Meta-analysis of Genome wide Association Studies on Childhood ADHD Symptoms and Diagnosis Reveals 17 Novel Loci and 22 Potential Effector Genes
Authors: Van der Laan Camiel M. , Ip Hill F. , Schipper Marijn , Hottenga Jouke-Jan , Krapohl Eva M. L. , Brikell Isabell , Soler Artigas María , Cabana-Domínguez Judith , Natalia Llonga , Nolte Ilja M. , St Pourcain Beate , Bolhuis Koen , Palviainen Teemu , Zafarmand Hadi , Gordon Scott , Zayats Tetyana , Aliev Fazil , Burt Alexandra S. , Wang Carol A. , Saunders Gretchen , Karhunen Ville , Adkins Daniel E. , Border Richard , Peterson Roseann E. , Prinz Joseph A. , Thiering Elisabeth , Vilor-Tejedor Natàlia , Ahluwalia Tarunveer S. , Allegrini Andrea , Rimfeld Kaili , Chen Qi , Lu Yi , Martin Joanna , Bosch Rosa , Ramos Quiroga Josep Antoni , Neumann Alexander , Ensink Judith , Grasby Katrina , Morosoli José J. , Tong Xiaoran , Marrington Shelby , Scott James G. , Shabalin Andrey A. , Corley Robin , Evans Luke M. , Sugden Karen , Alemany Silvia , Sass Lærke , Vinding Rebecca , Ehli Erik A. , Hagenbeek Fiona A. , Derks Eske , Larsson Henrik , Snieder Harold , Cecil Charlotte , Whipp Alyce M. , Korhonen Tellervo , Vuoksimaa Eero , Rose Richard J. , Uitterlinden André G. , Haavik Jan , Harris Jennifer R. , Helgeland Øyvind , Johansson Stefan , Knudsen Gun Peggy S. , Njolstad Pal Rasmus , Lu Qing , Rodriguez Alina , Henders Anjali K. , Mamun Abdullah , Najman Jackob M. , Brown Sandy , Hopfer Christian , Krauter Kenneth , Reynolds Chandra , Smolen Andrew , Stallings Michael , Wadsworth Sally , Wall Tamara , Eaves Lindon , Silberg Judy L. , Miller Allison , Havdahl Alexandra , Llop Sabrina , Lopez-Espinosa Maria-Jose , Bønnelykke Klaus , Sunyer Jordi , Arseneault Louise , Standl Marie , Heinrich Joachim , Boden Joseph , Pearson John , Horwood John , Kennedy Martin , Poulton Richie , Maes Hermine H. , Hewitt John , Copeland William E. , Middeldorp Christel M. , Williams Gail M. , Wray Naomi , Järvelin Marjo-Riitta , McGue Matt , Iacono William , Caspi Avshalom , Moffitt Terrie E. , Whitehouse Andrew , Pennell Craig E. , Klump Kelly L. , Jiang Chang , Dick Danielle M. , Reichborn-Kjennerud Ted , Martin Nicholas G. , Medland Sarah E. , Vrijkotte Tanja , Kaprio Jaakko , Tiemeier Henning , Davey Smith George , Hartman Catharina A. , Oldehinkel Albertine J. , Casas Miquel , Ribasés Marta , Lichtenstein Paul , Lundström Sebastian , Plomin Robert , Bartels Meike , Nivard Michel G. , Boomsma Dorret I. 
Published: April 2024

AbstractAttention-deficit/hyperactivity disorder (ADHD) is a heritable neurodevelopmental disorder for which genetic factors explain up to 75% of the variance. In this study, we performed a genome-wide association meta-analysis (GWAMA) of ADHD symptom measures, with an effective sample size of 120,092 (71,733 unique individuals from 28 population-based cohorts, with 288,887 quantitative ADHD symptom measures). Next, we meta-analyzed the results with a genome-wide association study (GWAS) of ADHD diagnosis. The GWAMA of ADHD symptoms returned no genome-wide significant variants. However, we estimated strong genetic correlations between our study of quantitative ADHD symptoms and the earlier study of ADHD diagnosis (rg= 1.00, SE= 0.06). Moderate negative genetic correlations (rg< -0.40) were observed with several cognitive traits. Genetic correlations between ADHD and aggressive behavior and antisocial behavior were around 1. This provides further evidence of the wide pleiotropic effects of genetic variants and the role that genetic variants play in the co-occurrence with (mental) health traits. The GWAMAs of ADHD symptoms and diagnosis identified 2,039 genome-wide significant variants, representing 39 independent loci, of which 17 were new. Using a novel fine-mapping and functional annotation method, we identified 22 potential effector genes which implicate several new potential biological processes and pathways that may play a role in ADHD. Our findings support the notion that clinical ADHD is at the extreme end of a continuous liability that is indexed by ADHD symptoms. We show that including ADHD symptom counts in large-scale GWAS can be useful to identify novel genes implicated in ADHD and related symptoms.