Subjects: case-control study

ADHD subjects involved in our initial case-control study were consented and enrolled at Vanderbilt University Medical Center (VUMC), Nashville, TN, USA and the University of Chicago Children’s Hospital, Chicago, IL, USA. Subject ascertainment was performed under a protocol approved by the Institutional Review Boards of both institutions. The VUMC sample consisted of 50 unrelated and 10 affected sib pairs (n = 63 subjects genotyped; 81% male/19% female; 51% Cacasian/12% African American) ranging from 6–17 years of age. The Kiddie-SADS-Present and Lifetime Version [35] was used to determine DSM-IV criteria for ADHD subtypes [36]. The University of Chicago cohort (n = 37 subjects genotyped; 70% male/30% female; 86% Caucasian/14% African American) consisted of a subset of unrelated children who had participated in an earlier pharmacogenetic study [37]. All subjects completed a semi-structured diagnostic interview and met DSM-IV criteria for ADHD. Children were excluded if they carried a diagnosis of autism or other brain disorders such as mental retardation. The Vanderbilt University control cohort consisted of 290 subjects, between 18–45 years of age that displayed no clinically significant abnormality based upon medical history, physical examination and routine laboratory testing.

Subjects: within-family association study

Clinic-referred sample

Four hundred and three children from 251 families were consented and enrolled from two sites, Atlanta, Georgia and Tucson, Arizona, USA (see Suppl Table 1 for details). The Emory University and University of Arizona Institutional Review Boards reviewed and approved the assessment procedures utilized. At the Atlanta site, subjects were recruited through the Center for Learning and Attention Deficit Disorders (CLADD) at the Emory University School of Medicine and the Emory University Psychological Center. Both clinics specialize in the assessment of childhood externalizing disorders such as ADHD, Oppositional Defiant Disorder (ODD), Conduct Disorder (CD) and learning disorders. At the Tucson site, subjects were recruited through a group psychiatric practice. Probands and their siblings between the ages of 4 and 18 (M = 10.7, SD = 3.9) were then recruited to participate in the current study. Any child previously diagnosed with autism, traumatic brain injury, or neurological conditions (e.g., epilepsy) was excluded from the study, as were children with IQs <75. Any other diagnosis previously assigned to a child remained confidential and did not influence inclusion in the study. Control subjects were also recruited from sites in Atlanta, Georgia and Tucson, Arizona. Subjects recruited at the Atlanta site represent a subsample of the Georgia Twin Registry, a sample of twins born between 1980 and 1991 recruited via birth records from the general population of Georgia. Twin families were originally recruited by mail to participate in a questionnaire-based study of childhood psychopathology. A subset of these families was contacted by phone to participate in a follow-up lab study of temperament and cognitive development that included DNA collection. Subjects from the Tucson site were drawn from the general population.

Parental ratings were obtained whenever possible for each child using the Emory Diagnostic Rating Scale (EDRS) [38], a symptom checklist developed to assess symptoms of major DSM-IV childhood psychiatric disorders such as ADHD, ODD, and CD. Because some children were being treated with medication, parents were asked to rate the status of the child’s symptoms when off medication. Parents rated each symptom on a 0–4 scale, with a score of 0 indicating that the symptom is “not at all” characteristic of the child and a score of 4 indicating that the symptom is “very much” characteristic of the child. Inattentive and hyperactive-impulsive symptom scores were generated by averaging the scores for the 9 items that constitute each symptom dimension. For the purposes of making ADHD and subtype diagnoses, ratings ≥2 for each symptom indicated that a symptom was present. In the case of discrepant parent ratings for a specific symptom, the symptom was considered present if endorsed (i.e., rated ≥2) by the mother when assigning ADHD diagnoses and the mother’s score was then used when creating symptom scales. Consistent with previous studies, mother and father ratings showed moderate agreement (r = .76 for inattentive symptoms and r = .69 for hyperactive-impulsive symptoms) [39]. Questionnaire-based diagnoses of ADHD and its constituent subtypes were assigned by applying DSM-IV symptom thresholds to each of the ADHD symptom dimensions. An earlier study demonstrated that the EDRS yielded diagnostic rates in a control population that were similar to the prevalence rates described in the DSM-IV [40]. The internal consistencies of the 9 hyperactive-impulsive symptoms and the 9 inattentive symptoms were independently evaluated in the clinic-referred and control samples to ensure acceptable reliabilities (values ranged from α = .85–.96).

Genotyping

DNA was collected from either buccal samples or from whole blood and extracted using a commercial DNA isolation kit (Gentra systems, Minneapolis, MN) as previously described [41]. An allelic discrimination assay was performed in the Vanderbilt Center for Human Genetics Research DNA Resources Core using TaqMan® SNP Genotyping Assay reagents (Applied Biosystems, Inc). Four nanograms (ng) of DNA (some samples had been subjected to one round of genomic amplification (Roche) with no evidence of altered SNP calls) was used as template in reactions containing 1X TaqMan® Universal PCR Master Mix and, for CHT Ile89Val (rs1013490), 900 nM forward (5’-TGTACCAGGTTATGGCCTAGCTT-3’) and reverse (5’-ACTGAGATTTGCACTTTCACTTACCT-3’) amplification primers, 200 nM VIC® (5’-CAGGCACCAATTGGATA-3’) and FAM® (5’-AGGCACCAGTTGGATA-3’) dye-labeled probes or, for the CHT 3’SNP (3’SNP, rs333229), forward (5’-GTGGACACACTTCTGGAGATTATACATTT-3’) and reverse (5’-GTCCACGGGCCCTAATATTATATTCT-3’) and 200 nM VIC® (5’- CTCTTAATAATTCCCCCCCACACT-3’) and FAM® (5’- CTCTTAATAATTCACCCCACACT-3’) dye-labeled probes. The 3’SNP has been previously described as a “3’UTR SNP” [33, 34] but our current genomic analyses place the variant 3’ of predicted polyadenylation sites and could not be identified with deposited ESTs. Thermal cycling (95°C for 10 min, followed by 50 cycles of 92°C for 15 sec and 60°C for 1 min) and product detection were accomplished using the ABI 7900HT Real-Time PCR System (ABI).

We conducted quality control analyses of the CHT SNP genotype data in our family samples. The call rate in our sample was 93% for the Ile89Val SNP and 94% for the 3’SNP. Reliability of the genotyping was assessed by examining the concordance of genotypes of twins within MZ twin pairs, in which there were no disagreements between the genotypes for the Ile89Val SNP (an allelic discordance rate = 0%, N = 68 alleles) and only one disagreement for the 3’SNP (an allelic discordance rate = 1.4%, N = 74 alleles). There were no Mendelian errors in the genotyping of the Ile89Val SNP whereas there were 8 errors for the 3’SNP, yielding a Mendelian error rate = 0.9%.

Data analyses

Crosstab analyses using SPSS version 15 (SPSS, Inc., Chicago, IL) were conducted for quality control analyses that included measures of genotype reliability and MZ twin agreement for genotypes. Call rates, Mendelian error rates, and exact Hardy Weinberg Equilibrium (HWE) tests and p-values were also estimated using the program PEDSTATS [42]. For the case-control studies, genotype call rates were found to be within HWE and significance determined using the χ2-test (results shown below). To protect against the possibility of interpreting a spurious association as substantive, significant results from the case-control analyses were then followed-up in an independent sample using family-based tests of association with the associated alleles from the case-control analyses designated as the ‘risk’ alleles.

Extensions of the Transmission Disequilibrium Test (i.e., TDT) [43] that are applicable to both categorical and continuous variables and tests of moderation [44–47] were used for family-based analyses of association and linkage. Such analyses have the advantage of robustness against possible population stratification effects that may bias the results of traditional case-control comparisons or other population-based analyses of association. A unifying approach to family-based association tests (FBATs) has been developed and implemented in the software packages FBAT and PBAT. Derived from the TDT, the FBAT and PBAT approaches have been extended to incorporate both intact and missing parental genotypes without introducing bias as well as affected and unaffected siblings and extended pedigrees [45, 48–50]. The FBAT and PBAT software packages also allow for the contribution of unaffected control subjects in the calculation of the FBAT test statistic. By specifying an offset equal to the population prevalence of the disorder, the FBAT and PBAT software makes use of genotypic transmissions in case and control subjects by contrasting the number of transmissions of a specific allele in the case population with the number of non-transmissions of that allele in the control population [45]. As such, both case and control subjects can be utilized within a TDT framework. Specifying the offset also serves to minimize the variance of the test statistic and increase statistical power [51]. Thus, the prevalence of the ADHD diagnosis and the respective subtypes in the control sample as assessed by the EDRS were used as offset values in the current study.

We also used a recently developed extension of the TDT [52] to test a priori hypotheses for the contrasts among the diagnostic subtypes. In this method, transmissions of a particular allele from heterozygous parents to children with a subtype of interest are contrasted with transmissions to children who have the other subtypes or who are unaffected. We implemented this test within the FBAT/PBAT analytic framework to test for the association of CHT SNPs with the Inattentive and Combined ADHD subtypes (the Hyperactive-Impulsive subtype was not tested due to small sample size). All of the analyses conducted in FBAT and PBAT yield a Z statistic that was used in hypothesis testing and which was converted into the effect size index R2 (i.e., proportion of the variance accounted for) using the formula Z 2 / N, where N = the number of informative families. Odds Ratios (OR) were calculated by first converting the R2 value into the effect size Cohen’s d using the formula d = (2 * R)/ √(1 - R2)[53], and then calculating an OR using the formula e(1.81 * d) described by Chinn [54].