A Molecular Epidemiology Study On The Association Of PPARγ And RXRα Genes Joint-action And The Susceptibility Of Metabolic Syndrome

The metabolic syndrome (MetS) is a set of aggregation onset obesity, high bloodsugar (diabetes), or glucose regulation abnormalities, dyslipidemia (high triglyceridesand (or) low high-density lipoprotein cholesterol) and high blood pressure, impact onhuman health seriously. Along with the development of our country’s economy, people’sliving standards improved, lifestyle changed, so that the prevalence of metabolicsyndrome is on the rise. According to preliminary statistics, the prevalence of MetS areas high as14%~18%in China and in patients with diabetes are as high as60%~80%[1]. MetS is more harmful, susceptibility to diabetes in patients with metabolicsyndrome is four times to the normal and two times for the susceptibility tocardiovascular disease [2].Epidemiological and clinical research showed that eachcomponent of MetS is risk factor for cardiovascular disease, patients with multipleanomalies occur to a greater risk of cardiovascular disease.The current view is that metabolic syndrome is a disease caused by the combinedeffects of multiple genes and multiple environmental factors, Insulin resistance (IR) isthe common incidence basis of a series of metabolic abnormalities. Obesity, geneticabnormalities, antagonistic hormones, drugs, and many other factors can lead to IR,however obesity especially central obesity is initiating reason caused by IR. Centralobesity is made by the accumulation of abdominal adipose tissue. Adipose tissue is notonly a tissue which stores excess energy, but also an endocrine tissue regulating themetabolism. Adiponectin, which is secreted by adipose tissue, has been confirmed to associate with MetS closely. The level of serum adiponectin is influenced not only bythe adiponectin gene polymorphisms, but also by the relevant regulatory genes. Thecurrent views have identified a functional PPAR-responsive element (PPRE) in humanadiponectin promoter in the promoter region of ADIPOQ encoding gene. PPARγ/RXRheterodimer which directly bound to the functional PPAR-responsive element (PPRE)could increase the human adiponectin promoter activity in cells. The genes codingPPARγ and RXRα located in the adiponectin pathway are therefore candidates forMetS and insulin resistance by its phenotype (plasma adiponectin). In this study, weadopted a case-control study design and used Realtime PCR methods andTaqman-MGB probe technology simultaneously. We chose both tags Singlenucleotide polymorphisms and the potential functional SNPs as the SNPs choicestrategy. We aimed to investigate the association of PPARγ and RXRα genespolymorphisms and the susceptibility of MetS, and the joint-action of genetic andenvironmental factors with the risk for MetS in southeast Han population of China.Part â… Genetic variants in PPARγ and RXRα gene and metabolicsyndrome riskIn this study, we conducted a case-control study aiming to investigate theassociation of PPARγ and RXRα genes polymorphisms and the susceptibility of MetSin southeast Han population of China. We tested four SNPs of PPARγ gene and fiveof RXRα gene in MetS patients (n=1012) and normal controls (n=1069). Associationsbetween genotypes and MetS risk (ORs and95%CI) were estimated by logisticregressions. The main results were as follows:1. The distribution in cases and controls of SNPs of PPARγWe analyzed four SNPs of PPARγ. After adjustment for age, sex, smoking, drinkingand physical activity, the variant of rs1801282（Câ†'G）was positively associated withrisk of MetS. Compared with the wild-type homozygote, the variant genotype ofrs1801282GG was associated with higher MetS risk [adjusted Ors (95%CI)=2.50(1.02-6.11)]. All the significances remained after the1000permutation test. The distribution of rs1801282C/G was significantly different in cases and controls(P<0.05). No evidence suggested other three SNPs were associated with MetS.2. The distribution in cases and controls of SNPs of RXRαWe analyzed five SNPs of RXRα. After adjustment for age, sex, smoking, drinkingand physical activity, the variant of rs3132291（Tâ†'C）was negatively associated withrisk of MetS. Compared with the wild-type homozygote TT, the variants genotypes ofrs3132291TC, CC and TC/CC were associated with lower MetS risk respectively[adjusted Ors (95%CI)=0.72(0.53-0.99),0.80(0.65-0.98),0.78(0.65-0.95)]. All thesignificances remained after the1000permutation test. The distribution of rs3132291T/C was significantly different in cases and controls (P=0.020). No evidencesuggested rs6537944, rs4240711, rs4842194and rs1045570SNPs were associatedwith MetS.3. Comparison of serum levels of adiponecin in SNPs genotypes of PPARγ and RXRαIn the MetS group, compared with rs1801282CC wild-type genotype, there was ahigher adiponectin level with homozygous rs1801282GG and CG/GG genotype(P=0.010,0.024). Compared with rs3132291TT wild-type genotype, there was ahigher adiponectin level with homozygous rs3132291CT, CC and CT/CC genotype(P=0.013,0.039,0.010).4. Haplotype analysis of PPARγ and RXRαHaplotype analysis of three potential functional SNPs of PPARγ indicated,compared with the most common haplotype CGC, no haplotypes showed anysusceptibility associated with MetS. Haplotype analysis of two tag SNPs indicated,compared with the most common haplotype AC, no haplotypes showed anysusceptibility associated with MetS.Haplotype analysis of four potential functional SNPs of RXRα indicated, afteradjustment for age, sex, smoking, drinking and physical activity, haplotype GCGC,with variant allele rs3132291C, rs4240711G, rs4842194C, could reduce the risk ofMetS compared with the most common haplotype GTAT [OR(95%CI)=0.79(0.65-0.96)]. Other haplotypes showed no such effect in haplotype analysis oftwo tag SNPs. Part â…¡Gene joint-action between PPARγ and RXRα gene andmetabolic syndromeIn this study, we use BPANN methods combined with multiple logistic regressionanalysis, and compared with the results of MDR and GMDR methods, to explore thegene joint-action between PPAR-γ and RXR-α gene with metabolic syndrome risk insoutheast Chinese Han population.1. Multiple logistic regression analysis for the associations between the related factorsand MetSIn multiple logistic regression analysis, with stepwise regressive method,6variables were into the model, including diabetes family history, hyperlipidemiafamily history, physical activity, gender, BMI and serum adiponectin.2. BPANN multiple analysis for the associations between the related factors and MetSUsing the19related factors as input variables and MetS diagnosis as outputvariables, we established BPANN model with all available samples. The transferfunction was logsig function. Learning rate was0.1. Training error was0.01.Maximum training steps set to1000steps. After the termination of training, the MIVwas obtained. And then according to the absolute value of MIV, we sequenced therelated factors in the order of BMI, serum adiponectin, rs4240711, gender, rs4842194,diabetes family history, rs2920502, physical activity, drinking and rs3856806whichwere the top ten factors.3. Gene joint-action between PPARγ and RXRα geneAll of nine SNPs in two genes were analyzed by the MDR method. The resultsshowed four models were all not statistically significant (P>0.05). Then, four SNPswhich located in the top ten in BPANN multiple analysis were analyzed by the MDRmethod. The results showed X1X2X3X4(rs2920502, rs4240711, rs4842194,rs3856806)model was the best model (Cross-validation consistency10/10, P=0.0447).Furthermore, after taking age, sex, smoking, drinking and physical activity asenvironment adjustment factors into the GMDR analysis, the results showed X1X2X3 X4(rs2920502,rs4240711,rs4842194, rs3856806)was the best model(Cross-validationconsistency10/10，P=0.0107). Four SNPs in the model were from two genes, thissuggested that there may be a joint-action between PPARγ and RXRα genes in thepathogenesis of MetS.