BDNF 196 G/A and COMT Val158Met Polymorphisms and Susceptibility to ADHD: A Meta-Analysis

Abstract

Objective: The aim of this study was to determine whether the brain-derived neurotrophic factor (BDNF) 196 G/A or catechol-O-methyltransferase (COMT) Val158Met polymorphisms is associated with susceptibility to ADHD. Method: We conducted a meta-analysis of the associations between the BDNF 196 G/A and COMT Val158Met polymorphisms and ADHD. Results: Sixteen studies consisting of 3,594 patients with ADHD and 4,040 controls were included in this meta-analysis. Our results showed no association between ADHD and the BDNF 196A allele in all participants (odds ratio [OR] = 0.958, 95% confidence interval [CI] = [0.800, 1.146], p = .638), European or Asian population. Meta-analysis indicated no association between ADHD and the COMT G allele in all study participants (OR = 1.078, 95% CI = [0.962, 1.207], p = .196), European or Asian population. Conclusion: This meta-analysis showed a lack of association between the BDNF 196 G/A and COMT Val158Met polymorphisms and ADHD.

Keywords

ADHD polymorphism meta-analysis

Introduction

ADHD is a common neurobehavioral disorder characterized by hyperactivity, impulsiveness, and a lack of attention. ADHD emerges during childhood, usually before 7 years of age, and has a prevalence of up to 5% (Franke et al., 2012). Although ADHD is complex and heterogeneous and its etiology has not been determined, a genetic susceptibility to ADHD has been identified in case–control, twin, and family studies (Mick & Faraone, 2008).

Brain-derived neurotrophic factor (BDNF), a member of the neurotrophin family of growth factors, promotes survival of and dopamine uptake by embryonic midbrain dopaminergic neurons and is necessary for the survival of striatal neurons in the brain. BDNF mRNA and protein are widely expressed in the central nervous system (Hyman et al., 1991). Of the many BDNF polymorphisms identified, the BDNF 196 G/A polymorphism (rs6265) has been most intensively studied in association with ADHD. BDNF 196 G/A causes a valine-to-methionine substitution at codon 66 (Val66Met) and results in reduced cell surface expression of BDNF (Egan et al., 2003).

Catecholamines (norepinephrine, epinephrine, and dopamine) are the neurotransmitters of the sympathetic nervous system. Catechol-O-methyltransferase (COMT) is the major catecholamine-degrading enzyme involved in the degradation of catecholamines in synapses in the cerebral cortex, preferentially affecting prefrontal cortical dopamine metabolism (Kaenmaki et al., 2010). COMT Val158Met is a single nucleotide polymorphism (rs4680), which consists of a G to A transition at codon 158, the result of which is an amino acid change. Val/Val, Val/Met, and Met/Met genotypes are associated with high, intermediate, and low activity of the enzyme, respectively (Lachman et al., 1996).

The BDNF 196 G/A and COMT Val158Met polymorphisms have been extensively studied in the context of ADHD (Aureli et al., 2010; Bobb et al., 2005; Cho et al., 2010; Das et al., 2011; Friedel et al., 2005; Halleland, Lundervold, Halmoy, Haavik, & Johansson, 2009; Kereszturi et al., 2008; Lanktree et al., 2008; Qian et al., 2007; Sanchez-Mora et al., 2010; Song, Paik, Kim, & Lim, 2009; Yatsuga et al., 2014; Zhang, Ruan, Le, & Zhang, 2003). However, published results on the genetic associations of these BDNF and COMT polymorphisms with the disorder are controversial and inconclusive. To overcome the limitations of individual studies, resolve inconsistencies, and reduce the likelihood of random errors causing false-positive or false-negative associations (Lee, Bae, Choi, Ji, & Song, 2011; Lee, Harley, & Nath, 2006; Lee, Rho, Choi, Ji, & Song, 2007), we carried out a meta-analysis to determine whether the BDNF 196 G/A and COMT Val158Met polymorphisms are associated with susceptibility to ADHD.

Method

Identification of Eligible Studies and Data Extraction

Using the MEDLINE and Embase citation databases, we performed a literature search to identify articles published up to February 2014 that examined associations between the BDNF 196 G/A and COMT Val158Met polymorphisms and ADHD. Combinations of keywords such as “brain-derived neurotrophic factor,” “BDNF,” “catechol-O-methyltransferase,” “COMT,” “attention-deficit/hyperactivity disorder,” and “ADHD” were entered as Medical Subject Heading terms and text words. References in the identified studies were used to identify additional studies not indexed by the electronic databases. Inclusion criteria were as follows: (a) case–control study design, (b) original data, and (c) genotype or allele data to calculate odds ratios (ORs). No language restriction was applied. Exclusion criteria were as follows: (a) overlapping data, (b) inability to ascertain the number of genotypes or alleles, and (c) family members studied because analysis was based on linkage considerations. Data were extracted from the original studies by two independent reviewers. Discrepancies between the reviewers were resolved by reaching a consensus or by consulting a third reviewer. The following information was extracted from each identified study: author, year of publication, ethnicity of the study population, demographics, and numbers of cases and controls for each BDNF196 G/A or COMT Val158Met polymorphism. Allele frequencies were calculated from the corresponding genotype distributions.

Evaluation of Statistical Associations

Meta-analyses were performed using allelic and homozygote contrast, and recessive and dominant models. Subgroup analyses were performed by ethnicity. Point estimates of risks, ORs, and 95% confidence intervals (CIs) were estimated for each study. Cochran’s Q-statistic was used to assess within- and between-study variation or heterogeneity. The heterogeneity test assessed the null hypothesis that all studies were evaluating the same effect. I² values were used to quantify heterogeneity. I² values ranged between 0% and 100% and represented the proportion of between-study variability attributable to heterogeneity rather than chance (Higgins & Thompson, 2002). I² values of 25%, 50%, and 75% were nominally assigned as low, moderate, and high estimates. The fixed effects model assumed that a genetic factor had the same effect on ADHD susceptibility across all studies investigated, and that variations between studies were caused by chance alone. The random effects model assumed that different studies had substantial diversity and assessed within-study sampling error and between-study variance. For homogeneous study groups, the two models were similar, but when this was not the case, the random effects model generated wider CIs than the fixed effects model. The random effects model was used for significant heterogeneity between studies (DerSimonian & Laird, 1986). Statistical manipulations were performed using the comprehensive meta-analysis program Biosta (Englewood, New Jersey, USA). Study power was computed as the probability of detecting an association between the BDNF 196 G/A or COMT Val158Met polymorphisms and ADHD at a significance level of .05, assuming an OR of a small effect size. Power analysis was performed using the G*Power statistical program (http://www.gpower.hhu.de).

Evaluation of Publication Bias

A chi-square test was used to determine whether observed genotype frequencies conformed to the Hardy–Weinberg equilibrium (HWE). Although funnel plots are often used to detect publication bias, funnel plotting requires a range of studies of varying sizes and involves subjective judgments. Accordingly, we evaluated publication bias using Egger’s linear regression test (Egger, Davey Smith, Schneider, & Minder, 1997), which measures funnel plot asymmetry using a natural logarithm scale of ORs.

Results

Studies Included in the Meta-Analysis

A total of 16 studies from 13 articles met all the inclusion criteria and were considered in our meta-analysis, which featured 3,594 patients with ADHD and 4,040 controls (Figure 1). Eight studies (seven European and one Asian) with 2,171 cases and 2,699 controls involved the BDNF polymorphism and eight studies (two European, four Asian, one Indian, and one mixed population) with 1,423 cases and 1,341 controls involved the COMT polymorphism (Aureli et al., 2010; Bobb et al., 2005; Cho et al., 2010; Das et al., 2011; Friedel et al., 2005; Halleland et al., 2009; Kereszturi et al., 2008; Lanktree et al., 2008; Qian et al., 2007; Sanchez-Mora et al., 2010; Song et al., 2009; Yatsuga et al., 2014; Zhang et al., 2003). Ethnicity-specific meta-analysis was conducted on European and Asian populations. Selected characteristics of the relationships found between the BDNF and COMT polymorphisms and ADHD are summarized in Table 1. The statistical power of the studies ranged from 14.7% to 96.7%; three of the studies had a statistical power exceeding 80%.

Figure 1.

Odds ratios and 95% CIs of studies and pooled data for the allelic association between BDNF 196 G/A (A) and COMT Val158Met (B) polymorphisms and ADHD in all participants.

Table 1.

Characteristics of Studies in the Meta-Analysis.

		Numbers		Case			Control
Study	Ethnicity	Case	Control	GG	GA	AA	GG	GA	AA	Association, p value^a	Power (%)^b
A: BDNF 196 G/A polymorphism
Cho et al. (2010)	Asian	202	159	60	99	43	46	74	39	.592	47.6
Aureli et al. (2010)	European	37	80	27	10	0	50	4	26	.001	19.1
Sanchez-Mora et al. (2010)	European	607	840	393	189	25	517	284	39	.223	96.7
Sanchez-Mora et al. (2010)	European	191	486	119	67	5	322	152	12	.384	73.9
Sanchez-Mora et al. (2010)	European	436	496	282	132	22	324	155	17	.539	86.2
Sanchez-Mora (2010)	European	211	425	122	79	10	266	141	18	.283	71.2
Lanktree et al. (2008)	European	117	117	NA	NA	NA	NA	NA	NA	.130	33.3
Friedel et al. (2005)	European	370	96	224	128	18	62	33	1	.237	57.8
B: COMT Val158Met polymorphism
Yatsuga et al. (2014)	Asian	32	50	4	28^c		20	30^c		.011^d	14.7
Das et al. (2011)	Indian	126	96	NA	NA	NA	NA	NA	NA	.673	31.9
Song et al. (2009)	Asian	60	100	33	27	0	65	29	6	.672	24.4
Halleland et al. (2009)	European	435	383	NA	NA	NA	NA	NA	NA	.662	81.5
Kereszturi et al. (2008)	European	173	284	49	87	37	53	151	80	.016	57.0
Qian et al. (2007)	Asian	317	194	153	140	24	99	78	17	.789	61.8
Bobb et al. (2005)	Mixed	163	129	NA	NA	NA	NA	NA	NA	.208	40.0
Zhang et al. (2003)	Asian	117	105	67	41	9	60	40	5	.731	31.9

Note. NA = genotype not available, but allele count available. BDNF = brain-derived neurotrophic factor; COMT = catechol-O-methyltransferase.

Allele contrast: 2 versus 1 allele.

Power calculations assume α = .05, small effect size.

GA + AA genotype.

GG versus GA + AA genotype.

Meta-Analysis of the BDNF 196 G/A Polymorphism and ADHD

Meta-analysis was performed for a combined ADHD patient population and by each individual ethnic category. No association was observed between ADHD and the BDNF 196A allele in the combined study participants (OR = 0.958, 95% CI = [0.800, 1.146], p = .638, Table 2A, Figure 1A). Ethnicity-specific meta-analysis indicated no association between the BDNF 196A allele and ADHD in either the European (OR = 0.956, 95% CI = [0.76, 1.179], p = .673) or Asian (OR = 0.923, 95% CI = [0.687, 1.238], p = .582) population (Table 2A). Analysis using recessive, dominant, or homozygote contrast models showed the same pattern for the BDNF 196A allele (Table 2A).

Table 2.

Analysis of the Association Between BDNF 196 G/A and COMT Val158Met Polymorphisms and ADHD.

Polymorphism	Population	No. of studies	Participant no.		Test of association			Test of heterogeneity
Polymorphism	Population	No. of studies	Case	Control	OR	95% CI	p value	Model	p value	I ²
A: BDNF 196 G/A Polymorphism
BDNF 196 G/A A versus G	Overall	8	2,171	2,699	0.958	[0.800, 1.146]	.638	R	.011	61.7
	European	7	1,969	1,587	0.956	[0.776, 11.179]	.675	R	.006	66.8
	Asian	1	202	159	0.923	[0.687, 1.238]	.582	NA	NA	NA
AA vs. AG + GG (recessive)	Overall	7	2,054	2,582	1.016	[0.668, 1.547]	.940	R	.091	44.9
	European	6	1,852	2,423	1.076	[0.620, 1.866]	.795	R	.070	50.8
	Asian	1	202	159	0.832	[0.508, 1.364]	.466	NA	NA	NA
AA + AG vs. GG (dominant)	Overall	7	2,054	2,582	1.010	[0.890, 1.145]	.882	F	.467	0
	European	6	1,852	2,423	1.014	[0.889, 1.156]	.841	F	.349	10.3
	Asian	1	202	159	0.963	[0.610, 1.521]	.873	NA	NA	NA
AA vs. GG	Overall	7	2,054	2,582	1.015	[0.759, 1.357]	.922	F	.116	41.2
	European	6	1,852	2,423	1.098	[0.639, 1.887]	.735	R	.084	48.4
	Asian	1	202	159	0.845	[0.474, 1.508]	.569	NA	NA	NA
B: COMT Val158Met Polymorphism
COMT Val158Met G vs. A	Overall	7	1,391	1,291	1.078	[0.962, 1.207]	.196	F	.374	7.02
	Asian	3	494	399	0.942	[0.760, 1.168]	.586	F	.964	0
	European	2	608	667	1.187	[0.898, 1.568]	.228	R	.091	64.8
GG vs. GA + AA (recessive)	Overall	5	699	733	0.874	[0.579, 1.393]	.572	R	.007	71.6
	Asian	4	526	449	0.817	[0.628, 1.063]	.132	F	.107	50.8
	European	0	NA	NA	NA	NA	NA	NA	NA	NA
GG + GA vs. AA (dominant)	Overall	4	667	683	1.383	[0.906, 1.814]	.160	F	.287	18.6
	Asian	2	494	399	1.072	[0.617, 1.862]	.805	F	.221	33.7
	European	0	NA	NA	NA	NA	NA	NA	NA	NA
GG vs. AA	Overall	4	667	683	1.444	[0.972, 2.143]	.069	F	.162	41.6
	Asian	2	494	399	1.020	[0.578, 1.801]	.944	F	.307	15.3
	European	0	NA	NA	NA	NA	NA	NA	NA	NA

Note. BDNF = brain-derived neurotrophic factor; COMT = catechol-O-methyltransferase; R = random effect model; F = fixed effect model; NA = not available.

Meta-Analysis of COMT Val158Met Polymorphism and ADHD

Meta-analysis showed no association between ADHD and the COMT G allele in all study participants (OR = 1.078, 95% CI = [0.962, 1.207], p = .196, Table 2B, Figure 1B). Stratification by ethnicity indicated no association between the COMT G allele and ADHD in European (OR = 1.187, 95% CI = [0.898, 1.568], p = .22, Table 2B) or Asian populations (OR = 0.942, 95% CI = [0.760, 1.168], p = .586, Table 2B). Analysis using recessive, dominant, or homozygote contrast models showed the same pattern for the COMT G allele (Table 2B).

Heterogeneity and Publication Bias

The distribution of the BDNF 196 G/A polymorphism in normal controls was not consistent with HWE in two studies included in our analysis (Aureli et al., 2010; Lanktree et al., 2008). Deviation from HWE among controls implies potential bias during control selection or genotyping errors. Excluding these studies, however, did not materially affect our results. Between-study heterogeneity was found in the meta-analysis of the BDNF 196 G/A polymorphism in all study participants but not in the analysis of the COMT Val158Met polymorphism in the combined population. Sensitivity analysis was performed by systematically removing a study from the analysis to assess the influence of each individual study on the pooled OR. This sensitivity analysis showed that no individual study significantly affected the pooled OR, suggesting statistically robust results from the meta-analysis. Funnel plots to detect publication bias were difficult to correlate because of the small number of studies in the meta-analysis. Egger’s regression test showed no evidence of publication bias in the meta-analysis (Egger’s regression test p values > .1).

Discussion

Although the multifactorial nature of ADHD is well recognized, genetic factors are considered strong determinants of the disease and, accordingly, numerous genes have been identified and studied in connection with ADHD. Two such genes are BDNF and COMT (Aureli et al., 2010; Bobb et al., 2005; Cho et al., 2010; Das et al., 2011; Friedel et al., 2005; Halleland et al., 2009; Kereszturi et al., 2008; Lanktree et al., 2008; Qian et al., 2007; Sanchez-Mora et al., 2010; Song et al., 2009; Yatsuga et al., 2014; Zhang et al., 2003). BDNF has a neuroprotective action on mesencephalic dopaminergic neurons and plays a role as a neuromodulator in cognitive and motor activities (Hyman et al., 1991). BDNF polymorphisms affecting BDNF expression have been studied as potential causes of ADHD. One of these polymorphisms, 196 G/A, generates an amino acid substitution (valine to methionine) in the amino terminus of BDNF, which is associated with abnormal intracellular distribution and decreased secretion of BDNF (Egan et al., 2003). Studies examining the association between COMT and ADHD have largely focused on a functional polymorphism in exon 4 that leads to a similar amino acid substitution (valine to methionine; Lachman et al., 1996). This polymorphism affects COMT enzyme activity, such that homozygosity for the valine allele results in 3 to 4 times greater activity than homozygosity for the methionine allele, leading to significant lower dopamine levels in the post-synaptic neuron (Lachman et al., 1996).

In this meta-analysis, we combined data from published studies to evaluate genetic associations between ADHD and the BDNF 196 G/A or COMT Val158Met polymorphisms. We found no association between the BDNF 196 G/A and COMT Val158Met polymorphisms and ADHD susceptibility in analyzed European and Asian populations. In addition, none of the genetic models that we used detected an association between the BDNF 196 G/A or COMT Val158Met polymorphisms and ADHD susceptibility in the combined study participants, European or Asian populations.

Our meta-analysis does not support an important role for the BDNF 196 G/A and COMT Val158Met polymorphisms in the susceptibility of ADHD. The results of our meta-analysis are not consistent with those of functional studies of these polymorphisms. In general, disagreements between epidemiological and functional studies of ADHD are not entirely unexpected, given that it is a complex disease involving multiple genes, genetic backgrounds, and environmental factors. In our case, the discrepancy may arise from mixed clinical subtypes or different neurological lesions in the study populations and further studies are required to examine this possibility. Consequently, it also could be that the results of our BDNF and COMT meta-analysis are due to Type II errors (false negatives).

Our study has several limitations. First, heterogeneity and confounding factors might have distorted the analysis, and publication bias might have affected our findings. Second, our ethnicity-specific analysis included data only from European and Asian patients; thus, the results are applicable only to these ethnic populations. Third, it would have been interesting to evaluate the association between the BDNF and COMT polymorphisms and activity or clinical features of ADHD but this was not possible owing to the limited data in this study. Finally, the number of studies included in this meta-analysis was small. There was only one Asian study on the BDNF polymorphism and two European studies on the COMT polymorphism in the subgroup analysis by ethnicity. The study numbers in the ethnicity-specific meta-analysis may not be sufficient to provide a conclusive result.

In conclusion, this meta-analysis of published data demonstrates that the BDNF 196 G/A and COMT Val158Met polymorphisms are not associated with susceptibility to ADHD in European and Asian populations. These data do not support the hypothesis that these polymorphisms play an important role in the susceptibility to ADHD. Larger scale studies in homogeneous populations of different ethnicities are necessary to investigate the roles of BDNF and COMT genes in the pathogenesis of ADHD.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Young Ho Lee is an MD and PhD and wrote the paper.

Gwan Gyu Song is an MD and PhD and contibuted the data analysis.

References

Aureli

Del Beato

Sebastiani

Marimpietri

Melillo

C. V.

Sechi

Di Loreto

(2010). Attention-deficit hyperactivity disorder and intellectual disability: A study of association with brain-derived neurotrophic factor gene polymorphisms. International Journal of Immunopathology and Pharmacology, 23, 873-880.

Bobb

A. J.

Addington

A. M.

Sidransky

Gornick

M. C.

Lerch

J. P.

Greenstein

D. K.

. . . Rapoport

J. L.

(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.

Cho

S. C.

Kim

H. W.

Kim

B. N.

Kim

J. W.

Shin

M. S.

Chung

. . . Son

J. W.

(2010). Gender-specific association of the brain-derived neurotrophic factor gene with attention-deficit/hyperactivity disorder. Psychiatry Investigation, 7, 285-290.

Das

Das Bhowmik

Bhaduri

Sarkar

Ghosh

Sinha

. . . Mukhopadhyay

(2011). Role of gene-gene/gene-environment interaction in the etiology of eastern Indian ADHD probands. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 35, 577-587.

DerSimonian

Laird

(1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177-188.

Egan

M. F.

Kojima

Callicott

J. H.

Goldberg

T. E.

Kolachana

B. S.

Bertolino

. . . Weinberger

D. R.

(2003). The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell, 112, 257-269.

Egger

Davey Smith

Schneider

Minder

(1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal, 315, 629-634.

Franke

Faraone

S. V.

Asherson

Buitelaar

Bau

C. H.

Ramos-Quiroga

J. A.

. . . International Multicentre persistent ADHD Collaboration. 2012. The genetics of attention deficit/hyperactivity disorder in adults, a review. Molecular Psychiatry, 17, 960-987.

Friedel

Horro

F. F.

Wermter

A. K.

Geller

Dempfle

Reichwald

. . . Hebebrand

(2005). Mutation screen of the brain derived neurotrophic factor gene (BDNF): Identification of several genetic variants and association studies in patients with obesity, eating disorders, and attention-deficit/hyperactivity disorder. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 132B, 96-99.

10.

Halleland

Lundervold

A. J.

Halmoy

Haavik

Johansson

(2009). Association between catechol-O-methyltransferase (COMT) haplotypes and severity of hyperactivity symptoms in adults. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 150B, 403-410.

11.

Higgins

J. P.

Thompson

S. G.

(2002). Quantifying heterogeneity in a meta-analysis. Statistics of Medicine, 21, 1539-1558.

12.

Hyman

Hofer

Barde

Y. A.

Juhasz

Yancopoulos

G. D.

Squinto

S. P.

Lindsay

R. M.

(1991). BDNF is a neurotrophic factor for dopaminergic neurons of the substantia nigra. Nature, 350, 230-232.

13.

Kaenmaki

Tammimaki

Myohanen

Pakarinen

Amberg

Karayiorgou

. . . Mannisto

P. T.

(2010). Quantitative role of COMT in dopamine clearance in the prefrontal cortex of freely moving mice. Journal of Neurochemistry, 114, 1745-1755.

14.

Kereszturi

Tarnok

Bognar

Lakatos

Farkas

Gadoros

. . . Nemoda

(2008). Catechol-O-methyltransferase Val158Met polymorphism is associated with methylphenidate response in ADHD children. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 147B, 1431-1435.

15.

Lachman

H. M.

Papolos

D. F.

Saito

Y. M.

Szumlanski

C. L.

Weinshilboum

R. M.

(1996). Human catechol-O-methyltransferase pharmacogenetics: Description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics, 6, 243-250.

16.

Lanktree

Squassina

Krinsky

Strauss

Jain

Macciardi

. . . Muglia

2008. Association study of brain-derived neurotrophic factor (BDNF) and LIN-7 homolog (LIN-7) genes with adult attention-deficit/hyperactivity disorder. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 147B, 945-951.

17.

Lee

Y. H.

Bae

S. C.

Choi

S. J.

J. D.

Song

G. G.

(2011). Associations between vitamin D receptor polymorphisms and susceptibility to rheumatoid arthritis and systemic lupus erythematosus: A meta-analysis. Molecular Biology Reports, 38, 3643-3651.

18.

Lee

Y. H.

Harley

J. B.

Nath

S. K.

(2006). Meta-analysis of TNF-alpha promoter −308 A/G polymorphism and SLE susceptibility. European Journal of Human Genetics, 14, 364-371.

19.

Lee

Y. H.

Rho

Y. H.

Choi

S. J.

J. D.

Song

G. G.

(2007). PADI4 polymorphisms and rheumatoid arthritis susceptibility: A meta-analysis. Rheumatology International, 27, 827-833.

20.

Mick

Faraone

S. V.

(2008). Genetics of attention deficit hyperactivity disorder. Child and Adolescent Psychiatric Clinics of North America, 17, 261-284, vii-viii.

21.

Qian

Wang

Yang

Wang

Zhou

. . . Faraone

S. V.

(2007). Evaluation of potential gene-gene interactions for attention deficit hyperactivity disorder in the Han Chinese population. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 144B, 200-206.

22.

Sanchez-Mora

Ribases

Ramos-Quiroga

J. A.

Casas

Bosch

Boreatti-Hummer

. . . Cormand

(2010). Meta-analysis of brain-derived neurotrophic factor p.Val66Met in adult ADHD in four European populations. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics: The Official Publication of the International Society of Psychiatric Genetics, 153B, 512-523.

23.

Song

E. Y.

Paik

K. C.

Kim

H. W.

Lim

M. H.

2009. Association between catechol-O-methyltransferase gene polymorphism and attention-deficit hyperactivity disorder in Korean population. Genetic Testing and Molecular Biomarkers, 13, 233-236.

24.

Yatsuga

Toyohisa

Fujisawa

T. X.

Nishitani

Shinohara

Matsuura

. . . Tomoda

(2014). No association between catechol-O-methyltransferase (COMT) genotype and attention deficit hyperactivity disorder (ADHD) in Japanese children. Brain & Development, 36, 620-625.

25.

Zhang

X. N.

Ruan

L. M.

Y. P.

Zhang

(2003). [Association analysis between attention-deficit hyperactivity disorder and Val158Met polymorphism of catechol-O-methyltransferase gene]. Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese Journal of Medical Genetics, 20, 322-324.