Case-Control Genome-Wide
Association Study of Attention-
Deficit/Hyperactivity Disorder
Benjamin M. Neale, Ph.D., Sarah Medland, Ph.D., Stephan Ripke, M.D.,
Richard J.L. Anney, Ph.D., Philip Asherson, M.R.C.Psych., Ph.D., Jan Buitelaar, M.D.,
Barbara Franke, Ph.D., Michael Gill, M.B., Bch, BAO, M.D., MRCPsych, F.T.C.D.,
Lindsey Kent, M.D., Ph.D., Peter Holmans, Ph.D., Frank Middleton, Ph.D.,
Anita Thapar, M.D., Klaus-Peter Lesch, M.D., Stephen V. Faraone, Ph.D.,
Mark Daly, Ph.D., Thuy Trang Nguyen, Dipl. Math. oec, Helmut Schäfer, Ph.D.,
Hans-Christoph Steinhausen, M.D., Ph.D., D.M.Sc., Andreas Reif, M.D.,
Tobias J. Renner, M.D., Marcel Romanos, M.D., Jasmin Romanos, M.D.,
Andreas Warnke, M.D., Ph.D., Susanne Walitza, M.D., Christine Freitag, M.D., M.A.,
Jobst Meyer, Ph.D., Haukur Palmason, Ph.D., Aribert Rothenberger, M.D., Ph.D.,
Ziarih Hawi, Joseph Sergeant, Ph.D., Herbert Roeyers, M.D., Ph.D., Eric Mick, Sc.D.,
Joseph Biederman, M.D., for the IMAGE II Consortium
Objective: Although twin and family studies have shown attention-deficit/hyperactivity
disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genomewide
significant level have yet to be identified. Thus additional genomewide association
studies (GWAS) are needed. Method: We used case-control analyses of 896 cases with
DSM-IV ADHD genotyped using the Affymetrix 5.0 array and 2,455 repository controls
screened for psychotic and bipolar symptoms genotyped using Affymetrix 6.0 arrays. A
consensus SNP set was imputed using BEAGLE 3.0, resulting in an analysis dataset of
1,033,244 SNPs. Data were analyzed using a generalized linear model. Results: No genomewide
significant associations were found. The most significant results implicated the following
genes: PRKG1, FLNC, TCERG1L, PPM1H, NXPH1, PPM1H, CDH13, HK1, and HKDC1.
Conclusions: The current analyses are a useful addition to the present literature and will
make a valuable contribution to future meta-analyses. The candidate gene findings are
consistent with a prior meta-analysis in suggesting that the effects of ADHD risk variants
must, individually, be very small and/or include multiple rare alleles. J. Am. Acad. Child
Adolesc. Psychiatry, 2010;49(9):906 –920. Key Words: ADHD, genetics, genome-wide association,
Imputation
Attention-deficit/hyperactivity disorder (ADHD) is among the most common childhood onset psychiatric disorders. The
worldwide prevalence of ADHD in children is 8% to 12%1 and the prevalence of ADHD in adults in the United States
is approximately 4%.2,3 Early studies found the risk of ADHD among parents of children with ADHD to be increased
by between two- and eightfold, with similarly elevated risk among the siblings of ADHD subjects (for a review of this
literature, see Faraone and Biederman 4). Faraone et al.5 extended these findings to families ascertained via adult
probands meeting criteria for either full DSM-IV ADHD or late-onset ADHD.
Adoption and twin studies are necessary to disentangle genetic from environmental sources of transmission observed
in family studies. Three studies found that biological relatives of ADHD 6 or hyperactive children 7,8 were more likely
to have hyperactivity than adoptive relatives. A more direct method of examining the heritability of ADHD is to study
twins: the extent to which monozygotic twins are more concordant for ADHD than dizygotic twins can be used to
compute the degree to which variability in ADHD in the population can be accounted for by genes (i.e., heritability).
Reviews of twin studies from the United States, Australia, Scandinavia and the European Union show heritability for
ADHD to be approximately 75%, which places it among the most heritable of psychiatric disorders.9–11
Candidate gene association studies have focused heavily on catecholaminergic pathways,16–20 the major target of most
pharmacotherapies for ADHD.21 However, genes within the serotonergic and neuro-developmental pathways have also
been examined. A meta-analysis found nominally significant (p < .05) associations at the following: SLC6A3/DAT1 (3'UTR
VNTR and rs27072), DRD4 (exon 3 VNTR and rs1800955), DRD5 (148-bp allele), SLC6A4/5HTT (5HTTLPR), HTR1B
(rs6296), and SNAP-25 (rs3746544)16; however, these effects, if present, are likely to be small and have not been
unequivocally confirmed by prior genome-wide association scans of ADHD.22–25
The present work continues the search for ADHD susceptibility genes by completing a new, independent, multi-site case-
control genome-wide association study (GWAS) of DSM-IV ADHD, using the Affymetrix 5.0 and 6.0 arrays.
In an attempt to find regions of chromosomes that might harbor genes for ADHD, several groups have conducted
genome-wide linkage scans. This approach examines many DNA markers across the genome to determine whether
any chromosomal regions are shared more often than expected among ADHD family members. These have produce
mixed results, with some reporting evidence of linkage 12,13 and others not.14 To determine whether there were any
significant linkage signals among these studies, Zhou et al.15 conducted a genome scan meta-analysis of these data.
They reported genome-wide significant linkage (pSR = .00034, pOR = .04) for a region on chromosome 16 between
64 Mb and 83 Mb. Although this finding is intriguing and worthy of follow-up, the lack of significant findings for other
loci suggests that many genes of moderately large effect are unlikely to exist, and that the method of association will
be more fruitful in the search for ADHD susceptibility genes.
Method
Participants
The 1,150 cases used in the present analysis consist of (a) samples collected by a subset of the International
Multicenter ADHD Genetics (IMAGE) Project sites but not included in the IMAGE GWAS 23; and (b) samples
collected at additional sites (Frankfurt/Homburg, Trier, Wuerzburg, Germany, Scotland, and Cardiff, United
Kingdom) that were assessed in a manner similar to IMAGE samples. Cases were identified mainly through
outpatient clinics at the data collection sites. They were predominantly of European origin from the United
Kingdom, Ireland, Germany, the Netherlands, and the United States. Of the cases, 81% met criteria for DSM-IV
ADHD. Children had been referred for assessment of hyperactive, disruptive or disorganized behavior and had
been clinically diagnosed as ADHD (or hyperkinetic disorder, the most closely equivalent category in the ICD-10
nomenclature used at some of the clinics). Clinical and demographic features of the case sample stratified by
site are provided in Table 1. All case data were collected with informed consent of parents and with the approval
of the site's institutional review board or ethical committee.
At the IMAGE sites, parents of children were interviewed with the Parental Account of Childhood Symptom
(PACS), a semi-structured, standardized, investigator-based interview developed as an instrument to provide
an objective measure of child behavior. Both parents and teachers completed the respective versions of the
Conners ADHD rating scales and the Strengths and Difficulties Questionnaire. Exclusion criteria were
autism, epilepsy, IQ <70, brain disorder, and any genetic or medical disorder associated with externalizing
behaviors that might mimic ADHD.
In Germany, families were recruited in order of clinical referral in the outpatient clinics in Wuerzburg,
Homburg, and Trier. Families were of German white ancestry. All cases met DSM-IV criteria for ADHD. The
index child was 6 years or more of age, and further affected siblings were included when at least 6 years of
age. All children were assessed by full semistructured interview (Kiddie-Sads-PL-German Version or Kinder-
DIPS) and parent and teacher ADHD DSM-IV–based rating scales to ensure pervasiveness of symptoms.
Exclusion criteria were IQ < 80, comorbid autistic disorders or somatic disorders (e.g., hyperthyroidism,
epilepsy, neurological diseases, severe head trauma), primary affective disorders, Tourette syndrome,
psychotic disorders or other severe primary psychiatric disorders, and birth weight <2,000 g.
At the Cardiff site, children ages 6 to 16, of British, Caucasian ancestry, were assessed by interviewing
parents with the Parent Child and Adolescent Psychiatric Assessment (CAPA)-a semi-structured research
diagnostic interview and a telephone interview with the teacher using the Child ADHD Teacher Telephone
Interview. All cases met diagnostic criteria for DSM-IV ADHD or ICD-10 hyperkinetic disorder or DSM-III-R
ADHD and had IQ test scores above 70. Exclusion criteria were pervasive developmental disorder, Tourette
syndrome, psychosis or any neurological conditions.
TABLE 1 Clinical and Demographic Characteristics of the Case Sample, Stratified by Site
At the Scottish site, children ages 6 to 16 years, of British white ancestry, were assessed by interviewing
parents with the Parent Child and Adolescent Psychiatric Assessment (CAPA), a semistructured research
diagnostic interview. To confirm pervasiveness, teachers completed the Conners Teacher Rating Scale. All
cases met diagnostic criteria for DSM-IV ADHD. Children with an IQ <70, autistic spectrum disorder, head
injury, known chromosomal abnormality, encephalitis or significant medical conditions such as epilepsy were
excluded.
The control sample (2,653 population controls of European ancestry) was collected for an institutional review
board–approved GWAS of schizophrenia and have been described elsewhere.26 Briefly, the control
participants were drawn from a US nationally representative survey panel (of approximately 60,000 adult
individuals at any one time, with constant turnover) ascertained via random digit dialing. Participants were
screened for psychosis and bipolar disorder. Control participants were not screened for ADHD. A blood
sample was collected via a US national phelbotomy service. Control participants gave written consent for
their DNA to be used for medical research at the discretion of NIMH.
Genotyping
Cases were genotyped using the Affymetrix 5.0 array at the State University of New York Upstate Medical University,
Syracuse using the standard protocol issued by Affymetrix. The genotypes were called using both BRLMM-P and
BIRDSUITE,27 with any calling discrepancies coded as missing. Controls were genotyped using the Affymetrix 6.0
array, at the Broad Institute National Center for Genotyping and Analysis. Genotype calls were made with the
BIRDSEED program, a module of the BIRDSUITE package.
The control genotype data initially quality controlled by the National Center for Biotechnology Information (NCBI). The
quality control (QC) of the control data has been described in detail elsewhere.26 Briefly, the 2,653 control samples
used in the present analyses had call rates >97%, genders consistent with site reports, and 26% to 28.5%
heterozygous genotypes, and were of European ancestry (as evaluated by EIGENSTRAT). The prior data-cleaning
efforts for this set of genotypes include SNP call rate <95%, Hardy–Weinberg equilibrium, p value <10-6, MAF <1%,
plate effects, and removal of SNPs showing more than two Mendelian errors (from a set of trios that are not included
in these analyses) or discordant genotypes for duplicate samples.
QC and Statistical Analyses
As the cases and controls were genotyped using different platforms, we undertook additional QC checks before
conducting imputation. To ensure imputation quality, we applied more stringent QC exclusion thresholds and carefully
examined differences between cases and controls. Our key criterion for QC consideration was call rate at the sample
and SNP levels, as well as call rate differences between cases and controls. These sample and SNP exclusion criteria
are found in Table 2.
TABLE 2 Summary of Case and Control Quality Control (QC) Filtering and Exclusion Criteria, in Order of Operation
