Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.
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The PGC’s policy is to make genome-wide summary results public. Summary statistics with the results from the ADHD GWAs meta-analysis of iPSYCH and the PGC samples are available on the PGC and iPSYCH websites (https://www.med.unc.edu/pgc/results-and-downloads and http://ipsych.au.dk/downloads/). GWA summary statistics with results from the GWAS of ADHD symptom scores analyzed in the EAGLE sample can be accessed at the PGC website (link above). Summary statistics for the 23andMe dataset can be obtained by qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For access to genotypes from the PGC cohorts and the iPSYCH sample, interested researchers should contact the lead PIs (iPSYCH, A.D.B.; P.G.C., B.M.N. and S.V.F.).
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The iPSYCH team acknowledges funding from the Lundbeck Foundation (grant no. R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, the European Research Council (project 294838), the European Community (EC) Horizon 2020 Programme (grant 667302 (CoCA)), from EC Seventh Framework Programme (grant 602805 (Aggressotype)), the Novo Nordisk Foundation for supporting the Danish National Biobank resource and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center.
The Broad Institute and Massachusetts General Hospital investigators would like to acknowledge support from the Stanley Medical Research Institute and NIH grants: 5U01MH094432-04(PI: Daly), 1R01MH094469 (PI: Neale), 1R01MH107649-01 (PI: Neale), 1R01MH109539-01 (PI: Daly).
We thank T. Lehner, A. Addington and G. Senthil for their support in the Psychiatric Genomics Consortium.
S.V.F. is supported by the K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Norway, the EC’s Seventh Framework Programme (grant 602805), the EC’s Horizon 2020 (grant 667302) and NIMH grants 5R01MH101519 and U01 MH109536-01.
J.M. was supported by the Wellcome Trust (grant 106047).
B.F.’s research is supported by funding from a personal Vici grant of the Netherlands Organisation for Scientific Research (NWO; grant 016-130-669, to B.F.), the EC’s Seventh Framework Programme (grant 602805 (Aggressotype), 602450 (IMAGEMEND), and 278948 (TACTICS)), and from the EC’s Horizon 2020 Programme (grant643051 (MiND) and 667302 (CoCA)). Additionally, this work was supported by the European College of Neuropsychopharmacology (ECNP Network ‘ADHD across the Lifespan’).
J.H. is supported by grants from Stiftelsen K.G. Jebsen, University of Bergen and The Research Council of Norway.
B.C. received financial support for this research from the Spanish ‘Ministerio de Economía y Competitividad’ (SAF2015-68341-R) and ‘Generalitat de Catalunya/AGAUR’ (2017-SGR-738). B.B., A.R. and collaborators received funding from the EC’s Seventh Framework Programme (grant 602805, Aggressotype), the EC’s H2020 Programme (grants 667302, CoCA, and 402003, MiND), the ECNP network ‘ADHD across the lifespan’ and DFG CRC 1193, subproject Z03.
O.A.A. is supported by the Research Council of Norway (grants: 223273, 248778, 213694, 249711), and KG Jebsen Stiftelsen.
A.T. received ADHD funding from the Wellcome Trust, Medical Research Council (MRC UK), Action Medical Research.
We thank the customers of 23andMe who answered surveys, as well as the employees of 23andMe who together made this research possible. The QIMR studies were supported by funding from the Australian National Health and Medical Research Council (grant numbers: 241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496739, 552485, and 552498, and, most recently, 1049894) and the Australian Research Council (grant numbers: A7960034, A79906588, A79801419, DP0212016, and DP0343921). SEM is supported by an NHMRC fellowship (1103623).
Additional acknowledgements can be found in the Supplementary Note.
Supplementary Figures 1–26, Supplementary Tables 1–14 and Supplementary Note
Extended results from genetic correlation analyses of ADHD and 219 phenotypes
Bayesian credible sets of variants for each of the 12 genome-wide significant loci
Summary of the observed annotations for the credible set at each genome-wide significant locus
Variant-level annotations for the credible set at each genome-wide significant locus
Results of gene set analyses using sets from Gene Ontology
Genome-wide significant index variants in meta-analyses of iPSYCH, PGC, deCODE, 23andMe and EAGLE/QIMR
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