| Objective:Hyperuricemia(HUA) not only induces uric acid kidney disease and gouty arthritis and kidney stones and gout, but can occur accompanying obesity diabetes and dyslipidemia and hypertension. We aim to explore the related risk factors and prevalence of metabolic disorders in Uyghur of Xinjiang province, probing into the relationship of uric acid and related metabolic diseases. The transport and excretion play the most important role in occurrence of hyperuricemia. Here, we explored polymorphism the genes (SLC17A1、SLC22A11、SLC16A9) encode proteins related to passive transporters and exchangers and give a light on genetic and environmental factors function in occurrence and development of hyperuricemia. The evidence this study provide may used for formulating preventive policy.Method:1. This hospital-based case-control study was been conducted at the First Affiliated Hospital of Xinjiang Medical University and the First People Hospital of Kashgar from July,2011to September2013. Patients whose SUA concentration above the criteria attended case group.For the control group, subjects who were enrolled for general health screening and SUA concentration were normal attended control group. Totally the study sample was2214, among which1031entered case group and1027control group. Participants completed a lifestyle and medical history questionnaire and had their blood pressure measured, and blood and urine samples taken. Also, the prevalence of metabolic diseases was estimated in different races, ages, and gender.2. The15SNP s of the3genes were genotyped by Sequenom MassARRAY of USA according to iPLEX Gold Application Guide. The Hardy-Weinberg equilibrium(HWE) was assessed using chi-square analysis. There were no significant deviations from HWE both in case and control groups (P>0.05) The characteristics of the study population were expressed as the mean±standard deviation or as a ratio. Correlation of HUA and demographic and biochemical characterizations was analyzed by SHEsis and SPSS18.0. General linear model analysis was undertaken to test for associations between SNP genotypes Participants completed a lifestyle and medical history questionnaire and had their blood pressure measured, and blood and urine samples taken.3. Crossover analysis was applied in gene-environmental and gene-gene interaction studies. Based on PCA (principal component analysis) and GMDR(generalized multifactor dimensionality reduction), we conducted reduction dimension strategy to find interaction of the SNP s of the three genes(SLC17A1, SLC22A11, SLC16A9) and HUA.Results:1.①The current prevalence of metabolic syndrome and HUA was31.6%8.2%. As the uric acid level elevating, the number of Coronary atherosclerotie heart disease (CAD)、hyperglycemia. hypertension、central obesity, dyslipidemia got larger. Blood pressure. FPG. glycosylated hemoglobin、TC、TG、Apo-A, LDL-c,BMI and WHR were getting higher along with elevating serum uric acid, while HDL-c lower in the meantime.②The HUA relevance ratio went down when the component of metabolic disease accumulated (Χ2=222.84, P<0.001). Along with HUA concentration increased, MS relevance ratio also went up (Χ2=317.99, P<0.001).③The results multiplicative Logistic regression analysis showed, the ORs with sort descending were WHR7.639(95%CI1.744-33.466). CAD2.784(95%CI1.718-4.510). HUA2.155(95%CI1.457-3.188). smoking1.437(95%CI1.071-1.927)、MS family history1.333(95%CI1.044-1.703)、work stress1.290(95%CI1.021-1.631), BMI1.146(95%CI1.112-1.181); work-out, less salt-intake were protective factors with OR0.472(95%CI0.370-0.604)and0.793(95%CI0.662-0.949).④The adjusted results of HUA risk factors corrected by ages, gender、level of education、origins showed alcohol drinking、work stress、smoking, hypertension were risk factors with OR1.366(95%CI1.123-1.663),1.136(95%CI0.795-0.922),1.727(95%CI1.496-1.966),1.669(95%CI1.129-2.466) respectively.2.1n case control study①The value of BMI, waistline, systolic blood pressure(SBP),Fasting Plasma Glucose(FPG), TG of case group were all higher than control group, while TC、HDL-c, LDL-c lower than control group(P<0.05);②There was positive correlation relationship between HUA and BMI. waistline、FPG、TG; and negative correlation relationship was found between HUA and HDL-C in Uyghur male. In Uyghur female positive correlation relationship was found between HUA and waistline. SBP、FPG, TG and negative between HUA and TC、HDL-C、DBP、SBP (P<0.05);③The prevalence of obesity、hypertension、hyperglycemia hypertrigliceridemia、low HDL-cemia、hyperlipemia, metabolic syndrome of case group were all higher than control group, the difference were significant (P<0.05). The relevance ratio of HUA went up along with metabolic disorder scores increasing;④In terms of the7SNP s of SLC17A1association was observed between CT genotype of rs-9467596and HUA, and it could increase the risk of HUA (OR=1.334,95%CI=1.082～1.644). GA of rs3923was also a risk genotype of HUA (OR=1.339,95%CI=1.092～1.643). TA of rs1179086has higher risk of HUA compared with TT of it (OR=1.246,95%CI=1.020～1.523). TC genotype of rs2096386increased the risk of HUA (OR=1.242,95%CI=1.015～1.51). All above indicate rs9467596、rs3923、 rs1179086, rs2096386were significantly associated with HUA (P<0.05).⑤In terms of the4SNP s of SLC22A11, A allele of rs1783811of case group significantly increased the risk of HUA compared with control group (Χ2=4.787, P=0.029), indicating polymorphism of rs1783811associated with HUA.⑥In term of rs1171614of SLC16A9of case group, AG and AA genotype both could increased the risk of HUA group obviously with OR=1.991,95%CI(1.032-3.842); OR=1.37,95%CI (0.694-2.705), TT and CT genotype of rs4948351have high risk of HUA compared with control group with OR=1.453,95%C/(1.079-1.957)、OR=1.53,95%CI (1.007-1.818).Significant different was observed in genotype of frequency between case and control(P=0.034),rs1171614and rs4948351were associated with HUA.⑦The results of Logistic regression revealed that hypertension, hyperglycemia, dyslipidemia, hyperuricemia mutation of rs9467596risk factors, the OR values were4.016(95%CI to1.984-8.129),2.448(95%CI1.143-5.242),12.576(95%CI1.576-10.346),1.623(95%CI1.132-3.599),2.936(95%CI1.014-8.503),9.050(95%CI4.151-19.733),3.429(95%CI1.566-7.507); and rs1783811were protective factors of hyperuricemia, its OR value was0.312(95%CI,0.113-0.862),(P<0.05).3.The further analysis was done to the second part study and the results showed①Association was observed between SLC16A9-rs117614(P=0.008) SLC17A1-rs946759(P=0.018) and HUA based on PAC logistic regression. After extracting6principle component to construct Conditional Logistic regression model, the result showed all six model had significant association with HUA.②In terms of SLC16A9and SLC17A1, two significant interaction were screened by crossover analysis. They are SLC16A9-rs1171614with SLC17A1-rs1179086(U=2.301, P<0.05)in additive model and SLC16A9-rs1171614with SLC17Al-rs2096386(U=2.341, P<0.05) in multiplicative model. While SLC16A9with SLC22A11no significant interaction was observed by2×4crossover analysis. However, significant interaction was observed between SLC17A1with SLC22A11by2×4the same way as before, the result showing SLC17A1-rs9467596with SLC22A11-rs1783811interaction with ORint=1.13(P<0.05). In gene-environment interaction analysis, there were significant positive interaction between SLC16A9-rs1171614and smoking(OR>1, P<0.05) in multiplicative model. Same happened on SLC17A1-rs1179806(ORint=1.50,P<0.05), SLC17A1-rs2096386(ORint=1.21, P<0.05) with alcohol drinking with OR>1.③The results of GMDR showed3factors (SLC17A1-rs1165196, SLC16A9-177604, SLC16A9-rs2242206) model could be the best of gene-gene analysis because of higher cross-validation consistency and accuracy of test sample. The best model of gene-environment of GMDR was SLC17A1-rs1165196and smoking and alcohol drinking model.Conclusion:1.As the uric acid level elevating, the number of Coronary atherosclerotie heart disease(CAD)、hyperglycemia、hypertension central obesity、 dyslipidemia got larger. Blood pressure、FPG、glycosylated hemoglobin、TC、TG、 Apo-A、LDL-C, BMI and WHR were getting higher along with elevating serum uric acid, while HDL-C lower in the meantime. Alcohol drinking, work stress, smoking, hypertension were risk factors.2. The mutation of rs9467596、rs3923、rs1179086、rs2096386SLC17A1, rs1783811in SLC22A11and rs1171614、rs4948351in SLC16A9associated with HUA3.Association was observed between SLC16A9-rs117614(P=0.008)、 SLC17A1-rs946759(P=0.018) and HUA based on PAC logistic regression. After extracting6principle component to construct Conditional Logistic regression model, the result showed all six model had significant association with HUA. By crossover analysis SLC16A9-rs1171614with SLC17A1-rs1179086(U=2.301, P<0.05) in additive model and SLC16A9-rs1171614with SLC17A1-rs2096386(U=2.341, P<0.05)in multiplicative model were significant interacted. Significant positive interaction between SLC17A1-rs9467596with SLC22A11-rsl783811was observed by2x4crossover analysis, the result showing interaction with ORint=1.013(P<0.05). There were significant positive interaction between SLC16A9-rs1171614and smoking in multiplicative model;Same things happened on SLC17A1-rs1179806, SLC17Al-rs2096386with alcohol drinking with. The results of GMDR showed3factors (SLC17A1-rs1165196, SLC16A9-177604, SLC16A9-rs2242206)model could be the best of gene-gene analysis because of higher cross-validation consistency and accuracy of test sample. The best model of gene-environment of GMDR was SLC17A1-rs1165196and smoking and alcohol drinking model, This study also confirmed the close relationship between the SLC16A9、SLC17A1、SLC22A11genes and the pathogenesis of HUA. |
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