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Keywords:

  • ADHD;
  • neurodevelopment;
  • synapses;
  • GIT1 gene;
  • candidate gene

Abstract

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

Attention-deficit hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in children with a worldwide prevalence of 5.3%. Recently, a Korean group assessed the G-protein-coupled receptor kinase-interacting protein 1 (GIT1) gene that had previously been associated with ADHD. In their work, 27 single nucleotide polymorphisms SNPs in the GIT1 gene were tested; however, only the rs550818 SNP was associated with ADHD susceptibility. Moreover, the presence of the risk-associated allele determined reduced GIT1 expression, and Git1-deficient mice exhibit ADHD-like phenotypes. The aim of this study was to determine if this association also occurs in a sample of Brazilian children with ADHD. No effect of GIT1 genotypes on ADHD susceptibility was observed in the case–control analysis. The odds ratios (ORs) were 0.75 (P = 0.184) for the CT genotype and 1.09 (P = 0.862) for the TT genotype. In addition, the adjusted OR of the CT+TT genotypes vs. the CC genotype was also estimated (P = 0.245). There were no dimensional associations between the GIT1 genotypes and both hyperactivity and /impulsivity, and only hyperactivity Swanson, Nolan and Pelham Scale-Version IV (SNAP-IV) scores (P= 0.609 and P = 0.247, respectively). The transmission/disequilibrium test indicated that there was no over-transmission of rs550818 alleles from parents to ADHD children (z = 0.305; P = 0.761). We conclude that rs550818 is not associated with ADHD in this Brazilian sample. More studies are required before concluding that this polymorphism plays a role in ADHD susceptibility.

Attention-deficit hyperactivity disorder (ADHD) is a common heterogeneous disorder characterized by inappropriate levels of inattention and impulsivity-hyperactivity, which affects 5.3% of children worldwide (Polanczyk et al. 2007). Evidence from several neurobiological studies supports the idea that dysregulation of the catecholaminergic systems underlies ADHD neurobiology (Genro et al. 2010; Volkow et al. 2009). Moreover, neurodevelopmental brain anomalies, such as reduced cortical volume and grey matter heterotopias, indicate that ADHD is a neurodevelopmental disorder (Valera et al. 2007; Wolosin et al. 2009).

Although the involvement of dopamine in ADHD has been consistently suggested in the literature, copy number variations and genome-wide linkage/association studies have identified neurodevelopmental genes other than dopamine-related genes as possible candidates for this disorder (Elia et al. 2010; Genro et al. 2010; Poelmans et al. 2011). In a recent paper, chromosomal regions previously associated with ADHD were searched for genes encoding proteins that affect neuronal functions (Won et al. 2011). One of these genes was the G-protein-coupled receptor kinase-interacting protein 1 gene (GIT1). The human GIT1 gene, located on chromosome 17p11.2, encodes a ubiquitous multidomain protein involved in diverse cellular processes, including synapse formation during development (Hoefen & Berk 2006; Lee & Silva 2011). Its major function appears to be the regulation of cytoskeletal dynamics during cell expansion and migration, especially in neurons (Hoefen & Berk 2006). Deletion of the ARF-GAP domain of GIT1 leads to the inhibition of neurite outgrowth (Albertinazzi et al. 2003). GIT1 also regulates the endocytic traffic of β2-adrenergic receptors and other G-protein-coupled receptors (GPCRs) as dopamine receptors (Claing et al. 2000; Premont et al. 1998).

The results of several studies have suggested that GIT1 is a possible candidate gene for neurological disorders. The first demonstration of GIT1's neurological function in vivo was performed by Schmalzigaug et al. (2009). Although Git1-knockout mice showed normal exploratory and anxiety- and depressive-like behaviours, these mice exhibited impaired responses to fear conditioning and fear-potentiated startle (Schmalzigaug et al. 2009). Importantly, although Git1-knockout mice were susceptible to early postnatal death, survivors developed normally and did not show any gross anatomical abnormalities (Schmalzigaug et al. 2009). In another study, the neurons of Git1-knockout mice exhibited decreased dendritic lengths and spine densities in the hippocampus (Menon et al. 2009). Moreover, behavioural analysis showed that these mice adapt poorly to new or changing environments (Menon et al. 2009).

Won et al. (2011) investigated 27 single nucleotide polymorphisms (SNPs) in the GIT1 gene; only the rs550818 polymorphism, located in intron 20, was associated with ADHD susceptibility in a sample of Korean children. The heterozygous CT genotype was significantly associated with increased ADHD susceptibility (2.66-fold; CI 95%: 1.33–5.31) when compared with C allele homozygotes. Moreover, the ADHD risk-associated allele resulted in a reduction in GIT1 expression when plasmid constructs containing major or minor allele residues in the position corresponding to the SNP coupled with a downstream luciferase reporter were compared (Won et al. 2011). Behavioural analysis of Git1-knockout mice showed that the mutant mice show hyperactive behaviour at 8 weeks of age when compared with wild-type mice in an open-field task. Git1-knockout mice also showed learning and memory impairments, and as in humans, amphetamine treatment rescued these phenotypes in the mutant mice (Won et al. 2011). On the basis of these findings, we have attempted to determine if this association also occurs in a sample of Brazilian children and adolescents with ADHD.

Materials and methods

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

Experimental subjects

This study included 646 unrelated Brazilian children and adolescents (521 children with ADHD and 125 unaffected controls).The largest subsample of cases was composed of 421 children with ADHD recruited in the Child and Adolescent Psychiatric Division at the Hospital de Clínicas de Porto Alegre (HCPA). A consensus diagnosis of ADHD and comorbidities was achieved through a three-stage process, which was previously described in detail (Roman et al. 2001). Briefly, a first evaluation was performed with a semi-structured interview (Schedule for Affective Disorders and Schizophrenia for School-Age Children, Epidemiological Version; K-SADS-E) (Orvaschel 1985), which was modified to assess DSM-IV criteria. Second, a discussion of each diagnosis that had been derived through the K-SADS-E was performed by a clinical committee chaired by one of the authors (L.A.R.). Third, a clinical evaluation of ADHD and comorbid conditions using DSM-IV criteria was assessed by a child psychiatrist who had previously received the results of the K-SADS-E. When a disagreement about a diagnosis occurred during the three-stage process, priority was given to the diagnoses derived from clinical interviews. Most of the patients presented the combined type (65.3%) followed by the inattentive subtype (25.4%). The Swanson, Nolan and Pelham Scale-Version IV (SNAP-IV) was applied to 277 individuals by child psychiatrists blinded to genotype. This questionnaire has frequently been used in ADHD investigations (Polanczyk et al. 2007; Swanson et al. 2001). The remaining 100 subjects were children with ADHD inattentive type. This group was ascertained from 12 public schools. Inclusion and diagnostic criteria for this sample were similar to those described above and have been fully described elsewhere (Schmitz et al. 2006). Of the 521 children with ADHD, the most common comorbidity was oppositional defiant disorder (37.4%) followed by anxiety disorders (29.0%), mood disorders (15.2%) and conduct disorder (11.9%). Control subjects were included if they showed no evidence of any current or past mental illness as defined by the DSM-IV. The diagnostic approach for the control sample from the community was the same as for the ADHD samples, and a very similar procedure to the one in the sample from the ADHD outpatient programme was used (Schmitz et al. 2006). The demographic characteristics of the subjects are shown in Table 1. The Ethics Committee of the HCPA approved the study protocol. The parents provided written informed consent, and the children provided verbal consent for participation in this study.

Table 1. Demographic characteristics of the case and control groups
CharacteristicsCases (N = 521)Controls (N = 125)P valuea
  1. Data are given as numbers (percentages) or means (±SD).

  2. a

    Calculated by the Mann–Whitney U-test (quantitative variables without normal distributions), the χ2-test or Fisher's exact test (categorical variables).

Age (years)10.6±3.1611.8±3.310.001
IQ92.5±13.8296.8±13.120.002
Sex (males)40076.8%7862.4%0.001
Ethnicity (European– Brazilian)40677.9%9576.0%0.336

Genotyping

DNA was extracted from whole blood lymphocytes by standard procedures. The rs550818 polymorphism was genotyped using a TaqMan SNP Genotyping Assay-on-Demand (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's recommended protocol.

Statistical analyses

Allele frequencies were estimated by counting. Deviations from Hardy–Weinberg equilibrium were assessed by the χ2 test. Comparisons among variables were performed using the χ2, Fisher's exact or Mann–Whitney U-test (for quantitative variables without normal distributions). The association of rs550818 with ADHD susceptibility was initially tested in a case–control design by multivariate logistic regression analysis. Because of unequal distributions in gender, age and IQ scores between cases and controls, the analysis was adjusted for these variables. Estimation of the statistical power of the logistic regression analysis was calculated by post hoc power analyses for given sample sizes, effect sizes and α levels using G*Power v. 3.1 software (Erdfelder et al. 1996). The R2 value for covariates (gender, IQ and age) was calculated by logistic regression. Hyperactivity/impulsivity SNAP-IV scores were compared among genotype groups by an anova followed by a test for a linear trend in the mean scores. The same analysis was performed for hyperactivity SNAP-IV symptoms separately from impulsivity symptoms in the subset of individuals for whom we had a detailed hyperactivity/impulsivity SNAP-IV subscale (i.e. all of the symptoms were in the data set and not only the mean subscale score). The quantitative analyses were performed controlling for gender because this variable was associated with hyperactivity/impulsivity or hyperactivity SNAP-IV scores and a GIT1 genotype with a P value lower than 0.1. All tests were performed with SPSS Version 18 software (SPSS, Inc., Chicago, IL, USA). The transmission/disequilibrium test (TDT) between rs550818 alleles and ADHD was carried out with the Family-Based Association Test (FBAT) version 2.0.3. software. This programme tests for the biased transmission of alleles and association (Laird et al. 2000). This procedure is robust for the detection of spurious associations arising from population stratification. The significance level accepted for all tests was 0.05.

Results

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

In ADHD cases, the frequencies of C and T alleles were 0.73 and 0.27, respectively, whereas in the controls, these frequencies were 0.72 and 0.28, respectively. These allele frequencies are consistent with the frequencies in the European population found in the HapMap data set. Among the ADHD cases, 53% of the individuals were CC, 40% were heterozygous and 7% were TT. In the controls, the genotypic distribution was 50% CC, 44% heterozygous and 6% TT. In both samples, the genotype distributions were in Hardy–Weinberg equilibrium (case group: χ2 = 0.2297; df = 1; P = 0.632 and control group: χ2 = 1.5432; df = 1; P = 0.214).

Adjusting for gender, age and IQ score, no effect of GIT1 genotypes on ADHD susceptibility was observed in the case–control analysis. The odds ratio (OR) for the CT genotype was 0.75 (CI 95%: 0.49–1.15, P = 0.184) and 1.09 (CI 95%: 0.42–2.79; P = 0.862; Table 2) for TT. In addition, the adjusted OR of CT + TT vs. the CC genotype was also estimated (0.782; CI 95%: 0.516–1.184; P = 0.245; Table 2). Although our sample had a 95% power to detect an association at P < 0.05, we did not find any significant OR such as the OR found by Won et al. (2011) (2.66; CI 95%: 1.33–5.31). With the TDT test, we did not detect the over-transmission of any rs550818 allele (C or T) from parents to ADHD children (z = 0.305; P = 0.761).

Table 2. The distribution of Attention-Deficit Hyperactivity Disorder (ADHD) among the GIT1 genotypes
GIT1 genotypesCasesControlsModel 1Model 2*a
N%N%OR95% CIP valueOR95% CIP value
  1. The OR, 95% CI and P values were calculated by multivariate logistic regression with adjustments for gender, age and IQ scores.

  2. a

    CT + TT against the CC genotype.

TT366.975.61.0870.42–2.790.8620.7820.516–1.1840.245
CT21040.35644.80.7490.49–1.150.184   
CC27552.86249.611

Quantitative analysis with an anova did not detect significant differences in hyperactivity/impulsivity scores or specifically in hyperactivity scores in the SNAP-IV between the genotype groups (Table 3). However, because increasing average hyperactivity scores were observed among the GIT1 genotypes (TT > CT > CC), a linear trend test of the means was performed. In this analysis, a significant increase in hyperactivity SNAP-IV scores with increasing numbers of the risk allele T was observed (F = 4.44; P = 0.04), but the mean increase among groups was small (0.14; Table 3).

Table 3. Mean SNAP-IV scores in the hyperactivity/impulsivity dimension and GIT1 genotypes compared by ANOVAa
SNAP-IV dimensionGIT1 genotypesNMean±SE95% CIFP value
Lower boundUpper bound
  1. a

    Degrees of freedom = 2.

Hyperactivity/ImpulsivityCC1371.5190.0731.3761.6620.4970.609
 CT1191.6090.0901.4311.787
 TT211.7380.3901.1682.308
HyperactivityCC1101.4730.0761.3221.6231.4080.247
 CT951.5880.0821.4261.749
 TT191.7840.1831.4242.144

Discussion

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

Won et al. (2011) showed that there was a possible association between the GIT1 gene and ADHD by several approaches; however, this study was unable to reproduce their results in a Brazilian sample. The rs550818 GIT1 gene polymorphism was not associated with ADHD in Brazilian children and adolescents investigated herein, although our sample size had a high statistical power to detect similar results. Moreover, no significant differences were found in the SNAP-IV hyperactivity/impulsivity or hyperactivity scores. However, a trend test showed that there was a linear relationship between increases in hyperactivity symptoms and increasing numbers of the T risk allele. The TDT test indicated that there was no over-transmission of any allele of the rs550818 polymorphism from parents to children with ADHD.

One common issue with genetic studies of complex disorders such as ADHD is their low replicability. The first association paper often has a positive result and gains much notoriety, but these results are poorly or never replicated. The literature comprises hundreds of publications showing considerable disagreement (Delisi & Faraone 2006). Data from a review on published putative positive associations between common gene variants and complex disorders showed that of the 166 putative associations that have been studied three or more times, only six have been replicated consistently (Hirschhorn et al. 2002). For psychiatric disorders, the underlying mechanisms of disease remain unknown, and the study of candidate genes has a greater influence. The study of neurodevelopmental disorders is difficult; frequently, it can lead to many false positive candidates because these genes might have connections with other aspects of brain development (Delisi & Faraone 2006).

Association studies must be corroborated by independent studies to ensure a sound basis for genetic risk calculations, and replication studies in the same or different populations provide good evidence of causal association (Campbell & Rudan 2002). In the case of GIT1, some explanations may be provided for this discrepancy. The genetic background of different populations leads to different allele frequencies and different risks for diseases. The population used in this study has a high degree of European ancestry, which is consistent with the extent of past immigration to the region (Wang et al. 2008). Therefore, the allele frequencies of this study are consistent with the frequencies found in the European population in the HapMap data set (MAF = 0.27), whereas the frequencies of Won et al. (2011) are similar to the frequencies in Asian populations (MAF between 0.06 and 0.09). Thus, they were unable to find TT homozygotes in the control group and just one subject with the TT genotype among the ADHD cases. These differences in population structure and the significant association found in the Korean sample can reflect linkage disequilibrium between the rs550818 polymorphism and a locus that is involved in disease causation specific to that population. Therefore, a genetic variant may be more or less important in different populations depending on population allele frequencies (Campbell & Rudan 2002). Gene–gene or gene–environment interactions that might differ between populations can also be a potential cause of variable findings. It is possible to speculate that the effect of the rs550818 polymorphism can only be manifested in populations with a particular genetic or environmental background (Hirschhorn et al. 2002). Moreover, the underlying genetic effect can be very weak. The association can be real but nonetheless not reproducible without extremely large sample sizes. This can occur when each study inaccurately estimates the strength of the effect. It is not uncommon for the first published paper to determine a statistical significance that overestimates the true effect of the variant tested (Hirschhorn et al. 2002). It should be noted that failure to achieve statistical significance and the absence of the effect seen in the first study should not necessarily be considered a refutation of the association between the GIT1 gene and ADHD. However, studies even larger than the present one and/or meta-analyses of multiple studies will be required to determine whether the genetic association between this polymorphism and ADHD is significant.

Studies in animal models can be useful for investigating the aetiology of human disorders such as ADHD. However, it is difficult to extrapolate these results to humans. In ADHD animal models, the three core symptoms of this disorder (attention deficit, hyperactivity and impulsivity) are expected to be present to support the face validity of the model (Sontag et al. 2010). The presence of a certain disease symptom does not necessarily indicate the presence of the entire disease. For this reason, the results of the Won et al. (2011) study in a Git1-knockout mouse model that showed only part of the ADHD phenotype (hyperactivity and impaired learning and memory in the mice) should also be interpreted with caution. The authors suggested that ADHD-like symptoms in the Git1-knockout mice may not have involved dopamine-related mechanisms, although GIT1 regulates the endocytosis of GPCRs. The mechanism by which the GIT1 deficiency leads to ADHD-like symptoms in mice appears to be an imbalance between excitatory and inhibitory neurons. In humans, this imbalance could be created differently, or its effect could be distinct. Therefore, the potential reduction in the expression of the T allele of rs550818 might not be sufficient to increase the risk of developing hyperactivity and consequently ADHD. The quantitative results obtained in this study with the SNAP-IV hyperactivity scores were not statistically significant. However, the trend test showed that there was a linear relationship between increased hyperactivity in children with ADHD and increased numbers of the risk allele T. Future studies including larger samples may clarify the importance of the GIT1 gene's role in hyperactivity and ADHD susceptibility in children.

This work should be interpreted in the context of some limitations. First, other genetic and environmental variants might have determined different G × E and/or gene–gene interactions with this polymorphism in this study's sample than the interactions found in the Korean sample, obscuring any effect of the gene (Thapar et al. 2006). Second, there is a disproportion between the number of cases and controls in this study (approximately 5–1). Ideally, a similar number of case and control subjects would be expected. In fact, this disproportion between case and control subsamples tends to increase the probability of a false positive finding; however, the results of this study were negative (Balding 2006).

Finally, it is important to emphasize that studies in different populations are essential for many reasons, including assurance that the results are reliable and determination of their generalizability and applicability. We were unable to reproduce the previously obtained results with respect to this polymorphism. In this study, the rs550818 polymorphism of the GIT1 gene was not found to be associated with ADHD susceptibility.

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  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
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Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments

The authors thank the financial support provided by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil).

Dr L.A.R. was on the speakers' bureau/advisory board and/or acted as a consultant for Eli-Lilly, Janssen-Cilag, Novartis and Shire in the past 3 years (<U$ 10 000 per year and reflecting <5% of his gross annual income). The ADHD and Juvenile Bipolar Disorder Outpatient Programmes that he chairs received unrestricted educational and research support from the following pharmaceutical companies in the past 3 years: Abbott, Eli-Lilly, Janssen-Cilag and Novartis. None of the other authors have any conflicts of interest to declare.