Jianping Li＊, Yongping Fu, Wenxiu Chang, Changrong Yi,Lihua Liu, and Haiyan Xing

1Department of Cardiovascular Internal Medicine, Affiliated Hospital of Shaoxing University,Xiaoxing, Zhejing 312000, China

2Laboratory of Molecular Biology,3Department of Statistics, Medical College of Shaoxing University, Shaoxing, Zhejiang 312000, China

Functional Variant of C-689T in the Peroxisome Proliferator-Activated Receptor-γ2 Promoter is Associated with Coronary Heart Disease in Chinese Nondiabetic Han People

Jianping Li1＊, Yongping Fu1, Wenxiu Chang1, Changrong Yi1,Lihua Liu2, and Haiyan Xing3

1Department of Cardiovascular Internal Medicine, Affiliated Hospital of Shaoxing University,Xiaoxing, Zhejing 312000, China

2Laboratory of Molecular Biology,3Department of Statistics, Medical College of Shaoxing University, Shaoxing, Zhejiang 312000, China

peroxisome proliferator-activated receptor-2; coronary heart disease;single nucleotide polymorphism

ObjectiveTo investigate the association between the polymorphism of C-689T in the peroxisome proliferator-activated receptor-γ2 (PPARγ2) promoter and coronary heart disease (CHD).

MethodsThis case-controlled study was conducted in nondiabetic Chinese Han people, which enrolled 455 patients with CHD (cases) and 693 subjects without CHD (controls). Data of clinical indexes were collected, including height, body weight, waist circumstance, systolic blood pressure (SBP), diastolic blood pressure (DBP), smoking, drinking, physical activity, as well as body mass index (BMI). Fasting blood glucose(FBG), plasma total cholesterol (TC) and triglyceride (TG) levels were measured. Polymerase chain reactionrestricted fragments length polymorphism (PCR-RFLP) was used to determine the PPARγ2 promoter C-689→T substitution. The genotype distribution of PPARγ2 promoter C-689T, allelic frequency, clinical indexes,and laboratorial measurements were compared between the two groups. The effect of genotype on the risk of CHD was assessed using univariate and multivariate regression model.

ResultsThe genotype frequencies of CC, CT and TT in PPARγ2 promoter C-689T were 89.7%, 9.9%and 0.4% in the case group, and 93.1%, 6.6% and 0.3% in the control group, respectively (CCvs. CT+TT,χ2= 6.243,P=0.041). Carriers of -689T allele (n=95) had significantly higher TC level than non-carriers(n=1053) (5.12±1.26vs.4.76±1.22 mmol/L,P=0.001). Male carriers of -689T allele (n=51) weresignificantly higher in waist circumference, body weight, TC and TG than male non-carriers (n=656) (allP＜0.05). In subjects whose BMI was over 25 kg/m2, carriers of -689T allele (n=82) had significantly higher levels of waist circumference, BMI, SBP and TC than non-carriers (n=231) (allp＜0.05). The -689T allele was an independent risk factor for CHD (OR=1.668, 95%CI: 1.031-2.705,P=0.037) after adjusting for age, gender,waist circumference, body weight, BMI, smoking, physical activities, SBP, DBP, FBG, TC and TG level.

ConclusionThese data support the hypothesis that the -689T allele is associated with an increased risk of CHD, in Chinese Han people and correlates significantly with the profiles of CHD-related risk factors.

P EROXISOME proliferator-activated receptors (PPARs),which belong to the steroid hormone receptor superfamily, were identified in the past twenty years. To date, three PPAR isotypes have been identified: PPARα, PPARβ/δ, and PPARγ.1The PPARγ gene,located on chromosome 3, has three isoforms according to differential promoter usage coupled with alternate splicing:PPARγ1 and PPARγ3, encode the same protein product;PPARγ2 contains an additional 28 amino acids at its aminoterminus. PPARγ1 exhibits widespread expression at a low level; PPARγ2 and PPARγ3 are highly expressed in adipose tissue.2These receptors bind to and are activated by fatty acids, eicosanoids, and numerous structurally dissimilar xenobiotics, known collectively as peroxisome proliferators.Upon activation, PPARs, as heterodimers with retinoid X receptors (RXRs), regulate gene expression by binding to specific PPAR response elements (PPRE), which is defined as a direct repeat of two core recognition motifs AGGTCA spaced by one nucleotide. PPARs binding to the promoter regions of specific target genes results in either activation or suppression of one specific gene.1PPARγ2 is a nuclear transcript factor with a very wide spectrum of biological activities. It is involved in regulation of many target genes and plays important roles in lipid and glucose metabolism,insulin sensitivity, obesity, cellular proliferation and differentiation, inflammation and atherosclerosis. Activation of PPARγ2 improves insulin sensitivity, and exerts antiatherogenic, anti-inflammatory, antioxidative, antifibrinolytic,and a wide range of metabolic effects. Accordingly, it has been generally considered beneficial to coronary heart disease (CHD).

Experimental and clinical studies have reported that thiazolidinediones (TZD), the ligands of PPARγ, could reduce myocardial infarct size,3attenuate restenosis after angioplasty,4and significantly reduce circulating platelet activity.5It suggests that PPARγ2 is a protective gene for CHD. Moreover, some studies demonstrate that a C-689→T substitution in the promoter of PPARγ2 gene reduces the transcription activity of PPARγ2, and -689T allele significantly affects body weight and LDL-cholesterol.6-7Therefore, the C-689T polymorphism may be associated with CHD, and affect the profile of CHD-related risk factors.However, data on this polymorphism and CHD still are insufficient. To our best knowledge, no study has focused directly on the relationship between C-689T polymorphism and CHD. The goal of present study is to investigate the association between C-689T polymorphism and CHD.

MATERIALS AND METHODS

Subjects recruiting

This case-control study was conducted in the Affiliated Hospital of Shaoxing University, and the protocol was approved by the local ethical committee. Participants were recruited from in-patients and the annual screening population among Chinese Han people in Shaoxing from 2011 to 2015. A questionnaire survey was administered to collect behavior information such as smoking, drinking and physical activity.

Candidates for the case group were selected from inpatients. Criteria for the diagnosis of CHD included evidences meeting any one of the described below: 1) ischemic symptoms accompanied with either diagnostic changes in electrocardiograms or typical abnormalities of cardiac enzymes; 2) the history of either typical angina pectoris or definite myocardial ischemia on electrocardiograms; 3) the coronary arteriography demonstrating stenosis ≥50%. Subjects who were concurrently with diabetes, cerebrovascular disease, or life-threatening malignancy were excluded.

Controls were recruited from healthy population who participated annual health check-up at the same hospital.Those with evidence of the followings were excluded: 1)myocardial infarction (MI) on electrocardiograms; 2) the history of angina; 3) MI and heart failure; 4) regular medication on aspirin or anticoagulants; 5) diabetes; 6) cerebrovascular disease; 7) life-threatening malignancy, or 8)renal inadequacy.

Totally, 455 patients with CHD and 693 healthy individuals were enrolled in the case group and the control group respectively. All enrolled subjects had no blood relation to each other.

Clinical measurements and laboratory examinations

All subjects took physical measurements including body weight, body height and waist circumference by trained nurses. Body mass index (BMI) was calculated by the formula: BMI=body weight (kg)/body height2(m2). Blood pressure was measured on the right upper arm using a standard mercury sphygmomanometer, with the subject in sitting position and resting for at least 5 minutes. The mean of two consecutive blood pressure readings was taken for analysis. Current cigarette smokers were defined as who smokes at least one cigarette per day. Alcohol consumption was defined as positive if a subject drinks alcohol such as wine, beer, cider, or spirits over 50 g per day. Being physically active was defined as positive if a subject takes physical activity 3-5 times a week and more than 30 minutes each time.

All blood samples were taken through venipuncture after the subjects had fasted for at least 10 hours, and stored in disodium EDTA tube for laboratory examinations. Fasting blood glucose (FBG) was measured by the glucose oxidase method. Plasma total cholesterol (TC) and triglyceride (TG) levels were enzymatically measured.

Single nucleotide polymorphism identification and genotyping

Genomic DNA was extracted from the buffy coat fraction of 4 ml centrifuged peripheral blood using a Pure gene DNA Isolation Kit (Gentra Systems, Minneapolis, MN, USA) according to the manufacturer's instructions, and stored in a–20oC refrigerator. The PPARγ2 promoter C-689T polymorphism was detected by the method of polymerase chain reaction-restricted fragments length polymorphism (PCRRFLP). As no restriction enzyme could recognize the substituted site, we introduced one mispairing base G (shading showed, origin was T) in the third site from 3′-end when designing the forward primer, expecting to give rise to the recognition site 5′-GATC-3′ under the condition that the C-689T is C. The sequences of the forward and reverse primers were 5′-TAGAGAACTCCATTTTTTCATTATGACATAGCACTGAT-3′ and 5′-ACTGACTGCTATCTAAATTCTG-3′ respectively. They were synthesized by AuGCT Biotechnology (Beijing, China).

The amplification was performed in a 25 μl volume containing 200 ng DNA, 0.3 μmol/L primers, 160 μmol/L dNTP,1.7 mmol/L MgCl2, 1 U of Taq polymerase and 2.5 μl 10×Taq Buffer with 100 mmol/L Tris-HCl (pH 8.8 at 25°C),500 mmol/L KCl, and 0.8% Nonidet P40 (Fermentas). PCR was run for 4 minutes of initial denaturation at 94°C, followed by 35 cycles, with each cycle consisting of 40 seconds of denaturation at 94°C, 45 seconds of annealing at 57.5°C, 40 seconds of extension at 72°C, and a final extension at 72°C for 5 minutes. The reaction yielded a DNA fragment of 214 bp. The PCR products were confirmed by electrophoresis on a 1% agarose gel containing 0.5 μg/ml ethidium bromide, and visualized by UV-induced fluorescence.

The confirmed products were digested withMboⅠ restriction enzyme [Takara, Bao bio engineering (Dalian) Co.Ltd. China, recognition site 5′-GATC-3′] at 37°C overnight. The digested products were detected by electrophoresis for 30 minutes at 8 V/cm on a 2.5% agarose gel containing 0.5 μg/ml ethidium bromide, and visualized by UV-induced fluorescence. The products of pUC19 DNA digested byMspI enzyme (Fermentas, Canada) were taken as markers. Replication quality control samples were included;and genotypes were detected with 100% concordance.

Statistical analyses

All continuous variables were expressed as means ± SD,and categorical variables were summarized by counts and percentages. Pearsonχ2test was used to compare the enumeration data of various genotypes with those expected for the population in Hardy–Weinberg equilibrium, and analyze differences of genotype distributions between cases and controls. Normally distributed clinical indexes (except for FBG, TC and TG) were compared between the two groups by independent samplest-test, while log-transformation was applied to FBG, TC and TG. The impacts of various factors on the risk of CHD, including genotypes (CC genotype was used as reference), age, gender, waist circumference, body weight, BMI, smoking, alcohol consumption, physical activities, SBP, DBP, FBG, TC and TG, were evaluated by univariate and multivariate logistic regression analyses. SPSS (version 19.0) was used for statistical analysis. AllPvalues presented were two-tailed, and ＜0.05 were considered statistically significant.

RESULTS

Comparison of clinical characteristics between cases and controls

The age and gender of the case group and the control group were well comparable (bothP＞0.05). However, the case group demonstrated significantly higher body weight(P=0.021) and waist circumference (P＜0.001) than thecontrol group, but mean BMIs of the two groups were not statistically different (P=0.621). Besides, the mean clinical measurements of the case group, including SBP, DBP,FBG, TC and TG, were significantly higher than those of the control group (allP＜0.05). The details are outlined in Table 1. Additionally, 42% of cases and 20% of controls had a history of hypertension (χ2=4.346,P=0.019), and 34% of cases had a history of percutaneous coronary intervention (PCI) or surgery of coronary artery bypass graft (CABG).

PPARγ2 promoter C-689T genotype distribution

PCR-RFLP method was used to detect the expression of PPARγ2 promoter C-689T genotype. Theoretically, digestion of the PCR products resulted in two fragments (179 bp and 35 bp) for the CC genotype, three fragments (214 bp,179 bp and 35 bp) for the CT genotype and one fragment(214 bp) for the TT genotype when the restriction site was eliminated by the C-689T substitution (5′-GATC-3′; the substituted base is underlined). In fact, only 179 bp and 214 bp fragments could be detected because 35 bp fragment was too small. Therefore, the digested products detected were one fragment (179 bp) for the CC genotype,two fragments (214 and 179 bp) for the CT genotype and one fragment (214 bp) for the TT genotype (Fig. 1).

The genotype frequencies of CC, CT and TT in PPARγ2 promoter C-689T are listed in Table 2. The distribution of these genotypes between the control group and the case group was significantly different (CCvs.CT+TT,P=0.041); the rare frequency of -689T allele showed significantly higher in the case group than that in the control group (5.4%vs.3.6%,P=0.040).

The relative genotype frequencies did not differ significantly between males and females. CC, CT, and TT frequencies were 92.8%, 6.9%, and 0.3% in males, and 90.0%, 9.5%, and 0.5% in females, respectively. The observed genotype frequencies were in accordance with Hardy–Weinberg equilibrium in total population, cases,controls, males, and females with a Chi-square value (Pvalue) of 1.781 (0.182), 0.392 (0.531), 1.439 (0.230),1.101 (0.294) and 0.595 (0.441), respectively.

Table 1.Comparison of clinical characteristics and laboratory measurements between cases and controls§

Figure 1.C-689T polymorphism enzyme restriction spectrum.1, 6.Marker; 2.PCR product; 3.CC genotype; 4.CT genotype; 5.TT genotype.

Association of genotypes and clinical characteristics

Comparison of clinical indexes between non-carriers and carriers of the -689T allele showed that the mean blood TC level of the carriers was significantly higher than that of the noncarriers (5.12±1.26vs.4.76±1.22 mmol/L,P=0.001) (Table 3). Subjects with C-689-T substitution showed a tendency to a higher TC level (OR=1.413, 95%CI: 1.170-1.707,P＜0.001)after adjusted for age, gender, body weight, waist circumference, BMI, smoking, drinking, physical activities, FBG, SBP,DBP, and TG.

Table 2.Distribution of genotypes and alleles of PPARγ2 promoter C-689T [n(%)]

Table 3. Association between genotypes and clinical characteristics in total study population

In male subjects, statistical differences in waist circumference, body weight, TC and TG were detected between carriers and noncarriers of -689T allele (allP＜0.05).Multivariate logistic regression analysis showed that only waist circumference was significantly different for C-689→T substitution (91.49±12.89vs. 87.00±10.37 cm), with anORof 1.031 (95%CI: 1.005-1.058,P=0.020). In females,only TC was found to be statistically different between carriers and non-carriers of -689T allele (4.98±1.24vs.5.35±1.27 mmol/L,P=0.039), which was consistent with the results from total study population.

In subjects whose BMI was over 25 kg/m2, we found that the carriers (n=82) and noncarriers of -689T allele(n=231) were significantly different in waist circumference(96.19±12.75vs. 93.09±9.05 cm,P=0.049), BMI (28.65±3.46vs.27.54±2.38 kg/m2,P=0.008), SBP (144.63±21.08vs.137.30±21.42 mm Hg,P=0.040) and TC (5.18±1.30vs.4.81±1.23 mmol/L,P=0.036). By multivariate logistic regression analysis, for C-689→T substitution, significant differences were only found in BMI and TC, with anORof 1.121 (95%CI: 1.012-1.241,P=0.029) and 1.337(95%CI: 1.017-1.758,P=0.037) respectively.

In the case group, carriers of -689T allele had significantly higher waist circumference, body weight, BMI, TC and TG than non-carriers (allP＜0.05). In the control group, only TC and TG of -689T allele carriers were found to be significantly higher than those of non-carriers (bothP＜0.05) (Table 4). Multivariate logistic regression analysis showed that only the difference in TC between carriers and non-carriers was significant, with anORof 1.549 (95%CI: 1.008-1.897,P=0.026) for C-689→T substitution.

Coronary heart disease risk factors

We analyzed the impact of the -689T allele, as well as the conventional risk factors, on CHD. Univariate logistic regression analysis confirmed that large waist circumference, heavy body weight, smoking, lack of physical activities, high SBP,high DBP, high FBG level, high TC level and high TG level were risk factors of CHD. Importantly, the -689T allele in the PPARγ2 promoter was a significant risk factor for CHD, with anORof 1.548 (95%CI: 1.016-2.358,P=0.042)(Table 5).

Results of multivariate logistic regression analysisshowed that the -689T allele was an independent risk factor for CHD, with anORof 1.668 (95%CI: 1.031-2.705,P=0.037), after adjusted for age, gender, waist circumference, body weight, smoking, physical activities, SBP, DBP,FBG, TC and TG level. Besides, FBG, SBP, smoking and lack of physical activities were found to have significant impact on the risk of CHD, with anORof 1.196 (95%CI: 1.114-1.285,P＜0.001), 1.024 (95%CI: 1.018-1.031,P＜0.001),2.340 (95%CI: 1.785-3.068,P＜0.001) and 4.251 (95%CI:3.239-5.578,P＜0.001), respectively.

Table 4.Association between genotypes and clinical characteristics in controls and cases

Table 5.Univariate logistic regression analysis of CHD risk factors

DISCUSSION

Since PPARγ2 was identified, studies on the association between PPARγ2 gene polymorphisms and diseases have sprung up. A common variant Pro12Ala in PPARγ2 gene has been confirmed to be associated with diseases such as type 2 diabetes mellitus, obesity, metabolic syndrome and cardiovascular disorders. Meirhaegheet al6found that, in French population, carriers of the -689T allele had elevated body weight and LDL-cholesterol concentration compared with the homozygous for the common allele, and a substitution C-689T in the promoter of PPARγ2 resulted in lower transcription activity of PPARγ2. In another article, the rare alleles of C–689T and Pro12Ala SNPs were reported to be associated with an increased risk of metabolic syndrome compared to the 1431CC genotype.7We assume that the activation of PPARγ2 depresses the development of CHD effectively, and C-689→T substitution in the promoter of PPARγ2 restrains its activity and therefore may be a significant risk factor for CHD. However, Dallongevilleet al8reported that there was no major consistent association ofPPARGC-681G, C-689T, Pro12Ala, and C1431T genotypes or related haplotypes with CHD risks.

In the present study, our results showed that the rare T allele of C-689T, in addition to the traditional risk factors,was a significant risk factor for CHD in nondiabetic Chinese Han people. Because insulin resistance, dyslipidemia, inflammation, artherosclerosis, endothelial dysfunction, andsmooth muscle cells proliferation play important roles in the development of CHD, PPARγ2 may have biological effects on improving insulin sensitivity, anti-atherosclerosis,anti-inflammation and protecting endothelial function.

We propose that PPARγ2 may take these effects through the following signaling pathways. Firstly, diacylglycerol (DAG) activates protein kinase C (PKC) isoforms and mediates many cellular functions, including cell growth,activation, and differentiation, so that the DAG-PKC signaling pathway mediates the pathogenesis of insulin-resistance. Meanwhile, Diacylglycerol kinase (DGK) can inhibit the DAG-PKC pathwayviadecreasing the intracellular DAG level by phosphorylation of DAG, which yields phosphatidic acid. PPARγ2 is able of increasing DGKα production and DGK activity, resulting in suppression of the DAG-PKC signaling pathway, therefore strengthens insulin sensitivity.9Additionally, GLUT2 is a major form of glucose transporter in pancreatic cells and plays an important part in allowing rapid equilibration of glucose across the plasma membrane.It has been described in a previous study that the promoter region of the GLUT2 gene contains PPRE, which indicates that PPAR may maintain glucose homeostasis by regulating the expression of the GLUT2 gene.10Therefore, PPARγ2 can reduce insulin resistance, and inhibit glucose-stimulated proinsulin biosynthesis and insulin release, and thus decreases fat synthesis and lipid accumulation.

Secondly, as PPARγ2 has been revealed to depress the expression of inflammatory response genes, including IFN-γ, IL-1?, IL-6, TNF-α, VCAM-1, NOS, MCP-1 and C-C chemokine receptor 2, it could promote the recruitment of monocytes and T cells in atherosclerotic lesions and their subsequent differentiation and activation.11So PPARγ2 may control inflammation by inhibiting cytokines and matrix metalloproteinases, and by restraining NF-κB, AP-1 and STAT-1 signaling pathways.12

Thirdly, PPARγ2 has been shown to activate ATP-binding cassette transporter A1 (ABCA1) expression indirectly by enhanced transcription of liver X receptor (LXR),therefore promote the efflux of cholesterol from macrophage foam cells.13In vascular smooth muscle cells(VSMCs), PPARγ2 has been showed to inhibit MMP-9 expression and down-regulate Ang II type I receptors, which result in blocking the Rho/Rho kinase pathway and inhibitting VSMCs proliferation.14The efficacy of PPARγ2 in reducing atherosclerosis is hence most likely a consequence of both anti-inflammatory and indirect LXR-mediated effects. Additional anti-atherosclerotic effects might result from reducing macrophage production of inflammatory cytokines, the expression of scavenger receptor type AI/II and the proliferation of VSMCs.13

Finally, PPARγ2 may take these effects through interacting with environment and other related genes, such as leptin, adiponectin and resistin by gene-environment interactions and gene-gene interactions. In our study, T allele carriers of C-689T were found to have a significant higher mean level of TC than non-carriers in the overall study population. This result may be related to the following two aspects. On one hand, PPARγ2 decreases plasma TC synthesisviainsulin-sensitizing and adipocytes differentiation-inhibitory effects; on the other hand, PPARγ2 increases the efflux of TC by controlling the expression of a gene network that mediate cholesterol efflux from cells and its transport in plasma.13Therefore, the T allele carriers have a higher TC level than non-carriers due to the lower activity of PPARγ2.

Since PPARγ2 is involved in a wide range of metabolic pathways, its activation or inhibition is likely to have complex consequences. Both our study and the study by Meirhaegheet al6found that the T allele was not associated with TG. Elevated body weight was found to be associated with T allele in the present study, which was different from the study of Meirhaegheet al.6Although T allele was not found to be associated with BMI, FBG, SBP or DBP in the total study population, interestedly, the associations between genotypes and phenotypes were found to be gender related. In males, T allele was associated with elevated waist circumference, body weight, TC and TG, indicating abdominal obesity in males may be associated with T allele.Additionally, in subjects with obesity (BMI≥25 kg/m2), the T allele was associated with increased waist circumference,BMI, SBP and TC.

In the study, we found that in the Han Chinese subjects that were free of diabetes, the total T allele frequency of C-689T was 4.3%, which was significantly lower than 12% as reported in French population.6This finding indicated that genetic mutation is specific to particular ethnic group and environment.

This study excluded subjects with diabetes mellitus,which enhances the power of the results, as diabetes mellitus was reported to be associated with the genetic mutation.15The large sample size of this study provided power of data that supported the results of our study. However, specimens of this study came from a single institute and from the population of one city in China, which may weaken the representativeness for the whole Han population.

In conclusion, PPARγ2 has a wide range of biological functions. The present study confirmed that the C-689→T substitution in the promoter of PPARγ2 is a significant risk factor for CHD, and is associated with an increased risk of CHD in nondiabetic Chinese Han people. Detection of thisgenotype may help in diagnosis, prevention and treatment of CHD.16Our results indicate the potential of developing PPARγ2-targeted pharmaceuticals in the management of CHD. More studies are needed in the future to further verify our results and investigate clinical values.

Conflict of Interest Statement

All authors have no conflict of interests to disclose.

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10.24920/J1001-9294.2017.042

for publication June 2, 2016.

＊Corresponding author Tel: 86-15906856131, E-mail：lijianping123456@sina.com