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Review
. 2015 Mar;20(3):289-97.
doi: 10.1038/mp.2014.183. Epub 2015 Jan 20.

The molecular genetic architecture of attention deficit hyperactivity disorder

Affiliations
Review

The molecular genetic architecture of attention deficit hyperactivity disorder

Z Hawi et al. Mol Psychiatry. 2015 Mar.

Abstract

Attention deficit hyperactivity disorder (ADHD) is a common childhood behavioral condition which affects 2-10% of school age children worldwide. Although the underlying molecular mechanism for the disorder is poorly understood, familial, twin and adoption studies suggest a strong genetic component. Here we provide a state-of-the-art review of the molecular genetics of ADHD incorporating evidence from candidate gene and linkage designs, as well as genome-wide association (GWA) studies of common single-nucleotide polymorphisms (SNPs) and rare copy number variations (CNVs). Bioinformatic methods such as functional enrichment analysis and protein-protein network analysis are used to highlight biological processes of likely relevance to the aetiology of ADHD. Candidate gene associations of minor effect size have been replicated across a number of genes including SLC6A3, DRD5, DRD4, SLC6A4, LPHN3, SNAP-25, HTR1B, NOS1 and GIT1. Although case-control SNP-GWAS have had limited success in identifying common genetic variants for ADHD that surpass critical significance thresholds, quantitative trait designs suggest promising associations with Cadherin13 and glucose-fructose oxidoreductase domain 1 genes. Further, CNVs mapped to glutamate receptor genes (GRM1, GRM5, GRM7 and GRM8) have been implicated in the aetiology of the disorder and overlap with bioinformatic predictions based on ADHD GWAS SNP data regarding enriched pathways. Although increases in sample size across multi-center cohorts will likely yield important new results, we advocate that this must occur in parallel with a shift away from categorical case-control approaches that view ADHD as a unitary construct, towards dimensional approaches that incorporate endophenotypes and statistical classification methods.

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