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Association between polymorphisms of DRD2 and DRD4 and opioid dependence Evidence from the current studies.

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RESEARCH ARTICLE
Neuropsychiatric Genetics
Association Between Polymorphisms of DRD2 and
DRD4 and Opioid Dependence: Evidence From the
Current Studies
Dingyan Chen,1 Fang Liu,1 Qinggang Shang,2 Xiaoqin Song,1 Xiaoping Miao,1 and Zengzhen Wang1*
1
Department of Epidemiology and Health Statistics, School of Public Health, Tongji Medical College,
Huazhong University of Science and Technology, Wuhan, P.R. China
2
Shenzhen Center for Chronic Disease Control, Shenzhen, P.R. China
Received 4 September 2010; Accepted 26 May 2011
Several studies have assessed the association between genetic
polymorphisms of DRD2 and DRD4 genes and opioid dependence risk, while the results were inconsistent. We performed a
meta-analysis, including 6,846 opioid dependence cases and
4,187 controls from 22 individual studies, to evaluate the roles
of four variants (DRD2 141ins/delC, rs1799732; DRD2 311
Ser > Cys, rs1801028; DRD2-related TaqI A, rs1800497 and
DRD4 exon III VNTR) in opioid dependence for the first
time. We found that the 141delC polymorphism was significantly associated with increased risk of opioid dependence
(homozygote comparison: odds ratios [OR], 2.71; 95% confidence interval [CI], 1.74–4.22; dominant comparison: OR, 1.27;
95% CI, 1.09–1.48). Similarly, the TaqI A1 polymorphism was
also significantly increased opioid dependence risk (homozygote
comparison: OR, 2.06; 95% CI, 1.25–3.42; dominant comparison:
OR, 1.34; 95% CI, 1.08–1.67). Moreover, long allele (5-repeat)
and 7-repeat allele of DRD4 exon III VNTR were found to be
associated with significantly increased opioid dependence risk
(OR, 1.50; 95% CI, 1.24–1.80 and OR, 1.57; 95%, 1.18–2.09,
respectively). However, no association was detected between the
DRD2 311 Ser > Cys polymorphism and opioid dependence. In
conclusion, our results suggested that DRD2 141ins/delC,
DRD2-related TaqI A and DRD4 exon III VNTR polymorphisms
might play important roles in the development of opioid dependence. 2011 Wiley-Liss, Inc.
Key words: addiction; susceptibility; dopamine receptor;
genetic polymorphism; meta-analysis
INTRODUCTION
Illicit opioid use is a significant public health issue, with approximately 15 million people abusing illicit opioids in the world
[UNODC, 2003]. It is not only associated with poor health, high
mortality rates, and criminal behavior, but also imposes disproportionately large economic and social costs upon the community
in general [Barratt et al., 2006]. Although the etiology remains
controversial, drug dependence is believed to be resulted from
gene–environment interactions [Duaux et al., 2000; Li et al., 2006].
2011 Wiley-Liss, Inc.
How to Cite this Article:
Chen D, Liu F, Shang Q, Song X, Miao X,
Wang Z. 2011. Association Between
Polymorphisms of DRD2 and DRD4 and
Opioid Dependence: Evidence From the
Current Studies.
Am J Med Genet Part B 156:661–670.
The dopaminergic system is a prime genetic candidate on drug
abuse for its rewarding and reinforcing role in the brain especially in
the mesolimbocortical region and its connections in the basal
forebrain which contribute to the positive reinforce of drugs abuse
[Li et al., 2002]. Among a number of potential candidate genes with
a dopaminergic function, the dopamine receptor D2 (DRD2) gene
and the dopamine receptor D4 (DRD4) gene, both belonging to the
dopamine receptor D2-like family, have been two of the most
extensively studied genetic biomarkers in opioid addictive disorders [Ho et al., 2008].
DRD2 and DRD4 are located on human chromosome 11q22–23
and 11p15.5 [Xu et al., 2004; Demiralp et al., 2007]. According to
the dbSNP database (http://www.ncbi.nlm.nih.gov/SNP accessed
July 22, 2010), DRD2 and DRD4 have at least 897 and 134 variants,
respectively. Previous studies have mainly focused on two common
single nucleotide polymorphisms (SNPs), namely 141ins/delC
(rs1799732) and 311 Ser > Cys (rs1801028) in DRD2, and a variable
number tandem repeat (VNTR) polymorphism in DRD4 (48-base
Grant sponsor: National Natural Science Foundation of China; Grant
number: NSFC-30872175.
*Correspondence to:
Prof. Zengzhen Wang, Department of Epidemiology and Health Statistics,
School of Public Health, Tongji Medical College, Huazhong University of
Science and Technology, 13 Hangkong Road, 430030 Wuhan, P.R. China.
E-mail: wzzh@mails.tjmu.edu.cn
Published online 28 June 2011 in Wiley Online Library
(wileyonlinelibrary.com).
DOI 10.1002/ajmg.b.31208
661
662
pair (bp) exon 3). These variants were inferred to affect gene
expression, function, or signal transmission. The 141delC allele,
located in the promoter region of DRD2, has been found to be
associated with significantly less promoter activity and consequently affected gene expression [Parsian et al., 2000]. The 311
Ser > Cys polymorphism, which leads to an amino acid substitution from serine to cysteine, has been shown to affect DRD2 signal
transduction via cyclic adenosine monophosphate (cAMP) inhibition [Cravchik et al., 1996; Parsian et al., 2000]. The 7-repeat or
longer VNTR allele has been shown to be less responsive to
dopamine stimulation [Asghari et al., 1995; Demiralp et al.,
2007]. Besides, the TaqI A polymorphism (rs1800497), previously
thought located in DRD2 but nowadays identified within the exon 8
of ankyrin repeat and kinase domain containing 1 (ANKK1), was
also considered in our study for its vicinity to DRD2 and modulatory role in function and expression of this gene [Jonsson et al.,
1999; Doehring et al., 2009]. Therefore, it was likely that these
variants might contribute to the inter-individual difference in the
susceptibility to opioid dependence.
Although the roles of DRD2 and DRD4 have been explored in
many studies, the findings are not consistent. Besides, single study
may have limited statistical power to detect the modest effect of
DRD2 or DRD4 variant on opioid dependence risk. In this metaanalysis, we used accumulated data from published studies to
provide statistical powerful evidence on the association between
the above-mentioned four variants (i.e., DRD2 141ins/delC,
DRD2 311 Ser > Cys, DRD2-related TaqI A, and DRD4 exon III
VNTR) and opioid dependence risk.
MATERIALS AND METHODS
Identification and Eligibility of Relevant Studies
We conducted an electronic search for relevant articles published
before July 22, 2010 from databases, including PubMed/MEDLINE,
EMBASE, and ISI Web of Science with the combination of the
following terms: ‘‘DRD2 or D2R or D2DR or DRD4 or D4DR or
TaqIA’’ and ‘‘opioid or opiate or heroin.’’ To expand the coverage
of our searches, we further carried out searches in Chinese National
Knowledge Infrastructure (CNKI) and Wanfang Database with the
translation of all English searching items. All retrieved articles were
examined by reading the titles and abstracts, and each potentially
relevant full-text copy was further checked for its suitability for this
meta-analysis. Reference lists in retrieved articles were also screened
for original studies. We included all case–control studies and cohort
studies with human subjects that investigated the association
between DRD2 or DRD4 or TaqI A polymorphisms and opioid
dependence risk with genotyping data for at least one of the four
polymorphisms, DRD2 141ins/delC, DRD2 311 Ser > Cys,
DRD2-related TaqI A, and DRD4 exon III VNTR in all languages.
Moreover, publications using the same population but examining
different gene polymorphisms were treated as one study. Abstract,
unpublished reports, reviews, and reports not offering the information of cases or controls were not considered. Additionally,
studies with obvious overlapping data were carefully examined, and
the study that included the largest number of individuals was finally
selected.
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
Data Extraction
The following information was extracted from each article: first
author, year of publication, country of origin, ethnicity, number of
cases and controls, source of control group, all relative alleles
investigated, genotyping method, genotype and allele frequencies,
blinding of personnel who performed genotyping to clinical status
of the study participants, use of age and sex matching, and consistency of genotype frequencies with Hardy–Weinberg equilibrium (HWE). For studies including subjects of different
ethnicities, data were extracted separately and categorized as Asians,
Caucasians, and others.
Statistical Analysis
We recalculated odds ratios (ORs) and 95% confidence intervals
(CIs) for each study. Heterogeneity was tested for all combined
results by using the c2-based Cochran’ Q-test, in which a P-value
greater than 0.05 suggested a lack of heterogeneity. Inconsistency
was also calculated using I2 metrics to determine the impact of
heterogeneity. The following suggested cutoff points were used:
I2 ¼ 0–25%, no heterogeneity; I2 ¼ 25–50%, moderate heterogeneity; I2 ¼ 50–75%, large heterogeneity; and I2 ¼ 75–100%,
extreme heterogeneity [Marcos et al., 2009]. Pooled ORs were
calculated by using fix-effect model when heterogeneity was negligible or random-effect model when heterogeneity was significantly
present. Publication bias was assessed using funnel plots and the
Egger’s test (liner regression analysis). Deviation from the HWE
among controls was checked for each of the four polymorphisms by
means of a c2-test. All the P values presented were two-sided with a
significance level at 0.05, and all analyses were done with Stata
Statistical Package (version 10.0).
RESULTS
Characteristics of Including Studies
A total of 197 relevant publications were identified after initial
screening (as of July 22, 2010). After exclusion of 175 articles
dissatisfied with inclusion criteria, we finally identified 22 publications, involving 6,846 opioid dependence cases and 4,187 controls in 22 case–control studies, since one publication [Xu et al.,
2004] provided two individual studies and two publications [Shao
et al., 2005a,b] using the same population but examining different
gene polymorphisms (Table I). Among the 22 publications, 14 were
published in English and the other 8 were in Chinese. Overall, there
were 5 articles (including 6 case–control studies) for DRD2
141ins/delC polymorphism, 3 articles (including 4 case–control
control studies) for DRD2 311 Ser > Cys polymorphism, 11 articles
(including 12 case–control studies) for DRD2-related TaqI A polymorphism, and 8 articles (including 8 case–control studies) for
DRD4 exon III VNTR polymorphism. Of these, 13 studies reported
data on Asians, and the remaining 9 studies reported data on
Caucasians or mixed ethnicity. There were 7 population-based
studies, 2 hospital-based studies, 10 studies with mixed controls,
and 3 studies without mention of this information (Table I). Four
studies were matched for sex and age.
CHEN ET AL.
663
TABLE I. Characteristics of the Studies Included in the Meta-Analysis
Studies
Persico et al. [1996]
Kotler et al. [1997]
Li et al. [1997]
Franke et al. [2000]
Lawford et al. [2000]
Li et al. [2000]
Zhao et al. [2001]
Cao et al. [2002]
Li et al. [2002]
Peng et al. [2002]
Cao et al. [2003]
Xu et al. [2004]
Shahmoradgoli Najafabadi et al. [2005]
Shao et al. [2005a]
Shao et al. [2005b]
Xu et al. [2005]
Barratt et al. [2006]
Xu et al. [2006]
Perez de los Cobos et al. [2007]
Crettol et al. [2008]
Hou and Li [2009]
Chien et al. [2010]
Country
USA
Israel
China
German
Australia
China
China
China
China
China
China
Mixed
Iran
China
China
China
Australia
China
Spanish
Switzerland
China
China
Ethnicity Case/control Source of control
Caucasian
40/119 Mixed
Caucasian 141/110 Population
Asian
121/154 Mixed
Caucasian 285/197 Mixed
Caucasian
95/50 Hospital
Asian
405/304 Mixed
Asian
102/64 Population
Asian
199/126 Not mentioned
Asian
465/298 Mixed
Asian
66/132 Mixed
Asian
302/177 Mixed
Mixed
957/505 Population
Caucasian 100/130 Not mentioned
Asian
380/275 Mixed
Asian
380/275 Mixed
Asian
965/300 Population
Mixed
71/95 Not mentioned
Asian
209/109 Population
Caucasian 281/145 Mixed
Caucasian 238/217 Hospital
Asian
530/500 Population
Asian
894/180 Population
Different genotyping methods were used to determine the four
polymorphisms in these studies. Twelve studies used restriction
fragment length polymorphism (RFLP) assay, eight studies used
direct polymerase chain reaction (PCR) sequencing, and the
remaining two used TaqMan assay. Only eight studies mentioned
blind design to case–control status in clinical investigation and/or
genotyping. Overall, the distribution of genotypes in the controls
was consistent with HWE except for the TaqI A polymorphism in
two studies [Peng et al., 2002; Hou and Li, 2009], the DRD2
141ins/delC polymorphism in the study by Shao et al. [2005b],
the DRD2 311 Ser > Cys polymorphism in the study by Xu et al.
[2005], and the DRD4 exon III VNTR polymorphism in the study
by Zhao et al. [2001]. However, the corresponding pooled ORs were
not substantially altered with or without including these studies
(data not shown).
The Association Between DRD2 141ins/delC and
Opioid Dependence Risk
The eligible studies included 3,058 cases and 1,550 controls. The
prevalence rate of 141delC allele was 13.1% (95% CI,
12.4%–13.9%) and 10.5% (95% CI, 8.8%–12.1%) in Asians
and Caucasians, respectively. Overall, there was no substantial
between-study heterogeneity (P > 0.05 and I2 < 50% for all
comparisons) among the six studies of the DRD2 141ins/delC
polymorphism. Using the fixed-effect model, we found
statistical evidence for the association between the increased opioid
dependence risk and the DRD2 141delC allele (homozygote
comparison, 141delC/141delC vs. 141insC/141insC: OR,
Polymorphisms
TaqI A
DRD4 exon III VNTR
DRD4 exon III VNTR
DRD4 exon III VNTR
TaqI A
DRD4 exon III VNTR
DRD4 exon III VNTR
DRD4 exon III VNTR
141ins/delC, 311 Ser > Cys, TaqI A
TaqI A
141ins/delC
141ins/delC, 311 Ser > Cys, TaqI A
TaqI A
DRD4 exon III VNTR
141ins/delC
141ins/delC, 311 Ser > Cys
TaqI A
TaqI A
TaqI A
TaqI A
TaqI A
DRD4 exon III VNTR
2.71; 95% CI, 1.74–4.22; dominant comparison, 141delC/
141delC þ 141delC/141insC vs. 141insC/141insC: OR,
1.27; 95% CI, 1.09–1.48; recessive comparison, 141delC/
141delC vs. 141delC/141insC þ 141insC/141insC: OR,
2.63; 95% CI, 1.70–4.07) (Fig. 1a and Table II). No publication
bias was detected by either the funnel plot (Fig. 2a) or the Egger’s
test (t ¼ 0.46, P ¼ 0.669) among the included studies.
The Association Between DRD2 311 Ser > Cys and
Opioid Dependence Risk
The eligible studies included 2,023 cases and 964 controls. The
prevalence rate of 311Cys allele was 5.8% (95% CI, 5.1%–6.4%) and
1.9% (95% CI, 1.2%–2.7%) in Asians and Caucasians, respectively.
Overall there was no substantial between-study heterogeneity
among the six studies of the DRD2 311 Ser > Cys polymorphism
(P > 0.05 and I2 < 50%). Using the fixed-effect model, our analysis
did not provide any statistical evidence of an association between
DRD2 311 Ser > Cys and the opioid dependence risk (Fig. 1b and
Table II). No publication bias was detected by either the funnel plot
(Fig. 2b) or the Egger’s test (t ¼ 0.10, P ¼ 0.929) among the included
studies.
The Association Between DRD2-Related TaqI A and
Opioid Dependence Risk
The eligible studies included 2,679 cases and 2,186 controls. The
prevalence rate of TaqI A1 allele was 28.2% (95% CI, 27.3%–29.1%)
in all subjects. For all studies combined, the TaqI A1 allele was
associated with significant increased opioid dependence risk in all
664
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
genetic models when random effects were used since substantial
statistical heterogeneities were detected between studies
(homozygote comparison, A1A1 vs. A2A2: OR, 2.06; 95% CI,
1.25–3.42; P < 0.001 for heterogeneity, I2 ¼ 67.5%; dominant comparison, A1A1 þ A1A2 vs. A2A2: OR, 1.34; 95% CI, 1.08–1.67;
P ¼ 0.002 for heterogeneity, I2 ¼ 62.3%; recessive comparison,
A1A1 vs. A1A2 þ A2A2: OR, 1.94; 95% CI, 1.17–3.22; P < 0.001
for heterogeneity, I2 ¼ 70.9%) (Fig. 1c and Table II). No publication
bias was detected by either the funnel plot (Fig. 2c) or the Egger’s test
(t ¼ 1.35, P ¼ 0.207) among the included studies.
The between-study heterogeneity for DRD2-related TaqI A
polymorphism mainly resulted from two independent studies by
Peng et al. [2002] and Shahmoradgoli Najafabadi et al. [2005]. After
exclusion of these two studies, the heterogeneity for all models
FIG. 1. Forest plots of the association between four most-studied polymorphisms of dopamine receptor gene and opioid dependence risks. (a) DRD2
141ins/delC (141delC/141delC þ 141delC/141insC vs. 141insC/141insC); (b) DRD2 311 Ser > Cys (Cys311/Cys311 þ Ser311/
Cys311 vs. Ser311/ Ser311); (c) DRD2-related TaqI A (A1A1 þ A1A2 vs. A2A2); (d) DRD4 exon III VNTR (long allele vs. short allele).
CHEN ET AL.
665
FIG. 1. (Continued)
effectively abrogated without substantial changes in opioid dependence risk (A1A1 vs. A2A2: OR, 1.47, 95% CI, 1.15–1.87, by fixed
effects; P ¼ 0.559 for heterogeneity, I2 ¼ 0.0%; A1A1 þA1A2 vs.
A2A2: OR, 1.17, 95% CI, 1.02–1.33, by fixed effects; P ¼ 0.773 for
heterogeneity, I2 ¼ 0.0%; A1A1 vs. A1A2 þ A2A2: OR, 1.35, 95%
CI, 1.08–1.68, by fixed effects; P ¼ 0.545 for heterogeneity,
I2 ¼ 0.0%).
The Association Between DRD4 Exon III VNTR and
Opioid Dependence Risk
The eligible studies included 2,527 cases and 1,410 controls. Two-,
4-, and 7-repeat alleles were the three most prevalent alleles. The
prevalence rates were 18.4% (95% CI, 17.5%–19.2%), 72.2% (95%
CI, 71.2%–73.2%), and 3.1% (95% CI, 2.7%–3.5%), respectively.
666
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
TABLE II. Associations Between the DRD2 141ins/delC, DRD2 311 Ser > Cys, and DRD2-Related TaqI A Polymorphism and Opioid
Dependence Risk
Studies
DRD2 141Cdel/ins
Li et al. [2002]
Cao et al. [2003]
Xu et al. [2004], Chinese
Xu et al. [2004], German
Shao et al. [2005b]
Xu et al. [2005]
All
DRD2 311 Ser > Cys
Li et al. [2002]
Xu et al. [2004], Chinese
Xu et al. [2004], German
Xu et al. [2005]
All
DRD2-related TaqI A
Persico et al. [1996]
Lawford et al. [2000]
Li et al. [2002]
Peng et al. [2002]
Xu et al. [2004], Chinese
Xu et al. [2004], German
Shahmoradgoli Najafabadi et al. [2005]
Barratt et al. [2006]
Xu et al. [2006]
Perez de los Cobos et al. [2007]
Crettol et al. [2008]
Hou and Li [2009]
All
Sample size
case/control
Homozygotea
OR (95% CI)
Dominantb
OR (95% CI)
Recessivec
OR (95% CI)
465/298
302/177
475/309
471/191
380/275
965/300
3,058/1,550
8.61 (1.12–66.23)
2.16 (0.69–6.75)
6.27 (0.79–49.76)
1.01 (0.19–5.24)
1.64 (0.91–2.97)
13.49 (1.85–98.56)
2.71 (1.74–4.22)
1.19 (0.82–1.72)
1.67 (1.07–2.60)
1.43 (0.99–2.08)
0.96 (0.63–1.46)
1.14 (0.82–1.58)
1.38 (0.97–1.96)
1.27 (1.09–1.48)
8.54 (1.11–65.64)
1.95 (0.62–6.06)
5.95 (0.75–47.19)
1.01 (0.20–5.27)
1.63 (0.91–2.92)
13.27 (1.82–96.86)
2.63 (1.70–4.07)
119/189
482/283
457/192
965/300
2,023/964
4.59 (0.19–113.62)
1.72 (0.07–42.29)
Noned
1.36 (0.62–2.97)
1.48 (0.71–3.09)
0.65 (0.27–1.52)
0.69 (0.39–1.21)
1.71 (0.63–4.63)
1.01 (0.67–1.51)
0.91 (0.68–1.22)
4.80 (0.19–118.74)
1.77 (0.07–43.51)
Noned
1.37 (0.63–2.99)
1.50 (0.72–3.13)
40/119
95/50
121/193
66/132
486/313
455/191
100/130
71/95
209/109
281/145
238/217
517/492
2,679/2,186
1.54 (0.27–8.84)
0.19 (0.02–1.94)
1.72 (0.73–4.07)
15.71 (5.77–42.78)
1.22 (0.79–1.89)
1.00 (0.41–2.48)
10.59 (2.24–50.10)
1.37 (0.19–10.08)
1.78 (0.35–9.03)
5.39 (1.23–23.56)
1.44 (0.46–4.49)
1.62 (1.10–2.41)
2.06 (1.25–3.42)
1.12 (0.51–2.45)
1.36 (0.65–2.84)
1.17 (0.74–1.85)
2.43 (1.24–4.75)
1.11 (0.83–1.50)
0.96 (0.67–1.36)
4.72 (2.58–8.62)
1.07 (0.56–2.04)
1.73 (0.98–3.03)
1.13 (0.74–1.73)
0.96 (0.64–1.43)
1.36 (1.04–1.78)
1.34 (1.08–1.67)
1.51 (0.27–8.59)
0.17 (0.02–1.65)
1.66 (0.72–3.83)
14.88 (6.04–36.69)
1.17 (0.78–1.74)
1.02 (0.42–2.50)
7.11 (1.52–33.24)
1.35 (0.19–9.81)
1.58 (0.31–7.97)
5.48 (1.26–23.78)
1.48 (0.48–4.58)
1.37 (0.97–1.94)
1.94 (1.17–3.22)
a
For DRD2 141ins/delC, homozygote comparison was del/del versus ins/ins; for DRD2 311 Ser > Cys, homozygote comparison was Cys/Cys versus Ser/Ser; for DRD2-related TaqI A, homozygote
comparison was A1/A1 versus A2/A2.
b
For DRD2 141ins/delC, dominant model was del/del þ del/ins versus ins/ins; for DRD2 311 Ser > Cys, dominant model was Cys/Cys þ Cys/Ser versus Ser/Ser; for DRD2-related TaqI A, dominant model
was A1/A1 þ A1/A2 versus A2/A2.
c
For DRD2 141ins/delC, recessive model was del/del versus del/ins þ ins/ins; for DRD2 311 Ser > Cys, recessive model was Cys/Cys versus Cys/Ser þ Ser/Ser; for DRD2-related TaqI A, recessive model
was A1/A1 versus A1/A2 þ A2/A2.
d
There was no people with Cys/Cys genotype in the study.
As suggested by most studies [Lopez Leon et al., 2005], DRD4 exon 3
VNTR allelic categories were defined as class S (short) for
<5 repeats and class L (long) for 5 repeats.
ORs for all alleles and genotypes were pooled by using fixedeffect models since there was no substantial between-study heterogeneity (P > 0.05, I2 < 50%) among the eight studies of the DRD4
exon III VNTR polymorphism. Increased OR for opioid dependence was observed in individuals with the L allele as compared with
those with the S allele (OR 1.50; 95% CI, 1.24–1.80) (Fig. 1d and
Table III). When we examined the effects of DRD4 2-, 4-, and 7repeat alleles, we found that there was statistical evidence of an
association between the reduced opioid dependence risk and the
4-repeat allele (OR, 0.84; 95%, 0.75–0.93), and an association
between the increased opioid dependence risk and the 7-repeat
allele (OR, 1.57; 95%, 1.18–2.09) (Table III). No association was
observed with the 2-repeat allele (OR, 1.05; 95%, 0.93–1.19)
(Table III). For genotypes, we also found statistical evidence of
an association between the increased opioid dependence risk and
the L allele (LS vs. SS: OR, 1.64; 95% CI, 1.31–2.05; LLþ LS vs. SS:
1.61; 95% CI, 1.30–1.98).
Finally, there was no publication bias detected by either the
funnel plot or the Egger’s test for 7-repeat allele in comparison with
remaining alleles (t ¼ 0.47, P ¼ 0.683), but for L allele in comparison with S allele (t ¼ 3.70, P ¼ 0.010) (Fig. 2d) among the included
studies.
DISCUSSION
The current meta-analysis examined the associations between four
well-characterized polymorphisms (DRD2 141ins/delC, DRD2
311 Ser > Cys, DRD2-related TaqI A, and DRD4 exon III VNTR)
with opioid dependence risk. A total of 6,846 cases and 4,187
CHEN ET AL.
667
controls from 22 independent publications were included in the
final analysis. We demonstrated that the DRD2 141ins/delC and
DRD2-related TaqI A polymorphisms were associated with significant increased opioid dependence risk in all of the homozygote,
dominant and recessive models, whereas the DRD2 311 Ser > Cys
polymorphism did not appear to have any influence on opioid
dependence susceptibility. For DRD4 exon III VNTR polymorphism, we found a significantly increased opioid dependence risk
for individuals carrying 7-repeat allele and a decreased opioid
dependence risk for individuals carrying 4-repeat allele. Besides,
increased opioid dependence risk was also found in individuals with
LL or LS genotype as compared with SS genotype in our study.
Our results demonstrating the associations between the variants
of DRD2 or DRD4 and susceptibility to opioid dependence are
biologically plausible. Accumulating evidence demonstrated that
drugs abuse stimulate reward pathways in the brain by increasing
the release of dopamine, therefore facilitating the dopamine neurotransmission in the mesocorticolimbic dopamine system [Pierce
and Kumaresan, 2006; Doehring et al., 2009]. DRD2 signaling has
been proposed involved in this reinforcing action [Noble, 2000;
Doehring et al., 2009]. The present meta-analysis supported a
significant association between DRD2 polymorphisms and opioid
dependence risk, especially showing that the 141delC variant
might be a risk factor of opioid dependency. Since the 141delC
allele was suggested to reduce the transcriptional activation and
subsequent protein expression of DRD2 and affect receptor binding
in striatum [Arinami et al., 1997; Hirvonen et al., 2009], which in
turn stimulates craving-reward pathway, individuals with the
deletion variant may be more susceptible to opioid dependence.
However, there are still a lot of ambiguous issues between the
141ins/delC polymorphism and function or expression of DRD2,
and further effort is needed to classify the underlying mechanism.
Another extensively focused variant was the TaqI A, which researchers are interested in partly because it associated with the expression
level of nearby DRD2 gene and may alter the function of DRD2
[Munafo et al., 2009]. The SNP has been reported to affect DRD2
availability in postmortem striatal samples [Noble et al., 1991], and
the A1 variant was indicated to be associated with lower mean
relative glucose metabolic rate in dopaminergic regions in the
human brain via in vivo study [Noble et al., 1997; Munafo et al.,
2009]. Evidence from another in vivo study [Jonsson et al., 1999]
also supported that the A1 variant was associated with decreased
dopamine receptor density using Positron emission tomography
(PET) scan. Therefore, individuals with TaqI A1 variant may have
functional deviations in the DRD2 gene and may subsequently get
less satisfaction with natural rewards such as food and sex, and
consequently tend to abuse drugs as a way to seek an enhanced
stimulation of reward pathways, according to the ‘‘rewarddeficiency syndrome’’ hypothesis [Blum et al., 2000; Doehring
et al., 2009].
The DRD4 is another strong candidate involved in reward and
reinforcement mechanisms in the brain, since it is expressed in the
FIG. 2. Funnel plot analysis to detect publication bias for each of
the polymorphisms. (a) DRD2 141ins/delC; (b) DRD2 311
Ser > Cys; (c) DRD2-related TaqI A; (d) DRD4 exon III VNTR.
668
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
TABLE III. Associations Between the DRD4 Exon 3 VNTR Polymorphism and Opioid Dependence Risk
Studies
Kotler et al. [1997]
Li et al. [1997]
Franke et al. [2000]
Li et al. [2000]
Zhao et al. [2001]
Cao et al. [2002]
Shao et al. [2005a]
Chien et al. [2010]
All
Sample size
case/control
141/110
121/154
285/197
405/304
102/64
199/126
380/275
894/180
2,527/1,410
Two-repeat
allele OR (95% CI)
0.60 (0.35–1.03)
1.12 (0.72–1.71)
1.28 (0.80–2.08)
1.22 (0.94–1.59)
0.40 (0.16–0.99)
1.05 (0.69–1.60)
1.06 (0.82–1.38)
1.02 (0.78–1.35)
1.05 (0.93–1.19)
Four-repeat
allele OR (95% CI)
0.92 (0.62–1.36)
0.75 (0.51–1.10)
0.76 (0.57–1.00)
0.76 (0.59–0.96)
1.05 (0.66–1.67)
0.91 (0.62–1.33)
0.89 (0.69–1.13)
0.87 (0.67–1.13)
0.84 (0.75–0.93)
Seven-repeat
allele OR (95% CI)
2.79 (1.49–5.24)
6.41 (0.31–134.22)
1.32 (0.93–1.86)
5.28 (0.27–102.31)
0.31 (0.06–1.70)
0.63 (0.04–10.15)
3.63 (0.17–75.74)
Nonea
1.57 (1.18–2.09)
Long allele
OR (95% CI)
1.85 (1.11–3.08)
2.30 (1.07–4.93)
1.16 (0.84–1.59)
1.57 (0.92–2.67)
1.48 (0.88–2.52)
1.42 (0.66–3.04)
1.40 (0.80–2.43)
2.89 (1.16–7.22)
1.50 (1.24–1.80)
a
There was no 7-repeat allele in the study.
limbic region of the brain and contains a highly polymorphic VNTR
in exon III which may affect receptor function [Li et al., 1997]. Our
current meta-analysis also supported a significant impact of DRD4
polymorphisms on opioid dependence risk, particularly proving
the role of the L allele and 7-repeat allele in susceptibility to opioid
dependence. The DRD4 exon III VNTR, which was originally
associated with the human personality trait of novelty seeking
[Ebstein et al., 1996], has been subsequently linked to many other
disorders, such as attention deficit hyperactivity disorder (ADHD)
[LaHoste et al., 1996], mood disorders [Lopez Leon et al., 2005],
obsessive compulsive disorder [Camarena et al., 2007], and pathological gambling [Perez de Castro et al., 1997]. The underlying
mechanism remains to be elucidated. As the 7-repeat allele may
have negative post-transcriptional effects on gene expression such
as mRNA stability or translation efficiency, a reduction of DRD4
expression was observed with the 7-repeat sequence as compared
with the 2- and 4-repeat sequences [Schoots and Van Tol, 2003;
Simpson et al., 2010]. Furthermore, an animal study [Rubinstein
et al., 1997] has suggested that mice lacking DRD4 were supersensitive to ethanol, cocaine, and methamphetamine. Thus a significant overrepresentation of 7-repeat allele or L allele in opioid
dependence subjects may be correlated with decreased DRD4
expression, which attenuated the inhibition of intracellular
cAMP accumulation. Moreover, greater cAMP in limblic regions,
specifically the nucleus accumbens, can result in greater motivation
for dopaminergic rewards, thereby promoting opioid dependence
[Knapp et al., 2001; Lynch and Taylor, 2005; Choi et al., 2006].
However, caution should be exercised when considering these
conclusions because of the presence of publication bias. The P
value of the Egger’s test was <0.05 for L allele as compared with S
allele, so there were some studies with negative results missing for
DRD4 exon III VNTR polymorphism.
Our meta-analysis also has some limitations. First, like most
other meta-analysis, the overall findings from the meta-analysis
were limited by the quality of the primary studies. As previously
described [Smith et al., 2008], all of the studies in our meta-analysis
also had one or more serious methodological shortcomings: lack of
blinding, inconsistent screening of control groups, and lack of or
inadequate description of genotyping methods. Second, although
we made a considerable effort to find published studies, a group of
unpublished negative studies could not be included in this metaanalysis as revealed by the Egger’s test and the funnel plot, particularly for the DRD4 exon III VNTR polymorphism. Besides,
although the Egger’s test and funnel plot suggested no significant
publication bias for the DRD2 311 Ser > Cys polymorphism, the
limited number of included studies may result in the low statistical
power of the Egger’s test [Zheng et al., 2009] and influence the
stability of analyses for this polymorphism. Third, there was significant between-study heterogeneity from studies of the DRD2related TaqI A polymorphism. However, exclusion of two studies,
from which the heterogeneity mainly originated, can effectively
abrogate the heterogeneity without significantly influencing the
estimates of opioid dependence risk. Based on these limitations, our
conclusions should be interpreted cautiously.
In conclusion, our meta-analysis supports the association
between the DRD2 141delC, DRD2-related TaqI A1, L allele
and 7-repeat allele of DRD4 exon III VNTR and increased opioid
dependence risk.
More studies with large sample sizes regarding the association
between dopamine receptor gene and opioid dependence are
required to confirm current findings.
ACKNOWLEDGMENTS
This work was supported by the National Natural Science Foundation of China NSFC-30872175 to Z. Wang.
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