In a sample of 727 children with ADHD and 5,081 comparison subjects, there was no evidence of genome-wide significant association with any SNP. In keeping with previous results from a subsample of the present study, we found an increased burden of large and rare CNVs. Analysis of our top 100 SNPs in the ADHD genetics consortium meta-analysis and deCODE data sets yielded no significant evidence of association, after allowing for testing of individual SNPs, when the 100 SNPs were considered together and when the discovery GWAS data were combined with those from the other data sets. These results add to the four published GWAS studies of ADHD (6
) that include meta-analyses in which no genome-wide significant findings had been found. The lack of significant GWAS findings could simply reflect sample sizes that are inadequate for the multiple testing burden, and it may be that when much larger samples are assembled for extended meta-analyses, common risk variants will be detected. That more sets of genes were significantly enriched for subthreshold association signals is consistent with this hypothesis, as it implies that the distribution of the association signals with respect to genes is not random.
One major motivation for undertaking genetic studies is to identify underlying biological risk mechanisms. In the present study, we sought evidence on whether the pathways enriched for SNP association converge with those enriched for rare CNVs. Our finding of significant evidence for such a convergence underscores our contention that it is premature to dismiss the contribution of SNP variation, but more importantly, it begins to provide evidence that genome-wide studies of ADHD, based on common or rare variants, are likely to inform processes of relevance to pathophysiology. At present, our study is not sufficiently powered to identify any of these categories unambiguously. Significant pathways included those related to cholesterol (four pathways) and CNS development. The latter has been previously implicated in ADHD (3
), although different methods were used. The lack of a clear overlap at the level of individual genes may reflect true differences in the specific genes within pathways implicated by SNPs and CNVs, perhaps arising from the different mutational mechanisms responsible for generating large CNVs and SNPs, neither of which occur randomly with respect to the genomic sequence context. However, it is also likely that it reflects low power to identify specific risk genes. Although not supported at a genome-wide level of significance, the convergence of SNP and CNV association at CHRNA7
, which encodes the cholinergic receptor nicotinic alpha 7, is intriguing. CHRNA7
is widely expressed in the brain, especially the hippocampus (34
), and is involved in rapid synaptic transmission. CHRNA7
has been examined in relation to schizophrenia, associated cognitive deficits, and nicotine dependence (35
), although findings have not been entirely consistent. There has been little published work on ADHD, although incomplete evaluations of the gene in much smaller samples have not been supportive (37
). Thus, to date this gene has yet to be comprehensively investigated in relation to ADHD.
Small duplications and deletions on 15q13.3 have been found to be associated with neuropsychiatric phenotypes that include ADHD. Recurrent deletions of chromosome 15q13.3 are associated with developmental delay and a variety of neuropsychiatric phenotypes. It has been suggested that haploinsufficiency of CHRNA7
may have a causal role (38
). Duplications spanning CHRNA7
have also been found to be associated with a broad range of neuropsychiatric phenotypes that include ADHD (39
). Increased dosage of CHRNA7 in these microduplications has been considered to be responsible.
GWAS and CNV studies capture only a proportion of genetic variation and do not allow for the effects of unmeasured genetic and environmental risk factors. In the future, the next generation of sequencing studies will go some way toward addressing some of these gaps. The pathway analysis using ALIGATOR relies on Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes pathways, Mouse Genome Informatics, and PANTHER-defined functional categories (28
). The ability to detect enriched pathways will depend on how well and how accurately biological processes are defined, and again, this knowledge will evolve over time.
In summary, in keeping with similarly sized previous genome-wide association studies of ADHD, we failed to find significantly associated common variants. We previously found large, rare CNVs to be associated with ADHD, and the results remain similar in this newly extended sample. Contrary to what some might expect, we found a highly significant overlap of biological pathways hit by both CNVs and SNPS. This implies that both types of gene variants are relevant to ADHD risk. Finally, our results suggest that CHRNA7 is a promising candidate to examine further.