Association between polygenic risk scores for attention-deficit hyperactivity disorder and educational and cognitive outcomes in the general population

Abstract Background: Children with a diagnosis of attention-deficit hyperactivity disorder (ADHD) have lower cognitive ability and are at risk of adverse educational outcomes; ADHD genetic risks have been found to predict childhood cognitive ability and other neurodevelopmental traits in the general population; thus genetic risks might plausibly also contribute to cognitive ability later in development and to educational underachievement. Methods: We generated ADHD polygenic risk scores in the Avon Longitudinal Study of Parents and Children participants (maximum N: 6928 children and 7280 mothers) based on the results of a discovery clinical sample, a genome-wide association study of 727 cases with ADHD diagnosis and 5081 controls. We tested if ADHD polygenic risk scores were associated with educational outcomes and IQ in adolescents and their mothers. Results: High ADHD polygenic scores in adolescents were associated with worse educational outcomes at Key Stage 3 [national tests conducted at age 13–14 years; β = −1.4 (−2.0 to −0.8), P = 2.3 × 10−6), at General Certificate of Secondary Education exams at age 15–16 years (β = −4.0 (−6.1 to −1.9), P = 1.8 × 10−4], reduced odds of sitting Key Stage 5 examinations at age 16–18 years [odds ratio (OR) = 0.90 (0.88 to 0.97), P = 0.001] and lower IQ scores at age 15.5 [β = −0.8 (−1.2 to −0.4), P = 2.4 × 10−4]. Moreover, maternal ADHD polygenic scores were associated with lower maternal educational achievement [β = −0.09 (−0.10 to −0.06), P = 0.005] and lower maternal IQ [β = −0.6 (−1.2 to −0.1), P = 0.03]. Conclusions: ADHD diagnosis risk alleles impact on functional outcomes in two generations (mother and child) and likely have intergenerational environmental effects.

[1]  G. Salmon,et al.  Attention deficit hyperactivity disorder. , 2018, British journal of hospital medicine.

[2]  R Plomin,et al.  Phenome-wide analysis of genome-wide polygenic scores , 2015, Molecular Psychiatry.

[3]  David M. Evans,et al.  Shared Genetic Influences Between Attention-Deficit/Hyperactivity Disorder (ADHD) Traits in Children and Clinical ADHD , 2015, Journal of the American Academy of Child and Adolescent Psychiatry.

[4]  M. O’Donovan,et al.  Genetic Risk for Attention-Deficit/Hyperactivity Disorder Contributes to Neurodevelopmental Traits in the General Population , 2014, Biological Psychiatry.

[5]  M. O’Donovan,et al.  Neurocognitive abilities in the general population and composite genetic risk scores for attention-deficit hyperactivity disorder , 2014, Journal of child psychology and psychiatry, and allied disciplines.

[6]  John P. Rice,et al.  Polygenic scores associated with educational attainment in adults predict educational achievement and ADHD symptoms in children , 2014, American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics.

[7]  David M. Evans,et al.  Genome-wide association study of height-adjusted BMI in childhood identifies functional variant in ADCY3 , 2014, Obesity.

[8]  G. Davey Smith,et al.  Mendelian randomization: genetic anchors for causal inference in epidemiological studies , 2014, Human molecular genetics.

[9]  Kristopher J Preacher,et al.  Manifest variable path analysis: potentially serious and misleading consequences due to uncorrected measurement error. , 2014, Psychological methods.

[10]  Shaun M. Purcell,et al.  Statistical power and significance testing in large-scale genetic studies , 2014, Nature Reviews Genetics.

[11]  John O. Willis,et al.  Wechsler Abbreviated Scale of Intelligence , 2014 .

[12]  C. Propper,et al.  Pre-school hyperactivity/attention problems and educational outcomes in adolescence: prospective longitudinal study , 2013, British Journal of Psychiatry.

[13]  R. Plomin Missing heritability, polygenic scores, and gene–environment correlation , 2013, Journal of child psychology and psychiatry, and allied disciplines.

[14]  M. Gill,et al.  Shared polygenic contribution between childhood attention-deficit hyperactivity disorder and adult schizophrenia , 2013, British Journal of Psychiatry.

[15]  M. Daly,et al.  Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis , 2013, The Lancet.

[16]  B. Franke,et al.  High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression , 2013, The American journal of psychiatry.

[17]  Tony Blakely,et al.  Misclassification of the mediator matters when estimating indirect effects , 2013, Journal of Epidemiology & Community Health.

[18]  A. Knafo,et al.  Gene–environment correlation in developmental psychopathology , 2013, Development and Psychopathology.

[19]  T. VanderWeele Invited commentary: structural equation models and epidemiologic analysis. , 2012, American journal of epidemiology.

[20]  D. Lawlor,et al.  Cohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort , 2012, International journal of epidemiology.

[21]  D. Lawlor,et al.  Cohort Profile: The ‘Children of the 90s’—the index offspring of the Avon Longitudinal Study of Parents and Children , 2012, International journal of epidemiology.

[22]  M. Gill,et al.  Investigating the Contribution of Common Genetic Variants to the Risk and Pathogenesis of ADHD , 2012, The American journal of psychiatry.

[23]  M. Bartels,et al.  A systematic review of prospective studies on attention problems and academic achievement , 2010, Acta psychiatrica Scandinavica.

[24]  Susanne Walitza,et al.  Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. , 2010, Journal of the American Academy of Child and Adolescent Psychiatry.

[25]  Teri A Manolio,et al.  Genomewide association studies and assessment of the risk of disease. , 2010, The New England journal of medicine.

[26]  S. Faraone,et al.  Molecular genetics of attention deficit hyperactivity disorder. , 2010, The Psychiatric clinics of North America.

[27]  Peter M Visscher,et al.  Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. , 2009, Human molecular genetics.

[28]  P. Visscher,et al.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder , 2009, Nature.

[29]  M. Bandi,et al.  Probability distribution of power fluctuations in turbulence. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  Kristopher J Preacher,et al.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models , 2008, Behavior research methods.

[31]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[32]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[33]  Eric A Youngstrom,et al.  Meta-analysis of intellectual and neuropsychological test performance in attention-deficit/hyperactivity disorder. , 2004, Neuropsychology.

[34]  David P Mackinnon,et al.  Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods , 2004, Multivariate behavioral research.

[35]  H. Meltzer,et al.  The Development and Well-Being Assessment: description and initial validation of an integrated assessment of child and adolescent psychopathology. , 2000, Journal of child psychology and psychiatry, and allied disciplines.

[36]  R Plomin,et al.  Genotype-environment interaction and correlation in the analysis of human behavior. , 1977, Psychological bulletin.

[37]  David M. Evans,et al.  Genome-Wide Association Study of Height-Adjusted BMI in Childhood Identifies Functional Variant in ADCY 3 , 2014 .

[38]  K. Bollen,et al.  DIRECT AND INDIRECT EFFECTS: CLASSICAL AND BOOTSTRAP ESTIMATES OF VARIABILITY , 1990 .

[39]  M. Sobel Some New Results on Indirect Effects and Their Standard Errors in Covariance Structure Models , 1986 .

[40]  M. Sobel Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[41]  T. Speed,et al.  Structural Analysis of Multivariate Data: A Review , 1982 .