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Genome-wide association meta-analysis of childhood ADHD symptoms and diagnosis identifies new loci and potential effector genes
Journal article   Open access   Peer reviewed

Genome-wide association meta-analysis of childhood ADHD symptoms and diagnosis identifies new loci and potential effector genes

Camiel M van der Laan, Hill F Ip, Marijn Schipper, Jouke-Jan Hottenga, Beate St Pourcain, Tetyana Zayats, René Pool, Eva M L Krapohl, Isabell Brikell, María Soler Artigas, …
Nature genetics
17/09/2025
Handle:
https://hdl.handle.net/10523/48009
Appears in  The Dunedin Study

Abstract

We performed a genome-wide association meta-analysis (GWAMA) of 290,134 attention-deficit/hyperactivity disorder (ADHD) symptom measures of 70,953 unique individuals from multiple raters, ages and instruments (ADHDSYMP). Next, we meta-analyzed the results with a study of ADHD diagnosis (ADHDOVERALL). ADHDSYMP returned no genome-wide significant variants. We show that the combined ADHDOVERALL GWAMA identified 39 independent loci, of which 17 were new. Using a recently developed gene-mapping method, Fine-mapped Locus Assessment Model of Effector genes, we identified 22 potential ADHD effector genes implicating several new biological processes and pathways. Moderate negative genetic correlations (rg < -0.40) were observed with multiple cognitive traits. In three cohorts, polygenic scores (PGSs) based on ADHDOVERALL outperformed PGSs based on ADHD symptoms and diagnosis alone. 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 helps to identify new genes implicated in ADHD.
url
https://rdcu.be/eHWlpView
Published (Version of record)Free to read via Springer Nature SharedIt InitiativeAll Rights Reserved Open

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