Despite strong pharmacological evidence implicating the norepinephrine transporter in ADHD, genetic studies have yielded largely insignificant results. We tested the association between 30 tag SNPs within the SLC6A2 gene and ADHD, with stratification based on maternal smoking during pregnancy, an environmental factor strongly associated with ADHD.
Children (6–12 years old) diagnosed with ADHD according to DSM-IV criteria were comprehensively evaluated with regard to several behavioral and cognitive dimensions of ADHD as well as response to a fixed dose of methylphenidate (MPH) using a double-blind placebo controlled crossover trial. Family-based association tests (FBAT), including categorical and quantitative trait analyses, were conducted in 377 nuclear families.
A highly significant association was observed with rs36021 (and linked SNPs) in the group where mothers smoked during pregnancy. Association was noted with categorical DSM-IV ADHD diagnosis (Z = 3.74, P = 0.0002), behavioral assessments by parents (CBCL, P = 0.00008), as well as restless-impulsive subscale scores on Conners’-teachers (P = 0.006) and parents (P = 0.006). In this subgroup, significant association was also observed with cognitive deficits, more specifically sustained attention, spatial working memory, planning, and response inhibition. The risk allele was associated with significant improvement of behavior as measured by research staff (Z = 3.28, P = 0.001), parents (Z = 2.62, P = 0.009), as well as evaluation in the simulated academic environment (Z = 3.58, P = 0.0003).
By using maternal smoking during pregnancy to index a putatively more homogeneous group of ADHD, highly significant associations were observed between tag SNPs within SLC6A2 and ADHD diagnosis, behavioral and cognitive measures relevant to ADHD and response to MPH. This comprehensive phenotype/genotype analysis may help to further understand this complex disorder and improve its treatment. Clinical trial registration information – Clinical and Pharmacogenetic Study of Attention Deficit with Hyperactivity Disorder (ADHD); www.clinicaltrials.gov; NCT00483106.
Citation: Thakur GA, Sengupta SM, Grizenko N, Choudhry Z, Joober R (2012) Comprehensive Phenotype/Genotype Analyses of the Norepinephrine Transporter Gene (SLC6A2) in ADHD: Relation to Maternal Smoking during Pregnancy. PLoS ONE 7(11): e49616. doi:10.1371/journal.pone.0049616
Editor: Takeo Yoshikawa, Rikagaku Kenkyūsho Brain Science Institute, Japan
Received: August 7, 2012; Accepted: October 11, 2012; Published: November 20, 2012
Copyright: © 2012 Thakur et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported in part by grants from the Fonds de la recherche en santé du Québec and the Canadian Institutes of Health Research to RJ. GAT holds a Frederick Banting and Charles Best Canada Graduate Scholarship doctoral award from CIHR. SS is a recipient of the 2008 NARSAD Young Investigator and 2009 Dr.Mortimer D. Sackler Developmental Psychology Investigator Awards. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent psychiatric disorder, with rates ranging from 5.9–7.1% in children and adolescents . It is heterogeneous in its clinical expression, with core symptoms of poor sustained attention, impulsivity, and hyperactivity. It is often associated with cognitive deficits, particularly in executive function and sustained attention. ADHD has an important genetic component, with a mean heritability estimate of 76%,  and it has been suggested that multiple genes are involved, each having a small effect. .
Psychostimulants, mostly methylphenidate (MPH)  are the first-line of treatment for ADHD. These medications are known to block the dopamine (DA) and norepinephrine (NE) transporters, resulting in increased synaptic concentration of both neurotransmitters. , ,  Short-term trials have concluded that MPH is efficacious in reducing ADHD symptoms in approximately 70% of affected children  and adults.  NE-specific pharmacological agents (including clonidine, guanfacine, desipramine, and atomoxetine) are effective in treating ADHD, thereby implicating this catecholamine as a major player in the pathophysiology of the disorder.  These studies reinforced the early evidence from neurochemical research that NE is involved in ADHD. ,  Neuroimaging  and animal studies  have provided further evidence for the role of NE in ADHD.
The NE transporter protein is a pivotal player in the regulation of catecholamines, involved in the re-uptake of both NE and DA into presynaptic terminals. Thus, it plays a key role in controlling the intensity and duration of signal transduction. The NE transporter is a member of the sodium- and chloride-dependent neurotransmitter transporter family, a transmembrane glycoprotein.  It is encoded by SLC6A2 which has been mapped to 16 q12.2.  The gene includes 14 exons spanning 45 kb,  predicting a protein of 617 amino acids.  Given the clinical efficacy of agents that block the NE transporter (including psychostimulants, MPH and amphetamine, and the NE-specific agent, atomoxetine), there has been considerable interest in SLC6A2 as a candidate in genetic and pharmacogenetic studies of ADHD. Importance of the NE transporter has been further emphasized since it is responsible for the reuptake of both NE and DA in the prefrontal cortex (PFC), a brain region critical for attention regulation and where there is a scarcity of the dopamine transporter , , thus pointing to a potentially greater role of the norepinephrine transporter.
Several family-based , , , , , , , , , ,  and case-control , , , , , ,  studies have investigated the association between specific polymorphisms within SLC6A2 and ADHD. While initial studies were conducted with a limited number of single nucleotide polymorphisms (SNPs) , , , , recent association studies have used arrays of SNPs covering the entire gene. , , , ,  A number of studies have examined the association between a functional SNP in the promoter region of the gene [−3081(A/T), rs28386840] and ADHD. , , , ,  Furthermore, association between SLC6A2 and ADHD endophenotypes, including neurocognitive measures ,  or quantitative symptom scores,  has also been studied.
Although many studies have been conducted thus far, findings have been limited and difficult to replicate. An earlier study reported an association between rs3785157 and rs998424 and ADHD.  Later, an independent group reported a trend for association with both these SNPs, however opposite alleles were conferring risk for the disorder in this study.  Although these results were not confirmed in the International Multi-centre ADHD Gene (IMAGE) project, associations were reported with two other SNPs (rs3785143, rs11568324),  and these were confirmed in two independent samples. ,  Several related groups have reported an association between ADHD and a functional promoter SNP rs28386840 [−3081(A/T)], using a case-control study design. , ,  However, two large family-based studies (one with more than 99% power), conducted by independent groups, failed to replicate this association. , .
Although several pharmacogenetic studies, including a genome-wide association study,  have examined the association between SLC6A2 SNPs and response to MPH , ,  (or OROS-MPH , ) treatment, only limited association was observed with a few polymorphisms (rs5569, rs28386840, rs17841329, and rs192303) with little replication between studies.
We have conducted a family-based study to test the association between a panel of 30 SNPs within SLC6A2 and ADHD. In addition to the DSM-IV diagnosis of ADHD, quantitative behavioral and cognitive phenotypes, as well as response of these measures with MPH treatment, were tested for association. The panel of SNPs included those analyzed in the IMAGE project (excluding SNPs having a minor allele frequency ≤0.02),  two SNPs selected to extend the 3′ flanking region examined (rs15534, rs7188230), and the functional promoter SNP, rs28386840.
Given that high comorbidity between ADHD and cigarette smoking (35%–45%) is well documented , and that children with ADHD are consistently reported to have higher exposure to cigarette smoking during pregnancy compared to the general population (OR = 2.39),  analyses were conducted based on stratification by maternal smoking during pregnancy (MSDP). Also, it has been suggested that shared pathways to the two pathologies may exist, at least in some groups of individuals,  and more precisely, with respect to monoamine dysregulation. The aim of the current study was to examine the differential association (if any) of genetic polymorphisms within SLC6A2 after MSDP stratification.
The study was approved by the Douglas Mental Health University Institute (DMHUI) Research and Ethics Board. All participating children agreed to take part in the study, and parents provided written consent.
Four hundred and seventy-five children with ADHD between 6 and 12 years of age [mean = 9; SD = 1.8] were included in this study. They were referred by schools, social workers, family doctors and pediatricians, and were recruited from the Disruptive Behavior Disorders Program and the children’s outpatient clinics of the DMHUI, a psychiatric teaching hospital in Montreal, Canada.
Each child was diagnosed with ADHD according to DSM-IV criteria. Further details pertaining to diagnostic procedures have previously been described. ,  Of the total number of affected children, 77.9% were male and 82.5% were of Caucasian ethnicity. 54.1% met DSM-IV criteria for the combined subtype, while 35.6% and 10.3% were diagnosed with the inattentive and hyperactive subtypes, respectively. Among comorbid disorders, 40.6% had oppositional defiant disorder, 22.9% had conduct disorder, 46.2% had anxiety disorder (including specific phobias), and 8.8% had a mood disorder (either/or major depressive episode, dysthymic disorder, manic episode, hypomanic episode).
The Conners’ Global Index for Parents (Conners’-P) and for Teachers (Conners’-T) ,  were used to evaluate the behavior of the child at home and in the classroom, respectively. The Conners’ Global Index scale has been validated from a genetic point of view, with research showing that genetic factors account for up to 78% of its variance.  Parents were also asked to complete the Child Behavior Checklist (CBCL), a comprehensive rating scale (113-item questionnaire) with well-established metric characteristics and representative norms.  The raw scores of these scales were transformed into standardized T scores with an average of 50; where a score higher than 65 is considered to be clinical. The mean (standard deviation) for the total CBCL, Conners’-P, and Conners’-T scores were: 68.6 (8.9), 73.1 (11.4), and 69.5 (12.7), respectively, in this sample of children. Since it has been shown that a low to moderate correlation exists between parent and teacher reports of ADHD symptoms, and that each may assess a different dimension of the child’s behavior , , , by collecting information from both parents and teachers, a comprehensive assessment of the child’s behavior was obtained.
In addition to clinical dimensions of ADHD, neuropsychological measures, mainly of executive function (EF), were included as quantitative traits in the genetic association analyses. EF encapsulates the range of cognitive abilities that are important for self-regulation and goal-directed behaviors, including response inhibition, sustained attention, working memory, set-shifting, planning, and organization. Deficits in EF have been implicated in the underlying pathophysiology of ADHD.  The following tests were included in the neuropsychological battery: Wisconsin Card Sorting Test (WCST; measure of cognitive flexibility and set-shifting),  Tower of London test (TOL; planning, organization, and problem-solving capacity),  Self-Ordered Pointing Task (SOPT; visual working memory, planning and response inhibition),  Conners’ Continuous Performance Test (CPT; attention, response inhibition, and impulse control)_ENREF_57  and Finger Windows (FW; visual-spatial working memory).  The WCST, TOL, SOPT, and CPT were performed as described elsewhere. ,  FW is a subtest of the Wide Range Assessment of Memory and Learning (WRAML). In this test, the child is required to repeat a sequential placement of a pencil into a series of holes on a plastic card, as conducted by the examiner. When children were medicated prior to their inclusion in the study, clinical and neuropsychological assessments were carried out at the end of a one-week washout period to limit variability due to medication effects.  In addition to these EF measures, IQ (full scale, verbal, and performance) was evaluated using the Wechsler Intelligence Scale (WISC-III/IV). .
Response to treatment with methylphenidate (MPH) was assessed in a double-blind, placebo-controlled, within-subject (crossover) randomized control trial conducted over a two-week period, as described (trial registration number: NCT00483106).  Following a one-week wash-out period, subjects received either one week of treatment with placebo (PBO) or one week of treatment with 0.5 mg/kg of MPH in a divided b.i.d. dose (0.25 mg/kg, morning and noon), and were then crossed over. At the end of each treatment week, parents and teacher were asked to evaluate the child’s behavior using the Conners’-P and Conners’-T, respectively. Assessments were performed before and after the administration of PBO and MPH. In addition, the clinical staff completed the Clinical Global Impression (CGI)-overall improvement scale based on their half day of behavioral observation while the child was completing various tasks in the clinic. In this study, MPH was used as a pharmacological probe to dynamically study the genetics of ADHD, rather than a classical trial of response to medication.
The Restricted Academic Situation Scale (RASS) was used to assess task-oriented behavior. During a simulated independent academic situation within a clinic setting , the child is assigned a set of math problems and the RASS (coding system) is used to record the child’s behavior as well as his or her ability for sustained attention to routine, repetitive academic work in the presence of potential distractions, with no adult supervision.  The task has previously been described in detail.  Over a 15 minute period, behavioral events are recorded at 30 second intervals, according to five categories: off-task (looking away from the task sheet), playing with objects (touching any object not directly used in the task), out of seat (lifting buttocks off chair or moving chair), vocalizing (any vocal noise, whether task related or not), and fidgeting (repetitive, purposeless movements). The RASS score is the total number of recorded behavioral events, and the difference score is obtained by subtracting the score after MPH administration from the score obtained after PBO. We have previously reported results from principal component analysis of the RASS  showing that off-task, out-of-seat, and playing with objects consist of one factor, while vocalizing and fidgeting appear to be independent factors.
Families were invited to participate in the genetic component of the study, where DNA was extracted, for each parent and child, from a blood sample, buccal swab, or saliva sample, if the subject was only amenable to the latter. Of the 377 nuclear families with one or more children diagnosed with ADHD, 184 were complete trios with information from both parents, 11 were trios with two affected children, 67 were trios with information from one parent and one or more unaffected sibling, 103 were duos including the proband and one parent, while 12 were families with two affected siblings and one parent.
Tag SNPs within SLC6A2, previously examined in the IMAGE project, were genotyped . Those with a very low minor allele frequency (MAF ≤0.02) were excluded, with one exception: rs11568324 (MAF = 0.01), since this SNP was shown to be associated with ADHD in the original IMAGE study  and in a subsequent replication study.  Another SNP (rs28386840) which encodes a functional polymorphism in the upstream promoter region of SLC6A2, was also included in the panel, since it has been associated with ADHD . In order to extend the flanking region examined in SLC6A2, two SNPs (rs15534, present in exon 14; rs7188230, present in the 3′ intergenic region) not genotyped in the IMAGE study, were also included in this study.
Sequenom iPlex Gold Technology  was used to genotype the panel of SNPs, where each plate included duplicates of two reference samples to estimate genotyping error. Genotypes for these samples were read with 100% accuracy on each of the plates. Five SNPs in the original panel in the IMAGE study (rs7201099, rs3760019, rs1362620, rs1861647, rs1566652) could not be genotyped on the Sequenom platform. Since these SNPs were in strong linkage disequilibrium (LD) with other SNPs in the panel, and were not shown to be specifically associated in any previous studies, they were excluded from subsequent analyses. The genotype distribution at each of the markers analyzed in this study did not depart from Hardy-Weinberg equilibrium.  By using genotype information from the current study  and the default definition in Haploview , an LD plot was generated in Haploview v4.0. In this method, 95% confidence bounds on D’ are generated for each pairwise comparison. A SNP block is formed if 95% of the informative comparisons are in strong LD with each other. As indicated by the color coded cells seen in Tables 1–6 and 8–10, three major haplotype blocks exist in SLC6A2.
Family-based tests of association (which examine the transmission disequilibrium of a specific allele/haplotype from parent to affected offspring) were conducted using the FBAT statistical package (version 2.0.3).  All analyses were performed under the assumption of an additive model, with a null hypothesis of no linkage and no association. Tests were first conducted with the total sample, and then by maternal smoking during pregnancy stratification (MSDP). Of the total number of nuclear families in the study (n = 377), we had information related to MSDP for 366 families, where 206 were coded as ‘non-smoking’ and 160 as ‘smoking’.
As noted in Tables 1, 2, and 3, marginal association was observed with several behavioral and cognitive dimensions of ADHD in the total sample. However, the most significant result was noted when FBAT analysis was conducted in the stratified group where mothers smoked during pregnancy (Table 4). Whereas a marginal association was observed with rs36021 in the total sample (Z = 2.54, P = 0.01), a highly significant association was observed on every measure tested, as well as treatment response in the stratified sample. The T allele of this SNP appears to be the risk allele for ADHD, showing an association with the categorical DSM-IV diagnosis (Z = 3.74, P = 0.0002). In the quantitative FBAT analysis, the T allele was over-transmitted to the higher number of inattention (Z = 3.91, P = 0.00009), hyperactivity (Z = 3.33, P = 0.0009), and impulsivity (Z = 2.93, P = 0.003) items on the DISC-IV, higher CBCL total scores (Z = 3.95, P = 0.00008) (as well as each of the dimensional scores), higher restless-impulsive subscale scores of Conners’-T (Z = 2.72, P = 0.006) and Conners’-P (Z = 2.75, P = 0.006). Taken together, this suggests that the T allele is associated with more severe psychopathology, as assessed in the home, school, and clinic.
In terms of cognitive function, the risk allele was associated with worse performance on the SOPT (Z = 3.69, P = 0.0002), CPT and WCST (Table 5). Since the SOPT score is not a standardized score, higher scores imply worse performance, i.e. poor spatial working memory, planning, and response inhibition. A highly significant association was observed with the CPT overall index (a weighted sum of all measures within the CPT) (Z = 3.49, P = 0.0005). The risk allele was over-transmitted to the higher scores, with higher T-scores implying worse performance. In particular, an association was noted with several dimensions evaluated in this test – hit reaction time (RT) standard error (SE) (Z = 3.5, P = 0.0005) and variability of SE (Z = 3.0, P = 0.003). High T-scores on these measures indicate highly variable reactions to the “target” and “non-target”, often related to inattentiveness.  Highly significant association was also observed with hit RT block change (Z = 3.74, P = 0.0002) and hit SE block change (Z = 2.86, P = 0.004). Here, the higher T-scores indicate a slowing in reaction time, as well as a loss of consistency, which together suggest a loss of vigilance, as the test progresses. The risk allele was also associated with poor performance on the WCST, which measures cognitive flexibility and set-shifting. The T allele showed an under-transmission (negative Z score) to the higher scores, specifically with non-perseverative errors (the higher standard scores imply a better performance on the test) (Z = -3.44, P = 0.0006). No association was observed with perseverative errors or responses. On the WCST, perseverative errors occur due to an inability to shift set, despite negative feedback.  Non-perseverative errors are incorrect categorizations not related to perseveration, and usually arise from distractibility as well as deficits in updating and monitoring working memory. Therefore, it appears that in the group where mothers smoked during pregnancy, children with the T allele at rs36021 exhibit EF deficits, specifically sustained attention (characterized by distractibility during the task and loss of vigilance as the test progresses), spatial working memory, planning, and response inhibition.
The T allele was also associated with response to MPH treatment (Table 6). The risk allele was associated with greater improvement as indexed by a higher change score (score after PBO – score after MPH) on the CGI (Z = 3.275, P = 0.001), Conners’-P (Z = 2.62, P = 0.009), as well as evaluation in the simulated academic environment, (Z = 3.58, P = 0.0003). Based on the factor structure of the RASS,  change scores were examined for fidgeting, vocalizing and task disengagement. Association was observed with the task disengagement factor (Z = 3.44, P = 0.0006), but not with the other factors.
FBAT analysis in the group where mothers smoked during pregnancy also showed significant association between other SNPs towards the 5′end of SLC6A2 and one or more behavioral/cognitive measures. These included: rs41154, rs187714, and to a lesser extent, rs4783899, rs2397771, and rs192303. Based on calculation of D’ and r2 in Haploview, it was noted that these markers are in strong LD with rs36021 (Table 7), explaining the parallel association observed on several of the measures. Conversely, markers that are not in strong LD with rs36021 (such as rs36023 and rs36024) do not show an association with ADHD or any of the relevant dimensions in this sub-group.
In the sample where mothers did not smoke during pregnancy, marginal association with rs3785152 was observed on several behavioral and cognitive dimensions (Tables 8, 9, 10). In contrast, this SNP showed a highly significant association with treatment response. As with rs36021, the C allele was associated with significant improvement on behavioral evaluations; CGI [PBO – MPH] (Z = 3.5, P = 0.0005), RASS task-disengagement (PBO – MPH) (Z = 3.58, P = 0.0003). No association was observed with rs36021 in this group. It is interesting that two adjacent SNPs (rs36021 and rs3785152) show highly divergent association in the two groups. In fact, LD between these two SNPs is low (Table 7). Therefore, it is likely that a recombination event at or close to these two SNPs resulted in at least two distinct variants of SLC6A2. Association was also observed with rs1814269, rs5569, rs998424, and rs36009 in this group, though the significance was marginal.
Conducting stratified analyses based on MSDP provides great insight into the complex association between SLC6A2 and ADHD. Although pharmacological, imaging, and neuropsychological studies have extensively implicated the norepinephrine transporter in ADHD, genetic studies have shown a minimal association. Although associations have been reported, non-replication between studies has resulted in a lack of overall significance when a meta-analysis was conducted.  Results presented here, and in an earlier report,  support the view that the lack of replication between studies may be explained, at least in part, by the inherent clinical and etiological complexity of the disorders.
The association between MSDP and ADHD is one of the most investigated in the field of environmental psychiatric epidemiology. Although consistently replicated , ,  and high in magnitude, there is now relative consensus that this association has little causal significance ,  and may instead be driven by other variables that are shared by the behavior of smoking during pregnancy in mothers and ADHD in their children. While environmental factors may play a role in this association, it is believed that genetic factors shared by mother and child play an important role in smoking during pregnancy in the former and ADHD in the latter. In this study, MSDP was used to index a subtype of ADHD with putatively more homogeneous genetic determinants shared within families of children with ADHD where mothers smoked during pregnancy. Consistent with this hypothesis, we have reported  that children in this subgroup present a more severe clinical picture with greater behavioral problems and lower cognitive function, when compared to children whose mothers did not smoke during pregnancy, and that this difference in clinical phenotype is significant even when important environmental factors are controlled for. The results of the current study emphasize the genetic differences in these two subtypes. Polymorphisms (rs36021 and linked SNPs) are important genetic determinants of behavior, cognition, and treatment response in ADHD children whose mothers smoked during pregnancy, and who may represent a more homogeneous group of ADHD patients, as previously reported.  In the subtype where mothers did not smoke during pregnancy, an association with a different region of the gene (towards the 3′ end of SLC6A2) is observed.
Given that the association between ADHD and rs36021 (and linked SNPs) is highly significant only in those children whose mothers smoked during pregnancy may suggest a true interaction between exposure to maternal smoking and carrying the risk allele(s) in the SLC6A2 gene. Indeed, the adverse consequences of in utero exposure to the toxic effects of nicotine are well documented, from animal and human studies.  MSDP is associated with pre- and peri-natal complications, deficits in cognitive development as well as long-term behavioral problems. Alternatively, but not exclusively, the etiology of smoking behavior and ADHD may involve closely related, but distinct pathways. Indeed, it is possible that the complex genetic background underlying smoking behaviors in mothers (which is transmitted in part to their children), interacts with risk alleles in SLC6A2 to increase the risk for ADHD in children. Under the latter scenario, MSDP may be considered as a phenotypic index used to select a subgroup of children with relatively more homogeneous genetic etiology.
Irrespective of the precise links between these pathways, this study strongly suggests that genetic variation in the SLC6A2 is an important factor in a more severe subtype of ADHD. If replicated in independent studies, this may represent an important step towards personalized medicine in treating children with ADHD. .
Results of the present study are perfectly congruent with reports by Song et al  and Yang et al,  but only in the group where mothers did not smoke during pregnancy. In this group, a significant over-transmission of the G allele to the higher difference scores was observed in the quantitative FBAT analysis on the Conners’-T (Table 10). Most of this effect appears to arise from the restless-impulsive factor scores, observed only in the group of non-smoking mothers. It is noted that when treatment response was assessed using the CGI-Improvement scale, two previous studies, ,  as well as the current study, did not find an association with 1287(G/A) (rs5569) (Table 10).
Several other previously-reported associations were replicated in the present study. Three studies had reported an association with rs3785143 and rs11568324. , ,  These markers are in complete LD with rs36021 (D’ = 1; albeit with a low correlation coefficient, r2; Table 7), indicating that the 3 SNPs are in one haplotype block not separated by a recombination event. In the total sample, rs3785143 showed marginal association with ADHD, but a significant association with all CBCL dimensional scores (Table 1). No association was observed when stratified analyses were carried out. Similarly, no association was observed with rs11568324 despite the fact that it is in complete LD with rs36021. This is most likely a result of the low heterozygosity of these markers, which make them non-informative in the FBAT analysis (as indicated by the number of informative families in Table 1). Two other previously-implicated SNPs, rs998424 and rs36017, showed marginal association with dimensions of ADHD in the sample where mothers did not smoke during pregnancy and the total sample, respectively.
Kim and colleagues , ,  reported an association between ADHD and a functional promoter SNP rs28386840 [-3081(A/T)] in several independent case-control studies. This association was not replicated in the current study, neither in the total sample, nor in the samples stratified by MSDP (Tables 1, 4, 8). The lack of association with ADHD was also reported in two other family-based studies. ,  A study examining the association between this polymorphism and treatment response reported an association with CGI-improvement scores , where T-allele carriers showed a better response to MPH treatment. In the current study, only a marginal association was observed with difference scores on the restless-impulsive subscale of the Conners’-T in the group where mothers smoked during pregnancy (Table 6).
In a previous report,  we investigated the association between ADHD and the panel of 30 SNPs examined in the present study, and noted that a complex pattern of association emerged between SLC6A2 SNPs/haplotypes, ADHD subtypes and gender. Gender and subtype are considered two dimensions that might help in reducing genetic heterogeneity in the ADHD syndrome. Although these results helped explain some of the discrepancies noted among previous studies, stratification according to these dimensions did not yield as strong an association with SLC6A2 as the stratification based on MSDP, which may suggest that the latter is more pertinent for future efforts to map genes implicated in ADHD.
SNPs that showed the most significant association in this study (rs36021 and rs3785152, in particular) are within introns, opening up two possibilities. The first possibility is that these intronic variants are involved in gene regulation. The second is that these polymorphisms are not the causal mutation, but are in LD with a functional variant. Fine-mapping of the region is required to identify the causal mutation(s) followed by molecular analysis to determine if the mutation affects transcriptional regulation of the gene or structure and function of the protein.
While we conducted a large number of comparisons and some correction for multiple testing is warranted, it is important to note that when we correct for multiple testing in relation to our primary hypothesis, that is association between SLC6A2 and ADHD in children stratified according to MSDP, the primary result of association (Z = 3.74, P = 0.0002) with rs36021 remains significant even if we apply the overly stringent Bonferroni correction (30 SNPs times two exposure strata, p = 0.002). In addition, the widespread exploratory associations that are observed with behaviors relevant to ADHD measured by different observers (parents, teachers, and research staff) and in different settings (school, home, clinic) with rs36021 suggest that these associations are unlikely to be chance findings. We believe that this considerable consistency of results strengthens the overall credibility of the primary results and help to understand how genetic vulnerability to ADHD is mediated through the traits and endophenotypes underlying this disorder.
To our knowledge, this is the largest study (among family-based and case-control studies) testing the association between ADHD and SLC6A2, with such detailed genotype and phenotype characterization. While collaboration between multiple research groups in large consortia is vital for genetic studies of ADHD, it has been shown that a significant amount of heterogeneity can be introduced in multicenter collaborative studies because of divergent clinical and evaluation practices.  This underscores the value of the current study where a relatively large sample has been collected at a single center using a highly standardized approach. It is also the largest study worldwide to use a double-blind, placebo-controlled design for evaluation of treatment response, combining extensive evaluation of executive function and behavioral domains, with genetic and environmental data. Nonetheless, these results must be considered exploratory and independent replication is awaited.
If confirmed in independent studies, these results will help to disentangle the complex etiological pathways of ADHD. In the long term, this would very likely lead to development of therapeutics targeting specific biochemical pathways in specific sub-groups of children with ADHD.
We thank Johanne Bellingham, Jacqueline Richard, Sandra Robinson, Marie-Ève Fortier, Phuong-Thao Nguyen, Rosherrie DeGuzman, Marina Ter-Stepanian, and Anna Polotskaia for technical and clinical assistance. A special word of thanks to all the families who participated in the study.
Conceived and designed the experiments: RJ NG. Analyzed the data: GAT SS ZC RJ. Wrote the paper: GAT SS RJ.
- 1. Willcutt EG (2012) The Prevalence of DSM-IV Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review. Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 9: 490–499. doi: 10.1007/s13311-012-0135-8
- 2. Biederman J, Faraone SV (2005) Attention-deficit hyperactivity disorder. Lancet 366: 237–248. doi: 10.1016/s0140-6736(05)66915-2
- 3. Faraone SV, Perlis RH, Doyle AE, Smoller JW, Goralnick JJ, et al. (2005) Molecular genetics of attention-deficit/hyperactivity disorder. Biological psychiatry 57: 1313–1323. doi: 10.1016/j.biopsych.2004.11.024
- 4. Greenhill LL, Pliszka S, Dulcan MK, Bernet W, Arnold V, et al. (2002) Practice parameter for the use of stimulant medications in the treatment of children, adolescents, and adults. Journal of the American Academy of Child and Adolescent Psychiatry 41: 26S–49S. doi: 10.1097/00004583-200202001-00003
- 5. Krause KH, Dresel SH, Krause J, Kung HF, Tatsch K (2000) Increased striatal dopamine transporter in adult patients with attention deficit hyperactivity disorder: effects of methylphenidate as measured by single photon emission computed tomography. Neuroscience letters 285: 107–110. doi: 10.1016/s0304-3940(00)01040-5
- 6. Madras BK, Miller GM, Fischman AJ (2005) The dopamine transporter and attention-deficit/hyperactivity disorder. Biological psychiatry 57: 1397–1409. doi: 10.1016/j.biopsych.2004.10.011
- 7. Volkow ND, Wang G, Fowler JS, Logan J, Gerasimov M, et al. (2001) Therapeutic doses of oral methylphenidate significantly increase extracellular dopamine in the human brain. The Journal of neuroscience : the official journal of the Society for Neuroscience 21: RC121.
- 8. Faraone SV, Spencer T, Aleardi M, Pagano C, Biederman J (2004) Meta-analysis of the efficacy of methylphenidate for treating adult attention-deficit/hyperactivity disorder. Journal of clinical psychopharmacology 24: 24–29. doi: 10.1097/01.jcp.0000108984.11879.95
- 9. Biederman J, Spencer T (2002) Methylphenidate in treatment of adults with Attention-Deficit/Hyperactivity Disorder. Journal of attention disorders 6 Suppl 1S101–107. doi: 10.1177/108705470100500401
- 10. Hanna GL, Ornitz EM, Hariharan M (1996) Urinary catecholamine excretion and behavioral differences in ADHD and normal boys. Journal of child and adolescent psychopharmacology 6: 63–73. doi: 10.1089/cap.1996.6.63
- 11. Shekim WO, Javaid J, Davis JM, Bylund DB (1983) Urinary MHPG and HVA excretion in boys with attention deficit disorder and hyperactivity treated with d-amphetamine. Biological psychiatry 18: 707–714.
- 12. Del Campo N, Chamberlain SR, Sahakian BJ, Robbins TW (2011) The roles of dopamine and noradrenaline in the pathophysiology and treatment of attention-deficit/hyperactivity disorder. Biological psychiatry 69: e145–157. doi: 10.1016/j.biopsych.2011.02.036
- 13. Arnsten AF, Pliszka SR (2011) Catecholamine influences on prefrontal cortical function: relevance to treatment of attention deficit/hyperactivity disorder and related disorders. Pharmacology, biochemistry, and behavior 99: 211–216. doi: 10.1016/j.pbb.2011.01.020
- 14. Uhl GR, Johnson PS (1994) Neurotransmitter transporters: three important gene families for neuronal function. The Journal of experimental biology 196: 229–236.
- 15. Bruss M, Kunz J, Lingen B, Bonisch H (1993) Chromosomal mapping of the human gene for the tricyclic antidepressant-sensitive noradrenaline transporter. Human genetics 91: 278–280. doi: 10.1007/bf00218272
- 16. Porzgen P, Bonisch H, Bruss M (1995) Molecular cloning and organization of the coding region of the human norepinephrine transporter gene. Biochemical and biophysical research communications 215: 1145–1150. doi: 10.1006/bbrc.1995.2582
- 17. Pacholczyk T, Blakely RD, Amara SG (1991) Expression cloning of a cocaine- and antidepressant-sensitive human noradrenaline transporter. Nature 350: 350–354. doi: 10.1038/350350a0
- 18. Chen J, Lipska BK, Halim N, Ma QD, Matsumoto M, et al. (2004) Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. American journal of human genetics 75: 807–821. doi: 10.1086/425589
- 19. Lachman HM, Papolos DF, Saito T, Yu YM, Szumlanski CL, et al. (1996) Human catechol-O-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics 6: 243–250. doi: 10.1097/00008571-199606000-00007
- 20. Barr CL, Kroft J, Feng Y, Wigg K, Roberts W, et al. (2002) The norepinephrine transporter gene and attention-deficit hyperactivity disorder. American journal of medical genetics 114: 255–259. doi: 10.1002/ajmg.10193
- 21. Biederman J, Kim JW, Doyle AE, Mick E, Fagerness J, et al. (2008) Sexually dimorphic effects of four genes (COMT, SLC6A2, MAOA, SLC6A4) in genetic associations of ADHD: a preliminary study. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 147B: 1511–1518. doi: 10.1002/ajmg.b.30874
- 22. Bobb AJ, Addington AM, Sidransky E, Gornick MC, Lerch JP, et al. (2005) Support for association between ADHD and two candidate genes: NET1 and DRD1. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 134B: 67–72. doi: 10.1002/ajmg.b.30142
- 23. Brookes K, Xu X, Chen W, Zhou K, Neale B, et al. (2006) The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes. Molecular psychiatry 11: 934–953. doi: 10.1038/sj.mp.4001869
- 24. Cho SC, Kim JW, Kim BN, Hwang JW, Park M, et al. (2008) No evidence of an association between norepinephrine transporter gene polymorphisms and attention deficit hyperactivity disorder: a family-based and case-control association study in a Korean sample. Neuropsychobiology 57: 131–138. doi: 10.1159/000138916
- 25. De Luca V, Muglia P, Jain U, Kennedy JL (2004) No evidence of linkage or association between the norepinephrine transporter (NET) gene MnlI polymorphism and adult ADHD. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 124B: 38–40. doi: 10.1002/ajmg.b.20075
- 26. Kim JW, Biederman J, McGrath CL, Doyle AE, Mick E, et al. (2008) Further evidence of association between two NET single-nucleotide polymorphisms with ADHD. Molecular psychiatry 13: 624–630. doi: 10.1038/sj.mp.4002090
- 27. McEvoy B, Hawi Z, Fitzgerald M, Gill M (2002) No evidence of linkage or association between the norepinephrine transporter (NET) gene polymorphisms and ADHD in the Irish population. American journal of medical genetics 114: 665–666. doi: 10.1002/ajmg.10416
- 28. Renner TJ, Nguyen TT, Romanos M, Walitza S, Roser C, et al. (2011) No evidence for association between a functional promoter variant of the Norepinephrine Transporter gene SLC6A2 and ADHD in a family-based sample. Attention deficit and hyperactivity disorders 3: 285–289. doi: 10.1007/s12402-011-0060-4
- 29. Xu X, Hawi Z, Brookes KJ, Anney R, Bellgrove M, et al. (2008) Replication of a rare protective allele in the noradrenaline transporter gene and ADHD. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 147B: 1564–1567. doi: 10.1002/ajmg.b.30872
- 30. Xu X, Knight J, Brookes K, Mill J, Sham P, et al. (2005) DNA pooling analysis of 21 norepinephrine transporter gene SNPs with attention deficit hyperactivity disorder: no evidence for association. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 134B: 115–118. doi: 10.1002/ajmg.b.30160
- 31. Joung Y, Kim CH, Moon J, Jang WS, Yang J, et al. (2010) Association studies of -3081(A/T) polymorphism of norepinephrine transporter gene with attention deficit/hyperactivity disorder in Korean population. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 153B: 691–694. doi: 10.1002/ajmg.b.31012
- 32. Kim CH, Hahn MK, Joung Y, Anderson SL, Steele AH, et al. (2006) A polymorphism in the norepinephrine transporter gene alters promoter activity and is associated with attention-deficit hyperactivity disorder. Proceedings of the National Academy of Sciences of the United States of America 103: 19164–19169. doi: 10.1073/pnas.0510836103
- 33. Kim CH, Waldman ID, Blakely RD, Kim KS (2008) Functional gene variation in the human norepinephrine transporter: association with attention deficit hyperactivity disorder. Annals of the New York Academy of Sciences 1129: 256–260. doi: 10.1196/annals.1417.023
- 34. Kollins SH, Anastopoulos AD, Lachiewicz AM, FitzGerald D, Morrissey-Kane E, et al. (2008) SNPs in dopamine D2 receptor gene (DRD2) and norepinephrine transporter gene (NET) are associated with continuous performance task (CPT) phenotypes in ADHD children and their families. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 147B: 1580–1588. doi: 10.1002/ajmg.b.30876
- 35. Song DH, Jhung K, Song J, Cheon KA (2011) The 1287 G/A polymorphism of the norepinephrine transporter gene (NET) is involved in commission errors in Korean children with attention deficit hyperactivity disorder. Behavioral and brain functions : BBF 7: 12. doi: 10.1186/1744-9081-7-12
- 36. Retz W, Rosler M, Kissling C, Wiemann S, Hunnerkopf R, et al. (2008) Norepinephrine transporter and catecholamine-O-methyltransferase gene variants and attention-deficit/hyperactivity disorder symptoms in adults. Journal of neural transmission 115: 323–329. doi: 10.1007/s00702-007-0822-5
- 37. Mick E, Neale B, Middleton FA, McGough JJ, Faraone SV (2008) Genome-wide association study of response to methylphenidate in 187 children with attention-deficit/hyperactivity disorder. American journal of medical genetics Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 147B: 1412–1418. doi: 10.1002/ajmg.b.30865
- 38. Kim BN, Kim JW, Hong SB, Cho SC, Shin MS, et al. (2010) Possible association of norepinephrine transporter -3081(A/T) polymorphism with methylphenidate response in attention deficit hyperactivity disorder. Behavioral and brain functions : BBF 6: 57. doi: 10.1186/1744-9081-6-57
- 39. Song J, Song DH, Jhung K, Cheon KA (2011) Norepinephrine transporter gene (SLC6A2) is involved with methylphenidate response in Korean children with attention deficit hyperactivity disorder. International clinical psychopharmacology 26: 107–113. doi: 10.1097/yic.0b013e32834152d1
- 40. Yang L, Wang YF, Li J, Faraone SV (2004) Association of norepinephrine transporter gene with methylphenidate response. Journal of the American Academy of Child and Adolescent Psychiatry 43: 1154–1158. doi: 10.1097/01.chi.0000131134.63368.46
- 41. Cho SC, Kim BN, Cummins TD, Kim JW, Bellgrove MA (2011) Norepinephrine transporter -3081(A/T) and alpha-2A-adrenergic receptor MspI polymorphisms are associated with cardiovascular side effects of OROS-methylphenidate treatment. Journal of psychopharmacology.
- 42. Lee SH, Kim SW, Lee MG, Yook KH, Greenhill LL, et al. (2011) Lack of association between response of OROS-methylphenidate and norepinephrine transporter (SLC6A2) polymorphism in Korean ADHD. Psychiatry research 186: 338–344. doi: 10.1016/j.psychres.2011.03.017
- 43. Pomerleau OF, Downey KK, Stelson FW, Pomerleau CS (1995) Cigarette smoking in adult patients diagnosed with attention deficit hyperactivity disorder. Journal of substance abuse 7: 373–378. doi: 10.1016/0899-3289(95)90030-6
- 44. Langley K, Rice F, van den Bree MB, Thapar A (2005) Maternal smoking during pregnancy as an environmental risk factor for attention deficit hyperactivity disorder behaviour. A review. Minerva pediatrica 57: 359–371.
- 45. McClernon FJ, Kollins SH (2008) ADHD and smoking: from genes to brain to behavior. Annals of the New York Academy of Sciences 1141: 131–147. doi: 10.1196/annals.1441.016
- 46. Grizenko N, Kovacina B, Amor LB, Schwartz G, Ter-Stepanian M, et al. (2006) Relationship between response to methylphenidate treatment in children with ADHD and psychopathology in their families. Journal of the American Academy of Child and Adolescent Psychiatry 45: 47–53. doi: 10.1097/01.chi.0000184932.64294.d9
- 47. Sengupta SM, Grizenko N, Thakur GA, Bellingham J, DeGuzman R, et al. (2012) Differential association between the norepinephrine transporter gene and ADHD: role of sex and subtype. Journal of psychiatry & neuroscience : JPN 37: 129–137. doi: 10.1503/jpn.110073
- 48. Conners CK, Sitarenios G, Parker JD, Epstein JN (1998) Revision and restandardization of the Conners Teacher Rating Scale (CTRS-R): factor structure, reliability, and criterion validity. Journal of abnormal child psychology 26: 279–291.
- 49. Conners CK, Sitarenios G, Parker JD, Epstein JN (1998) The revised Conners’ Parent Rating Scale (CPRS-R): factor structure, reliability, and criterion validity. Journal of abnormal child psychology 26: 257–268. doi: 10.1023/a:1022602400621
- 50. Hudziak JJ, Derks EM, Althoff RR, Rettew DC, Boomsma DI (2005) The genetic and environmental contributions to attention deficit hyperactivity disorder as measured by the Conners’ Rating Scales–Revised. The American journal of psychiatry 162: 1614–1620. doi: 10.1176/appi.ajp.162.9.1614
- 51. Achenbach TM (1991) The child behaviour checklist/4–18. Burlington: University of Vermont.
- 52. Mitsis EM, McKay KE, Schulz KP, Newcorn JH, Halperin JM (2000) Parent-teacher concordance for DSM-IV attention-deficit/hyperactivity disorder in a clinic-referred sample. Journal of the American Academy of Child and Adolescent Psychiatry 39: 308–313. doi: 10.1097/00004583-200003000-00012
- 53. Thapar A, Langley K, O’Donovan M, Owen M (2006) Refining the attention deficit hyperactivity disorder phenotype for molecular genetic studies. Molecular psychiatry 11: 714–720. doi: 10.1038/sj.mp.4001831
- 54. Touliatos J, Lindholm BW (1981) Congruence of parents’ and teachers’ ratings of children’s behavior problems. Journal of abnormal child psychology 9: 347–354. doi: 10.1007/bf00916839
- 55. Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF (2005) Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biological psychiatry 57: 1336–1346. doi: 10.1016/j.biopsych.2005.02.006
- 56. Heaton RK, Chelune GJ, Talley JL, Kay GG, Curtiss G (1993) The Wisconsin Card Sorting Test Manual–Revised and expanded. Odessa, FL: Psychological Assessment Resources.
- 57. Shallice T (1982) Specific impairments of planning. Philosophical transactions of the Royal Society of London Series B, Biological sciences 298: 199–209. doi: 10.1098/rstb.1982.0082
- 58. Petrides M, Milner B (1982) Deficits on subject-ordered tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia 20: 249–262. doi: 10.1016/0028-3932(82)90100-2
- 59. Conners CK (1995) Conners continuous performance test computer program. Toronto, Ontario: Multi-Health Systems.
- 60. Sheslow D, Adams W (1990) Wide Range Assessment of Memory and Learning: Administration Manual. Wilmington, DE: Jastak.
- 61. Gruber R, Grizenko N, Schwartz G, Bellingham J, Guzman R, et al. (2007) Performance on the continuous performance test in children with ADHD is associated with sleep efficiency. Sleep 30: 1003–1009.
- 62. Taerk E, Grizenko N, Ben Amor L, Lageix P, Mbekou V, et al. (2004) Catechol-O-methyltransferase (COMT) Val108/158 Met polymorphism does not modulate executive function in children with ADHD. BMC medical genetics 5: 30.
- 63. Kebir O, Tabbane K, Sengupta S, Joober R (2009) Candidate genes and neuropsychological phenotypes in children with ADHD: review of association studies. Journal of psychiatry & neuroscience : JPN 34: 88–101.
- 64. Weschler D (1991) Weschler Intellingence Scale for Children-Third Edition: Manual. San Antonio, TX: Psychological Corporation.
- 65. Barkley RA (1990) Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment. New York: Guilford Press.
- 66. Fischer M, Newby RF (1998) Use of the restricted academic task in ADHD dose-response relationships. Journal of learning disabilities 31: 608–612. doi: 10.1177/002221949803100611
- 67. Sengupta S, Grizenko N, Schmitz N, Schwartz G, Bellingham J, et al. (2008) COMT Val108/158Met polymorphism and the modulation of task-oriented behavior in children with ADHD. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 33: 3069–3077. doi: 10.1038/npp.2008.85
- 68. Karama S, Ben Amor L, Grizenko N, Ciampi A, Mbekou V, et al. (2009) Factor structure of the restricted academic situation scale: implications for ADHD. Journal of attention disorders 12: 442–448. doi: 10.1177/1087054708314605
- 69. Ehrich M, Bocker S, van den Boom D (2005) Multiplexed discovery of sequence polymorphisms using base-specific cleavage and MALDI-TOF MS. Nucleic acids research 33: e38. doi: 10.1093/nar/gni038
- 70. Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. American journal of human genetics 68: 978–989. doi: 10.1086/319501
- 71. Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, et al. (2002) The structure of haplotype blocks in the human genome. Science 296: 2225–2229. doi: 10.1126/science.1069424
- 72. Horvath S, Xu X, Laird NM (2001) The family based association test method: strategies for studying general genotype–phenotype associations. European journal of human genetics : EJHG 9: 301–306. doi: 10.1038/sj.ejhg.5200625
- 73. Conners CK (2000) Conners’ CPT II Technical Guide and Software Manual. North Tonowanda, NY: Multi-Health Systems, Inc.
- 74. Forero DA, Arboleda GH, Vasquez R, Arboleda H (2009) Candidate genes involved in neural plasticity and the risk for attention-deficit hyperactivity disorder: a meta-analysis of 8 common variants. Journal of psychiatry & neuroscience : JPN 34: 361–366.
- 75. Choudhry Z, Sengupta SM, Grizenko N, Fortier ME, Thakur GA, et al.. (2012) LPHN3 and attention-deficit/hyperactivity disorder: interaction with maternal stress during pregnancy. Journal of child psychology and psychiatry, and allied disciplines.
- 76. Linnet KM, Dalsgaard S, Obel C, Wisborg K, Henriksen TB, et al. (2003) Maternal lifestyle factors in pregnancy risk of attention deficit hyperactivity disorder and associated behaviors: review of the current evidence. The American journal of psychiatry 160: 1028–1040. doi: 10.1176/appi.ajp.160.6.1028
- 77. Linnet KM, Wisborg K, Obel C, Secher NJ, Thomsen PH, et al. (2005) Smoking during pregnancy and the risk for hyperkinetic disorder in offspring. Pediatrics 116: 462–467. doi: 10.1542/peds.2004-2054
- 78. Obel C, Linnet KM, Henriksen TB, Rodriguez A, Jarvelin MR, et al. (2009) Smoking during pregnancy and hyperactivity-inattention in the offspring–comparing results from three Nordic cohorts. International journal of epidemiology 38: 698–705. doi: 10.1093/ije/dym290
- 79. Lindblad F, Hjern A (2010) ADHD after fetal exposure to maternal smoking. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco 12: 408–415. doi: 10.1093/ntr/ntq017
- 80. Obel C, Olsen J, Henriksen TB, Rodriguez A, Jarvelin MR, et al. (2011) Is maternal smoking during pregnancy a risk factor for hyperkinetic disorder?–Findings from a sibling design. International journal of epidemiology 40: 338–345. doi: 10.1093/ije/dyq185
- 81. Thakur GA, Sengupta SM, Grizenko N, Schmitz N, Page V, et al.. (2012) Maternal Smoking During Pregnancy and ADHD: A Comprehensive Clinical and Neurocognitive Characterization. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.
- 82. Ernst M, Moolchan ET, Robinson ML (2001) Behavioral and neural consequences of prenatal exposure to nicotine. Journal of the American Academy of Child and Adolescent Psychiatry 40: 630–641. doi: 10.1097/00004583-200106000-00007
- 83. Wallis D (2010) The search for biomarkers for attention deficit/hyperactivity disorder. Drug news & perspectives 23: 438–449.
- 84. Muller UC, Asherson P, Banaschewski T, Buitelaar JK, Ebstein RP, et al. (2011) The impact of study design and diagnostic approach in a large multi-centre ADHD study: Part 2: Dimensional measures of psychopathology and intelligence. BMC psychiatry 11: 55. doi: 10.1186/1471-244x-11-55