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Middeldorp, Christel M.; Hammerschlag, Anke R.; Ouwens, Klaasjan G.; Groen-Blokhuis, Maria M.; St Pourcain, Beate; Greven, Corina U.; Pappa, Irene; Tiesler, Carla M. T.; Ang, Wei; Nolte, Ilja M.; Vilor-Tejedor, Natalia; Bacelis, Jonas; Ebejer, Jane L.; Zhao, Huiying; Davies, Gareth E.; Ehli, Erik A.; Evans, David M.; Fedko, Iryna O.; Guxens, Monica; Hottenga, Jouke-Jan; Hudziak, James J.; Jugessur, Astanand; Kemp, John P.; Krapohl, Eva; Martin, Nicholas G.; Murcia, Mario; Myhre, Ronny; Ormel, Johan; Ring, Susan M.; Standl, Marie; Stergiakouli, Evie; Stoltenberg, Camilla; Thiering, Elisabeth; Timpson, Nicholas J.; Trzaskowski, Maciej; Most, Peter J. van der; Wang, Carol; Nyholt, Dale R.; Medland, Sarah E.; Neale, Benjamin; Jacobsson, Bo; Sunyer, Jordi; Hartman, Catharina A.; Whitehouse, Andrew J. O.; Pennell, Craig E.; Heinrich, Joachim; Plomin, Robert; Smith, George Davey; Tiemeier, Henning; Posthuma, Danielle; Boomsma, Dorret I. (2016): A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts. In: Journal of the American Academy of Child and Adolescent Psychiatry, Vol. 55, No. 10: pp. 896-905
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Abstract

Objective: The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. Method: Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. Results: SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 x 10(-6) and 2.66 x 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. Conclusion: The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

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