| Background :Warfarin is currently widely used in the clinical anticoagulation treatment of artificial mechanical valve replacement,atrial fibrillation,atrial thrombus,cardiogenic stroke,deep vein thrombosis of the lower extremity,pulmonary embolism and other related diseases.However,the narrow therapeutic window and varying safety and efficacy in individuals make dose determination difficult.It may cause adverse events such as haemorrhage or thromboembolism,When the drug dosage is not selected properly.In recent years,although there are many new oral anticoagulant drugs(such as rivashaban and dabigatran)appling in clinic,warfarin is still the irreplaceable standard drug for oral anticoagulant treatment after artificial valve replacement.At the present stage,most domestic medical institutions adopt the fixed-dose administration mode,which is based on the international standardized ratio(INR)to guide the adjustment of drug dosage.This mode has low safety and serious adverse consequences.Precise individualized treatment needs to be further studied.It was reported that single nucleotide polymorphisms(SNP),such as Vitamin K epoxide reductase complex 1(VKORC1),Cytochrome P450 2C9(CYP2C9),Cytochrome P450 1A2(CYP1A2),γ-Glutamyl carboxylase(GGCX)and Uridine diphosphate glucuronate transferase 1A1(UGT1A1),have been shown to significantly affect warfarin dosage toleration and this effect varies among different populations.However,most of studies didn’t confirm the genotype-based algorithms,or others who establish the mathematic models were basing on one to three genes,which presented lower predicted percentage.Hence,we will detect a series of related gene polymorphisms of warfarin,and use the Multiple linear regression(MLR)to proceeding our large sample case-control study,basing on preliminary work.Then the new model,established by the MLR,will be verified.This study will provide the more predictive algorithms of warfarin dose variability and improve the security of anticoagulant therapy.Part 1: Effects of genetic variables and clinical data variables on the stable treatment dose of warfarin in Chinese Jiangxi populationObjectives:To evaluate the effects of VKORC1,CYP2C9,CYP1A2,GGCX and UGT1A1 gene polymorphisms and clinical data such as height,weight,sex,body surface area,medication history,and history of thrombosis on the stable treatment dose of warfarin in Chinese Jiangxi population.Methods:Clinical data of 476 patients who had been treated with artificial mechanical valve replacement in the Second Affiliated Hospital of Nanchang University were tracked and recorded in detail,including height,weight,body surface area,age,sex,combined medication,past history,INR value and daily dose of warfarin.The gene polymorphisms of VKORC1(rs9923231,rs9934438,rs7196161,and rs7294),CYP2C9(rs1057910),CYP1A2(rs2069514),GGCX(rs699664),and UGT1A1(rs887829)were determined by using the Sanger sequencing.Single factor linear regression was used to analyze the effects of various genetic and clinical variables on the daily stable dose of warfarin.Results:Single factor regression analysis revealed that VKORC1(rs9923231,rs9934438,rs7196161,and rs7294),CYP2C9(rs1057910),GGCX(rs699664),age,height,weight,body surface area,and amiodarone had statistically significant effects on daily stable dose of warfarin,while CYP1A2(rs2069514),UGT1A1(rs887829),gender,history of thrombosis,hypertension,diabetes,smoking history,ACEI and betaloc had no effect on the stable therapeutic dose of warfarin.Conclusion:1.Polymorphisms of VKORC1(rs9923231,rs9934438,rs7196161 and rs7294),CYP2C9(rs1057910)and GGCX(rs699664)genes may have an important impact on the stable treatment dose of warfarin in Jiangxi population of China.2.The stable dose of warfarin may not be affected by CYP1A2(rs2069514)and UGT1A1(rs887829)gene polymorphisms in Chinese Jiangxi population.Part 2: Establish and verify a prediction model of warfarin administration for Chinese Jiangxi population based on genetic and clinical variablesObjectives:To establish a warfarin dose prediction model for patients after prosthetic mechanical valve replacement for Chinese Jiangxi population in combination with clinical and genetic variables,improving the accuracy and ideal prediction percentage of the model.Methods:Based on the genetic data and clinical variable data obtained from part 1,Multiple linear regressions were used to analyse contribution of the gene polymorphisms and the clinical data variables,the variables which caused multicollinearity from screened stepwise were excluded,aiming to establish an algorithm model for predicting the daily maintenance dose of warfarin.The ideal prediction percentage of the model is calculated through the validation,and the value is used to test the clinical utility.Results:Eventually,a total of 395 patients were included in the deduction and validation of the model.The new algorithm model established based on multiple linear regression was as follows: Y=1.081-0.011(age)+1.532(BSA)-0.807(rs9923231AA)+1.788(rs9923231 GG)+ 0.530(rs1057910 AA)-1.061(rs1057910 AG)-0.321(rs699664 AA).The model accounted for 61.7% of individualised medication differences,with an ideal prediction percentage of 69%.Conclusion:1.To avoid resource waste,the sequencing of VKORC1 rs9923231,rs9934438,rs7196161,and rs7294 simultaneously is not recommended,because of the strong Linkage disequilibrium.2.GGCX(rs699664)may be a potential predictor of warfarin dose in Chinese Jiangxi population.3.The newly established model in this study is expected to guide the individualised use of warfarin in clinical practice in Chinese Jiangxi population. |
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