Rs10757274 gene polymorphisms in coronary artery disease: A systematic review and a meta-analysis.

BACKGROUND: It has been reported the rs10757274 SNP (present on locus 9p21 in the gene for CDKN2BAS1) might be associated with susceptibility to coronary artery disease (CAD). Owing to mixed and inconclusive results, we conducted a meta-analysis to investigate the association between rs10757274 polymorphism and the risk of CAD.
OBJECTIVES: The present study aimed to investigate the relationship between rs10757274 polymorphism and the risk of CAD.
METHODS: All studies of the rs10757274 SNP with CAD that were published between 2007 and 2018 were retrieved from the PubMed database. Meta-analysis was performed with Stata 14.0 software. The effect size of the rs10757274 SNP with CAD risk was assessed based on the odds ratios (ORs) with calculation of 95% confidence interval (CI).
RESULTS: Eleven studies including 52,209 subjects (cases: 7990, controls: 44,219) were included in the final data combination. Pooled overall analyses showed that rs10757274 (allele model: P < .001; dominant model: P < .001; recessive model: P < .001; Heterozygote codominant: P = .002; Homozygote codominant: P < .001) polymorphisms were significantly associated with the likelihood of CAD. Significant heterogeneity between individual studies appears in all 5 models. Further subgroup analyses revealed that rs10757274 polymorphisms were all significantly correlated with the likelihood of CAD and no heterogeneity were observed in West Asians.
CONCLUSIONS: Our findings indicated that rs10757274 polymorphisms may serve as genetic biomarkers of CAD, especially in West Asians.

Introduction

Coronary artery disease (CAD) still leads the causes of morbidity and mortality worldwide.[ The accurate mechanisms responsible for the incidence of CAD are still unclear, which is influenced by numerous factors.[ The risk factors such as hypertension, diabetes mellitus, abnormal serum cholesterol(LDL and HDL), cigarette smoking, high alcohol consumption, age, stress, family history of CAD, and obesity affect the development and security of CAD.[ Genetic factors have been defined as an important risk contributor for the pathogenesis of CAD,[ but the responsible molecular and genetic determinants remain largely unidentified.

Genome-wide association studies (GWAS) and candidate gene studies have reported that CDKN2BAS (cyclin-dependent kinase inhibitor 2B antisense RNA) is a risk gene for CAD susceptibility.[ CDKN2BAS encodes an antisense non-coding RNA, and is located near the CDKN2A-CDKN2B gene. The precise function of CDKN2BAS is unknown, but it regulates the expression of neighboring protein-coding genes, like CDKN2A, CDKN2B, and MTAP, that enhance the progression of atherosclerosis by influencing vascular remodeling, thrombogenesis, and plaque stability.[ Therefore, CDKN2BAS expression plays a crucial role in the development of CAD by altering the dynamics of vascular cell proliferation. In addition, single nucleotide polymorphisms (SNPs) in CDKN2BAS are connected with the risk of multiple diseases, such as CAD[ type 2 diabetes,[ ischemic stroke,[ and periodontitis.[

It has been reported that Gene rs10757274 A/G (present on locus 9p21 in the gene for CDKN2BAS) Polymorphism might be association with the susceptibility to CAD. Several studies have demonstrated a strong association of rs10757274 with CAD in Pakistani,[ Caucasian,[ and South-West Iranian[ population. However, 1 previous study found no association of rs10757274 with CHD in a Han Chinese population (Shenzhen).[ The results of these studies were controversial. Thus, we performed the present meta-analysis to better evaluate gene rs10757274 polymorphisms in CAD.

Material and methods

Study selection

To identify all the articles that examined the association of rs10757274 SNP (present on locus 9p21 in the gene for CDKN2BAS) polymorphisms with coronary artery disease, we conducted a comprehensive search of PubMed, Web of Science, Cochrane library, and EMBASE (the last search update was January 6, 2019). Search terms included rs10757274 or rs10757274 A/G; gene polymorphism, or genetic mutation and myocardial infarct, myocardial infarction, coronary artery disease, coronary heart disease, myocardial ischemia, ischemic heart disease, ischemic cardiomyopathy, angina, angina pectoris, acute coronary syndrome, acute coronary syndrome (ACS), coronary calcification, coronary flow reserve, ischemic heart failure, heart failure. We also screened references of the retrieved articles and review articles by a hand search. Studies in this meta-analysis had to meet the following inclusion criteria:

evaluation of the association between rs10757274 A/G polymorphisms and CAD;

case-control study;

studies focusing on humans;

detailed genotype data could be acquired to calculate the odds ratios (ORs) and 95% confidence intervals (CIs).

Exclusion criteria:

duplication of previous publications;

comment, review, and editorial;

family-based studies of pedigrees;

study with no detailed genotype data.

When there were multiple publications from the same population, only the largest study was included. Study selection was performed by 2 investigators independently, according to the inclusion and exclusion criteria by screening the title, abstract, and full text. Any dispute was solved by discussion.

Data extraction

For each study that met our criteria, the following information was collected: first author, year of publication, country of origin, ethnicity, criteria of diagnosis, number of cases and controls, genotype distribution, genotyping methods and allele frequency, the criteria of CAD, Hardy-Weinberg equilibrium, number of cases and controls, and genotype frequency in cases, and controls for rs10757274. All the searching work and data extraction work were conducted by 2 independent investigators. If dissent existed, they would recheck the original data of the included studies and have a discussion to reach a consensus. If the dissent still existed, the third investigator would be involved to adjudicate the disagreements.

Quality assessment

The quality of the included studies was assessed by 2 authors separately according to the methodological quality assessment scale. In this scale, 5 items—representativeness of cases, source of controls, sample size, quality control of genotyping methods, and Hardy-Weinberg equilibrium (HWE) —were carefully checked. The quality score ranges from 0 to 10, and a high score means good quality of the study. Two investigators scored the studies independently and solved disagreement through discussion (Table 1).[

Table 1

Characteristics of the studies included in the meta-analysis.

Statistical analysis

The strength of association between rs10757274 A/G polymorphisms and CAD was measured by the odds ratio (OR) corresponding to a 95% confidence interval (CI) according to the method of Woolf.[ Heterogeneity between studies was assessed by Cochran χ2-based Q statistic test.[ Where the P value for heterogeneity was less than .1, a random-effects model using the DerSimonian and Laird method[ was used to pool the results; otherwise, a fixed-effects model using the Mantel-Haenszel method was adopted.[ In order to better evaluate the extent of heterogeneity between studies, the I2 test was also used. This statistic yields results ranging from 0% to 100% (I2 = 0%–25%, no heterogeneity; I2 = 25%–50%, moderate heterogeneity; I2 = 50%–75%, large heterogeneity; I2 = 75%–100%, extreme heterogeneity).[

For the rs10757274 A/G promoter polymorphism, we investigated associations between the genetic variant and coronary artery disease risk in allelic contrast (G vs A), homozygote comparison (GG vs AA), heterozygote comparison (AG vs AA), dominant (AG/GG vs AA) and recessive (GG vs AG/AA) models, respectively. The significance of the pooled OR was determined by the Z-test (P < .05 suggests a significant association). Subgroup analyses were also conducted by ethnicity of participants. HWE was tested by the χ2 test at a significant level of P < .05.[ Publication bias was investigated by Begg funnel plot[ and by Egger linear regression test.[ Sensitivity analysis was also performed to evaluate the stability of the meta-analysis, All analyses were performed using STATA version 14.0 (StataCorp LP, College Station, Texas).

Result

Characteristics of included studies

In total, 11 articles were identified according to inclusion and exclusion criteria. The detailed screening process was shown in Figure 1.

Figure 1

Study selection process.

Meta-analysis results

For the rs10757274 A/G polymorphism and its relationship to CAD, significant heterogeneity between individual studies appears obvious in all 5 models. Therefore, the random-effect model (DerSimonian and Laird) was applied in all 5 models. There was a statistically significant association between rs10757274A/G polymorphism and CAD risk under the 5 models, the allele model (OR = 0.80, 95% CI: 0.73–0.87, Pv < .001) (Fig. 2); the dominant model (OR = 0.75, 95% CI: 0.65–0.86, Pv < .001) (Fig. 3); the recessive model (OR = 0.74, 95% CI: 0.67–0.83, Pv < .001); heterozygote model (OR = 0.82, 95% CI: 0.72–0.93, Pv = .002) and homozygote model (OR = 0.64, 95% CI: 0.54–0.75, Pv < .001) (Table 2).

Figure 2

Forrest plot of allelic model for overall comparison of rs10757274 polymorphisms and CAD.

Figure 3

Forrest plot of dominant model for overall comparison of rs10757274 polymorphisms and CAD.

Table 2

Results of meta-analysis for rs10757274 polymorphisms and CAD risks.

Having higher heterogeneity in all of models, we further performed subgroup analysis by ethnicity of participants (East Asians, West Asians, and Caucasian). The results showed that significant heterogeneity was still observed in East Asians and Caucasian. Additionally no heterogeneity was observed in West Asians and a statistically significant association was observed between rs10757274A/G polymorphism and CAD risk in all subgroups.

Sensitivity analysis

The results of sensitivity analysis (Fig. 6) showed that the pooled OR were not considerably affected by omitting any individual study using the 5 genetic models, which confirmed that the results of this meta-analysis were reliable and stable.

Figure 6

The results of sensitivity analysis showed that the pooled OR were not considerably affected by omitting any individual study using the 5 genetic models, which confirmed that the results of this meta-analysis were reliable and stable.

Publication bias

Publication biases were evaluated by Begg funnel plot (Fig. 5) and Egger linear regression test (Fig. 4). We did not find obvious asymmetry of funnel plots in any comparisons, which indicated that our findings were unlikely to be impacted by severe publication biases.

Figure 5

Funnel plot for publication bias test of the rs10757274 polymorphisms and CAD.

Figure 4

Egger plot for publication bias test of the rs10757274 polymorphisms and CAD.

Discussion

Our study was a report to pool published case-control studies to estimate the association between CDKN2BAS rs10757274 A/G polymorphism and susceptibility to CAD. Our results of meta-analysis showed that there were significant statistically associations between rs10757274 polymorphism with CAD under all genetic models, we found A allele that had a lower risk of CAD as compared to G allele. To explore the source of heterogeneity, we further performed subgroup publication bias and sensitivity analyses. The result of subgroup analysis showed that a statistically significant association was observed between rs10757274A/G polymorphism and CAD risk in East Asians, West Asians, and Caucasian. Moreover, we also found that no heterogeneity was observed in West Asians. Sensitivity analysis did not identify any sources of heterogeneity. It suggested that there was no evidence of publication bias among the studies using all of the genetic models.

Many genome-wide association studies have identified a great number of genetic loci, suggesting that common genetic variants contribute to the CAD development.[ A large number of polymorphisms at novel loci play a critical role for CAD.[ The rs10757274 is one of the most intensively examined polymorphisms of CDKN2B-AS gene at 9p21 locus.

The genetic/molecular basis of 9p21 genetic variation on CAD risk is unknown. The 9p21.3 locus is located outside of annotated genes. A role for CDKN2A and CDKN2B, which play an important role in regulation of the cell cycle and lie in relatively close proximity,[ appears to be excluded by resequencing studies of McPherson et al.[ Subsequently, Broadbent et al[ reported that the 9p21 high-risk haplotype collocates with a large antisense noncoding RNA gene, which is expressed in tissues and cell types affected by atherosclerosis and which might act as an important growth regulatory element.

Several limitations exist in our research. Firstly, only 11 studies were included this research analysis involving a total of 52,209 subjects. Therefore, more studies with a larger sample sizes should be included to enhance the reliability and stability of the meta-analysis. In addition, the interference of factors, such as environmental and genetic factors, and pharmaceuticals, requires further study. Finally, we did not analysis the association between the rs10757274 polymorphism and different subtypes, as myocardial infarction, angina, and other subtypes, due to lacking sufficient statistical data in the literatures.

The results of the current meta-analysis implied that rs10757274 polymorphisms may serve as genetic biomarkers of CAD, especially in West Asians. Considering the limitations discussed, our conclusion needed further verification by high quality studies with larger sample sizes and rigorous designs.

Author contributions

Conceptualization: Gui-Dong Xu, Ya-Feng Zhou.

Data curation: Gui-Dong Xu, Ya-Feng Zhou.

Formal analysis: Gui-Dong Xu, Ya-Feng Zhou, Yuan Li.

Funding acquisition: Gui-Dong Xu.

Investigation: Lang-Biao Xu, Nan-Nan Zhang, Biao Li.

Methodology: Lang-Biao Xu, Gui-Dong Xu, Jia-Yi Weng.

Project administration: Gui-Dong Xu, Xue-Xing Ma, Xiao-Yang Li, Wen-Chao Lu.

Resources: Xue-Xing Ma.

Software: Lang-Biao Xu, Yi-Qing Zhang, Hong-Tao He.

Supervision: Gui-Dong Xu, Lu Chen.

Validation: Gui-Dong Xu, Ya-Feng Zhou, Zhen Han.

Visualization: Gui-Dong Xu, Ya-Feng Zhou.

Writing – original draft: Lang-Biao Xu.

Writing – review & editing: Lang-Biao Xu.