Abstract
Background: A lot of studies have demonstrated that C242T polymorphism in CYBA genes may play an important role in the pathological process of acute coronary syndrome (ACS). However, the results are not consistent. To further evaluate this debate, we performed a meta-analysis to determine the relationship between C242T polymorphism and ACS. Methods and results: We screened PubMed/MEDLINE, EBSCIO, and EMBASE research reports until Mar. 2014 and extracted data from 10 studies involving 6102 ACS patients and 8669 controls. Subgroup analysis by ethnicity documented a significant decreased risk of ACS for C242T polymorphism in the Asian population under allelic comparison (odd ratio (OR) 0.73; 95% confidence intervals (CI) 0.64–0.83), dominant model (OR 0.71; 95% CI 0.62–0.82), and homozygote comparison (OR 0.57; 95% CI 0.35–0.92). However, in the overall population and especially with Caucasians, no significant association was uncovered. Further meta-regression analysis revealed that the heterogeneity among studies was largely attributed to ethnicity. No publication bias was detected through a funnel plot and an Egger’s linear regression test. Conclusions: Taken together, our results suggest that the C242T polymorphism might be a protective factor against developing ACS in the Asian population. Further researches will be needed to identify the confounding factors which modified the protective effect of T allele among Caucasians.
Keywords: CYBA, C242T polymorphism, Acute coronary syndrome
1. Introduction
With the extensive development of medication and interventional therapy, the mortality of coronary artery disease (CAD) in many countries has declined during the past decades (Nabel and Braunwald, 2012). However, a substantial number of patients still suffer from acute coronary syndrome (ACS) (Falk et al., 2013). In the USA, approximately 1.2 million patients are hospitalized for ACS each year (Roger et al., 2012). Rupture or erosion of an unstable atherosclerotic plaque and subsequent thrombosis are the chief pathological characteristics of ACS (Falk et al., 2013; Thompson et al., 2013).
Reactive oxygen species (ROS), including nitric oxide, superoxide, hydrogen peroxide, and peroxynitrite, play an important role in vascular pathophysiology and platelet aggregation (Griendling and Fitzgerald, 2003), which are also involved in the pathological process of ACS by activating matrix metalloproteinases (MMPs) (Galis et al., 1995), increasing smooth muscle cells apoptosis and thus leading to a plaque rupture (Bennett, 1999; Deshpande et al., 2002). NAD(P)H oxidase is the predominant cellular source of ROS in the atherosclerotic lesions (Mueller et al., 2005), which can be activated by p22phox (Sumimoto et al., 1996). p22-phox is encoded by the CYBA gene, which is located in the human chromosome 16q24. The C242T polymorphism of the CYBA gene leads to a decreased production of ROS in the vasculature (Whitehead and Fitzgerald, 2001), indicating a protective role of C242T polymorphism in ACS. A lot of studies have been carried out to investigate the relationship between the C242T polymorphisms and ACS. However, the results are not consistent. Hence, we conducted this meta-analysis to evaluate the association between the C242T polymorphism and ACS.
2. Materials and methods
2.1. Literature search strategy
An extensive literature searching of PubMed/MEDLINE, EBSCIO, and EMBASE reports was performed for relevant articles without restricting the language until Mar. 2014, using the combinations of the keywords “C242T”, “p22phox”, “CYBA”, “NAD(P)H oxidase”, “nicotinamide adenine dinucleotide phosphate oxidase”, “rs4673”, “polymorphism”, “mut*”, “varia*”, “coronary”, “myocardial infarction”, “atherosclerosis”, “acute coronary syndrome”, and “unstable angina pectoris”. Additional studies were identified by scanning the references of reviews and retrieved studies. We conducted the meta-analysis according to the guidelines of the 2009 Preferred Reporting Items for the Systematic Reviews and Meta-Analysis (PRISMA) statement (Checklist S1) (Moher et al., 2009).
2.2. Inclusion criteria
Identified studies were screened according to the following inclusion criteria: (1) Case-control or cohort study assessing the association between C242T polymorphism and ACS risk as an original study. (2) Studies providing adequate information for calculating the genotypic odd ratio (OR) with 95% confidence interval (CI). (3) Published literatures of human genetics without ethnicity restriction. (4) If multiple articles originated from the same population, only the largest scale study was included. (5) The genotype frequencies amongst case and control must conform to the Hardy-Weinberg equilibrium (HWE). (6) ACS was defined as an acute myocardial infarction (MI) and unstable angina (Falk et al., 2013).
2.3. Data extraction and quality assessment
All the data were extracted independently by two investigators following the inclusion criteria described above. The following was gathered from the eligible articles: name of the first author, publication year, ethnicity, endpoint, mean ages, sample sizes for case and control groups, genotype distributions and conformity to genotype frequencies with HWE, the proportion of male, hypertension, diabetes mellitus, and smoking. Two investigators used the Newcastle-Ottawa Scale (NOS) to assess the methodological quality of all eligible studies. Studies that were awarded 5 stars or more can be regarded to be of medium to high quality.
2.4. Statistical analysis
The HWE for the distributions of genotypes was assessed by the Pearson’s chi-square test. The pooled effect for the relationship between the C242T polymorphism and ACS risk was calculated under different models, containing allele comparison, dominant genetic model, recessive genetic model and homozygote comparison. The Cochran’s Q test and I 2 statistic were used to evaluate the between-study heterogeneity. The heterogeneity was qualified by I 2: I 2=0%–25%, low between-study heterogeneity; I 2=25%–50%, moderate heterogeneity; I 2=50%–100%, notable heterogeneity (Higgins et al., 2003). The random effect model (REM) was adopted in the presence of notable heterogeneity (I 2>50%); otherwise, the fixed-effect model (FEM) was applied. A meta-regression was run to explore the origin of the genetic heterogeneity and then stratified analysis by subgroup was adopted. Sensitivity analysis was applied to identify the influence of each study, with successive omission of individual studies (Patsopoulos et al., 2008). The Funnel plot and Egger’s test were applied to evaluate the probability of publication bias. All statistical analyses were carried out with Stata Version 12.0 (Stata Co., College Station, TX, USA) and Review Manager Version 5.2 (RevMan, Cochrane Collaboration, Oxford, England). P<0.05 was considered statistically significant.
3. Results
3.1. Characteristics of the studies
The flow chart for the literature search is shown in Fig. 1. A total of 271 relevant references were included, with 257 publications excluded. One study (Katakami et al., 2009) was excluded since it was overlapped by another study with a larger scale (Katakami et al., 2010). Three publications did not meet the requirements of HWE (P HWE<0.05) (Mata-Balaguer et al., 2004; Morgan et al., 2007; Hashad et al., 2014). Finally, a total of 10 case-control studies were retrieved on ACS and the CYBA C242T polymorphism (Gardemann et al., 1999; Stanger et al., 2001; Yamada et al., 2002; Murase et al., 2004; Vasiliadou et al., 2006; Macías-Reyes et al., 2008; Katakami et al., 2010; de Caterina et al., 2011; Goliasch et al., 2011; Narne et al., 2012).
Fig. 1.
Flow chart for the literature search strategy
The basic characteristics and genotype frequencies of the included studies are listed in Tables 1 and 2. All the included studies were conducted from 1999 to 2012, with 6102 ACS patients and 8669 controls. MI was employed as the primary endpoint in five studies (Yamada et al., 2002; Vasiliadou et al., 2006; Katakami et al., 2010; de Caterina et al., 2011; Goliasch et al., 2011), while MI and unstable angina were taken as the endpoint in two studies (Murase et al., 2004; Macías-Reyes et al., 2008). The endpoint of three studies was CAD, and MI was taken as the endpoint in subgroup analysis (Gardemann et al., 1999; Stanger et al., 2001; Narne et al., 2012). There were six studies based on the Caucasian population, and four studies conducted on the Asian population. The genotype distributions among patients and controls conformed to HWE. All the 10 studies were assessed according to the NOS scale and most studies (80%) scored 5 stars or more, suggesting a moderate to good quality (Table 3).
Table 1.
Characteristics of the included studies
| Fisrt author | Year | Ethnicity | End point | Mean age (year) | Male (%) | Sample size | Smoking (%) | HTN (%) | DM (%) |
| Gardemann | 1999 | Caucasian | MI* | 62.2/61.4 | 100/100 | 1031/499 | 62.0/54.0 | 19.0/11.0 | |
| Stanger | 2001 | Caucasian | MI* | 52.9/54.2 | 100/100 | 71/45 | |||
| Yamada | 2002 | Asian | MI | 62.1/62.0 | 100/100 | 1784/1074 | 57.8/55.2 | 47.0/57.3 | 34.7/16.2 |
| Murase | 2004 | Asian | UA/MI | 58.0/61.0 | 100/100 | 453/762 | 84.3/51.8 | 64.2/63.9 | 15.0/18.9 |
| Vasiliadou | 2006 | Caucasian | MI | 46.9/ | 197/204 | ||||
| Macías-Reyes | 2008 | Caucasian | UA/MI | 56.0/54.5 | 78/74 | 304/315 | 50.0/27.3 | 33.9/12.1 | |
| Katakami | 2010 | Asian | MI | 62.2/59.5 | 64/61 | 226/3593 | 45.1/43.2 | 82.3/72.9 | 100/100 |
| de Caterina | 2011 | Caucasian | MI | 39.6/39.6 | 89/89 | 1864/1864 | 87.2/48.9 | 27.42/9.18 | 7.6/0.8 |
| Goliasch | 2011 | Caucasian | MI | 37.3/34.7 | 87/90 | 99/192 | 78.0/43.1 | 42.0/17.5 | 30.0/12.5 |
| Narne | 2012 | Asian | MI* | 73/121 | 100/100 |
Data are expressed as values for case/control. MI: myocardial infarction; UA: unstable angina; HTN: hypertension; DM: diabetes mellitus
Subgroup analysis
Table 2.
CYBA gene C242T polymorphism genotype and allele distributions between ACS patients and controls, and P-value of HWE in controls and cases
| First author | Genotype (TT/TC/CC) |
Allele (C/T) (%) |
P
HWE |
|||
| Case | Control | Case | Control | Control | Case | |
| Gardemann | 127/457/447 | 65/208/226 | 65.5/34.5 | 66.1/33.9 | 0.12 | 0.54 |
| Stanger | 11/30/30 | 6/24/15 | 63.4/36.6 | 60.0/40.0 | 0.46 | 0.45 |
| Yamada | 25/319/1440 | 16/242/816 | 89.7/10.3 | 87.2/12.8 | 0.69 | 0.13 |
| Murase | 2/67/384 | 5/170/587 | 92.2/7.8 | 88.2/11.8 | 0.61 | 0.61 |
| Vasiliadou | 34/98/65 | 21/95/88 | 57.9/42.1 | 66.4/33.6 | 0.53 | 0.78 |
| Macías-Reyes | 48/137/119 | 47/145/123 | 61.7/38.3 | 62.1/37.9 | 0.69 | 0.42 |
| Katakami | 0/36/190 | 33/618/2942 | 92.0/8.0 | 90.5/9.5 | 0.93 | 0.19 |
| de Caterina | 322/888/654 | 296/889/679 | 58.9/41.2 | 60.3/39.7 | 0.86 | 0.49 |
| Goliasch | 11/47/41 | 31/79/82 | 65.2/34.8 | 63.3/36.7 | 0.11 | 0.65 |
| Narne | 5/27/41 | 22/54/45 | 74.7/25.3 | 59.5/40.5 | 0.42 | 0.85 |
HWE: Hardy-Weinberg equilibrium
Table 3.
Quality assessment conducted according to the Newcastle-Ottawa criteria for all the included studies
| First author | Year | Quality indicators |
||
| Selection | Comparability | Exposure | ||
| Gardemann | 1999 | ** | * | ** |
| Stanger | 2001 | ** | ** | * |
| Yamada | 2002 | **** | * | * |
| Murase | 2004 | *** | ** | |
| Vasiliadou | 2007 | ** | ||
| Macías-Reyes | 2008 | **** | ** | ** |
| Katakami | 2010 | ** | * | * |
| de Caterina | 2011 | *** | * | * |
| Goliasch | 2011 | *** | ** | * |
| Narne | 2012 | *** | ** | |
3.2. Quantitative synthesis
The combined results of the C242T polymorphisms with ACS are summarized in Table 4. There was no significant association observed under any of the four genetic models (allele comparison: P=0.18, OR=0.91, 95% CI 0.78–1.05; dominant model: P=0.22, OR=0.90, 95% CI 0.75–1.07; recessive model: P=0.58, OR=1.04, 95% CI 0.91–1.18; homozygote comparison: P=0.51, OR=1.05, 95% CI 0.91–1.21) (Figs. 2–5). We also found notable heterogeneity in the allele comparison (I 2=74) and dominant model (I 2=71).
Table 4.
Results of meta-analysis for CYBA gene C242T polymorphism and acute coronary syndrome
| Genotype contrast | Population | Study number (case/control) | Model for analysis | OR (95% CI) | P heterogeneity | I 2 (%) | P-value |
| Allele comparison (T vs. C) | Total | 10 (6102/8669) | REM | 0.91 (0.78, 1.05) | <0.001 | 74 | 0.18 |
| Asian | 4 (2536/5550) | FEM | 0.73 (0.64, 0.83) | 0.18 | 39 | <0.001 | |
| Caucasian | 6 (3566/3119) | FEM | 1.06 (0.99, 1.14) | 0.33 | 13 | 0.11 | |
| Dominant model (TT+CT vs. CC) | Total | 10 (6102/8669) | REM | 0.90 (0.75, 1.07) | <0.001 | 71 | 0.22 |
| Asian | 4 (2536/5550) | FEM | 0.71 (0.62, 0.82) | 0.21 | 34 | <0.001 | |
| Caucasian | 6 (3566/3119) | FEM | 1.07 (0.97, 1.19) | 0.47 | 0 | 0.16 | |
| Recessive model (TT vs. CT+CC) | Total | 10 (6102/8669) | FEM | 1.04 (0.91, 1.18) | 0.19 | 27 | 0.58 |
| Asian | 4 (2536/5550) | FEM | 0.63 (0.39, 1.02) | 0.31 | 16 | 0.06 | |
| Caucasian | 6 (3566/3119) | FEM | 1.08 (0.94, 1.24) | 0.33 | 13 | 0.26 | |
| Homozygote comparison (TT vs. CC) | Total | 10 (6102/8669) | FEM | 1.05 (0.91, 1.21) | 0.07 | 43 | 0.51 |
| Asian | 4 (2536/5550) | FEM | 0.57 (0.35, 0.92) | 0.20 | 35 | 0.02 | |
| Caucasian | 6 (3566/3119) | FEM | 1.11 (0.96, 1.29) | 0.27 | 21 | 0.16 |
OR: odds ratio; 95% CI: 95% confidence interval; REM: random-effects model; FEM: fix-effects model
Fig. 2.
Forest plot for the overall association between the C242T polymorphism and ACS under the allele comparison (T vs. C)
Fig. 5.
Forest plot for the overall association between the C242T polymorphism and ACS under the homozygote comparison (TT vs. CC)
Fig. 3.
Forest plot for the overall association between the C242T polymorphism and ACS under the dominant model (TT+CT vs. CC)
Fig. 4.
Forest plot for the overall association between the C242T polymorphism and ACS under the recessive model (TT vs. CT+CC)
3.3. Sensitivity analysis
A sensitivity analysis was run to look for studies making the largest contributions to the notable heterogeneity in allele comparisons and dominant models. The results showed that no single study dramatically affected the heterogeneity, ORs and 95% CIs (Table 5).
Table 5.
Sensitivity analysis of pooled OR
| Study omitted | OR (95% CI) | I 2 (%) |
| Allele comparison | ||
| Gardemann | 0.88 (0.74, 1.05) | 77 |
| Stanger | 0.91 (0.78, 1.06) | 77 |
| Yamada | 0.92 (0.79, 1.08) | 72 |
| Murase | 0.95 (0.82, 1.09) | 70 |
| Vasiliadou | 0.87 (0.75, 1.00) | 71 |
| Macías-Reyes | 0.89 (0.75, 1.05) | 77 |
| Katakami | 0.91 (0.78, 1.07) | 77 |
| de Caterina | 0.88 (0.74, 1.04) | 72 |
| Goliasch | 0.90 (0.77, 1.06) | 77 |
| Narne | 0.94 (0.82, 1.08) | 70 |
| Dominant | ||
| Gardemann | 0.87 (0.71, 1.06) | 72 |
| Stanger | 0.91 (0.76, 1.09) | 73 |
| Yamada | 0.92 (0.76, 1.11) | 67 |
| Murase | 0.95 (0.80, 1.12) | 64 |
| Vasiliadou | 0.85 (0.72, 1.01) | 68 |
| Macías-Reyes | 0.88 (0.73, 1.07) | 74 |
| Katakami | 0.90 (0.74, 1.09) | 74 |
| de Caterina | 0.87 (0.71, 1.07) | 68 |
| Goliasch | 0.88 (0.73, 1.07) | 74 |
| Narne | 0.93 (0.79, 1.11) | 68 |
3.4. Meta-regression analysis and subgroup analysis
In view of a notable heterogeneity, we performed a series of univariate meta-regression analysis under the allelic model and the dominant model by adding single covariates including publication year, age, ethnicity, the proportion of male, hypertension, diabetes mellitus, and smoking status. In the univariate analysis, a large proportion of the between-study heterogeneity was significantly attributed to ethnicity (Table 6). Hence, we undertook subgroup analyses on ethnicity and the heterogeneity significantly decreased both in the allelic model and the dominant model. The risk of ACS decreased in the Asian population (allelic comparison: P<0.01, OR=0.73, 95% CI 0.64–0.83; dominant model: P<0.01, OR=0.71, 95% CI 0.62–0.82; homozygote comparison: P=0.02, OR=0.57, 95% CI 0.35–0.92).
Table 6.
Meta-regression analysis for heterogeneity under the allelic model and dominant model of p22phox gene C242T polymorphism
| Variable | Coefficient | P-value | tau 2 -value | R 2 (%) |
| Allelic model | ||||
| Ethnicity | −0.4427 | 0.035 | 0.0506 | 45.68 |
| Year | 0.0006 | 0.981 | 0.1079 | −15.92 |
| Age | −0.0064 | 0.608 | 0.0925 | −12.55 |
| Male (%) | −0.7707 | 0.391 | 0.0736 | 1.56 |
| DM (%) | −0.4094 | 0.273 | 0.0875 | 5.48 |
| Hypertension (%) | −0.3943 | 0.211 | 0.0065 | 38.22 |
| Smoking (%) | −0.1693 | 0.238 | 0.0853 | 18.15 |
| Dominant model | ||||
| Ethnicity | −0.3109 | 0.015 | 0 | 100 |
| Year | 0.0178 | 0.372 | 0.0407 | −11.90 |
| Age | −0.0125 | 0.177 | 0.0303 | 20.22 |
| Male (%) | −0.3030 | 0.632 | 0.0218 | −16.66 |
| DM (%) | 0.0149 | 0.953 | 0.0236 | −25.00 |
| Hypertension (%) | −0.4886 | 0.294 | 0.0213 | 11.73 |
| Smoking (%) | 0.0892 | 0.922 | 0.0286 | −42.73 |
However, no significant association was observed in the Caucasian population (allelic comparison: P=0.11, OR=1.06, 95% CI 0.99–1.14; dominant model: P=0.16, OR=1.07, 95% CI 0.97–1.19; recessive model: P=0.26, OR=1.08, 95% CI 0.94–1.24; homozygote comparison: P=0.16, OR=1.11, 95% CI 0.96–1.29) (Table 4).
3.5. Publication bias
The Funnel plot (Fig. 6) and Egger’s regression were applied to evaluate the probability of publication bias. No significant publication bias was found in the overall estimates (t=−0.88, P=0.40 for allele comparison).
Fig. 6.
Funnel plot analysis to evaluate publication bias for the allele comparison of the C242T polymorphism
4. Discussion
Due to the conflicting results about the relationship between C242T polymorphisms and ACS, we conducted this meta-analysis. A total of 10 articles with 6102 ACS patients and 8669 controls were included in our study. Finally, in our meta-analysis, no significant association was observed under different genetic models with notable heterogeneity. This unexpected result may be due to the presence of notable heterogeneity, which confounded the possible effect.
Further meta-regression identified that a large proportion of between-study heterogeneity was explained by ethnicity. Subgroup analysis by ethnicity documented a significant decreased risk of ACS under allelic comparison, dominant model, and homozygote comparison in the Asian population, while no significant association was observed among Caucasians. ROS were involved in plaque rupture and platelet aggregation (Galis et al., 1995; Bennett, 1999; Deshpande et al., 2002; Griendling and Fitzgerald, 2003), suggesting the important role of ROS in the pathological process of ACS. NAD(P)H oxidase is the predominant cellular source of ROS in the context of atherosclerosis (Mueller et al., 2005), which can be activated by p22phox (Sumimoto et al., 1996). The C242T polymorphism results in a substitution of Tyr for His at residue 72 of p22phox, and significantly reduced vascular NAD(P)H oxidase activity (Guzik et al., 2000). This might be expected to reduce the generation of ROS, indicating a protective role of T allele in ACS, which is consistent with the results for the Asian population as suggested by our meta-analysis.
It is really puzzling to us that no significant association was observed among Caucasians. The ethnicity-related discrepancy in the effect of the C242T polymorphism could be attributed to multiple cardiovascular risk factors, which confound the possible effects. Fan et al. (2007) reported that body adiposity may modify the genetic effect of C242T polymorphism. The prevalence of adult obesity in the United States (2011–2012) is 34.9% (Ogden et al., 2014), while it is only 12.9% in China (2010) (Li et al., 2012). Obesity may be one of the confounding factors, which modified the effect of T allele among Caucasians, which is in accordance with the suggestion of previous meta-analysis studies (Wu et al., 2013). Recently, some investigators reported that increased body mass index (BMI) in adults is associated with increased methylation at the HIF3A (Dick et al., 2014). Hence, we forward the hypothesis that obesity regulated the methylation level of the CYBA gene, and then modified the protective effect of C242T polymorphism among Caucasians. Further researches will be needed to confirm our hypothesis, and the important effects of other confounding factors should also be studied. It has been reported that physical activity could modify this genetic effect of the CYBA gene (Zhu et al., 2012). The c.-930A>G promoter polymorphism and the 640A>G polymorphism in the CYBA gene have also been implicated in the development of cardiovascular disease (Goliasch et al., 2011; Xu et al., 2014). Further researches will be needed to clarify the possible correlation of the three haplotypes of the CYBA gene.
Three previous meta-analyses had evaluated the effect of the C242T polymorphism on CAD risk, the results are in conformity with notable heterogeneity. Fang et al. (2010) first undertook a meta-analysis suggesting that C242T polymorphism had a significant protective effect among Asians but not among Caucasians, which is consistent with the results as suggested by Xu et al. (2014). However, Wu et al. (2013) reported that the T allele had a marginal risk increase of CAD among Caucasians (recessive model: OR=1.21, 95% CI 1.00–1.46) and no significant association was observed in the Asian population. The typical pathology of ACS and stable angina are significantly different (Falk et al., 2013; Thompson et al., 2013). ROS play an important role in the pathological process of ACS rather than stable angina. The stable angina cases included in the three meta-analyses may be contributed to the notable heterogeneity. Analyzing the effect of the C242T polymorphism on ACS may be more convincing. Fang et al. (2010) and Xu et al. (2014) had not discussed the relationship between the C242T polymorphisms and ACS. Although Wu et al. (2013) had carried out tests to investigate the relationship between the C242T polymorphisms and ACS, the subgroup analysis included only six ACS studies with notable heterogeneity, and the genotype frequencies of one study did not conform to HWE (Morgan et al., 2007). Hence, our meta-analysis excluded patients with stable angina and conformed to HWE in both the controls and patients with ACS. A large proportion of between-study heterogeneity was explained by ethnicity in our meta-analysis. The heterogeneity of subgroup analysis by ethnicity was low or moderate. The reason for the similar results between our paper and two of the three meta-analyses may be the population source (Fang et al., 2010; Xu et al., 2014). A large proportion of the eligible articles, which are included in the two meta-analyses, were hospital-based, and most of the patients were hospitalized for ACS.
Although we have tried our best to improve this manuscript, there are still some limitations. First, the number of eligible articles in our meta-analysis is small. Second, the data of BMI in some articles are missing, which makes it difficult to confirm our hypothesis. Third, our meta-analysis did not account for the possible synergistic effects of the three common polymorphisms in the CYBA gene. Finally, the observed association between C242T polymorphism and ACS does not necessarily imply causality.
In conclusion, this meta-analysis suggests that C242T polymorphism is related to ACS risk reduction only in the Asian population. We forward the hypothesis that obesity may modify the protective effect of C242T polymorphism among Caucasians. Our observations support the need for further investigation into the modifying effect of possible confounding factors. We suggest that the “good” or “bad” effects of the CYBA gene are related to different haplotypes and confounding factors, not just C242T polymorphism.
Footnotes
Compliance with ethics guidelines: Po HU, Ming-yuan HUANG, Xin-yang HU, Xiao-jie XIE, Mei-xiang XIANG, Xian-bao LIU, and Jian-an WANG declare that they have no conflict of interest.
This article does not contain any studies with human or animal subjects performed by any of the authors.
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