Niclas Eriksson

Estimation of the warfarin dose with clinical and pharmacogenetic data.

BACKGROUND Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base. METHODS Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators. RESULTS In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm (49.4% vs. 33.3%, P<0.001, among patients requiring < or = 21 mg per week; and 24.8% vs. 7.2%, P<0.001, among those requiring > or = 49 mg per week). CONCLUSIONS The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.

A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose.

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<1.5×10−7) 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 ∼30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another ∼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 = 8.3×10−10) 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.

A Randomized Trial of Genotype-Guided Dosing of Warfarin

BACKGROUND The level of anticoagulation in response to a fixed-dose regimen of warfarin is difficult to predict during the initiation of therapy. We prospectively compared the effect of genotype-guided dosing with that of standard dosing on anticoagulation control in patients starting warfarin therapy. METHODS We conducted a multicenter, randomized, controlled trial involving patients with atrial fibrillation or venous thromboembolism. Genotyping for CYP2C9*2, CYP2C9*3, and VKORC1 (-1639G→A) was performed with the use of a point-of-care test. For patients assigned to the genotype-guided group, warfarin doses were prescribed according to pharmacogenetic-based algorithms for the first 5 days. Patients in the control (standard dosing) group received a 3-day loading-dose regimen. After the initiation period, the treatment of all patients was managed according to routine clinical practice. The primary outcome measure was the percentage of time in the therapeutic range of 2.0 to 3.0 for the international normalized ratio (INR) during the first 12 weeks after warfarin initiation. RESULTS A total of 455 patients were recruited, with 227 randomly assigned to the genotype-guided group and 228 assigned to the control group. The mean percentage of time in the therapeutic range was 67.4% in the genotype-guided group as compared with 60.3% in the control group (adjusted difference, 7.0 percentage points; 95% confidence interval, 3.3 to 10.6; P<0.001). There were significantly fewer incidences of excessive anticoagulation (INR ≥4.0) in the genotype-guided group. The median time to reach a therapeutic INR was 21 days in the genotype-guided group as compared with 29 days in the control group (P<0.001). CONCLUSIONS Pharmacogenetic-based dosing was associated with a higher percentage of time in the therapeutic INR range than was standard dosing during the initiation of warfarin therapy. (Funded by the European Commission Seventh Framework Programme and others; ClinicalTrials.gov number, NCT01119300.).

The largest prospective warfarin-treated cohort supports genetic forecasting

Genetic variants of cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose, but the effect of other genes has not been fully elucidated. We genotyped 183 polymorphisms in 29 candidate genes in 1496 Swedish patients starting warfarin treatment, and tested for association with response. CYP2C9*2 and *3 explained 12% (P = 6.63 x 10(-34)) of the variation in warfarin dose, while a single VKORC1 SNP explained 30% (P = 9.82 x 10(-100)). No SNP outside the CYP2C gene cluster and VKORC1 regions was significantly associated with dose after correction for multiple testing. During initiation of therapy, homozygosity for CYP2C9 and VKORC1 variant alleles increased the risk of over-anticoagulation, hazard ratios 21.84 (95% CI 9.46; 50.42) and 4.56 (95% CI 2.85; 7.30), respectively. One of 8 patients with CYP2C9*3/*3 (12.5%) experienced severe bleeding during the first month compared with 0.27% of other patients (P = .066). A multiple regression model using the predictors CYP2C9, VKORC1, age, sex, and druginteractions explained 59% of the variance in warfarin dose, and 53% in an independent sample of 181 Swedish individuals. In conclusion, CYP2C9 and VKORC1 significantly influenced warfarin dose and predicted individuals predisposed to unstable anticoagulation. Our results strongly support that initiation of warfarin guided by pharmacogenetics would improve clinical outcome.

Common VKORC1 and GGCX polymorphisms associated with warfarin dose

We report a novel combination of factors that explains almost 60% of variable response to warfarin. Warfarin is a widely used anticoagulant, which acts through interference with vitamin K epoxide reductase that is encoded by VKORC1. In the next step of the vitamin K cycle, gamma-glutamyl carboxylase encoded by GGCX uses reduced vitamin K to activate clotting factors. We genotyped 201 warfarin-treated patients for common polymorphisms in VKORC1 and GGCX. All the five VKORC1 single-nucleotide polymorphisms covary significantly with warfarin dose, and explain 29–30% of variance in dose. Thus, VKORC1 has a larger impact than cytochrome P450 2C9, which explains 12% of variance in dose. In addition, one GGCX SNP showed a small but significant effect on warfarin dose. Incorrect dosage, especially during the initial phase of treatment, carries a high risk of either severe bleeding or failure to prevent thromboembolism. Genotype-based dose predictions may in future enable personalised drug treatment from the start of warfarin therapy.

Warfarin pharmacogenetics: a single VKORC1 polymorphism is predictive of dose across 3 racial groups

Warfarin-dosing algorithms incorporating CYP2C9 and VKORC1 -1639G>A improve dose prediction compared with algorithms based solely on clinical and demographic factors. However, these algorithms better capture dose variability among whites than Asians or blacks. Herein, we evaluate whether other VKORC1 polymorphisms and haplotypes explain additional variation in warfarin dose beyond that explained by VKORC1 -1639G>A among Asians (n = 1103), blacks (n = 670), and whites (n = 3113). Participants were recruited from 11 countries as part of the International Warfarin Pharmacogenetics Consortium effort. Evaluation of the effects of individual VKORC1 single nucleotide polymorphisms (SNPs) and haplotypes on warfarin dose used both univariate and multi variable linear regression. VKORC1 -1639G>A and 1173C>T individually explained the greatest variance in dose in all 3 racial groups. Incorporation of additional VKORC1 SNPs or haplotypes did not further improve dose prediction. VKORC1 explained greater variability in dose among whites than blacks and Asians. Differences in the percentage of variance in dose explained by VKORC1 across race were largely accounted for by the frequency of the -1639A (or 1173T) allele. Thus, clinicians should recognize that, although at a population level, the contribution of VKORC1 toward dose requirements is higher in whites than in nonwhites; genotype predicts similar dose requirements across racial groups.

Anticoagulation control in Sweden: reports of time in therapeutic range, major bleeding, and thrombo-embolic complications from the national quality registry AuriculA

AIMS In anticoagulation treatment with warfarin, the risk of thrombo-embolic events must be weighed against the risk of bleeding. Time in therapeutic range (TTR) is an important tool to assess the quality of anticoagulation treatment, and has been shown to correlate with less bleeding and thrombo-embolic complications. AuriculA, the Swedish national quality registry for atrial fibrillation and anticoagulation, is used for follow-up and dosage control of warfarin. This is the first report of TTR in AuriculA and, in a subgroup of two centres, bleeding and thrombo-embolic complications during 2008. METHODS AND RESULTS Prothrombin complex (International normalized ratio) values from 18 391 patients in 67 different centres were analysed. The mean (SD) age was 70 (12) years. The main indications for warfarin treatment were: atrial fibrillation (64%), venous thromboembolism (19%), and heart valve dysfunction (13%). Time in therapeutic range for all patients was 76.2%. The mean weekly dose of warfarin decreased with age and TTR increased with age. In 4273 patients from two centres in AuriculA, the frequency of major bleedings and venous/arterial thrombo-embolism were 2.6 and 1.7% and for atrial fibrillation, 2.6 and 1.4%, per treatment year, respectively. A correlation between age and the risk of major bleeding (P< 0.001), but not thrombo-embolic complications (P= 0.147), was seen. CONCLUSION Compared with prospective randomized trials of warfarin treatment, TTR in the AuriculA population was higher. Complications were low, probably due to the organization of anticoagulation treatment in Sweden. Use of the AuriculA dosing programme could have contributed to the results by keeping dosing regimens consistent over all centres.

Integration of genetic, clinical, and INR data to refine warfarin dosing

Well‐characterized genes that affect warfarin metabolism (cytochrome P450 (CYP) 2C9) and sensitivity (vitamin K epoxide reductase complex 1 (VKORC1)) explain one‐third of the variability in therapeutic dose before the international normalized ratio (INR) is measured. To determine genotypic relevance after INR becomes available, we derived clinical and pharmacogenetic refinement algorithms on the basis of INR values (on day 4 or 5 of therapy), clinical factors, and genotype. After adjusting for INR, CYP2C9 and VKORC1 genotypes remained significant predictors (P < 0.001) of warfarin dose. The clinical algorithm had an R2 of 48% (median absolute error (MAE): 7.0 mg/week) and the pharmacogenetic algorithm had an R2 of 63% (MAE: 5.5 mg/week) in the derivation set (N = 969). In independent validation sets, the R2 was 26–43% with the clinical algorithm and 42–58% when genotype was added (P = 0.002). After several days of therapy, a pharmacogenetic algorithm estimates the therapeutic warfarin dose more accurately than one using clinical factors and INR response alone.

Genetic Determinants of Dabigatran Plasma Levels and Their Relation to Bleeding

Background— Fixed-dose unmonitored treatment with dabigatran etexilate is effective and has a favorable safety profile in the prevention of stroke in atrial fibrillation patients compared with warfarin. We hypothesized that genetic variants could contribute to interindividual variability in blood concentrations of the active metabolite of dabigatran etexilate and influence the safety and efficacy of dabigatran. Methods and Results— We successfully conducted a genome-wide association study in 2944 Randomized Evaluation of Long-term Anticoagulation Therapy (RE-LY) participants. The CES1 single-nucleotide polymorphism rs2244613 was associated with trough concentrations, and the ABCB1 single-nucleotide polymorphism rs4148738 and the CES1 single-nucleotide polymorphism rs8192935 were associated with peak concentrations at genome-wide significance (P<9×10−8) with a gene-dose effect. Each minor allele of the CES1 single-nucleotide polymorphism rs2244613 was associated with lower trough concentrations (15% decrease per allele; 95% confidence interval, 10–19; P=1.2×10−8) and a lower risk of any bleeding (odds ratio, 0.67; 95% confidence interval, 0.55–0.82; P=7×10−5) in dabigatran-treated participants, with a consistent but nonsignificant lower risk of major bleeding (odds ratio, 0.66; 95% confidence interval, 0.43–1.01). The interaction between treatment (warfarin versus all dabigatran) and carrier status was statistically significant (P=0.002), with carriers having less bleeding with dabigatran than warfarin (hazard ratio, 0.59; 95% confidence interval, 0.46–0.76; P=5.2×10−5) in contrast to no difference in noncarriers (hazard ratio, 0.96; 95% confidence interval, 0.81–1.14; P=0.65). There was no association with ischemic events, and neither rs4148738 nor rs8192935 was associated with bleeding or ischemic events. Conclusions— Genome-wide association analysis identified that carriage of the CES1 rs2244613 minor allele occurred in 32.8% of patients in RE-LY and was associated with lower exposure to active dabigatran metabolite. The presence of the polymorphism was associated with a lower risk of bleeding. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00262600.

Prediction of warfarin dose: why, when and how?

Prediction models are the key to individualized drug therapy. Warfarin is a typical example of where pharmacogenetics could help the individual patient by modeling the dose, based on clinical factors and genetic variation in CYP2C9 and VKORC1. Clinical studies aiming to show whether pharmacogenetic warfarin dose predictions are superior to conventional initiation of warfarin are now underway. This review provides a broad view over the field of warfarin pharmacogenetics from basic knowledge about the drug, how it is monitored, factors affecting dose requirement, prediction models in general and different types of prediction models for warfarin dosing.