Genome-wide association meta-analysis of childhood ADHD symptoms and diagnosis identifies new loci and potential effector genes.
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| 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 (ADHD). Next, we meta-analyzed the results with a study of ADHD diagnosis (ADHD). ADHD returned no genome-wide significant variants. We show that the combined ADHD 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 (r < -0.40) were observed with multiple cognitive traits. In three cohorts, polygenic scores (PGSs) based on ADHD 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. |
| Year of Publication | 2025
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| Journal | Nature genetics
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| Date Published | 09/2025
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| ISSN | 1546-1718
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| DOI | 10.1038/s41588-025-02295-y
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| PubMed ID | 40962958
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