The norepinephrine transporter (NET) gene is an attractive candidate gene for attention-deficit hyperactivity disorder (ADHD). Noradrenergic systems are critical to higher brain functions such as attention and executive function, which are defective in ADHD. The clinical efficacy of medications that target NET also supports its role in the etiology of ADHD. Here, we have applied a dense mapping strategy to capture all genetic variations within the NET gene in a large number of ADHD families (474 trios). As a result, we found association of the same alleles from two single-nucleotide polymorphisms (rs3785143 and rs11568324) previously identified in another large-scale ADHD genetic study (International Multisite ADHD Geneproject). Furthermore, the effect sizes were consistent across both studies. This is the first time that identical alleles of NET from different studies were implicated, and thus our report provides further evidence that the NET gene is involved in the etiology of ADHD.
Attention-deficit hyperactivity disorder (ADHD) is a serious public health problem that is estimated to affect 8–12% of school-age children,1 with boys suffering as much as three or four times as frequently as girls.2, 3 The major symptoms are chronic levels of inattention, hyperactivity/impulsivity or both such that daily function is compromised in different settings. As many as two-thirds of children with ADHD have comorbid disorders, including language and communication disorders, learning disorders, conduct and oppositional defiant disorder, anxiety disorders, mood disorders and Tourette's syndrome.4
Empirical studies consistently support the assertion that ADHD runs in families.5 Parents of ADHD children have a two- to eightfold increase in the risk for ADHD.6 Studies of siblings of children with ADHD also suggest that ADHD is familial.7, 8, 9, 10, 11, 12 Data from twin studies of ADHD13 show an average heritability of 0.76, among the highest in psychiatric disorders, attributing about 80% of the population variance of ADHD to genetic factors.
The noradrenergic system modulates higher cortical functions such as attention, alertness, vigilance and executive functions, which are impaired in a variety of psychiatric disorders such as ADHD.14 Brain imaging and neuropsychological studies of ADHD indicate dysfunction of the fronto-subcortical pathway, which is rich in catecholamines such as norepinephrine. Blockade of noradrenergic neurotransmission in the prefrontal cortex markedly impairs prefrontal cortex function and mimics most of the symptoms of ADHD, including impulsivity and locomotor hyperactivity. Conversely, stimulation of noradrenergic transmission in the prefrontal cortex strengthens prefrontal cortex regulation of behavior and reduces distractibility.15
The norepinephrine transporter (NET) is an important component of the noradrenergic system and its function is involved in the reuptake of norepinephrine into the presynaptic terminals. Also, dopamine reuptake in the frontal cortex depends primarily on the NET, whereas dopamine uptake in the striatum depends primarily on the dopamine transporter.16 It is plausible that abnormalities in NET function may lead to perturbed norepinephrine levels (and dopamine levels in frontal cortex) and increase the risk of developing psychiatric disorders such as ADHD. In support of this, data from pharmacological studies indicate that medications that selectively target NET are efficacious in the treatment of ADHD.17
Quite a few genetic analyses of this gene had been conducted with regard to ADHD.18, 19, 20, 21, 22, 23, 24, 25 Earlier studies investigated only a few genetic markers in NET and found no evidence of association.18, 19, 20 Xu et al.21 investigated 21 single-nucleotide polymorphisms (SNPs) spanning the NET region in 180 cases and 334 controls and reported 1 SNP (rs3785157) that was significant with a nominal P-value of 0.05 (P=0.04). Another study by Bobb et al.22 also reported significant results for rs3785157 (P=0.009) and one other SNP rs998424 (P=0.002) in ADHD family samples. However, the association for rs3785157 was found with opposite alleles in the two papers.25 The allele frequencies were similar across both studies. Recently, a novel promoter SNP showed some evidence of association in a set of 94 ADHD cases and 60 controls (P=0.029).23 Additionally, a methylphenidate response study of ADHD found that a synonymous SNP rs5569 (1287G/A) in exon 9 was associated with response to the drug (P=0.012).24 However, none of these results were replicated, and it is currently unclear whether there exists an association between ADHD and NET.
Of note, a recent multicenter study that collected 674 European ADHD families (International Multisite ADHD Gene (IMAGE) project) analyzed 51 genes for association to ADHD.25 The genes were involved in the regulation of major neurotransmitter pathways such as dopamine, norepinephrine and serotonin. A high-density SNP map was constructed for each gene on the basis of tagging SNPs and SNPs within known functional regions to look for associations. This study is the most in-depth genetic association study performed in the largest set of ADHD patients to date. The study implicated 18 interesting genes including NET in the etiology of ADHD. For NET, the study included 43 SNPs spanning the gene region and found evidence of association for two SNPs (rs3785143 and rs11568324) (P<0.05). None of the previously implicated SNPs in NET were found to be associated in the IMAGE study (P>0.05).25 Thus, given the inconsistencies of association with NET, further exploration of this gene is warranted.
In this study, we examined the NET gene thoroughly by applying a tag SNP-based dense mapping approach. We systematically selected tag SNPs based on the SNP database from HapMap (Phase II; release #20). Additionally, we genotyped previously associated SNPs to replicate reports from other studies including the IMAGE study. We tested a total of 24 SNPs spanning the NET gene, which covers most of the genetic variations within this gene (average r2=0.81).
Materials and methods
The current analyses are derived from family studies of ADHD (N=213 families) and bipolar disorder (N=104 families) conducted at the Massachusetts General Hospital. Subjects from our case–control family studies of boys and girls with ADHD8, 26 were referred from psychiatric and pediatric sources. Psychiatric probands were selected from consecutive referrals to a pediatric psychopharmacology program. Pediatrically referred probands with ADHD came from a large Health Maintenance Organization in the Boston area.
For these studies, screening and recruitment occurred prior to the publication of DSM-IV; thus, initial affection status for individuals and their relatives was based on DSM-IIIR criteria; however, lifetime DSM-IV criteria were asked at followup interviews. During the screening phase, mothers were administered a telephone questionnaire containing criteria for DSM-IIIR ADHD and exclusionary criteria for their referred child. Potential probands were excluded if they were adopted, if their nuclear family was not available for study or if they had major sensorimotor handicaps, psychosis, autism or a full-scale IQ less than 80. Individuals who screened positive for DSM-IIIR ADHD were invited to enroll in the study along with their first-degree relatives. Referrals with ‘subthreshold’ ADHD diagnoses were excluded. Cases were identified as ‘subthreshold’ if they did not have enough symptoms for full DSM criteria or if the age at onset was greater than 7 years of age. Study procedures were reviewed with all subjects, and participants were informed that they could withdraw at any time. Individuals who were 18 years of age or older provided written informed consent for themselves. Mothers provided written informed consent for minor children, and children provided written assent. Those classified as having ADHD at both the screen and the interview (described below) were included as index cases.
The final data set used in this study consisted of 474 ADHD-affected offspring. Of those, 266 were probands and the remaining 208 were siblings who had ADHD. DNA was available for both parents in all families (100%). The age of the ADHD patients at the time of assessment ranged from 2 to 39 years. At the time of assessment, 361 patients were children and 83 patients were adults. The demographic and clinical characteristics of the sample are indicated in Table 1.
Diagnoses on probands and siblings 12 years of age and older were obtained from independent interviews with them and their mothers using the Schedule for Affective Disorders—Epidemiologic Version for children (Kiddie SADS-E27), which, for all studies except the family studies of girls and boys with ADHD, was adapted to include DSM-IV criteria. For children younger than 12 years, diagnostic information on these subjects came from parent interviews only. Interviewers were unaware of the proband's diagnosis. Diagnostic assessments of parents and siblings older than 18 years were based on direct interviews using the Structured Clinical Interview for DSM-IIIR (SCID28), also adapted to include DSM-IV criteria in the relevant studies.
Interviews were conducted by highly trained research interviewers with master's or bachelor's degree in psychology or a related field (for example, child development). Interviewers underwent an extensive training program and were supervised throughout the study by board-certified child and adolescent psychiatrists and licensed clinical psychologists. We computed κ-coefficients of agreement by having three experienced, board-certified child and adult psychiatrists diagnose 173 subjects from audiotaped interviews made by the research interview staff. The κ-values for ADHD, conduct disorder, bipolar disorder and depression were 0.99, 0.93, 0.94 and 0.86, respectively. As Faraone et al.29 reported, the 1-year test–retest κ-values were 0.95 for ADHD, 0.66 for major depression and 0.71 for bipolar disorder.
Diagnoses were scored as positive if all DSM criteria were unequivocally met. For children older than 12, diagnoses were based on combined data from child and parent interviews, by considering a diagnosis positive if criteria were met in either interview. Diagnostic uncertainties were resolved by a committee of board-certified child psychiatrists and psychologists who were unaware of the subject's ascertainment group and all data collected from family members.
Selection of SNPs
We downloaded SNP genotype data from the Phase II HapMap data (release #20) for each gene plus designated region (10 kb to both 5′ and 3′ sides of the gene). We used the online program ‘Tagger’ (http://www.broad.mit.edu/mpg/tagger/)30 to select tag SNPs that correlated highly with SNPs with minor allele frequency (MAF) ⩾0.05. SNPs that were implicated in previous association studies were ‘forced-in’ to be chosen as tag SNPs. SNPs that do not appear in the HapMap database but were implicated by previous association studies were additionally included regardless of their MAF. The two SNPs (rs3785143 and rs11568324) implicated from the IMAGE project were ‘forced-in’ also. (For comparison between the SNPs of our study and the SNPs from the IMAGE project, see Supplementary Table 1.)
The genotyping for SNPs was performed using a multiple base extension reaction with allele discrimination by MassArray mass spectrometry system (Bruker-Sequenom) as previously described.31
A number of quality control measures were implemented to ensure the accuracy of the data collected. Genotypes from intra- and inter-plate controls were compared for accuracy, and negative test controls were confirmed to have no genotypes called. In addition, assays that failed in over 10% of the samples and samples that failed in over 10% of the assays were excluded. SNPs with a Hardy–Weinberg equilibrium P-value less than 0.001 were excluded from analysis. Families with Mendel error rates greater than 5% and SNPs with Mendel error rates greater than 1% were excluded.
For the transmission disequilibrium test (TDT), the TDTPHASE program of the UNPHASED set was used.32 The pedigree data were screened for genotype inconsistencies by using PLINK33 (Shaun Purcell; http://pngu.mgh.harvard.edu/~purcell/plink/). PLINK was also used to assess genotype distributions for departures from Hardy–Weinberg equilibrium. The P-values were not corrected for multiple testing.
Results show positive associations for SNPs rs3785143 and rs11568324 (Table 2). For rs3785143, there was overtransmission of the minor allele (T) to ADHD offspring (OR=1.45, 95% CI=1.05–1.99; P=0.02), and for rs11568324 there was overtransmission of the major allele (C) (OR=3.25, 95% CI=1.05–9.96; P=0.029). Other previously associated SNPs (rs3785157, rs5569 and rs998424) were not associated with ADHD in our study (P>0.05).
These SNPs (rs3785143 and rs11568324) were the two markers implicated from the IMAGE project25 with alleles transmitting in the same direction (Table 3). The effect sizes observed were similar in both studies. The combined results indicated a stronger association with ADHD for rs3785143 (OR=1.42, 95% CI=1.16–1.74; P=0.0006) and rs11568324 (OR=3.37, 95% CI=1.53–7.42; P=0.0013).
The distance between rs3785143 and rs11568324 is ∼31 kb and the linkage disequilibrium (LD) is low (Figure 1). This LD relationship suggests that associations for these two SNPs with ADHD are independent of each other. The previously associated SNPs21, 22, 24 (rs3785157, rs5569 and rs998424) are within 3–5 kb of rs11568324 and are in high LD (D′=0.96–1.0).
We replicated association of alleles from two SNPs (rs3785143 and rs11568324) previously identified in the IMAGE project, providing further evidence that the NET gene is associated with ADHD. The IMAGE project collected a total of 776 affected individuals from eight different European countries.25 It screened a total of 1038 SNPs in 51 candidate genes implicating 18 genes including NET. Further replication in large samples was necessary to identify genetic risk variants that predispose to ADHD. Our sample consists of 474 ADHD trios, which is also one of the largest ADHD genetics studies. Of note, the effect size for each implicated allele was also consistent across the two studies. For rs3785143, the OR for the T allele was 1.45 in our study and 1.4 in the IMAGE study. For rs11568324, the OR for the C allele was 3.25 in our study and 3.5 in the IMAGE study.
The IMAGE project tested 43 SNPs in NET and our study tested 24 SNPs. Apart from rs3785143 and rs11568324, no other SNP showed evidence of association in either study. It is encouraging that even with all of the different markers tested, the results pinpoint two distinct loci. We acknowledge that none of the results from the two studies, if considered separately, are likely to survive the correction for multiple testing given their modest P-values. However, since our analyses were intended as a replication study, we did not correct for multiple testing.
The consistent findings across these two studies (Massachusetts General Hospital (MGH) and IMAGE) suggest negligible population heterogeneity in NET effects between the American and European samples. With the exception of SLC6A3, meta-analyses of the association between ADHD and several candidate genes found no statistically significant evidence of heterogeneity across American, Canadian, European and Israeli samples.34, 35, 36 Because the ADHD susceptibility alleles are likely to be common alleles that cause minor, additive deviations in neurodevelopment and brain function, we expect these to influence the etiology of ADHD in both the MGH and IMAGE samples.
SNP rs11568324 is located in intron 5, within 5 kb from all three SNPs (rs3785157, rs5569 and rs998424) previously reported to be associated with ADHD.21, 22, 24 Only rs3785157 was previously reported to be associated in two independent studies;21, 22 however, the opposite alleles were reported for each study. SNP rs5569 (1287 G/A) is a synonymous coding SNP that is located in exon 9. Although the SNP's functional consequences are unknown, the G/G and G/A genotypes were reported to be associated with favorable treatment response to methylphenidate (P=0.012).24 Interestingly, the G/G genotype was also reported to be associated with favorable response to norepinephrine uptake inhibitors (nortriptyline) in depressed patients (P<0.001).37 The results for these three SNPs (rs3785157, rs5569 and rs998424) were not significant in our study (P>0.05).
However, as we can see by the proximity of these SNPs (rs3785157, rs5569 and rs998424) with rs11568324, LD is very high (D′=0.96–1.0) between each marker pair (Figure 1). So it is possible that the previous ADHD association signals may have been due to high LD with rs11568324. The overtransmitted allele for rs11568324 was the major allele (C) and had an allele frequency of 99%. Moreover, the involvement of opposite alleles of rs3785157 in previous studies might be explained as a ‘flip-flop’ phenomenon resulting from correlation (by LD) of the investigated variant (rs3785157) with the ‘causal’ variant (rs11568324) at another locus.38
The minor allele (T) of rs11568324 has an allele frequency of just 1% and was undertransmitted to ADHD offspring. This allele showed a strong protective effect in our study (OR=0.31, 95% CI=0.10–0.94). In the future, it may be worth investigating the characteristics of individuals carrying the T (protective) allele through clinical studies such as brain imaging or neuropsychological studies.
However, it should be noted that association results of rs11568324 from our study and the IMAGE study (Table 3) are based on a small number of observations, and the findings should be interpreted with caution. The findings from each study lose statistical significance if Fisher's exact test is used instead of the standard χ2 analysis (P=0.157 for MGH study and P=0.164 for IMAGE study). The combined result of both studies, however, still remains significant even after applying the Fisher's exact test (P=0.025).
SNP rs3785143 is located in intron 1, a region reported to be responsible for high-level transcription of NET.39 Recently, a novel SNP (−3081[A/T]) in the nearby promoter was identified and reported to be modestly associated with ADHD in a set of 94 ADHD cases and 60 controls (P=0.029).23 Although this SNP is currently not available in the public database, the location of −3081[A/T] is 3081 bp upstream of the transcription start site and there were no indications that recombination had occurred between rs3785143 and SNPs around this upstream region (D′=1) (Figure 1). So it is also possible that this association may have been due to high LD with rs3785143.
Currently, we do not have evidence that suggests any direct functionality for our two associated SNPs. However, we can speculate on the functional consequences of the two SNPs indirectly through reports from previous biological studies. First, SNP rs3785143 is located in intron 1, which is a region reported to be responsible for high-level transcription of NET.39 In combination with the promoter region, the intron 1 region contributed to the highest level of transcriptional activity within noradrenergic cells.39 So it is biologically plausible that this SNP or a variant that is in high LD with this SNP may affect NET expression and thus increase the risk of developing ADHD.
Also, in a study of 10 nonsynonymous NET SNPs and their effects on gene expression and trafficking, two SNPs with the most dramatic effects (N292T, A369P) were located in exons 6 and 8.40 These regions are in high LD with SNP rs11568324, which lies in intron 5 (Figure 1).
In summary, we report replication of association for two NET SNPs previously implicated in the large multicenter IMAGE project. Of note, the associated alleles were concordant between the two studies. Since the functional significance of these SNPs is unknown at present, future efforts should be guided toward elucidating the functional consequences of the implicated alleles. Additionally, further resequencing of adjacent regions may be necessary to find additional variants that may affect the function of the gene.
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We are grateful for the families and individuals who participated in this study. We thank Dr Keeley Brookes and Professor Philip Asherson for sharing their data with us, and Brian Galloway for technical assistance. This work was supported by National Institutes of Health (NIH) Grants HD37694, HD37999 and MH66877 to SVF and NARSAD Young Investigator Award to JWK. JWK is an NARSAD Sidney R Baer Jr Foundation Investigator.
About this article
Association analysis of norepinephrine transporter polymorphisms and methylphenidate response in ADHD patients
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