Association Between BDNF Gene Polymorphisms and Attention Deficit Hyperactivity Disorder in Korean Children

Abstract

Background: Attention deficit hyperactivity disorder (ADHD) is a common childhood neuropsychiatric disorder characterized by behavioral problems such as attention deficit, hyperactivity, and impulsivity. The brain-derived neurotrophic factor (BDNF) is the most abundant neurotrophin in the brain. Aims: The aim of the present study was to investigate the association between the genotype and alleles for the BDNF gene in Korean children with ADHD. Methods: The sample consisted of 180 ADHD children and 159 control children. We diagnosed ADHD according to the DSM-IV. ADHD symptoms were evaluated with Conners' Parent Rating Scales and Dupaul Parent ADHD Rating Scales. Blood samples were taken from the 339 subjects, DNA was extracted from blood lymphocytes, and polymerase chain reaction was performed for BDNF rs6265, rs11030101, rs10835210, rs7103873, and rs2030324 polymorphisms. Alleles and genotype frequencies were compared using the Chi-square test. We compared the allele and genotype frequencies of the BDNF gene polymorphism in the ADHD and control groups. Results: This study showed that there was a significant correlation among the allele frequencies of the rs11030101 and rs10835210 single nucleotide polymorphisms (SNPs) (odds ratio=0.61, 95% confidence interval=0.39-0.96, p=0.034), but the final conclusions are not definite. Follow-up studies with larger patient or pure subgroups are expected. These results suggest that the BDNF allelic structure may impact ADHD symptoms.

Introduction

Attention deficit hyperactivity disorder (ADHD) is a common childhood neuropsychiatric disorder characterized by behavioral problems such as attention deficit, hyperactivity, and impulsivity (American Psychiatric Association Committee on Nomenclature and Statistics, 1994). It has a prevalence of 2-7.6% among children of school age in Korea (Cho and Shin, 1994; Kim et al., 1999). Family studies reported that ADHD showed a heredity as high as 80-90% (Faraone et al., 2001), and molecular genetic studies are actively carried out accordingly.

The brain-derived neurotrophic factor (BDNF) is the most abundant neurotrophin in the brain. It enhances the growth and maintenance of several neuronal systems, serves as a neurotransmitter modulator, and participates in mechanisms of neuronal plasticity, such as long-term potentiation and learning (Theonen et al., 1995).

The evidence from neurobiological and pharmacological research supports the role of neurotrophic factors in ADHD pathogenesis. Given that ADHD is a neurodevelopmental disorder, neurotrophic factors supporting neuronal survival, proliferation, and differentiation, as well as survival and synaptic plasticity in the central nervous system might be involved in ADHD susceptibility. Among neurotrophic factors, BDNF, which is critical for the survival and differentiation of midbrain dopaminergic neurons and the phenotypic differentiation of locus ceruleus noradrenergic neurons, has been a focus (Hyman et al., 1991; Huang and Reichardt, 2001; Traver et al., 2006). The BDNF gene is expressed in the mesolimbic dopaminergic system, the prefrontal cortex, the limbic system, and the cerebellum, which have been implicated in ADHD pathogenesis (Huang and Reichardt, 2001). Moreover, BDNF mediates psychostimulant-induced neuroadaptations and locomotor activity through the dopaminergic, serotoninergic, and noradrenergic neurotransmitter systems (Ribasés et al., 2008). A Korean study reported a positive correlation between plasma BDNF levels and severity of omission errors on the continuous performance test in patients with ADHD (Shim et al., 2008).

The previous studies on BDNF gene polymorphism and ADHD had conflicting results. One study found evidence for preferential transmission of the Val allele (rs6265) in a family-based sample (Kent et al., 2005). Another case-control (Aureli et al., 2010) association study and a haplotype association analysis (Lanktree et al., 2008) also found that the Val allele was significantly associated with ADHD. However, others could not replicate the results (Friedel et al., 2005; Lee et al., 2007; Schimmelmann et al., 2007; Xu et al., 2007; Ribasés et al., 2008; Cho et al., 2010; Tzang et al., 2013) (Table 1).

Table 1.

The Previous Studies of ADHD with BDNF Gene

Study reference	Polymorphisms	Methods	Population	Study result
Kent et al. (2005)	rs6265 (Val66Met)	Family based	341 families	Positive result
Friedel et al. (2005)	rs6265 (Val66Met)	Case/control	96 and 88	Negative result
Lee et al. (2007)	rs6265, rs11030104, rs2049046	Family based	266 families	Negative result
Xu et al. (2007)	rs6265	Family based	180 and 212 proband	Negative result
Schimmelmann et al. (2007)	rs6265	Family based	294 families	Negative result
Ribasés et al. (2008)	rs1491850, rs11030096	Case/control	325 and 539	Negative result
Lanktree et al. (2008)	rs6265	Family based	80 trios	Positive result
Cho et al. (2010)	rs11030101, rs6265, rs16917204	Case/control and family-based study	202 and 159; 151 trios	Negative result, but a positive result in only girl with rs11030101
Aureli et al. (2010)	rs6265	Case/control	—	Positive result
Tzang et al. (2013)	rs1519480, rs6265, rs7940188, rs7103411, rs7103873	Family based	285 families	Negative result

ADHD, attention deficit hyperactivity disorder; BDNF, brain-derived neurotrophic factor.

The aim of the present study was to investigate the association between the genetic type and alleles for the BDNF gene in Korean children with ADHD.

Materials and Methods

Subjects

A questionnaire was conducted with about 16,000 elementary school students in a city whose population is about 500,000 from September 2008 to August 2010. An interview was performed randomly with the children whose Korean version of the Dupaul Attention Deficit Hyperactivity Disorder rating scale (K-ARS) (Kim et al., 2002) score was 19 or higher, and 180 ADHD children who consented to the genetic study were selected. For the control group, 159 children in the same area were selected by matching the sex and age of the subjects in the patient group. For both the patient and control groups, a clinical evaluation and the DSM-IV diagnosis (American Psychiatric Association Committee on Nomenclature and Statistics, 1994) were performed by a child psychiatrist. The number of ADHD children was 180, including 132 boys (73.3%) and 48 girls (26.7%), and the mean age was 8.67±0.84. The number of children in the control group was 159, including 100 boys (62.9%) and 59 girls (37.1%), and the mean age was 8.59±0.79. There was no significant difference in the sex and age between the two groups (Table 2). Subjects were excluded from the study if there was any evidence of conduct disorder, mood disorder, anxiety disorder, Tourette's disorder, pervasive development disorder, mental retardation (IQ <70), and neurological disorders, including epilepsy. None of the children who participated in the study had ever undergone drug treatment before the evaluation. Informed consent was obtained before study entry. The study was also approved by the hospital ethics committee. None of the children was taking psychostimulants at the time of the study.

Table 2.

Epidemiological Characteristics Between the ADHD Group and the Control Group

Rating scale	ADHD group (n=180) mean±SD	Control group (n=159) mean±SD	F or χ²	p-Value
Age^a	8.67±0.84	8.59±0.79	0.06	0.813
Sex (n, %)^b
Female	48 (26.7%)	59 (37.1%)	3.79	0.052
Male	132 (73.3%)	100 (62.9%)

These data represent mean±SD, by independent t-test,^a or n (%), by χ² test,^b significant p-value<0.05.

On the day of visiting the hospital, the child psychiatrist performed a clinical interview as well as Kovac's Children's Depression Inventory (Kovacs, 1983), State Anxiety Inventory (SAIC), Trait Anxiety Inventory (TAIC) (Cho et al., 1989), Dupaul Attention Deficit Hyperactivity Disorder rating scales (K-ARS) (Kim et al., 2002), computerized ADHD diagnostic system (ADS) (Shin et al., 2000), and completed a questionnaire survey regarding the pregnancy, infancy, developmental history, and anamnesis of the children with their parents. Subjects were included from our sample if they had a score over two standard deviations from the norm on the tests for ADS (T-score >70). ADHD had a lot of comorbid disorders, such as depressive disorder and anxiety disorder. Therefore, we excluded children with a high score of depressive symptoms and anxiety symptoms. Subjects with high anxiety scores (a Spielberger Trait/State Anxiety Scale Score >47/49) on the Korean version of the Spielberger Trait/State Anxiety Scale for children were excluded, and subjects with high depression scores (Kovacs Depression Inventory Score >29) on Kovacs Depression Inventory for children were also excluded. In addition, a professional clinical psychologist performed a comprehensive psychological test, including an intelligence test, on each subject.

DNA extraction and genotyping

DNA was extracted from leukocytes using a commercial DNA extraction kit, the Wizard Genomic DNA Purification Kit (Promega, Madison, WI). The BDNF single-nucleotide polymorphism (SNP) was genotyped by polymerase chain reaction according to the protocol described by studies (Cho et al., 2010). We selected the following five SNPs in the BDNF gene (NM170733 and NR002832): rs6265 (axon 1), rs11030101 (axon 1), rs10835210 (intron 1), rs7103873 (3′-flanking region), and rs2030324 (intron 1) that were genotyped by Illumina, Inc. (San Diego, CA) through the use of their Integrated Bead Array System (Table 3). We supplied Illumina with barcoded DNA microtiter plates containing the DNA quantified with Pico Green to be at 100 ng/mL and Illumina delivered genotypes with quality scores calculated by proprietary Illumina algorithms.

Table 3.

Single-Nucleotide Polymorphisms Considered in This Study

SNP ID	Chromosome	Location	Position (coordinate)	Distance	Alleles
BDNF
rs6265	11	UTR	27636491	128/93	G/A
rs11030101	11	UTR	27637319	26/31	A/T
rs10835210	11	Intron	27652485	−934	C/A
rs7103873	11	Flanking 3l	27656892	−965	G/C
rs2030324	11	Intron	27683490	−3762	T/C

NCBI gene ID (Accession) is 2562 (NR002832 and NM170733).

SNP, single-nucleotide polymorphism.

Statistical analysis

We performed independent t-tests for age, chi-square (χ²) tests for sex, and χ² tests to compare the results of the control group and the ADHD group through the frequency of the genotypes and alleles. SPSS PC software (version 15.0) was used for the statistical analysis, and the significance level was set to the p-value being less than 0.05. The calculation revealed that a sample size of 210 subjects is required to obtain a power that is 95% or higher in the χ² test between the control group and the patient group. Our study was conducted with 339 subjects and the power was 97.41%. This indicates that the association of the BDNF gene polymorphism and ADHD can be sufficiently accounted for by the results in this study. However, we performed the power program analysis for the χ² test with 339 subjects and the result showed that the effect size was 0.46 (moderate level).

Results

Demographic characteristics of the subjects

The subjects were a total of 339 children. The children in both the ADHD group and the control group had never taken any psychostimulant in advance. There was no difference in the age (F=0.06, p=0.813) and sex (F=3.79, p=0.052) between the control group and the ADHD children group (Table 2).

Comparison of the frequency of the genotypes and alleles with genetic polymorphism of BDNF between the control group and the ADHD group

The BDNF-rs6265 genotypes of the 159 subjects in the control group and the 180 subjects in the ADHD group were G/G (28.48%: 29.78%), G/A (51.90%: 46.07%), and A/A (19.62%: 24.16%), and there was not a significant difference in the frequency between the two groups (χ²=0.64, df=2, p=0.522) (Table 4). The BDNF-rs11030101 genotypes of the 159 subjects in the control group and the 180 subjects in the ADHD group were A/A (40.51%: 50.00%), A/T (51.27%: 38.76%), and T/T (8.23%: 11.24%), and there was a significant difference in the frequency between the two groups (χ²=−2.11, df=2, p=0.034) (Table 4). The BDNF-rs10835210 genotypes of the 159 subjects in the control group and the 180 subjects in the ADHD group were C/C (40.51%: 50.00%), C/A (51.27%: 38.76%), and A/A (8.23%: 11.24%), and there was a significant difference in the frequency between the two groups (χ²=−2.11, df=2, p=0.034) (Table 4). The BDNF-rs7103873 genotypes of the 159 subjects in the control group and the 180 subjects in the ADHD group were G/G (24.68%: 26.97%), G/C (52.53%: 48.88%), and C/C (22.78%: 24.16%), and there was not a significant difference in the frequency between the two groups (χ²=−0.61, df=2, p=0.544) (Table 4). The BDNF-rs2030324 genotypes of the 159 subjects in the control group and the 180 subjects in the ADHD group were T/T (24.05%: 26.97%), T/C (53.16%: 48.88%), and C/C (22.78%: 24.16%), and there was not a significant difference in the frequency between the two groups (χ²=−0.75, df=2, p=0.455) (Table 4).

Table 4.

Multivariate Model for Genotype Distributions and Allele Frequencies in the ADHD Group and the Control Group

	Control		ADHD
Characteristics	n	%	n	%	OR	95% CI	χ²	p
BDNF-rs6265 (G/A)
Genotype					0.85	0.51-1.40	0.64	0.522
GG	45	28.48	53	29.78
GA	82	51.90	82	46.07
AA	31	19.62	43	24.16
Allele					1.07	0.79-1.44	0.42	0.672
G	172	54.43	190	52.81
A	144	45.57	170	47.19
BDNF-rs11030101 (A/T)
Genotype					0.61	0.39-0.96	−2.11	0.034
AA	64	40.51	89	50.00
AT	81	51.27	69	38.76
TT	13	8.23	20	11.24
Allele					0.87	0.63-1.20	−0.87	0.385
A	209	66.14	247	69.38
T	107	33.86	109	30.62
BDNF-rs10835210 (C/A)
Genotype					0.61	0.39-0.96	−2.11	0.034
CC	64	40.51	89	50.00
CA	81	51.27	69	38.76
AA	13	8.23	20	11.24
Allele					0.87	0.63-1.20	−0.87	0.385
C	209	66.14	247	69.38
A	107	33.86	109	30.62
BDNF-rs7103873 (G/C)
Genotype					0.85	0.51-1.43	−0.61	0.544
GG	39	24.68	48	26.97
GC	83	52.53	87	48.88
CC	36	22.78	43	24.16
Allele					0.98	0.73-1.33	−0.12	0.910
G	161	50.95	183	51.40
C	155	49.05	173	48.60
BDNF-rs2030324 (T/C)
Genotype					0.82	0.49-1.38	−0.75	0.455
TT	38	24.05	48	26.97
TC	84	53.16	87	48.88
CC	36	22.78	43	24.16
Allele					0.97	0.72-1.31	−0.20	0.840
T	160	50.63	183	51.40
C	156	49.37	173	48.60

These data represent n (%) by χ² test, significant p-value<0.05.

CI, confidence interval; OR, odds ratio.

Odds ratio of the genotypes and alleles with genetic polymorphism of BDNF between the control group and the ADHD group

The odds ratio (OR) of the BDNF-rs11030101 and rs10835210 genotypes was significant at 0.61 (confidence interval [CI]: 0.39-0.96, p=0.034) and the OR of the -rs11030101 and rs10835210 alleles was not significant at 0.87 (CI: 0.63-1.20, p=0.385) (Table 4).

Discussion

This study is a case-control study, in which the frequency of the genotypes and alleles of BDNF was compared between the ADHD children and the control group in Korea. The correlation between the genotypes and alleles of one candidate BDNF SNP was investigated. This study showed that there was a significant correlation between the frequencies of the BDNF-rs11030101 and rs10835210 and ADHD. To our knowledge, this result is the first report on the association between the BDNF polymorphism and ADHD in Asia.

In a study of Korean children, which is the only previous study about the female-specific association between ADHD and BDNF, Cho et al. (2010) reported the association between the rs11030101 genetic polymorphism of the BDNF gene and ADHD that was reported first in Korea. However, in this study, the correlation between ADHD and BDNF-rs11030101 and rs10835210 genetic polymorphism was found first. Combining the results about the correlation between the BDNF-rs11030101 and rs10835210 and ADHD, it can be understood that the failure of BDNF regulation may cause the pathogenesis of ADHD. Several lines of evidence suggest that BDNF plays a role in the etiology of ADHD. First, earlier studies demonstrated that BDNF plays a key role in the survival and differentiation of midbrain dopaminergic neurons in vivo (Hyman et al., 1991) and in vitro (Spina et al., 1992). Since the dysfunction in the midbrain system is crucial in ADHD pathogenesis (Solanto, 2002), a decreased midbrain BDNF activity may cause midbrain dopaminergic dysfunction and, therefore, resulting in ADHD. Second, psychostimulants, such as methylphenidate, are the agents commonly used in the treatment of ADHD. The classical action mechanism of psychostimulants involves enhancement of the release of dopamine and norepinephrine in the midbrain. BDNF has been shown to modulate the release of dopamine through activation of TrkB receptors (Blochl and Sirrenberg, 1996) and has also been implicated in the release of dopamine as well as in dopamine-related behaviors induced by the psychostimulant, methamphetamine (Narita et al., 2003). Furthermore, psychostimulants and antidepressants are the agents commonly used for the treatment of ADHD, and both have been found to elevate central BDNF (Meredith et al., 2002). Third, earlier studies showed that BDNF heterozygous null mutants (Kernie et al., 2000) and BDNF conditional knockout mice (Rios et al., 2001) exhibit increased locomotor hyperactivity, which mimics fundamental behavioral characteristics of ADHD (Sagvolden et al., 2005). Fourth, reduced central serotonergic activity has been implicated in poor impulse regulation, which is a feature of ADHD in young children, adults, and animals (Lucki, 1998), and a subset of BDNF heterozygous mice demonstrate physiological disturbance in central serotonergic neurons linked with behavioral abnormalities, including increased aggressiveness. This suggests that endogenous BDNF may be critical for normal development and function of central serotonergic neurons (Lyons et al., 1999) and hence impulse regulation.

The methodological limitations of this study are as follows: first, the number of subject children was small. The subjects of this study were 180 ADHD children and 159 children in the control group. Second, the covariance factors (i.e., the socioeconomic status, the educational level of parents, the regional differences) of ADHD could not be removed when the result of the study was analyzed. Besides, physical examination for ADHD was not performed. Third, we surveyed one city of the Republic of Korea, and our survey findings were therefore subject to selection bias of the methodology. Fourth, the results of this study may not be generalized for the cases of other racial or ethnic groups since the frequency of alleles can vary due to racial differences. The distribution of the allele frequency in the ADHD patient children and parent group in this study was also different from that of other countries. Fifth, only a few SNPs were investigated in this study among the many genes related with the various ADHD phenotypes. Although it is clear that not just one genetic factor causes the increased ADHD vulnerability, we did not consider the interaction with other risk factors.

Despite the methodological limitations described before, this study has several advantages. First, the patient group and the control group had no difference in the frequency of sex and age. The prevalence of ADHD is higher among males and in adolescence; thus, the sex and age characteristics can have a great effect. Considering this, our study was evaluated by adjusting the age and sex of the patient group and the control group with each other. Second, this study used population-based samples. Previous studies in Korea were hardly considered to represent the general population because the subjects were usually ADHD children who visited hospitals for their clinical symptoms. In this study, the subjects in the risk group were selected by the questionnaire survey from the whole population in a region, and the patient and control samples were obtained by random contact. Thus, the subjects in this study may be more appropriate to the characteristics of general population than those of the study performed with the patients who visited hospitals. Third, this study might have compared relatively homogenous groups that had the characteristics of Koreans, different from the studies conducted in other countries with subjects from various ethnic groups and nations. Fourth, both the patient group and control group in this study underwent clinical evaluation and DSM-IV diagnosis by child psychiatrists, applying the inclusion and exclusion criteria strictly, and thus the patient group was composed of pure ADHD-diagnosed subjects.

We expect that different allele distribution results may be produced from future studies on the quantitative correlation of the ADHD performance in the pure ADHD group from which coexisting diseases are excluded; the patient group composed of only boys or girls, the subtype groups such as the hyperactivity dominant group and attention deficiency dominant group, and the drug response group.

Footnotes

Acknowledgments

This work was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI13C0747) and was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013R1A1A4A01007101).

Author Disclosure Statement

No competing financial interests exist.

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