Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0034065 (pulmonary embolism)
 14,979 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5 x 10(-7)) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that approximately 30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another approximately 12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10(-78)) at SNPs clustering near VKORC1 and the second lowest p-values (p<10(-31)) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p = 8.3 x 10(-10)) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.
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PMID:A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. 1930 Apr 99

The objective of our present study was to develop a warfarin dosing algorithm for the Omani patients, as performances of warfarin dosing algorithms vary across populations with impact on the daily maintenance dose. We studied the functional polymorphisms of CYP2C9, CYP4F2 and VKORC1 genes to evaluate their impact on the warfarin maintenance dose in an admixed Omani patient cohort with Caucasian, African and Asian ancestries. We observed a 64-fold inter-patient variability for warfarin to achieve stable international normalized ratio in these patients. Univariate analysis revealed that age, gender, weight, atrial fibrillation, deep vein thrombosis/pulmonary embolism and variant genotypes of CYP2C9 and VKORC1 loci were significantly associated with warfarin dose in the studied patient population. However, multiple regression model showed that only the atrial fibrillation, and homozygous CYP2C9 variant genotypes (*2/*3 and *3/*3) and VKORC1 GA and AA genotypes remained significant. A multivariate model, which included demographic, clinical and pharmacogenetic variables together explained 63% of the overall inter-patient variability in warfarin dose requirement in this microgeographically defined, ethnically admixed Omani patient cohort on warfarin. This locally developed model performed much better than the International Warfarin Pharmacogenetics Consortium (IWPC) model as the latter could only explain 34% of the inter-patient variability in Omani patients. VKORC1 3673G>A polymorphism emerged as the single most important predictor of warfarin dose variability, even in this admixed population (partial R(2)=0.45).
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PMID:Warfarin pharmacogenetics: development of a dosing algorithm for Omani patients. 2285 39