tended towards a growth mindset. Knowledge about behavioural genetics was low, but openness to learning more about genetics was high. Statistically significant differences were observed between groups based on age of children taught (openness higher among primary teachers) and state versus independent (more growth-minded in state sector). CONCLUSIONS Although teachers have a limited knowledge of behavioural genetics, they are keen to learn more.
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Affiliation(s)
- Madeline Crosswaite
- Psychology in Education Research Centre, Department of Education, University of York, UK
| | - Kathryn Asbury
- Psychology in Education Research Centre, Department of Education, University of York, UK
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23
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Abstract
Intelligence - the ability to learn, reason and solve problems - is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.
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Affiliation(s)
- Robert Plomin
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, UK
| | - Sophie von Stumm
- Department of Psychological and Behavioural Science, London School of Economics and Political Science, Queens House, 55-56 Lincoln's Inn Fields, London WC2A 3LJ, UK
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