The Associations between Apolipoprotein E Gene Epsilon2/Epsilon3/Epsilon4 Polymorphisms and the Risk of Coronary Artery Disease in Patients with Type 2 Diabetes Mellitus

Background and Objective: Apolipoprotein E (APOE) plays important roles in lipoprotein metabolism and cardiovascular disease. Evidence suggests the APOE gene epsilon2/epsilon3/epsilon4 (ε2/ε3/ε4) polymorphisms might be associated with the susceptibility of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM). However, no clear consensus has yet been established. Therefore, the aim of this meta-analysis is to provide a precise conclusion on the potential association between APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM based on case-control studies. Methods: Pubmed, Embase, Chinese National Knowledge Infrastructure (CNKI), and Wanfang databases were searched for all relevant studies prior to August 2017 in English and Chinese language. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were used to assess the strength of the relationships. The between-study heterogeneity was evaluated by Cochran's Q-test and the I2 index to adopt fixed- or random- effect models. Results: A total of 13 studies were eligible for inclusion. There was evidence for significant associations between APOE ε4 mutation and the risk of CAD in patients with T2DM (for ε3/ε4 vs. ε3/ε3: OR = 1.69, 95% CI = 1.38–2.08, P < 0.001; for ε4/ε4 vs. ε3/ε3: OR = 2.72, 95% CI = 1.61–4.60, P < 0.001; for ε4/ε4+ε3/ε4 vs. ε3/ε3: OR = 1.83, 95% CI = 1.52–2.22, P < 0.001; for ε4 allele vs. ε3 allele: OR = 1.64, 95% CI = 1.40–1.94, P < 0.001). In contrast, no significant associations were found in genetic model of APOE ε2 mutation (for ε2/ε2 vs. ε3/ε3: OR = 1.67, 95% CI = 0.90–3.09, P = 0.104; for ε2/ε3 vs. ε3/ε3: OR = 1.18, 95% CI = 0.93–1.51, P = 0.175; for ε2/ε2+ε2/ε3 vs. ε3/ε3: OR = 1.26, 95% CI = 0.88–1.82, P = 0.212; for ε2 allele vs. ε3 allele: OR = 1.34, 95% CI = 0.98–1.84, P = 0.07). Conclusions: The APOE gene ε4 mutation is associated with an increased risk of CAD in patients with T2DM, while the ε2 variation has null association with this disease.

Background and Objective: Apolipoprotein E (APOE) plays important roles in lipoprotein metabolism and cardiovascular disease. Evidence suggests the APOE gene epsilon2/epsilon3/epsilon4 (ε2/ε3/ε4) polymorphisms might be associated with the susceptibility of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM). However, no clear consensus has yet been established. Therefore, the aim of this meta-analysis is to provide a precise conclusion on the potential association between APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM based on case-control studies.
Methods: Pubmed, Embase, Chinese National Knowledge Infrastructure (CNKI), and Wanfang databases were searched for all relevant studies prior to August 2017 in English and Chinese language. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were used to assess the strength of the relationships. The between-study heterogeneity was evaluated by Cochran's Q-test and the I 2 index to adopt fixed-or random-effect models.

INTRODUCTION
Type 2 diabetes mellitus (T2DM) is a long-term metabolic disease with a high incidence and prevalence in the world. T2DM is often accompanied by various complications such as hypertension, dyslipidemia and coronary artery disease (CAD) (Naito and Miyauchi, 2017). As the disease progresses, patients with T2DM have a 2 to 4-fold increased risk for developing CAD compared with non-diabetic individuals (Mohan et al., 2001;Emerging Risk Factors et al., 2010). In addition, cardiovascular disease including CAD in patients with T2DM is associated with significant mortality (Zhang et al., 2014b;Freitas Lima et al., 2015). Therefore, early prevention and vigorous control of T2DM and its complications are becoming an ever-increasing global health priority. A better understanding of the etiology of CAD in patients with T2DM will result in better clinical management.
Dyslipidemia, hypertension, obesity, and smoking status are well-established risk factors for T2DM (Paneni et al., 2013;Wang et al., 2015a). Additionally, human genetic association studies have revealed that numerous genetic mutations and polymorphisms also play a critical role (Wei et al., 2014;Raj et al., 2015;Sumi et al., 2017). Among the previous studies, apolipoprotein E (APOE) gene has been regarded as one of the most likely candidate genes which may be associated with CAD in T2DM patients.
APOE is a class of plasma apolipoprotein totaling 299 amino acids, and it is involved in lipoprotein metabolism and the development of cardiovascular diseases (Zheng et al., 1998). The APOE gene is mapped to chromosome 19q13.2 in a cluster with apolipoprotein C1 and C2 gene, and it consists of three introns and four exons. APOE is a polymorphic gene and the most commonly studied alleles/isoforms are: epsilon2 (ε2), epsilon3 (ε3), and epsilon4 (ε4). The differences between the three isoforms are the location of 112 and 158 in the amino acid chain where cysteine or arginine is present. These three APOE alleles are determined by the rs7412 and rs429358 singlenucleotide polymorphisms. The three alleles, APOE-ε2 (cys112 and cys158), APOE-ε3 (cys112 and arg158) and APOE-ε4 (arg112 and arg158), yield six different genotypes for the APOE gene: ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4, and ε4/ε4. Because the ε3 allele or ε3/ε3 genotype is the most common allele or genotype among the population, they are well accepted as the "wild-type" and used as the "reference" in the genetic models (Zhang et al., 2000;Guo et al., 2007;Izar et al., 2009;Chaudhary et al., 2012;Hong et al., 2017).
The role of APOE ε2/ε3/ε4 polymorphisms in the development of CAD in patients with T2DM is widely studied, but the results are still controversial and conflicting. In 1998, Zheng et al. firstly investigated the association between APOE gene polymorphism and T2DM complicated with CAD in the Chinese population. The results showed that APOE-ε4 allele increased the risk of CAD in T2DM (Zheng et al., 1998). Other studies have also confirmed Zheng's findings (Chaaba et al., 2008;Hong et al., 2017). However, APOE-ε2 allele was also found to be associated with the risk of CAD in T2DM (Halim et al., 2012). In addition, no significant association between APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in T2DM was reported in some studies (Zhang et al., 2000;Guo et al., 2007;Izar et al., 2009). To demonstrate with certainty the associations between the APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM, we conducted a systematic review and meta-analysis on published case-control studies.

Literature Search
This study was undertaken according to the methodology of MOOSE (Meta-analysis of Observational Studies in Epidemiology) statement (Stroup et al., 2000). We thoroughly searched all published studies in the Embase, PubMed, China National Knowledge Infrastructure (CNKI) and Wanfang databases up to August 2, 2017. The included articles were limited to Chinese and English language. The following keywords were used for searching: "apolipoprotein E" OR "APOE" AND "polymorphism" OR "single nucleotide polymorphism" OR "SNP" OR "variant" OR "variation" AND "coronary artery disease" OR "coronary heart disease" OR "CAD" OR "CHD" OR "atherosclerosis" OR "myocardial infarction" OR "myocardial infarct" OR "heart attack" OR "MI" AND "type 2 diabetes" OR "non-insulin dependent diabetes mellitus" OR "diabetes mellitus, type 2" OR "diabetes, type 2" OR "diabetes mellitus, non-insulin dependent" The Chinese databases were searched using the equivalent Chinese terms. In addition, hand searches for all related articles were performed. The detailed search strategies are presented in Supplementary Table 1.

Inclusion and Exclusion Criteria
The first two investigators independently accessed the eligibility of the studies by screening the title, abstract and full-text, based on the inclusion and exclusion criteria. The inclusion criteria for all studies were as follows: (1) study on the associations between APOE ε2/ε3/ε4 polymorphisms and CAD in patients with T2DM, regardless of sample size. (2) case-control design.
(3) detailed data for the APOE alleles or genotype distribution in case and control groups to estimate odds ratio (OR) with 95% confidence interval (CI). Exclusion criteria: (1) duplication of previous data; (2) review, comment and editorial; (3) no sufficient genotype data. Any dispute about the eligibility of an article was resolved by discussion.

Data Extraction
The data was drawn out based on a standard protocol. The following information was carefully extracted from all eligible publications independently by two authors (JQL and HR) using a standardized form: last name of first author, year of publication, study country, sample size in cases and controls, methods of genotyping, number genotypes and alleles. If similar data sets presented in different articles by the same research group, the data would be adopted only once. The collected data were compared, and possible disagreements were discussed by the authors and resolved with consensus.

Quality Score Assessment
The study quality was independently assessed by two reviewers. Quality assessment of genetic associations between APOE ε2/ε3/ε4 polymorphisms and CAD in patients with T2DM is described in the Supplementary Table 2. The scores were adjusted according to the criteria developed for meta-analysis of molecular association studies by Thakkinstian et al. (2005). The total scores ranged from 0 to 13, with 13 representing the highest quality.
Frontiers in Physiology | www.frontiersin.org by the Z-test with P < 0.05. Heterogeneity between studies was calculated by using the Cochran's Q-test and Higgins I 2 index.
In the absence of between-study heterogeneity (I 2 < 50%), the fixed effect model (Mantel-Haenszel method) was chosen to calculate the pooled estimates. Otherwise, random effect model (DerSimonian and Laird method) would be adopted if the I 2 > 50% (Higgins et al., 2003). Subgroup analysis was performed according to the source of patients (Chinese and non-Chinese).
Galbraith plot analysis and sensitivity analysis were conducted to detect whether there were outliers that could be the potential sources of heterogeneity between studies when heterogeneity was moderately large. Publication bias was evaluated by Begg's funnel plot and Egger's regression test (Begg and Mazumdar, 1994;Egger et al., 1997). If there is evidence of significant publication bias, the trim and fill method was performed to assess the potential influence of publication bias (Duval and Tweedie, 2000).

RESULTS
The Characteristics of the Included Studies As depicted in Figure 1, a total of 222 articles were obtained by online search, and 2 articles were included by manual search. After removing duplicates, 175 articles were included. After screening title and abstract, 115 articles were excluded. As a result, 13 articles (Zheng et al., 1998;Zhang et al., 2000Zhang et al., , 2008Pan et al., 2002;Guo et al., 2007;Chaaba et al., 2008;Izar et al., 2009;Shi et al., 2009;Vaisi-Raygani et al., 2010;Al-Majed et al., 2011;Chaudhary et al., 2012;Halim et al., 2012;Hong et al., 2017) were eligible for the meta-analysis. The characteristics of the included articles are summarized in Table 1. The included studies were conducted in several countries including China, Brazil, Thailand, Egypt, Iran, Kuwait, and Tunisia. All studies were performed in a case-control design and the sample sizes varied from 70 to 990. The quality score of the included studies ranged from 5 to 12 (mean: 9.69) out of a maximal score of 13.
In the subgroup analysis according to the source of patients (Chinese and non-Chinese), the pooled ORs of all genetic models except the ε2/ε4 vs. ε3/ε3 model were consistent with the results in the overall population. In the Chinese population, the ε2/ε4 genotype increased the risk of CAD in patients with T2DM (OR = 2.17, 95% CI = 1.10-4.28, P = 0.026).

Galbraith Plot Analysis and Sensitivity Analysis
There was evidence of moderately large between-study heterogeneity in the genetic model of ε2 allele vs. ε3 allele (P heterogeneity = 0.054, I 2 = 44.70%) and ε2/ε2+ε2/ε3 vs. ε3/ε3 (P heterogeneity = 0.071, I 2 = 39.50%), so Galbraith plot analysis and sensitivity analysis were performed to detect the possible sources of heterogeneity. Under the genetic model of ε2 allele vs. ε3 allele, the Galbraith plot analysis (Figure 4A) showed that the Halim et al. study was the outlier, which is consistent with the results of sensitivity analysis ( Figure 4B). No heterogeneity existed after this outlier study was omitted (P heterogeneity = 0.460, I 2 = 0%). Thus, the study by Halim et al. may be the source of heterogeneity in the meta-analysis for the ε2 allele vs. ε3 genetic model. Similarly, under the genetic model of ε2/ε2+ε2/ε3 vs. ε3/ε3, the Galbraith plot analysis ( Figure 4C) and sensitivity analysis ( Figure 4D) indicated that Halim and Chaudhary's FIGURE 2 | Forest plot for the association between APOE gene polymorphism and the risk of coronary artery diseases in type 2 diabetes patients under the genetic model of ε4/ε4+ε3/ε4 vs. ε3/ε3. The center of each square represents the OR, the area of the square is for the weight of studies, and the horizontal line indicates the 95% CI. study were the outliers. When the two outlier studies were omitted, no heterogeneity existed in the remaining studies (P heterogeneity = 0.681, I 2 = 0%). Therefore, the studies of Halim et al. and Chaudhary et al. may be the main contributors to the source of heterogeneity in the meta-analysis for the ε2/ε2+ε2/ε3 vs. ε3/ε3 genetic model.

DISCUSSION
T2DM is a well-established risk factor for the development of CAD. The management of CAD in patients with T2DM poses great challenges to the medical profession (Wei et al., 2015). The identification of susceptibility genes would be very helpful for the management of CAD in patients with T2DM. The link between APOE ε2/ε3/ε4 polymorphisms and CAD in diabetic patients has been highlighted in our study. This meta-analysis provides evidence for the significant associations between APOE ε4 mutation (ε3/ε4 vs. ε3/ε3; ε4/ε4 vs. ε3/ε3; ε4/ε4+ε3/ε4 vs. ε3/ε3; ε4 allele vs. ε3 allele) and an elevated risk of CAD in patients with T2DM. In contrast, no significant association was found in genetic model of APOE ε2 variation (ε2/ε2 vs. ε3/ε3; ε2/ε3 vs. ε3/ε3; ε2/ε2+ε2/ε3 vs. ε3/ε3; ε2 allele vs. ε3 FIGURE 3 | Forest plot for the association between APOE gene polymorphism and the risk of coronary artery diseases in type 2 diabetes patients under the genetic model of ε2/ε2+ε2/ε3 vs. ε3/ε3. The center of each square represents the OR, the area of the square is for the weight of studies, and the horizontal line indicates the 95% CI. allele). However, CAD in patients with T2DM is believed to be multifactorial and involved in many susceptibility genes with small individual effects. Therefore, the integration of information derived from several polymorphisms in multiple susceptibility genes may become clinically useful.
It has been reported that lipoprotein-related mechanisms are associated with the impairment of the cardiovascular system among patients with diabetes (Jenkins et al., 2004). For example, serum low-density lipoprotein cholesterol (LDL-C) level was identified as an independent risk factor for CAD in T2DM patients (Jayashankar et al., 2016). APOE is initially recognized for its important role in plasma lipid metabolism and thus affects the serum lipid profiles in the body. The three APOE alleles (ε2, ε3, ε4) differ from each other by only one or two amino acids at positions 112 and 158, but these slight differences alter the structure and function of APOE. In general, the APOE-ε4 allele is associated with higher and the APOE-ε2 allele with lower total plasma cholesterol and LDL-C concentrations compared with the APOE-ε3 allele (Bennet et al., 2007;Larifla et al., 2017). Therefore, abnormalities of lipoprotein metabolism may explain, at least in part, the associations between APOE ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM.
Several meta-analysis studies have been conducted to assess the association between APOE ε2/ε3/ε4 polymorphisms and risk of CAD in the general population. In 2004, Song et al firstly found that carriers of the APOE-ε4 allele had a 42% increased risk for CAD (OR = 1.42, 95% CI = 1.26-1.61) compared with the ε3/ε3 genotypes (Song et al., 2004). Xu et al. found similar results which showed that the ε4 allele had a 46% higher risk of CAD (OR = 1.46, 95% CI = 1.28-1.66) (Xu et al., 2016). Similar findings were also observed in other meta-analysis (Yin et al., 2013;Xu et al., 2014Xu et al., , 2016Zhang et al., 2014aZhang et al., , 2015Wang et al., 2015b). Interestingly, the role of APOE-ε2 allele in the risk of CAD may be dependent on the patient ethnicity (Xu et al., 2016). In addition, the association between APOE ε2/ε3/ε4 polymorphisms and the risk of T2DM in the general population was also well explored in previous meta-analysis (Anthopoulos et al., 2010;Yin et al., 2014). The results indicated that both APOE ε2 and ε4 alleles were associated with an increased risk of T2DM in the general population. In 2015, Wu et al. performed a meta-analysis on the association between APOE ε2/ε3/ε4 polymorphisms and T2DM patients with CAD among Chinese Han population. They found that APOE-ε4 allele resulted in an increased risk of T2DM patients with CAD in China (Wu et al., 2015). However, only five individual studies were included in their meta-analysis. To our knowledge, our meta-analysis represents the largest study to investigate the association between APOE ε2/ε3/ε4 polymorphisms and risk of CAD in the T2DM patients. Heterogeneity across studies is common in meta-analysis of genetic association study (Munafo and Flint, 2004). Heterogeneity should be taken into consideration in the interpretation of the meta-analysis results. However, one of the strengths in this meta-analysis was the lack of significant heterogeneity in all genetic models except the genetic model of ε2 allele vs. ε3 allele. Between-study heterogeneity can be attributed to the potential differences such as the definition of disease, ethnicity, genotyping methods and sample size in the included studies. To explore the potential sources of heterogeneity under the genetic model of ε2 allele vs. ε3 allele, Galbraith plot analysis and sensitivity analysis were employed to detect whether there were outliers that could be the potential sources of heterogeneity between studies. The study conducted by Halim et al was considered as the main contributors to between-study heterogeneity. The heterogeneity was effectively decreased after omitting the study. The frequency of APOE-ε3 allele was nearly 95% in Halim's study, whereas lower than 90% in other studies (Zhang et al., 2008;Izar et al., 2009;Chaudhary et al., 2012;Hong et al., 2017). Consequently, the heterogeneity can be due to the distinct frequency of APOE ε2/ε3/ε4 polymorphisms among the included studies. Although Halim's study caused the substantial heterogeneity in the genetic model of ε2 allele vs. ε3 allele, the pooled effect was still insignificant after removing it.
There are several limitations in this meta-analysis that should be noted. First, the included studies were limited to only English or Chinese languages in our research and some eligible studies may be published in other languages, which would cause bias of the results. Second, all the included studies in this meta-analysis were the type of retrospective case-control studies, which may result in some selection bias. Third, publication bias existed in the following three genetic models: ε3/ε4 vs. ε3/ε3; ε3/ε4+ε4/ε4 vs. ε3/ε3; ε4 allele vs. ε3 allele. However, by using the trim and fill method, the recalculated ORs and their 95% CIs did not change, which indicated the stability and robustness of meta-analysis results. Last but not the least, T2DM complicated with CAD is a multifactorial disease caused by both genetic and environmental factors. The APOE-environment interactions should be considered. For example, the study by Talmud et al. has found that the impact of the APOE-ε4 on the risk of CAD appeared to be restricted to smokers (Talmud et al., 2004).
FIGURE 6 | Funnel plot with trim and fill method for the association between APOE gene polymorphism and the risk of coronary artery diseases in type 2 diabetes patients under the genetic model of ε3/ε4 vs. ε3/ε3 (A), ε4/ε4+ε3/ε4 vs. ε3/ε3 (B), and ε4 allele vs. ε3 allele (C). Circle represents the included studies; Square represents the possibly missing studies.
In conclusion, we observed a significant association between the APOE gene ε4 mutation and an increased risk of CAD in patients with T2DM, while the ε2 variation had null association with this disease. Taking into account the above limitations, more studies with larger sample size and incorporated with geneenvironment interactions are needed to definitively determine the association between the APOE gene ε2/ε3/ε4 polymorphisms and the risk of CAD in patients with T2DM.

AUTHOR CONTRIBUTIONS
Conceived and designed the study: J-QL and HR. Performed the search: J-QL, HR, M-ZL. Analyzed the data: J-QL and HR. Contributed reagents/material/analysis tools: J-QL, HR, M-ZL, PX, P-FF, and D-XX. Wrote and review the manuscript: J-QL, HR and HB. Reference collection, data management, statistical analyses, paper writing, and study design: J-QL and HR.

ACKNOWLEDGMENTS
This work was funded by the National Natural Science Foundation of China (NO. 81703623).