Association Between −1562C>T Polymorphism in the Promoter Region of Matrix Metalloproteinase-9 and Coronary Artery Disease: A Meta-Analysis

Abstract

Aims: The present study was undertaken to determine the association between −1562C>T polymorphism in the promoter region of matrix metalloproteinase-9 (MMP-9) and coronary artery disease (CAD) risk. Methods: This meta-analysis was on the basis of 26 studies that included 12,776 cases and 6371 controls, heterogeneity of which was assessed by the Q-statistic test and the I²-statistic test. Sensitivity analysis was conducted by sequentially omitting any single study and recalculating the odds ratios (ORs) and 95% confidence intervals (CIs). Funnel plots and Egger's test were performed to test the potential publication bias. All data were analyzed by using STATA version 12.0. Results: We found that −1562C>T polymorphism did not contribute to the risk of CAD in the overall results. But the stratified analysis by ethnicity indicated that −1562C>T polymorphism might decrease susceptibility to CAD in Asians (OR, 0.94; 95% CI, 0.88-1.00; p_h=0.956 for CC vs. CT+TT). Conclusions: Our meta-analysis supports the fact that −1562C>T polymorphism may have association with CAD risk in Asian populations. But further larger studies are required to confirm our findings.

Introduction

Coronary artery disease (CAD), a leading cause of mortality throughout the world, has a complicated genetic pathogenesis (Jia et al., 2007). Current evidence has well documented that CAD is induced by the disorders resulted from genetic inheritance (Nordlie et al., 2005). The functional polymorphisms of several genes, such as matrix metalloproteinase-3 (MMP-3), MMP-9, and MMP-12, have been known to be genetic risk factors contributing to CAD (Ye et al., 1995; Terashima et al., 1999; Zhang et al., 1999; Jormsjo et al., 2000). Of the three aforementioned genes, the role of MMP-9 in CAD has been frequently explored in recent years.

The potential candidate gene MMP-9, also known as gelatinase B or 92-kDa type IV collagenase, is a member of the MMP family that plays a key role in the development of atherosclerotic cardiovascular diseases (Galis et al., 1994). Since MMP-9 has broad substrate specificity and distal position in the matrix proteolytic cascade, it would cause extracellular matrix degradation and subsequent rupture of atherosclerotic plaques. This facilitates cell migration into the intima after an arterial injury (Newby et al., 1994; Pauly et al., 1994; Brown et al., 1995). There are many polymorphisms in the promoter, coding, and untranslated regions of the MMP-9 gene (Yasmin et al., 2006), of which the −1562C>T polymorphism has attracted great attention from many investigators.

Despite an increasing body of studies concerning −1562C>T polymorphism and CAD risk, their findings remain uncertain (Wang et al., 2001; Cho et al., 2002; Morgan et al., 2003; Chen et al., 2005; Haberbosch et al., 2005; Tang et al., 2005; Meng et al., 2006; Nuzzo et al., 2006; Chen et al., 2007b; Horne et al., 2007; Nanni et al., 2007; Wang et al., 2007; Koh et al., 2008; Alp et al., 2009; Wu et al., 2009; Fallah et al., 2010; Gao and Wang, 2010; Ghaderian et al., 2010; Ma, 2010; Yong, 2010; Zhang et al., 2010; Zhi et al., 2010; Han et al., 2012; Opstad et al., 2012; Spurthi et al., 2012; Wang et al., 2012). For example, Morgan et al. demonstrated that −1562C>T polymorphism influences the development and progression of CAD (Morgan et al., 2003), while Haberbosch et al. (2005) supported the notion that this polymorphism is not a risk factor. This is probably because the single studies differ in sample sizes and study designs, which could be avoided through meta-analysis. Therefore, we performed a comprehensive meta-analysis with sufficient statistical power to assess whether there was relationship between −1562C>T polymorphism and the risk of CAD.

Materials and Methods

Search strategy

We searched the databases of the PubMed, EMBASE, and CNKI for eligible studies regarding the association of −1562C>T polymorphism and CAD risk published before January 2013 with a limit to human subjects. The search was performed by using the following key phrases: “matrix metalloproteinase,” “matrix metalloproteinase-9,” or “MMP-9”; “−1562C>T” or “rs3918242”; “coronary artery disease” or “CAD”; and “coronary heart disease” or “CHD.” The additional relevant publications were identified by manually searching the review articles and the references of the retrieved studies.

Inclusion criteria

The inclusion criteria for literature selection were as follows: (1) on the basis of a case-control study, (2) investigating the association of −1562C>T polymorphism and CAD risk, (3) providing sample sizes in cases and controls, and (4) having available data to retrieve the numbers of the genotypes. But reviews, editorials, and articles with insufficient information were excluded. In terms of the studies with overlapping data, the most recent one or the one with the larger sample was selected.

Data extraction

Strictly complying with the inclusion criteria, two investigators (Fengxiang Zhang and Dapeng Sun) independently extracted the data from all eligible publications. The extracted information included the first author, year of publication, study country, origin of the subjects, genotyping methods, sample sizes in the cases and controls, and the genotype distribution. The disagreements were resolved by discussion among the authors.

Statistical analysis

The strength of the association between −1562C>T polymorphism and CAD risk was evaluated by pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs). The summary ORs were calculated for CC versus TT, CC+CT versus TT, CC versus CT+TT, allele C versus allele T, and CT versus TT, respectively. Subgroup analyses by ethnicity and source of control were also conducted to further determine the relationship of −1562C>T polymorphism and CAD susceptibility. The between-study heterogeneity of the included studies in this meta-analysis was assessed by the Q-statistic test and the I²-statistic test. p<0.1 and I²>50% indicated significant evidence of heterogeneity (Cochran, 1950; Higgins et al., 2003). If p>0.1 and I²<50%, then the fixed-effect model was applied by the Mantel-Haenszel's method (Mantel and Haenszel, 1959); otherwise, the random-effect model was adopted by the DerSimonian and Laird's method (DerSimonian and Laird, 1986). To identify the source of between-study heterogeneity, we conducted subgroup analyses and meta-regression (Thompson and Higgins, 2002). Hardy-Weinberg equilibrium (HWE) for the genotype distribution of −1562C>T polymorphism in the controls was tested to estimate the quality of the included studies (Salanti et al., 2005). Sensitivity analysis was performed by sequentially omitting any single study and recalculating the ORs and 95% CIs to examine the stability and credibility of the results. Funnel plots and Egger's test were performed to test the potential publication bias (Egger et al., 1997; Stuck et al., 1998). All data were analyzed by using STATA version 12.0 (Stata Corporation, College Station, TX). p<0.1 was deemed statistically significant.

Results

Characteristics of eligible studies

We initially extracted a total of 37 articles according to the predescribed selection criteria. Having been further examined the full tests, 11 of them were excluded, for 5 failed to provide definite numbers of the genotypes (Zhang et al., 1999; Kim et al., 2002; Blankenberg et al., 2003; Medley et al., 2004; Liu et al., 2012), 2 were updated by a subsequent study included in the current meta-analysis (Chen et al., 2007a), 2 were based on case-only design (Pollanen et al., 2001; Saedi et al., 2012), and 2 were review articles (Abilleira et al., 2006; Niu and Qi, 2012). At last, 26 studies with 12,776 cases and 6371 controls were available for the meta-analysis. The sample size of the available studies ranged from 130 to 3801. The ethnic subgroups consisted of 8663 Caucasians and 10,484 Asians. In addition, the majority of the studies eligible for this meta-analysis were based on hospital controls. The main information of the included studies is listed in Table 1.

Table 1.

Characteristics of Literature Included in the Meta-Analysis

						Case						Control
First author	Year	Country	Ethnicity	Source	Genotyping method	Sample size	CC	CT	TT	C	T	Sample size	CC	CT	TT	C	T	HWE
Wang et al.	2001	Australia	CA	HB	PCR-RFLP	619	479	128	12	1086	152	169	128	41	0	297	41	0.073
Cho et al.	2002	Korea	A	HB	PCR-RFLP	63	48	15	0	111	15	67	63	4	0	130	4	0.801
Morgan et al.	2003	UK	CA	HB	PCR-RFLP	998	779	203	16	1761	235	265	223	42	0	488	42	0.161
Haberbosch et al.	2005	Germany	CA	PB	PCR-RFLP	3266	2495	710	61	5700	832	535	414	109	12	937	133	0.138
Chen et al.	2005	China	A	HB	PCR-RFLP	78	57	21	0	135	21	81	73	8	0	154	8	0.640
Tang et al.	2005	China	A	HB	PCR-RFLP	101	73	27	1	173	29	105	91	13	1	195	15	0.495
Meng et al.	2006	China	A	HB	PCR-RFLP	117	91	26	0	208	26	99	80	18	1	178	20	0.991
Nuzzo et al.	2006	Italy	CA	PB	PCR-RFLP	115	73	39	3	185	45	123	86	36	1	208	38	0.182
Horne et al.	2007	USA	CA	NM	TaqMan	1967	1475	452	40	3402	532	1122	830	269	23	1929	315	0.826
Nanni et al.	2007	Italy	CA	HB	PCR-RFLP	200	136	62	2	334	66	201	135	63	3	333	69	0.147
Chen et al.	2007a	China	A	HB	PCR-RFLP	90	63	25	2	151	29	70	58	11	1	127	13	0.574
Wang et al.	2007	China	A	HB	PCR-RFLP	64	46	17	1	109	19	84	66	18	0	150	18	0.271
Koh et al.	2008	Korea	A	HB	PCR-RFLP	206	151	51	4	353	59	173	142	31	0	315	31	0.196
Alp et al.	2009	Turkey	A	HB	PCR-RFLP	146	99	42	5	240	52	122	90	29	3	209	35	0.718
Wu et al.	2009	China	A	HB	PCR-RFLP	1356	1078	263	15	2419	293	689	545	143	1	1233	145	0.007
Zhang et al.	2010	China	A	HB	PCR-RFLP	92	67	22	3	156	28	95	83	12	0	178	12	0.511
Fallah et al.	2010	Iran	A	NM	PCR-RFLP	145	77	57	11	211	79	157	62	76	19	200	114	0.559
Zhi et al.	2010	China	A	HB	PCR-RFLP	762	585	174	3	1344	180	555	442	110	3	994	116	0.165
Ghaderian et al.	2010	Iran	A	PB	TaqMan	234	177	47	10	401	67	200	141	53	6	335	65	0.709
Gao and Wang	2010	China	A	NM	PCR-RFLP	96	49	38	9	136	56	78	59	18	1	136	20	0.775
Ma	2010	China	A	HB	PCR-RFLP	362	266	84	12	616	108	419	348	67	4	763	75	0.700
Yong	2010	China	A	HB	PCR-RFLP	128	97	30	1	224	32	106	92	14	0	198	14	0.467
Wang et al.	2012	China	A	HB	PCR-RFLP	384	286	87	11	659	109	451	373	72	6	818	84	0.244
Opstad et al.	2012	Norway	CA	PB	TaqMan	996	756	225	15	1737	255	204	154	46	4	354	54	0.795
Spurthi et al.	2012	India	A	NM	PCR-RFLP	100	40	47	13	127	73	100	48	46	6	142	58	0.242
Han et al.	2012	China	A	HB	PCR-RFLP	91	65	25	1	155	27	101	75	25	1	175	27	0.489

CA, Caucasian; A, Asian; HB, hospital-based; PB, population-based; NM, not mentioned; PCR-RFLP, PCR-restriction fragment length polymorphism; TaqMan, TaqManSNP; HWE, Hardy-Weinberg equilibrium.

Meta-analysis results

The principal results of this meta-analysis are displayed in Table 2. In general, no evidence for statistically significant association was found between −1562C>T polymorphism and CAD risk under all contrast models. However, in the stratified analyses by ethnicity, we observed a protective effect under the CC versus CT+TT genetic model in Asian populations (OR, 0.94; 95% CI, 0.88-1.00; p_h=0.956) (Figs. 1 and 2). Similarly, when stratifying the subgroups by source of control, we found a borderline association under the contrast model of CC versus CT+TT in hospital-based studies (OR, 0.94; 95% CI, 0.88-1.00; p_h=1.000).

FIG. 1.

Forest plot of estimates of the ORs for −1562C>T polymorphism in coronary artery disease (CAD) under CC versus TT. The squares and horizontal lines correspond to odds ratios (ORs) and 95% confidence intervals (CIs) of specific study, and the area of squares reflects study weight (inverse of the variance). The diamond represents the pooled ORs and its 95% CIs.

FIG. 2.

Forest plot of estimates of the ORs for −1562C>T polymorphism in CAD under CC versus CT+TT. The squares and horizontal lines correspond to ORs and 95% CIs of specific study, and the area of squares reflects study weight (inverse of the variance). The diamond represents the pooled ORs and its 95% CIs.

Table 2.

Meta-Analysis of the 1562C>T Polymorphism on Coronary Artery Disease Risk

	CC vs. TT		CC+CT vs. TT		CC vs. CT+TT		C vs. T		CT vs. TT
	OR (95% CI)	p_h	OR (95% CI)	p_h	OR (95% CI)	p_h	OR (95% CI)	p_h	OR (95% CI)	p_h
Fixed-effect model
Ethnicity
Caucasian	1.00 (0.93-1.07)	1.000	1.00 (0.94-1.06)	1.000	0.99 (0.93-1.06)	0.991	1.00 (0.95-1.04)	0.998	0.99 (0.87-1.13)	1.000
Asian	0.99 (0.92-1.06)	1.000	0.99 (0.93-1.05)	1.000	0.94 (0.88-1.00)	0.956	0.97 (0.92-1.01)	0.999	0.96 (0.85-1.10)	1.000
Source of control
Hospital	0.99 (0.92-1.05)	1.000	0.99 (0.93-1.05)	1.000	0.94 (0.88-1.00)	1.000	0.97 (0.93-1.01)	1.000	0.97 (0.85-1.10)	1.000
Population	1.00 (0.89-1.12)	0.999	1.00 (0.91-1.10)	0.999	1.00 (0.90-1.11)	0.924	1.00 (0.93-1.07)	0.979	1.00 (0.81-1.22)	0.985
Total	0.99 (0.94-1.04)	1.000	0.99 (0.95-1.04)	1.000	0.96 (0.92-1.01)	0.992	0.98 (0.95-1.01)	1.000	0.98 (0.89-1.07)	1.000

p_h, p-value of heterogeneity test; OR, odds ratio; CI, confidence interval.

Heterogeneity analysis

There was no observed between-study heterogeneity in the included studies (p>0.1). Therefore, the fixed-effect model was applied for the pooled analyses to assess the association between −1562C>T polymorphism and CAD susceptibility.

Sensitivity analysis

Sensitivity analysis was performed via sequentially excluding each single study, one at a time and recalculating the ORs and 95% CIs to detect the credibility and stability of our results. The sensitivity analysis suggested that no single study changed the pooled ORs qualitatively (data not shown).

Publication bias

Funnel plot and Egger's test were conducted to access the publication bias of all studies. The symmetrical shape of the funnel plots indicated that there existed no evident publication bias (Fig. 3). Moreover, no obvious evidence was observed in Egger's test, suggesting that there was no significant publication bias in this meta-analysis (CC vs. CT+TT: p=0.450).

FIG. 3.

Funnel plot for publication-bias test (CC vs. CT+TT).

Discussion

The MMP-9 gene is located on chromosome 20. Overexpression and increased circulation level of this protein have been reported to be correlated with CAD in previously published studies (Brown et al., 1995; Yasmin et al., 2005). Recently, a large number of individual studies have paid much attention to the effects of the functional −1562C>T polymorphism of the MMP-9 gene on CAD susceptibility, yet the findings remain inconclusive and inconsistent. Of them, seven studies demonstrated that the functional 1562C>T polymorphism is not a risk contributor to CAD susceptibility (Wang et al., 2001; Haberbosch et al., 2005; Nuzzo et al., 2006; Alp et al., 2009; Wu et al., 2009; Han et al., 2012; Opstad et al., 2012). Conversely, as many as 24 single publications indicated a different finding (Cho et al., 2002; Morgan et al., 2003; Chen et al., 2005; Tang et al., 2005; Meng et al., 2006; Chen et al., 2007b; Horne et al., 2007; Nanni et al., 2007; Wang et al., 2007; Koh et al., 2008; Fallah et al., 2010; Gao and Wang, 2010; Ghaderian et al., 2010; Ma, 2010; Yong, 2010; Zhang et al., 2010; Zhi et al., 2010; Wang et al., 2011; Spurthi et al., 2012; Wang et al., 2012; Li et al., 2013). There are possible explanations for this discordance, such as small sample sizes, incorrect multiple hypothesis testing, and potential publication bias.

In addition, two meta-analyses were carried out in 2011 (Wang et al., 2011) and 2013 (Li et al., 2013) separately, supporting the fact that the MMP9-1562C>T polymorphism is a risk factor for CAD susceptibility. As compared with the former two meta-analyses of the association of MMP9-1562C/T polymorphism and CAD risk, our study showed that −1562C>T polymorphism did not have statistically significant association with the susceptibility to CAD. Our meta-analysis is superior to the others, due to the far larger number of participants (26 included studies with 12,776 cases and 6371 controls) compared with the study by Li et al. (2013) (12 included studies with 8281 cases and 3940 control) and with the study by Wang et al. (2011) (seven included studies with 4473 cases and 3343 controls). The substantially large sample size ensures the reliability of the results, despite no relationship indicated in the analysis.

Wang et al. (2011) have identified that −1562C>T polymorphism plays different roles in different ethnic populations; thus, subgroup analysis by ethnicity was carried out. The analysis indicated supportive evidence for correlation between the polymorphism of −1562C>T and the risk of CAD in Asian populations rather than Caucasian populations. It is likely that genetic background plays a crucial role in the susceptibility to CAD.

Moreover, the CC versus CT+TT genetic model was implicated to be potentially associated with CAD risk in the hospital-based studies. The included studies had different criteria when selecting their control subjects. Some control groups may not be representative of the general population, leading to the occurrence of selection bias.

Several limitations in this meta-analysis need to be pointed out. One limitation is that our study only investigated one single-gene polymorphism, which would have less power to completely interpret the genetic risk for CAD. Because CAD is a multifactorial disease caused by genetic and environmental factors. Another limitation refers to the potentially unobservable heterogeneity in our study. In the subgroup analyses by ethnicity and source of control, we did not find any significant heterogeneity in the distribution of the genotypes of −1562C>T polymorphism. The insignificant heterogeneity should be further confirmed by stratified analysis by other unmeasured characteristics.

To sum up, the current meta-analysis provided evidence that −1562C>T polymorphism may have modification effects on CAD susceptibility in Asians. Future studies with more genetic polymorphisms and better study designs are necessary to confirm our current findings, which might provide more insights into the pathogenesis and targeted prevention of CAD.

Footnotes

Acknowledgments

This work was supported by Natural Science Foundation of Liaoning Province (2013022010); Youth Science Foundation of Liaoning Medical University (Y2012Z011); Youth Science Foundation of The First Hospital of Liaoning Medical University (FY2012-17).

Author Disclosure Statement

No competing financial interests exist.

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