Association between polymorphisms of DRD2 and DRD4 and opioid dependence Evidence from the current studies.код для вставкиСкачать
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: firstname.lastname@example.org 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.  Kotler et al.  Li et al.  Franke et al.  Lawford et al.  Li et al.  Zhao et al.  Cao et al.  Li et al.  Peng et al.  Cao et al.  Xu et al.  Shahmoradgoli Najafabadi et al.  Shao et al. [2005a] Shao et al. [2005b] Xu et al.  Barratt et al.  Xu et al.  Perez de los Cobos et al.  Crettol et al.  Hou and Li  Chien et al.  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. , and the DRD4 exon III VNTR polymorphism in the study by Zhao et al. . 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.  and Shahmoradgoli Najafabadi et al. . 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.  Cao et al.  Xu et al. , Chinese Xu et al. , German Shao et al. [2005b] Xu et al.  All DRD2 311 Ser > Cys Li et al.  Xu et al. , Chinese Xu et al. , German Xu et al.  All DRD2-related TaqI A Persico et al.  Lawford et al.  Li et al.  Peng et al.  Xu et al. , Chinese Xu et al. , German Shahmoradgoli Najafabadi et al.  Barratt et al.  Xu et al.  Perez de los Cobos et al.  Crettol et al.  Hou and Li  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.  Li et al.  Franke et al.  Li et al.  Zhao et al.  Cao et al.  Shao et al. [2005a] Chien et al.  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. REFERENCES Arinami T, Gao M, Hamaguchi H, Toru M. 1997. 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