Association of PPARγ and AGTR1 Polymorphisms with Hypertriglyceridemia in Chinese Population

Hypertriglyceridemia (HTG) is an important metabolic disease and strongly associated with the development of hypertension, atherosclerosis, coronary artery disease, and type 2 diabetes mellitus (T2DM). HTG risk is affected by various factors and might occur owing to the complex synergistic interaction between the genetic background and environmental factors^[1].

Among peroxisome proliferator-activated receptors (PPARs), PPARγ is an isotype that was recognized to play a major role in the regulation of fatty acid metabolism, probably in the adipose tissue storage and free fatty acids reduction. Several studies suggested that the single nucleotide polymorphisms (SNPs) in PPARγ including rs10865710, rs1805192, and rs709158 are associated with HTG related diseases. However, the results obtained from these studies remain controversial.

Angiotensin Ⅱ type Ⅰ receptor (AGTR1) is a G-protein-coupled receptor of angiotensin Ⅱ that is a peptide hormone and plays a fundamental role as a vasoconstrictor in the regulation of cardiovascular function, renal homeostasis, oxidative stress, and lipid and cholesterol metabolism^[2]. During the past decades, several studies reported the association between the AGTR1 polymorphisms and risk of HTG-related diseases. HTG risk is affected by several gene polymorphisms or interactions among several genes and PPARγ as well as AGTR1 are risk factors of HTG-associated diseases; however, to date, merely a few studies focused on the effects of PPARγ-AGTR1 interaction on HTG risk. Therefore, in this study, we aimed to investigate the effect of PPARγ and AGTR1 polymorphisms and synergistic interaction between these two genes on the HTG risk.

In this study, we included a total of 1, 591 participants who were selected from a prospective cohort study of '135' in Soochow, China, that was performed during the period from August, 2012 to March, 2013 and designed to investigate the prevention strategy for chronic diseases^[3]. In the current study, the age range of subjects was 53.95 ± 9.61 and the protocol was approved by the independent ethics committee of Suzhou Industrial Park (Soochow, China) in accordance with the Declaration of Helsinki (1975). A written informed consent was obtained from each participant.

The body weight, height, and waist circumference (WC) were measured by following the standardized procedures. Blood pressure (BP) was measured thrice in a seated position with 1 min interval between measurements using a mercury sphygmomanometer. Blood samples were collected in the morning after fasting for at least 8 h. All the plasma and serum samples were frozen at -80 ℃ until their use in the laboratory experiments. Plasma glucose was measured using oxidase enzymatic method.

The triglyceride (TG) levels were quantified and HTG was established according to the criteria defined by the National Cholesterol Education Program (NCEP) Adult Treatment Panel Ⅲ (ATP Ⅲ) that is TG ≥ 1.7 mmol/L.

In this study, all the SNPs were selected based on the criteria of minor allele frequency (MAF) ≥ 0.05 and r² ≥ 0.8 according to the linkage disequilibrium (LD) values obtained using haploview version 4.2 software. The functional SNPs were analyzed by using the websites of selection tool for SNPs and SNPs with predictive biological effects were retuned as tag-SNPs (Supplementary Table S1, available in www.besjournal.com).

The DNA extraction and genotyping were performed by following the previously described method^[3]. (Supplementary Table S2, available in www.besjournal.com)

Linear regression was applied to analyze the association between the gene polymorphisms and HTG risk. The association between the tag-SNPs and HTG risk was analyzed using SNPAssoc package of R. The potential gene-gene interactions among the selected polymorphisms were validated using model-based multifactor dimensionality reduction (MB-MDR) method^[20]. All the statistical analyses were performed using R (X64 3.2.5) and SAS 9.4. P ≤ 0.05 was considered to be statistically significant.

In this study, among the 1, 591 participants 29.4% were identified as HTG patients and 44.4% of these HTG patients were males. The HTG group exhibited a higher systolic BP (SBP) and diastolic BP (DBP), body mass index (BMI), WC, TG, total cholesterol (TC), low-density lipoprotein cholesterol LDL-C, and fast blood glucose (FBG) levels as well as propensity for smoking and drinking than those in the normal-TG group. Contradictorily, the high-density lipoprotein cholesterol (HDL-C) levels in the HTG group were lower than those in the normal-TG group (Table 1).

After adjustment based on the gender, age, BMI, and drinking and smoking propensity, the homozygous wild type A allele (AA, recessive model) of rs13433696 was associated with a decreased HTG risk compared to the carriers of (GA+AA) genotype (difference =-0.186, 95% CI =-0.362 to-0.011, P = 0.038). However, the homozygous wild type C allele (CC, recessive model) of rs5182 was associated with an increased HTG risk compared to the carriers of (TT+TC) genotype (difference = 0.208, 95% CI = 0.001 -0.415, P = 0.049) (Table 2). However, the remaining ten SNPs did not exhibit any association with HTG after the covariates adjustment (Supplementary Tables S3-S4, available in www.besjournal.com). The results of Hardy-Weinberg equilibrium (HWE) test to identify candidate SNPs was presented in Supplementary Table S5 (available in www.besjournal.com).

We observed that 2 to 9-locus models were significantly associated with HTG by quantitative trait that indicated a potential gene-gene interaction among rs5182, rs1492100, rs2972164, rs9817428, rs1175543, rs3856806, rs2920502, rs2638360, and rs12631819 after adjustment for gender, age, drinking and smoking status (Table 3). As rs13433696 in PPARγ as well as rs5182 in AGTR1 were potentially associated with HTG risk, we further analyzed the gene-gene interactions among the remaining ten SNPs using MB-MDR method (Supplementary Table S6, available in www.besjournal.com).

In the present study, our results demonstrated that the AA genotype individuals with rs13433696 in PPARγ exhibited a decreased HTG risk, while the CC genotype individuals with rs5182 in ATGR1 exhibited an increased HTG risk. Furthermore, we observed that the gene-gene interactions existed in the HTG-associated SNPs as well as HTG-non-associated SNPs of PPARγ and AGTR1.

Although the studies that analyzed the association between AGTR1 polymorphisms and risk of HTG are rare, the association between rs5182 SNP and BP was extensively discussed^[4-6]. Additionally, in a case-control study, screening the exon 5 and 3x-untranslated region of ATGR1 demonstrated that solely the +1166 SNP in the 3x-untranslated region was significantly associated with hypertension among the five polymorphisms that are +573 (rs5182), +1062, +1166, +1517, and +1878. Therefore, although our results from the present study suggest that rs5182 in C allele is a risk factor for HTG, further studies are necessary to investigate the functions of ATGR1 polymorphisms.

Our previous studies suggested that PPARγ polymorphisms such as rs3856806 allele are significantly associated with the apoA-I/apoB ratio in the Chinese Han population^[7]. Additionally, Chan et al. found a borderline significant association between the Pro12Ala (rs1801282) variant in PPARγ and risk of T2DM in women's health initiative-observational study (WHI-OS)^[8]. Moreover, the results of a study in Kazakh population suggested that PPARγ polymorphism rs1175543 is significantly associated with metabolic syndromes^[9]. In this study, we reported that a novel variant of AA genotype with rs13433696 in PPARγ is significantly associated with HTG susceptibility indicating that the polymorphisms of PPARγ might play a critical role in dyslipidemia associated diseases.

PPARγ inactivation leads to familial partial lipodystrophy (FPLD) syndrome associated with early-onset severe hypertension^[10]. Considering that PPARγ and AGTR1 are located on the chromosome 3, it is not surprising that the gene-gene interactions exist not only in HTG-associated SNPs but also in HTG-non-associated SNPs.

In conclusion, the present study suggested that the polymorphisms of PPARγ and AGTRI contribute to the HTG risk either independently or in an interactive manner in the Chinese population. Further multiple comprehensive studies must be performed to confirm this genetic association using large sample size and to analyze the probable interactions of these SNPs with other gene variants.