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Meta-Analysis
. 2010 Sep;49(9):884-97.
doi: 10.1016/j.jaac.2010.06.008. Epub 2010 Aug 1.

Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder

Benjamin M Neale  1 , Sarah E Medland, Stephan Ripke, Philip Asherson, Barbara Franke, Klaus-Peter Lesch, Stephen V Faraone, Thuy Trang Nguyen, Helmut Schäfer, Peter Holmans, Mark Daly, Hans-Christoph Steinhausen, Christine Freitag, Andreas Reif, Tobias J Renner, Marcel Romanos, Jasmin Romanos, Susanne Walitza, Andreas Warnke, Jobst Meyer, Haukur Palmason, Jan Buitelaar, Alejandro Arias Vasquez, Nanda Lambregts-Rommelse, Michael Gill, Richard J L Anney, Kate Langely, Michael O'Donovan, Nigel Williams, Michael Owen, Anita Thapar, Lindsey Kent, Joseph Sergeant, Herbert Roeyers, Eric Mick, Joseph Biederman, Alysa Doyle, Susan Smalley, Sandra Loo, Hakon Hakonarson, Josephine Elia, Alexandre Todorov, Ana Miranda, Fernando Mulas, Richard P Ebstein, Aribert Rothenberger, Tobias Banaschewski, Robert D Oades, Edmund Sonuga-Barke, James McGough, Laura Nisenbaum, Frank Middleton, Xiaolan Hu, Stan Nelson; Psychiatric GWAS Consortium: ADHD Subgroup
Collaborators, Affiliations
Meta-Analysis

Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder

Benjamin M Neale et al. J Am Acad Child Adolesc Psychiatry. 2010 Sep.

Abstract

Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. As prior genome-wide association studies (GWAS) have not yielded significant results, we conducted a meta-analysis of existing studies to boost statistical power.

Method: We used data from four projects: a) the Children's Hospital of Philadelphia (CHOP); b) phase I of the International Multicenter ADHD Genetics project (IMAGE); c) phase II of IMAGE (IMAGE II); and d) the Pfizer-funded study from the University of California, Los Angeles, Washington University, and Massachusetts General Hospital (PUWMa). The final sample size consisted of 2,064 trios, 896 cases, and 2,455 controls. For each study, we imputed HapMap single nucleotide polymorphisms, computed association test statistics and transformed them to z-scores, and then combined weighted z-scores in a meta-analysis.

Results: No genome-wide significant associations were found, although an analysis of candidate genes suggests that they may be involved in the disorder.

Conclusions: Given that ADHD is a highly heritable disorder, our negative results suggest that the effects of common ADHD risk variants must, individually, be very small or that other types of variants, e.g., rare ones, account for much of the disorder's heritability.

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Figures

Figure 1
Figure 1
Quantile-Quantile (QQ) plot of the meta-analysis of four attention-deficit/hyperactivity disorder genome-wide associations studies. Note: The QQ plot shows the distribution of expected p-values based against observer distribution. There is slight inflammation in the distribution of results, as indicated by the lambda of 1.025. The red dashed line represents the 95% confidence interval for the distribution of results.
Figure 2
Figure 2
Regional association plots for the top three hits in the attention-deficit/hyperactivity disorder meta-analysis. Note: Three region association plots are shown here. On the x-axis is the base pair position based on the human genome 18 build, with gene regions coded in green. On the left y-axis, the log10(P-value) is reported. On the right y-axis, the recombination rate of cM per Mb is shown. The points are each individual single-nucleotide polymorphism (SNP), color-coded by r2 to the most significant SNP in the region with red indicating high values and white indicating low values.
Figure 2
Figure 2
Regional association plots for the top three hits in the attention-deficit/hyperactivity disorder meta-analysis. Note: Three region association plots are shown here. On the x-axis is the base pair position based on the human genome 18 build, with gene regions coded in green. On the left y-axis, the log10(P-value) is reported. On the right y-axis, the recombination rate of cM per Mb is shown. The points are each individual single-nucleotide polymorphism (SNP), color-coded by r2 to the most significant SNP in the region with red indicating high values and white indicating low values.
Figure 2
Figure 2
Regional association plots for the top three hits in the attention-deficit/hyperactivity disorder meta-analysis. Note: Three region association plots are shown here. On the x-axis is the base pair position based on the human genome 18 build, with gene regions coded in green. On the left y-axis, the log10(P-value) is reported. On the right y-axis, the recombination rate of cM per Mb is shown. The points are each individual single-nucleotide polymorphism (SNP), color-coded by r2 to the most significant SNP in the region with red indicating high values and white indicating low values.
Figure 3
Figure 3
Quantile-Quantile (QQ) plot of candidate genes. Note: The QQ plot shows the distribution of expected p-values based against the observer distribution. The red dashed line represents the 95% confidence interval for the distribution of results. These p-values are uncorrected.
See this image and copyright information in PMC

Comment in

  • The new genetics in child psychiatry.
    Hudziak JJ, Faraone SV. Hudziak JJ, et al. J Am Acad Child Adolesc Psychiatry. 2010 Aug;49(8):729-35. doi: 10.1016/j.jaac.2010.06.010. J Am Acad Child Adolesc Psychiatry. 2010. PMID: 20643308 No abstract available.

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