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. 2016 Dec 9;12:3129–3144. doi: 10.2147/NDT.S118614

Associations between dopamine D2 receptor gene polymorphisms and schizophrenia risk: a PRISMA compliant meta-analysis

Hairong He 1, Huanhuan Wu 1,2, Lihong Yang 1, Fan Gao 1, Yajuan Fan 3, Junqin Feng 3, Xiancang Ma 1,3,✉
PMCID: PMC5158172  PMID: 28003749

Abstract

Objective

To determine the relationships between dopamine D2 receptor gene polymorphisms and the risk of schizophrenia using meta-analysis.

Method

The PubMed, Embase, and China National Knowledge Infrastructure databases were searched to identify relevant literature published up to February 2016. The allele contrast model was used. Stata software was used for statistical analysis, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated to evaluate the associations between dopamine D2 receptor gene polymorphisms and the risk of schizophrenia. Meta-regression and publication bias, trim-and-fill, subgroup, sensitivity, cumulative, and fail-safe number analyses were also performed.

Results

This meta-analysis included 81 studies. The rs1801028 and rs1799732 were associated with schizophrenia risk among Asians (P=0.04, OR =1.25, 95% CI =1.01–1.55; P<0.01, OR =0.76, 95% CI =0.63–0.92, respectively), while the rs6277 was associated with schizophrenia risk in Caucasians (P<0.01, OR=0.72, 95% CI =0.66–0.79). The rs1800497 was also associated with schizophrenia risk in population-based controls (P<0.01, OR =0.84, 95% CI =0.72–0.97). The rs6275, rs1079597, and rs1800498 were not associated with schizophrenia risk. In addition, meta-regression indicated that the controls may be sources of heterogeneity for the rs1801028 single-nucleotide polymorphism (SNP), while ethnicity may be sources of heterogeneity for the rs6277 SNP. Publication bias was significant for the rs1801028 SNP, and this result changed after the publication bias was adjusted using the trim-and-fill method.

Conclusion

This meta-analysis demonstrated that the rs1801028 may be a risk factor for susceptibility to schizophrenia among Asians, while the rs1799732 may be a protective factor for that population. Large-sample studies are necessary to verify the results of this meta-analysis.

Keywords: dopamine D2 receptor, polymorphisms, schizophrenia

Introduction

Schizophrenia is a severe mental disorder characterized by changes in its higher functions and deterioration of behavior, cognition, emotions, motivation, and perception, and is marked by socio-occupational dysfunction. Schizophrenia manifests with a wide variety of positive (auditory hallucinations and paranoid delusions), negative (affective flattening, anhedonia, and alogia), and cognitive (declined attention and memory) symptoms.1 It is a complex multifactorial psychiatry disorder involving genetic and environmental factors, with a global lifetime prevalence of 0.5%–1%.2

Family, twin, and adoption studies have shown that genetic factors play a significant role in the pathogenesis of schizophrenia, with the heritability of schizophrenia being estimated at 70%–80%.3,4 Additionally, Lee et al estimated that 23% of variation in liability to schizophrenia is captured by single-nucleotide polymorphisms (SNPs).5 For schizophrenia, some genetic factors were shared with other psychiatric disorders (bipolar disorder, major depressive disorder, autism spectrum disorders, and attention-deficit/hyperactivity disorder),6 and some genetic factors associated with its risk were overlapped with those associated with reproduction traits (eg, age at first birth).7 In short, schizophrenia is highly polygenic.8

The dopamine hypothesis is one of the main ideas for explaining the etiology of schizophrenia.9 There are several lines of evidence implicating dopamine D2 receptor (DRD2) as the main candidate gene for the risk of schizophrenia.10 In humans, the DRD2 gene is located on chromosome 11 at q22–q23, extends over 270 kb, and has eight exons.11 Associations between schizophrenia risk and four SNPs have been widely studied: rs1799732 (–141C Ins/Del), rs1801028 (311 Ser/Cys), rs1800497 (TaqIA), and rs6277 (C957T).12,13 The rs1799732 SNP is located in the DRD2 promoter region and has been demonstrated to affect gene expression in vitro.14 The rs1801028 SNP is the missense variant 960C/G in exon 7 of the DRD2 gene15 that can alter the physiology and function of the D2 receptor.12 The rs1800497 SNP was previously thought to be located in the DRD2 3′-untranslated region and was recently identified as being in exon 8 of the ankyrin repeat and kinase domain containing 1 (ANKK1) gene. This SNP has been considered to alter substrate-binding specificity.16 The rs6277 SNP is located in exon 7 of the DRD2 gene and alters mRNA folding, leading to a decrease in mRNA stability and translation, and markedly changing dopamine-induced up-regulation of DRD2 expression.17 In addition, associations between schizophrenia risk and the rs6275 (C939T), rs1079597 (TaqIB), and rs1800498 (TaqID) SNPs have been widely reported.18,19

While associations between DRD2 gene polymorphisms and the risk of schizophrenia have been studied extensively, there are still some uncertainties about these associations. The present meta-analysis was therefore performed to further identify the associations between DRD2 gene polymorphisms and schizophrenia risk. Meta-regression and publication bias, nonparametric trim-and-fill, subgroup, sensitivity, cumulative, and fail-safe number analyses were also performed.

Method

Search strategy

The PubMed, Embase, and China National Knowledge Infrastructure databases were independently searched by two reviewers (He and Wu) to collect the literature related to associations between DRD2 gene polymorphisms and schizophrenia risk. The last search update was performed in February 2016, and the following keywords were used in the literature search: “schizophrenia”, “psychosis”, “schizophrenic,” “DRD2,” “dopamine receptor 2,” “dopamine receptor D2”, “dopamine D2 receptor”, “polymorphism”, “variant”, “variation”, “allele”, and “genotype”. The species was limited to human. Moreover, the literature references in all of the included documents were searched to find more studies that were consistent with the eligibility criteria.

Eligibility criteria

  1. Studies that met the following inclusion criteria were included:
    1. Research study with a case–control design.
    2. Written in Chinese or English.
    3. Investigation of the associations between DRD2 gene polymorphisms and the risk of schizophrenia.
    4. Providing sufficient allele or genotype distribution data of the included cases and controls.
  2. Studies that met any of the following exclusion criteria were excluded:
    1. Repetition of information in other literature.
    2. A review, comment, or conference proceedings.
    3. Results obtained in an animal model.
    4. Series of reports or case reports.

Research screening

The studies were first screened by browsing the titles and abstracts of the identified documents. Secondary screening was then performed by reading the full text of selected reports. Finally, data extraction and quality assessment were performed for the included studies.

Data extraction

In our present study, two reviewers (He and Wu) independently extracted the following information from the included literature: first author, publication year, mean age of the cases and controls, country, ethnicity, source of controls, numbers of cases and controls, DRD2 gene locus, diagnostic criteria of schizophrenia, genotyping method, and conformity with Hardy–Weinberg equilibrium (HWE) for the controls. If the allele or genotype distribution data of the cases and controls were not reported in the original articles, the corresponding author was contacted by mail to obtain this information.

Quality assessment

Two authors (HH and HW) independently performed quality assessment using quality scoring criteria20 based on criteria previously applied in observational studies for addressing genetic epidemiological issues, with the scores ranging from 0 points (worst) to 9 points (best) (Table S1). A study was classified as being of low quality when it scored <6 points. Sensitivity analysis was conducted by deleting these low-quality studies.

Statistical analysis

Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the strengths of the associations between DRD2 gene polymorphisms and schizophrenia risk. Pooled effect sizes were calculated using the random-effects model. This model evaluated different underlying influences considering both within- and between-study variations, which provided the advantage of accommodating diversity between studies and yielding a more conservative estimate of the assessed effect.21 The present study used an allele comparison model because this maximized the number of included studies.

Cochran’s Q statistic was used to estimate the degree of heterogeneity in the included studies. Heterogeneity was considered to be high when the P-value was <0.1. The heterogeneity was also quantified using the I2 statistic and was considered high when I2>50%. Based on clinical knowledge, the ethnicity and source of controls were considered to be responsible for heterogeneity, and so these parameters were set as covariates in the meta-regression. A subgroup analysis was also conducted.

Publication bias was analyzed using Begg’s funnel plots. An asymmetrical funnel plot indicated the presence of significant publication bias. The symmetry of Begg’s funnel plots was judged using Egger’s linear regression, and a P-value of <0.05 was considered to indicate that the funnel plots were significantly asymmetrical. The trim-and-fill method was used to correct for publication bias and also to assess the impact of publication bias on the results.

Sensitivity analysis was used to assess both the potential impact of single studies on the pooled effect size and the impact of removing low-quality studies on the obtained results. Cumulative analysis by publication year was used to explore temporal trends in the results. Finally, the fail-safe number of negative studies that would be required to nullify (ie, make P>0.05) the effect size was calculated.

All of the statistical analyses were conducted using Stata software, version 12.0 (Stata Corporation, College Station, TX, USA).

Results

Study characteristics

A flow chart of the study selection procedure is shown in Figure 1. Briefly, 1,267 studies were identified after eliminating 304 duplications. After reviewing the abstracts or reading full texts carefully according to eligibility criteria, a further 1,186 studies were excluded. Finally, 81 studies were identified for exploring the associations between DRD2 gene polymorphisms and susceptibility to schizophrenia in a meta-analysis.

Figure 1.

Figure 1

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Flow diagram of the study selection process.

Abbreviations: CNKI, China National Knowledge Infrastructure; DRD2, dopamine D2 receptor.

The main features of the included studies are listed in Table 1. The 81 studies comprised 45 studies focused on Caucasians, 34 on Asians, and 2 on mixed populations. The distributions of genotypes in the control groups deviated from HWE for the rs1801028, rs1800497, and rs1800498 SNPs in seven studies.11,22–27 The quality assessment revealed that four studies were of low quality.26,28–30

Table 1.

Characteristics of case–control studies on DRD2 gene polymorphisms and schizophrenia risk included in the meta-analysis

Author Year Country Ethnicity No of sample
Control sources Mutation analysis method Criteria SNP HWE (P-value) Quality score
Cases Controls
Caprini et al28 2011 Scandinavia Caucasians 837 1,471 PB – ICD-10 + DSM-III-R + DSM-IV TaqID Yes 5
Dollfus et al35 1996 France Caucasians 62 161 PB PCR-RFLP DSM-III-R TaqIA Yes 8
Luo24 2008 China Asians 211 201 PB Direct sequencing DSM-IV −141C Ins/Del Yes 6
Watanabe et al36 2012 Japan Asians 648 664 PB TaqMan DSM-IV Ser311Cys Yes 7
Crawford et al31 1996 America Caucasians 84 81 HB Direct sequencing DSM-III-R Ser311Cys Yes 6
Dubertret et al13 2010 France Caucasians 50 50 PB PCR DSM-IV TaqIB – –
TaqIA Yes 7
Himei et al37 2002 Japan Asians 190 103 PB PCR-RFLP DSM-IV Ser311Cys Yes 7
−141C Ins/Del Yes 7
Jonsson et al87 1996 Sweden Caucasians 118 78 PB PCR DSM-III-R TaqIA Yes 7
Kunii et al62 2014 Japan Asians 12 12 PB PCR-RFLP DSM-IV TaqIA Yes 8
Srivastava et al4 2010 India Caucasians (Indians) 233 224 PB PCR-RFLP DSM-IV −141C Ins/Del Yes 8
TaqIA Yes 8
TaqIB – –
Ser311Cys Yes 8
Arinami et al47 1996 Japan Asians 136 279 PB PCR ICD-10 + DSM-III-R Ser311Cys Yes 7
Arinami et al57 1997 Japan Asians 260 312 PB PCR-RFLP DSM-III-R −141C Ins/Del Yes 7
Aslan et al23 2010 Turkey Caucasians 99 109 PB PCR DSM-IV TaqIA No 6
Behravan et al11 2008 Iran Caucasians 38 63 PB PCR DSM-IV TaqIB Yes 7
TaqIA No 6
Betcheva et al1 2009 Bulgaria Caucasians 255 556 PB PCR DSM-IV C957T Yes 8
C939T Yes 8
Breen et al63 1999 England Caucasians 439 437 PB PCR DSM-III-R + DSM-IV −141C Ins/Del Yes 7
Chen et al38 1996 China Asians 114 88 PB PCR DSM-III-R Ser311Cys Yes 6
Cordeiro et al14 2009 Brazil Mixed 229 733 PB – DSM-IV −141C Ins/Del Yes 8
Cordeiro and Vallada16 2014 Brazil Mixed 235 834 PB PCR DSM-IV TaqIA Yes 8
Dubertret et al15 2004 France Caucasians 103 83 PB PCR-RFLP DSM-IV −141C Ins/Del Yes 7
TaqIB – –
TaqID – –
Ser311Cys Yes 7
TaqIA Yes 7
Dubertret et al13 2010 France Caucasians 144 142 PB TaqMan DSM-IV TaqIA Yes 8
C957T – –
Ser311Cys Yes 8
−141C Ins/Del Yes 8
TaqID – –
TaqIB – –
Fan et al39 2010 China Asians 421 404 PB PCR DSM-IV Ser311Cys Yes 7
C957T Yes 7
C939T Yes 7
Golimbet et al40 2011 Russia Caucasians 366 387 PB PCR ICD-10 Ser311Cys Yes 8
Gupta et al41 2009 India Caucasians (Indians) 254 225 PB PCR DSM-IV −141C Ins/Del Yes 8
Ser311Cys Yes 8
C957T Yes 8
C939T Yes 8
Hanninen et al64 2006 Finland Caucasians 188 384 PB PCR DSM-IV C957T Yes 8
Harano42 1997 Japan Asians 70 101 HB PCR DSM-III-R Ser311Cys Yes 6
Hoenicka et al65 2006 Spain Caucasians 131 364 PB PCR DSM-IV C957T Yes 7
Hori et al43 2001 Japan Asians 241 201 PB PCR DSM-IV Ser311Cys Yes 7
−141C Ins/Del Yes 7
Iwata et al44 2003 Japan Asians 51 63 PB PCR-RFLP DSM-IV Ser311Cys Yes 7
Jonsson et al66 1999 Sweden Caucasians 129 179 HB PCR DSM-III-R −141C Ins/Del Yes 6
Jonsson et al45 2003 Sweden Caucasians 173 236 HB PCR DSM-III-R Ser311Cys Yes 6
Kaneshima et al46 1997 Japan Asians 78 112 PB PCR RDC + DSM-IV Ser311Cys Yes 7
Kukreti et al2 2006 India Caucasians (Indians) 101 145 PB PCR DSM-IV C957T Yes 8
C939T Yes 8
Kurt et al67 2011 Turkey Caucasians 73 60 PB PCR-RFLP DSM-IV −141C Ins/Del Yes 7
Lafuente et al68 2008 Spain Caucasians 243 291 HB PCR DSM-IV TaqIB Yes 7
TaqIA Yes 7
−141C Ins/Del Yes 7
Laurent et al48 1994 France Caucasians 113 184 PB – DSM-III-R Ser311Cys Yes 6
Lawford et al10 2005 Australia Caucasians 154 148 PB PCR DSM-IV C957T Yes 7
Li et al70 1998 England Caucasians 151 145 HB PCR DSM-IV + DSM-III-R −141C Ins/Del Yes 6
Monakhov et al69 2008 Russia Caucasians 311 364 PB PCR DSM-IV C957T Yes 7
C939T Yes 7
TaqIA Yes 7
Ohara et al3 1996 Japan Asians 153 121 PB PCR DSM-IV Ser311Cys Yes 7
Ohara et al71 1998 Japan Asians 170 121 PB PCR DSM-IV −141C Ins/Del Yes 8
Parsons et al25 2007 Spain Caucasians 119 165 PB PCR-RFLP DSM-IV −141C Ins/Del Yes 7
TaqIA No 6
Saiz et al72 2010 Spain Caucasians 288 421 PB PCR-RFLP DSM-IV −141C Ins/Del Yes 9
Sanders et al49 2008 Europe Caucasians 1,870 2,002 PB TaqMan DSM-IV Ser311Cys Yes 8
−141C Ins/Del Yes 8
Sasaki et al26 1996 Europe Caucasians 273 255 HB PCR DSM-III-R Ser311Cys Yes 5
Spurlock et al50 1998 Europe Caucasians 373 413 PB PCR DSM-III-R Ser311Cys Yes 7
Stöber et al73 1998 German Caucasians 260 290 PB PCR ICD-10 −141C Ins/Del Yes 7
Tallerico et al74 1999 America Caucasians 50 51 PB PCR DSM-III-R −141C Ins/Del Yes 7
Tanaka et al51 1996 Japan Asians 106 106 PB PCR DSM-III-R Ser311Cys Yes 7
Tsutsumi et al22 2011 Japan Asians 407 384 PB PCR-RFLP DSM-IV C957T Yes 7
Ser311Cys No 6
Verga et al52 1997 Italy Caucasians 103 97 PB PCR DSM-III-R Ser311Cys Yes 7
Fujiwara et al54 1997 Japan Asians 52 26 PB PCR DSM-IV + ICD-10 Ser311Cys Yes 7
Kampman et al75 2003 Finland Caucasians 93 94 PB PCR DSM-IV −141C Ins/Del Yes 7
Morimoto et al55 2002 Japan Asians 48 48 PB PCR DSM-IV + ICD-10 Ser311Cys Yes 7
Vijayan et al19 2007 India Caucasians (Indians) 213 196 PB PCR DSM-IV TaqIB Yes 8
TaqIA Yes 8
TaqID Yes 8
C939T Yes 8
Ser311Cys Yes 8
Xiao et al76 2013 China Asians 120 100 PB PCR DSM-IV-TR −141C Ins/Del Yes 7
Comings et al77 1991 America Caucasians 87 69 HB PCR DSM-III-R TaqIA Yes 7
Sanders et al78 1993 America Caucasians 55 51 PB PCR-RFLP DSM-III-R + RDC TaqIA Yes 8
Campion et al79 1994 France Caucasians 80 80 PB PCR-RFLP DSM-III-R TaqIA Yes 7
Itokawa et al58 1993 Japan Asians 50 110 PB PCR-RFLP
SSCP analysis		 DSM-III-R Ser311Cys Yes 7
Nothen et al34 1993 German Caucasians 60 60 PB PCR DSM-III-R TaqIA Yes 7
Arinami et al9 1994 Japan Asians 156 300 HB PCR DSM-III-R Ser311Cys Yes 6
Asherson et al59 1994 England Caucasians 112 64 PB PCR DSM-III-R Ser311Cys Yes 6
Gejman et al61 1994 America Caucasians 106 113 HB PCR-RFLP DSM-III-R Ser311Cys Yes 7
Hattori et al27 1994 Japan Asian 100 100 PB PCR-RFLP DSM-III-R Ser311Cys No 6
Nanko et al60 1994 Japan Asian 100 100 PB PCR DSM-III-R Ser311Cys Yes 6
Nothen et al34 1993 German Caucasians 179 138 PB PCR DSM-III-R Ser311Cys Yes 7
Shaikh et al29 1994 England Caucasians 147 100 HB PCR DSM-III-R Ser311Cys No 5
Sobell et al30 1994 America Caucasians 338 1,914 HB – – Ser311Cys Yes 5
Inada et al80 1999 Japan Asian 234 94 PB PCR ICD-10 −141C Ins/Del Yes 8
Serretti et al81 2000 Italy Caucasians 366 267 HB – – Ser311Cys Yes –
Itokawa et al53 2010 Japan Asian 156 300 HB SSCP DSM-III-R Ser311Cys Yes 7
291 579 PCR
Li82 2014 China Asian 915 421 PB PCR-AFLP
Sequenom
MassARRAY		 ICD-10 + CCMD-II-R TaqIA Yes 7
Fan et al56 1996 China Asian 105 108 PB PCR ICD-10 Ser311Cys Yes 7
Liu et al33 2012 China Asian 317 310 PB PCR DSM-IV TaqIA Yes 7
Liu et al83 2009 China Asian 128 124 PB PCR-RFLP CCMD-3 −141C Ins/Del Yes 7
Luo24 2008 China Asian 512 480 PB PCR DSM-IV −141C Ins/Del Yes 7
Ser311Cys No 6
C957T Yes 7
C939T Yes 7
TaqIA No 6
Shen et al84 2011 China Asian 120 100 PB PCR DSM-IV −141C Ins/Del Yes 7
Zhang et al85 2003 China Asian 67 77 PB PCR CCMD-II-R TaqIA Yes 6
Zheng18 2012 China Asian 92 96 PB PCR – C957T Yes 6
C939T Yes 6
Ser311Cys Yes 6
Liang86 2005 China Asian 101 105 PB PCR DSM-IV + CCMD-3 −141C Ins/Del Yes 7
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Abbreviations: AFLP, amplified fragment length polymorphism; CC, complication or comorbidity; CCMD, Chinese Classification of Mental Disorders; DSM, The Diagnostic and Statistical Manual of Mental Disorder; HB, hospital-based; PB, population-based; HWE, Hardy–Weinberg equilibrium; ICD-10, International Statistical Classification of Diseases and Related Health Problems – 10th version; PCR, polymerase chain reaction; RDC, Research Diagnostic Criteria; SNP, single-nucleotide polymorphisms; RFLP, restriction fragment length polymorphism.

Association between the rs1801028 (311 Ser/Cys) and schizophrenia risk

A meta-analysis of 42 case–control studies (9,771 cases and 11,900 controls) revealed that the variant allele G (Cys) was associated with increased schizophrenia risk in all populations (P=0.009, OR =1.23, 95% CI =1.05–1.44; Figure 2A). The fail-safe number was 104.52, and there was moderate heterogeneity (I2=35%). Meta-regression indicated that the source of controls may have been responsible for this heterogeneity (P<0.01). The subgroup analysis, whose results are presented in Table 2, revealed that the G allele was associated with increased susceptibility to schizophrenia in Asians (P=0.04, OR =1.25, 95% CI =1.01–1.55) and hospital-based controls (P<0.01, OR =1.91, 95% CI =1.39–2.61).

Figure 2.

Figure 2

Figure 2

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Calculated OR and 95% CI for the associations between DRD2 gene polymorphism and schizophrenia risk.

Notes: (A) rs1801028; (B) rs6277; (C) rs1799732; (D) rs1800497. weights are from random effects analysis.

Abbreviations: CI, confidence interval; DRD2, dopamine D2 receptor; OR, odds ratio.

Table 2.

Subgroup analysis of case–control studies on DRD2 gene polymorphisms and schizophrenia risk

SNP Subgroup type Subgroup N P-value OR 95% CI I2 (%)
rs1801028 Control sources Population-based 31 0.99 1.00 0.88, 1.14 0
Hospital-based 11 <0.01 1.91 1.39, 2.61 31
Ethnicity Caucasians 19 0.09 1.22 0.97, 1.54 41
Asians 23 0.04 1.25 1.01, 1.55 31
rs6277 Ethnicity Caucasians 8 <0.01 0.72 0.66, 0.79 0
Asians 4 0.37 1.17 0.83, 1.64 46
rs1799732 Control sources Population-based 24 0.36 0.92 0.78, 1.10 77
Hospital-based 3 0.46 0.81 0.47, 1.41 71
Ethnicity Caucasians 15 0.33 1.11 0.90, 1.36 71
Asians 11 0.004 0.76 0.63, 0.92 56
Mixed 1 0.002 0.61 0.44, 0.83 –
rs1800497 Control sources Population-based 20 0.02 0.84 0.72, 0.97 71
Hospital-based 2 0.46 1.50 0.51, 4.47 86
Ethnicity Caucasians 16 0.24 0.88 0.72, 1.08 71
Asians 5 0.29 0.85 0.63, 1.15 82
Mixed 1 0.06 0.82 0.66, 1.01 –
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Abbreviations: CI, confidence intervals; DRD2, dopamine D2 receptor; OR, odds ratios; SNP, single-nucleotide polymorphisms.

Sensitivity analysis indicated that no single study qualitatively changed the pooled ORs (Figure 3). Removing the low-quality studies26,29,30 did not change the results. Four of the studies deviated from HWE,22,24,26,27 but removing them from the analysis did not change the results. Cumulative analysis by publication year confirmed that pooled ORs and 95% CIs were stable and that there was a reliable temporal trend in the results from 199631 (Figure 4).

Figure 3.

Figure 3

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Sensitivity analysis via deletion of each individual study reflecting the relative influence of each individual dataset on the pooled ORs for the rs1801028.

Abbreviations: CI, confidence interval; OR, odds ratio.

Figure 4.

Figure 4

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Cumulative meta-analyses according to publication year for the rs1801028.

In terms of publication bias, Egger’s linear regression showed that the funnel plots were asymmetrical (P=0.023). The trim-and-fill method suggested that eight studies were missing, and the results for the association between the rs1801028 SNP and schizophrenia changed after replacing the data for these eight studies (OR =1.063, 95% CI =0.892–1.266; Figure 5). This indicates that our analyses were not stable and that future research is very likely to produce different results.

Figure 5.

Figure 5

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Trim-and-fill plot to correct publication bias for the rs1801028.

Abbreviation: SE, standard error.

Association between the rs6277 (C957T) and schizophrenia risk

A meta-analysis of 12 case–control studies (2,919 cases and 3,600 controls) revealed that the variant allele T was associated with decreased schizophrenia risk (P=0.002, OR =0.80, 95% CI =0.69–0.92; Figure 2B). The fail-safe number was 91.00, there was high heterogeneity (I 2=58.5%), and meta-regression indicated that ethnicity may have been responsible for this heterogeneity (P<0.01). A subgroup analysis based on ethnicity showed that the T allele was associated with decreased susceptibility to schizophrenia in Caucasians (P<0.01, OR =0.72, 95% CI =0.66–0.79).

Cumulative analysis by publication year did not show a reliable temporal trend. Sensitivity analysis showed that no single study qualitatively changed the pooled ORs. In terms of publication bias, Egger’s linear regression showed that the funnel plots were symmetrical (P=0.119).

Association between the rs1799732 (−141C Ins/Del) and schizophrenia risk

A meta-analysis of 27 case–control studies (6,770 cases and 7,347 controls) demonstrated that the rs1799732 SNP was not associated with schizophrenia risk (P=0.26, OR =0.91, 95% CI =0.78–1.07; Figure 2C). There was high heterogeneity (I2=76%), and meta-regression indicated that neither ethnicity (P=0.119) nor the source of controls (P=0.452) was responsible for this heterogeneity. A subgroup analysis based on ethnicity showed that the variant type (−141C Del) was associated with decreased susceptibility to schizophrenia in Asians (P=0.004, OR =0.76, 95% CI =0.63–0.92). A subgroup analysis based on the source of controls found no significant association between the rs1799732 SNP and schizophrenia risk in population-based controls or hospital-based controls. In terms of publication bias, Egger’s linear regression showed that the funnel plots were symmetrical (P=0.173).

Association between the rs1800497 (TaqIA) and schizophrenia risk

A meta-analysis of 22 case–control studies (4,017 cases and 4,209 controls) demonstrated that the rs1800497 SNP was not associated with schizophrenia risk (P=0.06, OR =0.87, 95% CI =0.75–1.01; Figure 2D). There was high heterogeneity (I2=72%), and meta-regression indicated that neither ethnicity (P=0.612) nor the source of controls (P=0.372) was responsible for this heterogeneity. A subgroup analysis based on the source of controls revealed that the variant allele A (A2) was associated with decreased schizophrenia risk in population-based controls (P<0.01, OR =0.84, 95% CI =0.72–0.97). A subgroup analysis based on ethnicity revealed that the rs1800497 SNP was also not associated with susceptibility to schizophrenia. There were four studies of the rs1800497 SNP that included controls that did not conform with HWE, but they did not influence the results.11,23–25 In terms of publication bias, Egger’s linear regression showed that the funnel plots were symmetrical (P=0.861).

Association between the other SNPs and schizophrenia risk

There was no evidence that the susceptibility to schizophrenia was associated with the rs6275 (T vs C, P=0.10, OR =0.92, 95% CI =0.83–1.02), rs1079597 (T vs C, P=0.12, OR =0.72, 95% CI =0.47–1.10), or rs1800498 (T vs C, P=0.52, OR =1.03, 95% CI =0.93–1.15) SNP. Sensitivity analysis indicated that no single study of the rs1800498 SNP qualitatively changed the pooled ORs. Removing the low-quality study28 did not change the result.

Discussion

A comprehensive analysis about schizophrenia-associated genetic loci had been performed in a genome-wide association study.32 Our meta-analysis results provide evidence that the rs1801028 and rs6277 SNPs are associated with the risk of schizophrenia. A subgroup analysis indicated that the rs1801028 SNP may increase the risk of schizophrenia in Asians and hospital-based controls, the rs6277 SNP may reduce the risk of schizophrenia in Caucasians, the rs1799732 SNP may reduce the risk of schizophrenia in Asians, and the rs1800497 SNP may reduce the risk of schizophrenia in population-based controls.

Yao et al performed a similar study of the associations between DRD2 gene polymorphisms and schizophrenia risk.12 That study used a genetic model, while our study used an allele contrast model since this made it possible to include the largest number of documents and the maximum sample sizes. Other advantages of the present study were 1) the inclusion of more published documents (including those written in Chinese), which increased the statistical power of our results, 2) more SNPs being investigated, and 3) the application of meta-regression and publication bias, nonparametric trim-and-fill, subgroup, sensitivity, cumulative, and fail-safe number analysis also being performed.

The results of the present study show that the rs1801028 SNP may increase the risk of schizophrenia in Asians and hospital-based controls. Yao et al reported the same result under the dominant model.12 Different results may be obtained for different races due to differences in genetic backgrounds and living conditions.33 Moreover, the results for the subgroup analysis based on hospital-based controls are not reliable because such controls may not be representative and samples of hospital-based controls are often too small, and so these results should be treated cautiously. The results for publication bias were significant, and these changed after being adjusted using the trim-and-fill method, which indicated that those results may not be very stable. This means that if new articles are published in the future, the results of a complete meta-analysis including all available data are very likely to change. The presence of significant publication bias was probably due to our meta-analysis including many small-sample studies. Yao et al found only slight publication bias, but this was not corrected using the trim-and-fill method.12

Twelve of the included documents related to the rs6277 SNP and the meta-analysis showed that this SNP may reduce the risk of schizophrenia in Caucasians; however, Yao et al did not study this SNP.12 However, our included samples for this SNP were small and the cumulative analysis by publication year did not show a reliable trend. This means that the statistical power of the results may not have been high.

In our meta-analysis the rs1799732 SNP was not associated with schizophrenia risk, and Yao et al obtained the same result under the dominant model.12 After performing subgroup analysis, the current meta-analysis indicated that the rs1799732 SNP might reduce the risk of schizophrenia in Asians. In contrast, Yao et al did not find any correlation between the rs1799732 SNP and schizophrenia risk in different races and different populations. The possible reasons for different conclusions being drawn based on the current and previous meta-analyses of the rs1799732 SNP are 1) more documents being included in the present study, especially the Chinese literature, because this is likely to have greatly increased the sample size for Asians, and 2) the use of different genetic models.

The previous meta-analyses did not explore the correlations between the rs1800497 SNP and schizophrenia risk in all populations. After performing subgroup analysis, the present study found that the rs1800497 SNP was associated with schizophrenia risk in population-based controls. In contrast, Yao et al found that the rs1800497 SNP may increase the risk of schizophrenia in Caucasians.12 The possible reasons for the current and previous meta-analyses drawing different conclusions from their subgroup analyses of the rs1800497 SNP are 1) Yao et al applying the wrong allele or genotype distribution data of cases and controls regarding the study of Nothen et al;34 2) the smallness of the study sample of Yao et al; 3) that study not including Chinese studies; and 4) our use of different genetic models. These factors mean that the statistical power would have been higher for the present study.

It is important to note the limitations of our meta-analysis. 1) Meaningless or negative results might not be published, which would lead to some degree of publication bias. 2) Schizophrenia is a multifactorial disease, whereas the present study only considered the impact of the DRD2 gene on schizophrenia risk, and also ignored the possible impacts of environmental factors, age, gender, lifestyle, and diagnosis standards.

In conclusion, this meta-analysis has shown that the rs1801028 SNP may be a risk factor for susceptibility to schizophrenia in Asians, the rs6277 SNP may be a protective factor for susceptibility to schizophrenia in Caucasians, and the rs1799732 SNP may be a protective factor for susceptibility to schizophrenia in Asians. However, the occurrence of schizophrenia represents the cumulative effect of multiple genes, and so only studying a single gene or single polymorphism is unlikely to be adequate. Future studies should pay more attention to the interactions within and between genes as well as within and between their polymorphisms in order to better explain the genetic mechanisms underlying mental illness.

Supplementary material

Table S1.

Scale for quality assessment

Criteria Score
Representativeness of cases
Consecutive/randomly selected form case population with clearly defined sampling frame 2
Consecutive/randomly selected form case population without clearly defined sampling frame or with extensive 1
Not described 0
Definition of the DR
Population- or health-based 2
Hospital-bases 1
Not described 0
Hardy–Weinberg equilibrium in controls
Hardy–Weinberg equilibrium 2
Hardy–Weinberg disequilibrium 1
Genotyping examination
Genotyping done under “blinded” condition 1
Unblinded done or not mentioned 0
Association assessment
Assess association between genotypes and head and neck cancer with appropriate statistics and adjustment for confounders 2
Assess association between genotypes and head and neck cancer with appropriate statistics and without adjustment for confounders 1
Inappropriate statistics used 0
Open in a new tab

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No 81471374).

Footnotes

Author contributions

HRH and HHW performed literature research, data extraction, statistical analysis, and data interpretation. XCM contributed to the study concept and study design. LHY and FG contributed to make figures and tables. YJF and JGF were responsible for the quality control of data and algorithms. All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

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Supplementary Materials

Table S1.

Scale for quality assessment

Criteria Score
Representativeness of cases
Consecutive/randomly selected form case population with clearly defined sampling frame 2
Consecutive/randomly selected form case population without clearly defined sampling frame or with extensive 1
Not described 0
Definition of the DR
Population- or health-based 2
Hospital-bases 1
Not described 0
Hardy–Weinberg equilibrium in controls
Hardy–Weinberg equilibrium 2
Hardy–Weinberg disequilibrium 1
Genotyping examination
Genotyping done under “blinded” condition 1
Unblinded done or not mentioned 0
Association assessment
Assess association between genotypes and head and neck cancer with appropriate statistics and adjustment for confounders 2
Assess association between genotypes and head and neck cancer with appropriate statistics and without adjustment for confounders 1
Inappropriate statistics used 0
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