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International Journal of Clinical and Experimental Medicine logoLink to International Journal of Clinical and Experimental Medicine
. 2014 Oct 15;7(10):3777–3788.

Plasminogen activator inhibitor-1 4G/5G polymorphism is associated with coronary artery disease risk: a meta-analysis

Huifeng Zhang 1, Pingshuan Dong 1, Xuming Yang 1, Zhenghao Liu 1
PMCID: PMC4238518  PMID: 25419432

Abstract

Background: The aim of the current study was to evaluate the association of PAI-1 4G/5G polymorphism with coronary artery disease (CAD) risk using a meta-analysis. Methods: All eligible studies were identified through a search of PubMed, EMBASE, China National Knowledge Infrastructure (CNKI), Database of Chinese Scientific and Technical Periodicals, and China Biology Medical literature database (CBM) before June 2014. The association between the PAI-1 4G/5G polymorphism and CAD risk was estimated by odds ratio (OR) and 95% confidence interval (CI). Results: A total of 72 studies including 23557 cases and 21526 controls were eventually collected. The PAI-1 4G/5G polymorphism was significant associated with CAD risk in overall population (OR=1.19, 95% CI 1.10-1.28, P < 0.00001). The combination of adjusted ORs for CAD was 1.20 (95% CI 1.03-1.40, P=0.02). This polymorphism was associated with CAD risk in Caucasians (OR=1.10, 95% CI 1.02-1.19, P=0.01) and Asians (OR=1.46, 95% CI 1.21-1.75, P < 0.0001). This polymorphism significantly increased MI risk (OR=1.15, 95% CI 1.06-1.25, P=0.001). In the subgroup analysis by age, this polymorphism was significantly associated with early-onset CAD risk (OR=1.21, 95% CI 1.02-1.43, P=0.03). In the gender subgroup analyses, a statistically significant association was found in male CAD patients (OR=1.10, 95% CI 1.01-1.20, P=0.04). Both T2DM patients and non-T2DM patients carrying 4G allele showed increased CAD risks (OR=2.23, 95% CI 1.27-3.92, P=0.005 and OR=1.64, 95% CI 1.19-2.25, P=0.002, respectively). Conclusions: This meta-analysis suggested that PAI-1 4G/5G polymorphism was a risk factor for CAD.

Keywords: Coronary artery disease, plasminogen activator inhibitor-1, meta-analysis, genetic

Introduction

Cardiovascular diseases, the first cause of death in the Western countries are a real common health problem. Despite the high responsibility of factors such as high level of total cholesterol, systemic hypertension, smoking, type 2 diabetes (T2DM) in coronary artery disease (CAD), evidence from family studies show that genetic factors contribute to the predisposition to CAD.

The plasminogen activator inhibitor-1 (PAI-1), a 52 kDa glycoprotein belong to the serine proteinase inhibitor super family, is a multifaceted proteolytic factor. It is the principal inhibitor of tissue and urinary plasminogen activators, and therefore constitutes an important regulatory protein in fibrinolysis [1]. Impaired fibrinolysis due to high PAI-1 activity has been shown to be associated with an increased risk of thrombotic events [2]. PAI-1 overexpression may also promote development of weak plaques with thin fibrous caps by inhibiting both u-PA receptor- and integrin-mediated cell adhesion and migration [3]. In addition, increased plasma PAI-1 levels have been reported in survivors of myocardial infarction (MI) compared with the general population [4]. Therefore, PAI-1 might play an important role in the pathogenesis of CAD.

The PAI-1 gene, located in 7q21.3-22, spans 12.3 kb and contains 9 exons and 8 introns. The polymorphism of the 4G/5G gene is located in the PAI-1 gene promoter region. The most commonly studied functional variant in the PAI-1 gene is the guanine deletion polymorphism at position -675 nucleotides relative to the transcription start site (rs1799889). The PAI-1 -675 4G allele has higher transcriptional activity than the PAI-1 -675 5G allele and homozygous possession of -675 4G is associated with higher plasma PAI-1 levels [5]. A number of papers investigated the association between this polymorphism and CAD risk. However, the results remained inconclusive [6-73]. Metaanalysis is a useful method for investigating associations between genetic factors and diseases, because a quantitative approach is used to combine the results from different studies on the same topic, thereby providing more reliable conclusions. Thus, we performed a meta-analysis to clarify the association of PAI-1 4G/5G polymorphism with CAD.

Methods

Publication search

A computerized literature search was performed to identify the relevant studies from five electronic databases including PubMed, EMBASE, China National Knowledge Infrastructure (CNKI), Database of Chinese Scientific and Technical Periodicals, and China Biology Medical literature database (CBM). The search terms were used as follows: (coronary artery disease or coronary heart disease or atherosclerosis) and (polymorphism or variant or mutation) and (plasminogen activator inhibitor-1 or PAI-1). All searched studies were retrieved and the bibliographies were checked for other relevant publications.

Inclusion and exclusion criteria

The following criteria were used for the literature selection: first, studies should concern the association of PAI-1 4G/5G polymorphism with CAD risk; second, studies must be observational studies (case-control or cohort); third, papers must offer the size of the sample, odds ratios (ORs) and their 95% confidence intervals (CIs), the genetic distribution or the information that can help infer the results. Studies were excluded if one of the following existed: first, studies were not relevant to PAI-1 or CAD; second, the design based on family or sibling pairs; third, sample size or OR and 95% CI were not reported; fourth, reviews and abstracts. As for the studies from the same institution, only the one with the largest sample size was included. No language restrictions were imposed.

Data extraction

Data were extracted by two authors independently. If encountered the conflicting evaluations, an agreement was reached following a discussion; if could not reached agreement, another author was consulted to resolve the debate. The following information was extracted from each study: first author, year of publication, original country, ethnicity, endpoint, age, gender, sample size, covariates.

Statistical analysis

OR and 95% CI were employed to evaluate the strength of the association between 4G/5G polymorphism and the risk of CAD in dominant model. Departure from Hardy-Weinberg equilibrium (HWE) in controls was tested by the chi-square test. The Q statistic and the I2 statistic were used to assess the degree of heterogeneity among the studies included in the meta-analysis. The random-effects model was used to estimate the pooled OR (the DerSimonian and Laird method). Subgroup analyses were carried out by ethnicity, endpoint, age, gender and T2DM. We defined the early-onset CAD was the first event before 50 years old. Sensitivity analysis was performed through sequentially excluded individual studies to assess the stability of the results. The potential publication bias was examined visually in a funnel plot of log [OR] against its standard error (SE), and the degree of asymmetry was tested using Egger’s test [74].

All statistical tests were performed using Revman 5.1 software (Nordic Cochrane Center, Copenhagen, Denmark) and STATA 11.0 software (Stata Corporation, College Station, TX, USA). A P value < 0.05 was considered statistically significant, except for tests of heterogeneity where a level of 0.10 was used.

Results

Study characteristics

The flow chart in Figure 1 summarizes this literature review process. In this current study, a total of 68 eligible studies met the inclusion criteria [6-73]. Four articles reported two cohorts, and each cohort was considered as a case-control study. Finally, a total of 72 studies involving 23557 cases and 21526 controls were included in this meta-analysis. There were 24 studies performed using Asians, 45 studies using Caucasians, and 2 studies using Africans. Thirteen studies included only male CAD patients, and four studies included female CAD patients. Ten studies reported adjusted ORs and CIs and four studies reported the information of T2DM. Three studies were not in HWE. The characteristics of each study included in this meta-analysis are presented in Table 1. Genotype frequencies and HWE examination results are listed in Table 2.

Figure 1.

Figure 1

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Flow of study identification, inclusion, and exclusion.

Table 1.

Characteristics of the included studies

First author Year Country Ethnicity Endpoint Age of patients Female (%) Case (n) Control (n) Adjustment for covariates
Dawson 1993 Sweden Caucasian MI < 45 (39.9±0.4) 14 107 73 NA
Eriksson 1995 Sweden Caucasian MI < 45 0 93 100 NA
Ye 1995 France/UK Caucasian MI 25-64 0 476 601 NA
Mansfield 1995 UK Caucasian CAD 61-70 0 38 122 NA
Burzotta 1997 Italy Caucasian MI > 45 (59±7) 25 108 175 NA
Ridker 1997 USA Caucasian MI 62.9±8.8 0 374 495 NA
Ossei-Gerning 1997 UK Caucasian MI 59.8 NA 158 150 NA
Iwai 1998 Japan Asian MI 59.3±10.3 22.5 204 148 NA
Kohler 1998 Finland Caucasian MI 57-59 27.7 181 188 NA
Margaglione 1998 Italy Caucasian MI 22-65 23 198 981 NA
Pastinen 1998 Finland Caucasian MI 58.1±4.9 19.2 151 150 NA
Junker 1998 Germany Caucasian MI 38.6±4.4 0 241 179 NA
Sugano 1998 Japan Asian MI 63.1±9.2 12.1 66 62 NA
Ardissino 1999 Italy Caucasian MI 40.7±4.1 7.5 200 200 NA
Anderson 1 1999 USA Caucasian MI 63.7±11.6 23 375 978 NA
Anderson 2 1999 USA Caucasian CAD 62.5±10.9 20 898 329 NA
Doggen 1999 Netherlands Caucasian MI 56.1±9.0 0 331 302 NA
Gardemann 1 1999 Germany Caucasian CAD 62.7 0 1791 594 NA
Gardemann 2 1999 Germany Caucasian MI 62.2 0 1214 1351 NA
Grancha 1999 Spain Caucasian CAD 56±5 100 41 62 NA
Beneš 2000 Czech Caucasian CAD 49.5±4.5 0 175 222 NA
Canavy 2000 France Caucasian CAD/MI 55 22 244 244 NA
Hooper 2000 USA African MI 60.7±9.2 53 110 185 NA
Mikkelsson 2000 Finland Caucasian MI 47.9±9 0 68 164 NA
Song 2000 Korea Asian CAD 60.7±9.2 37.3 158 139 NA
Fu 2000 China Asian MI 51.3±6.7 42.5 87 92 NA
Viitanen 2001 Finland Caucasian CAD 56±1 40.7 118 110 NA
Dai 2001 China Asian CAD/MI 57±9 NA 250 95 NA
Fu 2001 China Asian CAD 66±10 50 123 172 NA
Shang 2001 China Asian CAD NA NA 38 80 NA
Ortlepp 2002 Germany Caucasian CAD 58±12.8 68 100 100 NA
Yamada 2002 Japan Asian MI 62.5±10.8 100 589 704 NA
Guan 2002 China Asian CAD 34-90 38.1 126 121 NA
Li 2002 China Asian CAD 60 ± 8 33.3 36 16 NA
ATVBISG 2003 Italy Caucasian MI < 45 12.3 1210 1210 Smoking, diabetes, hypertension, family history,
body mass index, hypercholesterolemia, alcohol,
cocaine, physical exercise
Crainich 2003 USA Caucasian MI 73.5±5.5 40.2 264 753 NA
Juhan-Vague 2003 Europe Caucasian MI < 60 0 483 507 NA
Leander 1 2003 Sweden Caucasian MI 58.3±7.1 0 851 1051 Age, residential area
Leander 2 2003 Sweden Caucasian MI 61.5±6.8 100 361 505 Age, residential area
Petrovič 2003 Slovenia Caucasian MI 58.3±11.3 33.8 154 194 NA
Zhan 2003 China Asian MI 67.1±10.4 21.4 56 83 NA
Ding 1 2003 China Asian CAD NA NA 60 109 Age, body mass index, family history
Ding 2 2003 China Asian CAD NA NA 49 63 Age, body mass index, family history
Wang 2003 China Asian CAD 59±12 24 67 30 NA
Zhai 2003 China Asian CAD 62.8±9 32 122 172 NA
Tobin 2004 UK Caucasian MI 61.9±9.2 32 547 505 NA
Pegoraro 2005 Indian Asian MI < 45 NA 195 300 NA
Whiting 2005 USA Caucasian CAD NA NA 881 261 Diabetes, family history
Zak 2005 Poland Caucasian CAD 45.9±6 34.9 146 121 NA
Agirbasli 2006 Turkey Caucasian CAD < 55 20 100 100 NA
Su 2006 China Asian CAD 54.5±8.9 21.6 812 931 Age, sex, BMI, HDL-C, LDL-C, hypertension, diabetes, and smoking
Xia 2006 China Asian CAD 57.7±8.1 28.6 166 63 NA
Morange 2007 France Caucasian MI 51.91±5.44 0 510 543 NA
Sampaio 2007 Brazil Caucasian MI 34.4±4.9 38.1 115 104 Age, gender, ethnic background, hypertension, diabetes, hypercholesterolemia, obesity, smoking, stress, and sedentary lifestyle
Taymaz 2007 Turkey Caucasian CAD NA NA 115 41 NA
Onalan 2008 Turkey Caucasian MI 59±11 19.9 156 281 NA
Saely 2008 Austria Caucasian CAD NA NA 406 266 Age, gender, BMI, smoking, hypertension, LDL cholesterol, HDL cholesterol, triglycerides, and use of aspirin, statins, angiotensin converting enzyme inhibitors and beta adrenoreceptor blocking agents
Sarecka 2008 Poland Caucasian CAD 43.8±6.1 32.6 178 202 Smoking, elevated level of total cholesterol, LDL-cholesterol, triacylglycerols, overweight or obesity
Zhang 2008 China Asian CAD 63.6±4.9 27 155 190 NA
Isordia-Salas 2009 Mexico Caucasian MI 40±4.6 16.5 127 127 NA
Tàssies 2009 Spain Caucasian CAD 60±13 23 248 200 NA
Var 2009 Turkey Caucasian CAD 55.3±11.3 35 86 90 Age, sex, smoking and hypertension
Chen 2009 China Asian CAD 60±11 51 293 178 NA
Abboud 2010 Tunisia African MI 59.0±12.0 19 305 328 NA
Cao 2010 China Asian MI 64.62 33.6 116 60 NA
Koch 2010 Germany Caucasian MI 64±12 24.2 3657 1211 Age, gender, history of arterial hypertension, history of hypercholesterolaemia, current cigarette smoking, and diabetes mellitus
Agirbasli 2011 Turkey Caucasian CAD 45.4±7 43.3 90 90 NA
Ahmed 2011 Pakistan Caucasian MI 52.1±11.3 19.7 229 217 NA
Ashavaid 2011 India Asian CAD 58.6±10.4 19.7 446 473 NA
Lima 2011 Brazil Caucasian CAD 60 50 123 38 NA
Zhao 2012 China Asian CAD 40-82 32.9 146 113 NA
Lin 2012 China Asian CAD 43±14 38 65 132 NA
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MI, myocardium infarction; HDL, high-density lipoprotein; LDL, low-density lipoprotein; BMI, body mass index; NA, not available.

Table 2.

Distribution of PAI-1 -675 4G/5G polymorphism among patients and controls

Case Control
Study 4G/4G 4G/5G 5G/5G 4G/4G 4G/5G 5G/5G HWE
Dawson 29 51 27 23 24 26 No
Eriksson 40 38 15 26 54 20 Yes
Ye 148 230 98 189 271 141 No
Mansfield 20 15 3 37 67 18 Yes
Burzotta 32 46 30 52 86 37 Yes
Ridker 101 191 82 133 247 115 Yes
Ossei-Gerning 59 73 26 36 65 49 Yes
Iwai 83 99 22 53 76 19 Yes
Kohler 66 91 27 54 86 48 Yes
Margaglione 68 85 45 239 493 249 Yes
Pastinen 46 74 31 30 80 40 Yes
Junker 86 112 43 52 93 34 Yes
Sugano 5 28 33 6 27 29 Yes
Ardissino 38 93 69 32 102 66 Yes
Anderson 1 105 193 77 303 457 218 Yes
Anderson 2 267 433 198 97 155 77 Yes
Doggen 88 170 73 84 150 68 Yes
Gardemann 1 624 985 362 167 305 122 Yes
Gardemann 2 382 606 226 409 684 258 Yes
Grancha 6 23 12 11 30 21 Yes
Beneš 53 91 31 77 103 42 Yes
Canavy 48 97 56 64 121 59 Yes
Hooper 7 42 59 11 79 104 Yes
Mikkelsson 18 38 12 29 78 57 Yes
Song 62 64 32 54 60 25 Yes
Fu 39 29 19 25 45 22 Yes
Viitanen 29 65 24 28 51 31 Yes
Dai 85 110 55 12 48 35 Yes
Fu 58 49 16 38 85 49 Yes
Shang 13 18 7 20 37 23 Yes
Ortlepp 36 48 16 24 54 22 Yes
Yamada 215 300 75 315 316 73 Yes
Guan 50 52 24 23 70 28 Yes
Li 13 18 5 5 11 0 Yes
ATVBISG 335 589 286 342 588 280 Yes
Crainich 70 136 58 200 387 166 Yes
Juhan-Vague 125 249 109 133 269 105 Yes
Leander 1 256 415 153 283 542 203 Yes
Leander 2 103 180 61 153 226 110 Yes
Petrovič 45 74 35 68 89 37 Yes
Zhan 40 14 2 25 52 6 No
Ding 1 8 26 26 15 39 55 Yes
Ding 2 15 23 11 10 25 28 Yes
Wang 8 35 24 2 7 21 Yes
Zhai 58 49 16 38 85 49 Yes
Tobin 159 280 108 162 237 106 Yes
Pegoraro 42 99 54 65 132 103 Yes
Whiting 263 427 191 78 121 62 Yes
Zak 34 74 38 44 58 19 Yes
Agirbasli 28 46 26 23 60 17 Yes
Su 272 390 150 275 446 210 Yes
Xia 79 67 20 18 28 17 Yes
Morange 105 236 120 96 254 124 Yes
Sampaio 23 47 45 16 45 43 Yes
Taymaz 31 58 26 15 20 6 Yes
Onalan 51 75 30 73 112 96 Yes
Saely NA NA NA NA NA NA Yes
Sarecka 38 94 46 69 103 30 Yes
Zhang 58 62 35 52 87 51 Yes
Isordia-Salas 9 64 54 17 38 72 Yes
Tàssies 56 121 71 48 92 60 Yes
Var 43 24 19 24 36 30 Yes
Chen 100 140 53 47 99 32 Yes
Abboud 88 156 61 42 180 106 Yes
Cao 61 41 14 15 27 18 Yes
Koch 1091 1787 779 360 590 261 Yes
Agirbasli 36 35 19 24 43 23 Yes
Ahmed 64 86 79 52 89 76 Yes
Ashavaid 112 218 116 113 247 113 Yes
Lima 46 34 43 12 12 14 Yes
Zhao 46 68 32 23 57 33 Yes
Lin 29 28 8 34 63 35 Yes
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HWE, Hardy-Weinberg equilibrium.

Quantitative data synthesis

The results of this meta-analysis are shown in Table 3. We found that PAI-1 4G/5G polymorphism was significant associated with CAD risk in overall population (OR=1.19, 95% CI 1.10-1.28, P < 0.00001, Figure 2). The combination of adjusted ORs for CAD was 1.20 (95% CI 1.03-1.40, P=0.02). In the subgroup analysis according to ethnicity, the results suggested that PAI-1 4G/5G polymorphism was associated with CAD risk in Caucasians (OR=1.10, 95% CI 1.02-1.19, P=0.01) and Asians (OR=1.46, 95% CI 1.21-1.75, P < 0.0001). However, no significant association was observed in Africans (OR=1.38, 95% CI 0.70-2.70, P=0.35). In terms of subgroup analyses by endpoint, the PAI-1 4G/5G polymorphism significantly increased MI risk (OR=1.15, 95% CI 1.06-1.25, P=0.001). In the subgroup analysis by age, the PAI-1 4G/5G polymorphism was significantly associated with early-onset CAD risk (OR=1.21, 95% CI 1.02-1.43, P=0.03) but not with late-onset CAD risk (OR=0.90, 95% CI 0.72-1.13, P=0.37). In the gender subgroup analyses, a statistically significant association was found in male CAD patients (OR=1.10, 95% CI 1.01-1.20, P=0.04) but not with female CAD patients (OR=1.03, 95% CI 0.89-1.19, P=0.73). Stratification by T2DM status showed that both T2DM patients and non-T2DM patients carrying 4G allele were associated with increased CAD risks (OR=2.23, 95% CI 1.27-3.92, P=0.005 and OR=1.64, 95% CI 1.19-2.25, P=0.002, respectively).

Table 3.

The effect of PAI-1 -675 4G/5G polymorphism on CAD risk

Comparison Study No. ofstudies Test of association Heterogeneity
OR (95% CI) Z P Value χ 2 P Value I 2 (%)
4G/4G + 4G/5G vs. 5G/5G Overall 72 1.19 (1.10-1.28) 4.54 < 0.00001 144.13 < 0.00001 51
4G/4G + 4G/5G vs. 5G/5G Adjusted 10 1.20 (1.03-1.40) 2.29 0.02 13.95 0.12 36
4G/4G + 4G/5G vs. 5G/5G Caucasian 45 1.10 (1.02-1.19) 2.54 0.01 70.61 0.007 38
4G/4G + 4G/5G vs. 5G/5G Asian 24 1.46 (1.21-1.75) 4.03 < 0.0001 55.19 0.0002 58
4G/4G + 4G/5G vs. 5G/5G African 2 1.38 (0.70-2.70) 0.93 0.35 5.12 0.02 80
4G/4G + 4G/5G vs. 5G/5G MI 39 1.15 (1.06-1.25) 3.27 0.001 68.35 0.002 44
4G/4G + 4G/5G vs. 5G/5G Early-onset 12 1.21 (1.02-1.43) 2.20 0.03 6.31 0.71 0
4G/4G + 4G/5G vs. 5G/5G Late-onset 4 0.90 (0.72-1.13) 0.89 0.37 1.83 0.61 0
4G/4G + 4G/5G vs. 5G/5G Male 13 1.10 (1.01-1.20) 2.10 0.04 7.23 0.84 0
4G/4G + 4G/5G vs. 5G/5G Female 4 1.03 (0.89-1.19) 0.34 0.73 4.54 0.21 34
4G/4G + 4G/5G vs. 5G/5G T2DM 4 2.23 (1.27-3.92) 2.80 0.005 0.48 0.79 0
4G/4G + 4G/5G vs. 5G/5G Non-T2DM 3 1.64 (1.19-2.25) 3.03 0.002 0.57 0.75 0
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MI, myocardium infarction; T2DM, type 2 diabetes.

Figure 2.

Figure 2

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Meta-analysis of the association between the PAI-1 4G/5G polymorphism and CAD risk.

Sensitivity analysis was used to evaluate the stability of the overall results by sequential omission of individual studies. In this meta-analysis, the results of sensitive analysis showed that any single study did not influence the overall results qualitatively (data not shown).

Funnel plots and the Egger’s test were used to assess publication bias. In the funnel plot analysis, the shape of the funnel plot seemed symmetrical (Figure 3). Furthermore, Egger’s test did not detect any publication bias (P=0.239). Therefore, there was no significant publication bias in the studies included in current analyses.

Figure 3.

Figure 3

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Funnel plot of the association between the PAI-1 4G/5G polymorphism and CAD risk.

Discussion

This present meta-analysis investigating the relationship between PAI-1 4G/5G polymorphism and risk of CAD. Seventy-two studies with a total of 45083 subjects were eligible. At the overall analysis, the PAI-1 4G/5G polymorphism was significantly associated with CAD risk. Even the studies reporting adjusted ORs were included, the result was still significant. We also found that this polymorphism increased MI risk significantly. In the subgroup analysis by ethnicity, we noted that Asians and Caucasians carrying the 4G allel had an increased CAD risk. Only two studies investigated the association between PAI-1 4G/5G polymorphism and risk of CAD in Africans. Therefore, more studies are still needed. In the stratified analysis by age, we found PAI-1 4G/5G polymorphism showed increased early-onset CAD risk but not late-onset CAD risk. There were only four studies about late-onset CAD risk, the positive association between PAI-1 4G/5G polymorphism and late-onset CAD risk could not be ruled out, because studies with small sample size may have insufficient statistical power to detect a slight effect. The subgroup analysis based on gender found that this polymorphism showed increased CAD risk in male patients but not in female patients. Since the number of studies included in female subgroup analysis was small, the results lacked sufficient reliability to confirm or refute an association in a definitive manner. In the future, more studies should be designed to analyze these associations. When subgroup analysis was performed according to T2DM status, significant associations were showed in T2DM patients and non-T2DM patients. This result suggested that T2DM did not change the effect of PAI-1 4G/5G polymorphism on CAD. Previous meta-analysis has assessed the association between PAI-1 4G/5G polymorphism and risk of CAD. For example, Koch and coworkers found that the risk of MI in 4G allele carriers was found to be significantly elevated [67]. Li suggested that PAI-1 4G/5G polymorphism was associated with increased CAD risk in Chinese Han population [75]. Nikolopoulos et al. also indicated that PAI-1 4G allele slightly increased the risk for MI [76]. These results were all in line with our results. However, our study had some advantages. First, it was the first time studying T2DM and PAI-1 4G/5G polymorphism interactions. Second, we sought to find as many publications as we could by means of various searching approaches. Third, the main result remained statistically signifiant when the adjusted ORs were combined.

PAI-1 is a glycoprotein that belongs to the serine protease inhibitor superfamily. It is equimolecularly combined with the tissue plasminogen activator (tPA) single chain, double chains, and double chain urokinase plasminogen activator (uPA). Consequently, tPA and uPA activities are rapidly inhibited by PAI-1. Mice in which PAI-1 gene was invalidated were protected from thrombotic risk after vascular injury [77]. Case-control studies in humans have shown that high PAI-1 plasma levels were associated with an increased risk of CAD and that plasma levels of PAI-1 were higher in patients with MI than in control individuals [78]. Therefore, PAI-1 might be involved in the development of CAD. PAI-1 4G/5G polymorphism is one of the DNA sequence variations that plays a key rolein regulating PAI-1 gene expression. Studies have shown that the PAI-1 activity of the 4G allele promoter is higher than that of 5G in a cytokine-stimulated state. Unlike the 5G allele that binds a transcription repressor protein, resulting in low PAI-1 expression, the 4G allele does not bind a transcription repressor, thus conferring a high PAI-1 expressor nature to the allele [5].

Some limitations should be addressed. First, there was only two case-control study investigated the association of PAI-1 4G/5G polymorphism and risk of CAD in Africans. Therefore, more studies with large sample sizes are needed to further identify the association among Africans. Second, because small negative studies are less likely to be published, the possibility of publication bias cannot be ruled out completely, even though the Egger’s test and funnel plots did not provide the evidence of publication bias in this meta-analysis. Third, a lack of original data from the eligible studies limited evaluation of the effects of the gene-gene and gene-environment interactions during CAD development.

In conclusion, this meta-analysis suggested that PAI-1 4G/5G polymorphism was associated with increased CAD risk. Further studies with large sample size were needed to confirm our findings.

Disclosure of conflict of interest

None.

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