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Although multiple reports have documented the influence of CYP2C9 and VKORC1 variantson warfarin dose, risk of over-anticoagulation and hemorrhage, their influence on anticoagulation maintenance and individual proportion of time spent in target INR range (PPTR) is limited. Moreover the potential benefit of genotype-guided dosing implemented after initiation of therapy in a racially diverse population has not been explored. Herein we present the influence of CYP2C9 and VKORC1 C1173T on warfarin response during the first 30 days of therapy.
Warfarin dose was empirically determined in 250 African Americans 271 European Americans. The influence of CYP2C9 and VKORC1 on rate of INR increase, anticoagulation maintenance, risk of over-anticoagulation, and change in dose over 30days was evaluated after adjustment for socio-demographic, lifestyle and clinical factors.
Possession of variant VKORC1 (± variant CYP2C9) genotype was associated with a more rapid attainment of target INR and higher frequency of dose adjustments. Patients possessing variant genotypes spent less time in target range. However adjustment for rate of INR increase rendered the association non-significant. European Americans (but not African Americans) possessing variant VKORC1 (± variant CYP2C9) genotype had a higher risk of over-anticoagulation. Neither CYP2C9 nor VKORC1 influenced the risk of minor hemorrhage. CYP2C9 and VKORC1 explained 6.3% of the variance in dose change over the first 30 days of therapy demonstrating that the usefulness of genotype-guided dosing may extend beyond first day of therapy.
The benefit of genotype-based dose prediction may extend beyond first few days of therapy. Whether genotype-guided dosing will decrease the risk of over-anticoagulation, improve anticoagulation control and most importantly improve outcomes for chronic warfarin users remains to be proven.
Initiation of warfarin therapy in a qualifying patient has long been an iterative process, in which, initially a standard dose is prescribed and then adjusted based on observed response. Recognition and incorporation of the influence of patient-specific factors (e.g. age, weight, medications, etc) has facilitated improvements in estimating dose. However despite these refinements, stabilizing therapy may take weeks to months. Even after stabilization, the International Normalized Ratio (INR) is maintained in target range only 40–60% of the time.[2; 3; 4; 5] Therefore, during the remaining un-protected time periods, especially during initiation of therapy, patients may be at an increased risk of hemorrhagic or thromboembolic complications. [6; 7; 8]
The recognition of genetic control of warfarin response has stimulated efforts to quantify this influence. The significant influence of Cytochrome P4502C9 (CYP2C9, *2 and *3) and Vitamin K epoxide reductase (VKORC1 C1173T and -1639G/A) variants on warfarin dose has been demonstrated in observational studies among patients of European [9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25] and African [26; 27; 28] descent, prospective studies [29; 30] and randomized clinical trials.[31; 32] This evidence served as the main impetus to the recent warfarin package insert update (http://www.fda.gov/cder/drug/infopage/warfarin/default.htm) by the United States Food and Drug Administration (FDA). Although this change may be a sign of personalized medicine making initial steps into the mainstream several key issues including feasibility of implementation, utility and effectiveness of genotype-based therapy in clinical practice need to be addressed. As genotype-based therapy is a fairly recent development, few laboratories provide such services. Therefore the availability of genotype information prior to administration of the first warfarin dose is not feasible for most patients. Delaying initiation of warfarin therapy is not an option as this will likely delay discharge in hospitalized patients, prolong the use of heparins in ambulatory patients and increase healthcare costs. Therefore it is likely that even proponents of genotype-based therapy will initiate warfarin without genotype information.
Although prospective efforts [29; 31; 32] demonstrated the superiority of genotype-based dosing in prediction of warfarin dose, they failed to demonstrate improvement in anticoagulation control. Millican et al and Schwarz et al recently reported on the influence of CYP2C9 and VKORC1 on warfarin response during initiation of therapy in Caucasian cohorts.[29; 33] However the influence of genes on initial warfarin response in a racially diverse population is not well documented and the benefit of genotype-guided dosing implemented a few days after initiation of therapy has not been explored.
Herein we present the influence of CYP2C9 (*2, *3, *5, *6 and *11) and VKORC1 C1173T (hereafter referred to as VKORC1) genotype on warfarin response in both African Americans and European Americans during initiation (first 30 days) of therapy. Specifically we evaluate the influence of CYP2C9 and VKORC1 on the rate of INR increase, percent INRs in target range, and risk of over-anticoagulation. We also evaluate whether implementation of CYP2C9 and VKORC1 genotyping can improve dose refinement by assessing genotype effects on change in warfarin dose over the first 30 days of therapy.
The Pharmacogenetic Optimization of Anticoagulation Therapy (POAT) is an ongoing prospective cohort study aimed at defining the influence of polymorphisms in CYP2C9 and other genes on warfarin response over a 2-year follow-up period. Patients were enrolled from the anticoagulation clinic at The Kirklin Clinics and the Jefferson Clinic P.C., Jefferson County Health System under the approval of the respective Institutional Review Boards. Both clinics follow a standardized empiric approach to manage anticoagulation therapy.
Patients ≥20 years of age were identified at the initiation of warfarin therapy. Patients were considered eligible if the intended duration of anticoagulation therapy was ≥ 2 years, therapy was managed at the anticoagulation clinic and the target INR range was 2–3.
A structured interview form was used at the time of enrollment to obtain a detailed medical lifestyle and concomitant medication history. Information on self-reported race, indication for therapy, demographics, height and weight, medications and co-morbid conditions was documented. Lifestyle and socioeconomic data included smoking, alcohol use, education, annual household income, medical insurance, physical activity, and dietary vitamin K intake. Medical history was then verified by medical records review. All patients were followed at monthly intervals for up to two years from initiation of therapy. At each visit factors influencing warfarin response such as warfarin dose, INR, concurrent medications, dietary vitamin K (number of servings of foods rich in vitamin K consumed per week) alcohol intake (number of alcoholic drinks per week), compliance and level of physical activity were documented. For this study we focused on warfarin response in the first month of therapy.
DNA extraction and genotyping methodology for CYP2C9 and VKORC1 variants were detailed in recent manuscripts.[28; 34] Briefly CYP2C9 genotyping was conducted using pyrosequencing methods and PCR-RFLP methodology. VKORC1 C1173T (rs9934438) genotyping was conducted using the Sequenom iPLEX technology at the Broad Institute (http://www.sequenom.com).
Analysis of variance was used to assess group differences for continuous variables and χ2 test of independence for categorical variables. The assumption of Hardy Weinberg Equilibrium (HWE) was tested using the χ2 test of independence and exact statistics obtained using a Markov Chain Monte Carlo algorithm.  CYP2C9 and VKORC1 genotypes were first categorized into two groups: variant (one or both variant alleles) versus wild-type. The resulting four genotypic groups were; wild-type for both VKORC1 and CYP2C9 (referent group), variant VKORC1 and wild-type CYP2C9, wild-type VKORC1 and variant CYP2C9, and variant VKORC1 and variant CYP2C9 (multiple variants). All multivariable analysis models included genetic (VKORC1 and CYP2C9), socio-demographic, lifestyle and clinical factors (age, race, gender, education, medical insurance, income, alcohol, smoking, compliance, vitamin K intake, comorbid conditions, use of interacting drugs, etc).
Rate of INR increase was calculated for each patient utilizing all INR assessments up to the time at which target INR was first attained. Patients with fewer than three assessments (n=35) prior to attaining target were excluded as a patient specific rate could not be estimated. The influence of CYP2C9 and VKORC1 genotypes on the rate of INR increase, warfarin maintenance dose, and change in dose over the first 30 days (difference in dose = dose on day 30 − dose on day 1) was evaluated using multivariable regression analysis.
We recently reported the influence of CYP2C9 and VKORC1 on attainment of target INR and stable dosing. Herein we assess the influence of CYP2C9 and VKORC1 on anticoagulation control using proportion INRs in range. Computation of this measure encompassed the period of time after attainment of target INR until the completion of 30 days. Proportion of INRs in range was calculated by dividing the number of INR’s within target range by the total number of INR’s during the selected time interval for each patient. Assessing genotypic differences in percent INRs in/below/above range can be misleading as it ignores three vital issues; the influence of socio-demographic, clinical and environmental factors (e.g. drug interactions), the correlation between repeat INR measurements within an individual, and the inequality in the number of INR measurements between patients. To account for this we conducted multivariable analyses using PROC MIXED (SAS version 9.1).
Over-anticoagulation was defined as episodes where the patients INR exceeded four. Hemorrhagic complications were classified as minor or major using the scheme detailed by Fihn et al. Minor hemorrhages included mild nosebleeds, microscopic hematuria, mild bruising, and mild hemorrhoidal bleeding. Serious, life threatening and fatal bleeding episodes were combined into one endpoint; ‘Major hemorrhage’ since these events are infrequent and demand intervention. All major hemorrhagic complications were adjudicated by the Director of the Anticoagulation Clinic blinded to genotype.
In any given patient, INR deviates from target (2.5, range 2–3) over time in response to many independent perturbations. Higher intra-individual variation in INR (due to unobserved/unmeasured factors) may influence (increase) the risk of over-anticoagulation and hemorrhagic complications. To capture its effect we computed a patient-specific variance growth rate (Vscore), a cumulative measure of time-weighted variance of the INR for each time interval (between visits) as proposed by Fihn et al, with minor modification. This measure adjusts for the influence of the number of visits and the interval between visits on INR variation for each patient. The use of the Vscore from the preceding interval accounts for the patient-specific unobserved heterogeneity in the analyses of time to over-anticoagulation.
To assess the risk of over-anticoagulation and hemorrhagic complications the hazard ratio (HR) and 95% CI were obtained using the counting process format in the PH model. This format allows individuals to contribute more than one event. Valid confidence intervals were obtained by correction of dependence using robust variance estimation.[38; 39] These multivariable analyses also included changes in medications, vitamin K and alcohol intake, and Vscore as time-varying covariates. The evaluation of gene-hemorrhage association also included INR at the time of the event. All analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC) at a non-directional alpha level of 0.05.
Patients meeting eligibility criteria between August 2003 and April 2007 (n=621) were asked to participate in the study. Forty-three (6. 9%) patients declined participation. Genotypic, socio-demographic and medical characteristics of the cohort (N=578, 47.2% African American, 51% men) have been detailed in prior publications.[28; 34; 36; 40] Since the purpose of the study was to assess response to warfarin therapy during the first 30 days of therapy, we excluded patients (n=57 due to follow-up duration was <30 days, unavailable data on initial dosing and INR response, and unavailable genotype information). Additionally three Hispanic patients were excluded resulting in a final analyzable cohort of 521 participants. There were no significant differences in age, BMI, indication for therapy, number of comorbid conditions, concurrent medications, and proportion of men, current smokers and insured participants across the four genotype groups (Table 1).
Genotype distributions for CYP2C9 and VKORC1 were in HWE among European Americans (all p-values >0.5) and African Americans (all p-values >0.25). Of the variant CYP2C9 alleles tested only CYP2C9*5, CYP2C9*6, and CYP2C9*11 were observed among African Americans while CYP2C9*2, and CYP2C9*3 were observed among European Americans and African Americans.[28; 34; 36] Variant CYP2C9 genotype was more common among European Americans than among African Americans (33% versus 11%, P<0.0001). European Americans had higher frequency of variant VKORC1 C1173T genotype compared to African Americans (60.4% versus 20.1%, P<0.0001). European Americans had a higher prevalence of multiple variants (i.e. variant CYP2C9 and VKORC1 genotype, Table 1).
The association of warfarin dose on INR increase (Figure 1A) in response to the doses administered (Figure 1B) during initiation of therapy is significantly influenced by CYP2C9 and VKORC1 genotype status. Median time to attain target INR was 9.0 days (Inter-quartile-range- IQR: 4.2–26.4). Attainment of target INR was significantly faster among patients with variant VKORC1 only (median 6.0, IQR 3.4–19.1) and variant CYP2C9 and VKORC1 (median 5.0, IQR 2.5–11.2) compared to those with variant CYP2C9 only (median 12.7, IQR 4.3, 26.3) and no variant CYP2C9 and VKORC1 alleles (median 12.3, IQR 5.7, 31.7, P< 0.0001).
The mean rate of INR increase, 0.12 units per day (median 0.1, inter-quartile range (IQR) 0.03 to 0.19), did not differ across race (P=0.68). The rate of INR increase was significantly influenced by possession of variant CYP2C9 and VKORC1 alleles in univariate and multivariable analyses (p<0.0001, Table 2). Neither socio-demographic factors (age, gender, race, alcohol intake, current smoking, health insurance, income or education; all p-values > 0.15) nor concomitant medications (CYP2C9 inducers, inhibitors or substrates, statins; all p-values >0.5) influenced rate of INR increase. Higher comorbidity (p=0.1), average loading dose (p=0.07) and weight (or BMI, p=0.09) showed marginal statistically significant influence.
As this was an observational study, dose determination was based on demographic and clinical characteristics only with adjustments based on INR assessments without knowledge of patients’ genotype. Initial warfarin doses, determined by the treating physician, reflect varying dosing patterns with 61% patients receiving 5mg (17.5% 2.5mg, 3.5% 7.5mg, 10.5% 10mg and 7.5% other) per day.
Univariate analyses showed strong association between genotype and dose at the time of attainment of first target INR (P=0.002 European Americans, P=0.004 for African Americans) and on Day 30 (P<0.0001 for European and African Americans). Multivariable analyses demonstrated significant influence of variant genotypes in both race-adjusted (all P-values ≤ 0.0004) and race stratified analyses. Adjusted initial dose, mean dose at time of attainment of target INR and mean dose on Day 30 are displayed in Figure 2A stratified by CYP2C9 and VKORC1 genotype status. Among European Americans possession of lone VKORC1 (P<0.0001), lone CYP2C9 (P=0.0004) and VKORC1+CYP2C9 (P<0.0001) variants was associated with significant dose reduction (27%, 26% and 50% respectively). Among African Americans possession of lone VKORC1 (P=0.003) and VKORC1+CYP2C9 (P<0.0001) variants was associated with significant dose reduction (24%, and 80% respectively). Although possession of lone CYP2C9 was associated with a 17% reduction in dose requirement, it did not attain statistical significance (P=0.17). This is consistent with our earlier report.
To assess whether incorporation of genotype information after initiation of therapy would help refine dose adjustments we assessed the influence of CYP2C9 and VKORC1 on dose difference (Day30 dose –Day1 dose). Dose difference was not significantly different among patients possessing lone CYP2C9 variant (p =0.7), marginally significant among those with lone VKORC1 variant (p =0.12) genotype. Among patients with wild-type CYP2C9 and wild-type VKORC1 genotype dose on Day1 was significantly lower (by approximately 0.5 mg/day) than dose required to maintain target INR on Day30. Among patients with variant CYP2C9 and variant VKORC1 genotype dose on Day1 was significantly higher by approximately 2.0 mg/day) than dose required to maintain target INR (Figure 2B, Table 3) on Day 30. These differences were consistent across race and remained significant after adjustment for other covariates (p<0.0001) with VKORC1 and CYP2C9 explaining 6.3% (P<0.0001) of the variance in dose difference (Day30 dose −Day1 dose).
In the first 30 days, patients possessing variant in both CYP2C9 and VKORC1 and those possessing lone VKORC1 variants had a higher frequency of clinic visits and more frequent dose adjustments (Table 4). Among patients with no variants 54% of adjustments required a decrease in dose while 46% required dose increment. Dose adjustments more often involved dose decrement among patients with variant VKORC1 (80%), CYP2C9 (67%) and variant VKORC1+CYP2C9 (89%)genotypes.
After attainment of first target INR, percent INRs in target range (for the remainder of the 30 days) was higher among patients with no variants compared to those possessing variant CYP2C9, variant VKORC1 and variant VKORC1+CYP2C9 genotypes (P=0.026, Table 4). This finding, influenced more so by the presence of VKORC1 variants (P=0.02) than presence of CYP2C9 variant (p=0.84), remained consistent after adjusting other covariates (P=0.038). The absence of dose change between visits was a significant predictor (p<0.0001) of maintenance of INR in target range. Although patients with any variant (CYP2C9, or VKORC1, or both) had a high frequency of INRs above target range (INR >3, P=0.016) the association was not statistically significant (P=0.16) in multivariable analyses.
Since warfarin dosing patterns differed significantly across patients, we recognize that the rate of INR increase (time to target INR) may be influenced by doses administered in the first few days. This in turn may have influenced percent INRs in range after attainment of therapeutic anticoagulation. For example a patient may receive 10 mg/day while another (with the same genotypic and clinical characteristics) may receive 5.0 mg/day for the first two days. Although the 10mg/day dose can shorten the time to attain target INR the maintenance of target INR may differ compared to 5mg/day dose. Therefore time to attainment of target INR may be an independent predictor of maintenance of therapeutic anticoagulation. Moreover the different times to attain target INR would result in different length of observation period thereby allowing more or less opportunity for INR deviation from target range. Therefore we reassessed the gene-percent-INR after incorporating time to attainment of target INR as a predictor in the multivariable model. Patients who attained target INR in less than 5 days were significantly more likely to have INR<2 (p=0.02), less likely to maintain INR in target range (p=0.0002) and more likely to have INR>3 (p=0.04). The influence of CYP2C9 and VKORC1 was not statistically significant (all p-values ≥0.12).
One hundred and fifty eight episodes (6.0% of all INR measurements) of over–anticoagulation were encountered in 124 patients during the first 30 days of therapy. Over-anticoagulation was less frequent among patients with no variants compared to those possessing variant CYP2C9, variant VKORC1 and variant VKORC1+CYP2C9 genotypes (P<0.0001, Table 4) with VKORC1 variants (P<0.0001) showing a stronger influence than CYP2C9 variant (P=0.04).
The frequency of over-anticoagulation was higher in European Americans (98 episodes in 78 patients) than African Americans (60 episodes in 46 patients, P=0.017) but did not differ across gender (P=0.53). The frequency of over-anticoagulation did differ by genotype groups among European Americans (P=0.0016) but not among African Americans (P=0.33). However within African Americans (P=0.08) and European Americans (P=0.0003) over-anticoagulation was more frequent among patients with variant VKORC1 genotype (Table 5). Therefore we present results of both race-adjusted and race-stratified analyses.
In multivariable analyses, after adjusting for race, possession of variant VKORC1 (P=0.003) or variant VKORC1 +CYP2C9 (P=0.0008) genotype increased the risk of over-anticoagulation while possession of lone CYP2C9 variant (P=0.41) did not (Table 5). Race-stratified analyses indicate statistically significant influence of VKORC1 variants among European Americans (P<0.01, Figure 3A) but not in African Americans (P>0.3, Figure 3B). Possession of lone CYP2C9 variant has a marginally significant effect among European Americans (P=0.12) but not among African Americans (P=0.87).
Thirty-seven minor hemorrhages were encountered in 28 patients during the first month. There was no difference in occurrence of minor hemorrhages across race (p=0.41). Neither CYP2C9 nor VKORC1 influenced the risk of minor hemorrhage (Table 5, all P-values >0.35). Race stratified analyses could not be conducted due to the limited number of event during the 30 day study period. The association of CYP2C9 and VKORC1 could not be evaluated as only two major hemorrhages were encountered during the first 30 days.
Our prospectively ascertained cohort study demonstrates the influence of VKORC1 and CYP2C9 on warfarin dose among both African Americans and European Americans. Consistent with prior reports possession of VKORC1 variant was associated with significant dose reduction in both race groups whereas possession of CYP2C9 variant was associated with statistically significant dose reduction only among European Americans.[27; 36] Recent studies have demonstrated that pre-prescription genotype-based dosing significantly improves dose prediction.[31; 32; 41] This study, by assessing the influence of these genes on dose change over the first 30 days, demonstrates that the usefulness of genotype-based dose prediction may extend beyond the first day of initiation of therapy even with standard empiric dosing.
Among patients who possessed sole VKORC1 or CYP2C9 variants initial dose based on clinical and demographic characteristics were close approximations of dose on Day 30. Patients with no variant alleles and those that possessed both variant VKORC1 and CYP2C9 required significant dose adjustments over the 30 day study period. Dose prediction in these groups (comprising 60% of the cohort) could potentially be refined further by implementation of genotype-based dosing. This is consistent with the report by Anderson et al who identified 55.6% of the cohort (wild-type for VKORC1 and CYP2C9 and those with multiple variants) that can potentially benefit from genotype-guided therapy. These findings have several significant implications for assessing the utility and cost effectiveness of genotype based therapy. First, consistent with the recent report by Anderson et al, genotype-guided therapy will improve dose prediction for a significant proportion (>50%) of warfarin users. Second, as reported by Millican et al  genotype-based dose refinement may be beneficial even if implemented after the administration of clinically-determined dose for the first few days. The recent report by Schwarz et al  indicates that both the CYP2C9 and VKORC1 had a significant influence on the required warfarin dose after the first 2 weeks of therapy. This latter finding, by allowing a more feasible genotyping time-frame, may facilitate implementation of such therapy in clinical practice. Incorporation of genotype information to determine warfarin dose can be facilitated through nomograms. One such dosing nomogram can be assessed at www.warfarindosing.org.
We demonstrate the larger influence of VKORC1 in attaining target INR. In the first 30 days of therapy, possession of variant VKORC1 was also associated with poor anticoagulation control (both percent INRs and percent time spent in target range) in multivariable analyses. However, incorporation of rate of target INR attainment rendered these associations statistically non-significant. These findings are consistent with the findings of a recent randomized clinical trail by Anderson et al who concluded that pharmacogenetically guided therapy did not improve time spent within target INR range. 
Our results with regard to the rate of target INR attainment are consistent with those of Schwarz et al  but discordant with regard to percent INR in target range. The latter difference may be due to the differences in populations studied, the number and nature of covariates and the adjustment for time to attain target INR in our analyses. The influence of rate of INR attainment on quality of anticoagulation control needs to be assessed further. This constellation of findings suggests that genotype-guided therapy (by improved dose prediction) may allow the attainment of target INR at a rate that may favor improved maintenance of therapeutic anticoagulation.
Among Europeans, Schalekamp et al reported an increased risk of over-anticoagulation (INR>6) among phenprocoumon users possessing variant CYP2C9 and/or variant VKORC1 genotype and among acenocoumarol users possessing both variant CYP2C9 and variant VKORC1 genotype. Schelleman et al, Kealey et al and Schwarz et al also reported a significantly increased risk of over-anticoagulation (INR>4) among European American warfarin users possessing variant VKORC1 genotype after adjustment for CYP2C9 and clinical covariates.[26; 27; 33] Our findings among European Americans concur with these earlier reports. The differences in risk ratios among European American populations in our study and prior studies may perhaps be explained by the number and nature of clinical covariates and the inclusion of a measure of intra-patient variability in INR (unobserved heterogeneity) in our analyses. Inability to account for such heterogeneity has been recognized as a limitation by several investigators. [27; 44] Our results provide evidence that the gene-over-anticoagulation association is independent of such heterogeneity. The recent prospective randomized study by Anderson et al confirms these gene-over-anticoagulation associations with the excess risk of over-anticoagulation driven mainly by the concurrent possession of CYP2C9 and VKORC1 variants. 
Despite the lower frequency of variant genotypes and episodes of over-anticoagulation, the marginally significant VKORC1 effect among African Americans (p=0.08) in our cohort suggests that effect of VKORC1 variants is similar across race groups. However as reported by Schelleman et al the association of VKORC1 on risk of over-anticoagulation among African Americans was not significant in multivariable analyses. Although we cannot explain the differential influence of variant VKORC1 and CYP2C9 on risk of over-anticoagulation across race groups, we can speculate on the influence and interplay of various factors:
To our knowledge, our cohort represents the largest population of African Americans genotyped for CYP2C9 and VKORC1. Inclusion of the *5, *6 and *11 variants in the genotyping provides a robust estimate of the CYP2C9 allele frequencies in this previously underrepresented racial group. We did not assess the -1639G/A polymorphism (rs9923231) as studies have demonstrated that the 1173C and -1639G allele are in linkage disequilibrium among both African Americans and European Americans. We also recognize our sample-size was inadequate to detect significant CYP2C9-VKORC1 interaction in either race group. Documentation of vitamin K intake was based on patient report using vitamin K inventory and was not quantified by assay/measurements. However, all measurements were used consistently; therefore, bias if any should be non-differential. We recognize that many factors including changes in vitamin K intake can contribute to INR fluctuation.[46; 47] The inclusion of the Vscore potentially accounts for the changes in unmeasured/unobserved environmental influences. We assessed the influence of only two genes (CYP2C9 and VKORC1) and recognize that other genes may influence warfarin response or modify the effect of these genes. ApoE has recently been shown to influence warfarin dose among African Americans.[48; 49] Other genes such as gamma-glutamyl carboxylase,[15; 21; 50; 51; 52] calumenin,[50; 53] epoxide hydroxylase[23; 53] may influence warfarin dose in this race group. However, the extent to which variability in other genes in the warfarin pathways influences warfarin response is yet to be resolved.
The benefit of genotype-based dose prediction may extend beyond first few days of therapy. Incorporation of genotype information after a few doses will allow enough time for offsite genotyping, avoid delaying initiation of therapy and make implementation of this technology more feasible in clinical practice. Whether genotype-guided dosing will decrease the risk of over-anticoagulation, improve anticoagulation control and most importantly improve outcomes for chronic warfarin users remains to be proven.
The authors thank Joyce Blaisdell for her work with CYP2C9 genotyping. We are grateful to all the patients that participated in the study. We thank Janice Ware for her untiring efforts with patient recruitment and the staff of the Anticoagulation Clinic at The Kirklin Clinic, the Cooper Green Hospital and Jefferson Clinic P.C for their help with identification of potential participants. We also thank the physicians, especially Drs. Mark Wilson, and Melissa Baird; at the University of Alabama at Birmingham and the Health Service Foundation for their support of this research. Thanks to Steve Duncan and Darlene Green and the Office of Data Resources for their work with the POAT database and quality assurance.
This work was supported in part by a grants from the National Heart Lung and Blood Institute (RO1HL092173) and the National Institute of Neurological Disorders and Stroke (K23NS45598) and in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences.
The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278-01 from the National Center for Research Resources.
Supported in part by a grants from the National Heart Lung and Blood Institute (RO1HL092173) and the National Institute of Neurological Disorders and Stroke (K23NS45598) and in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences
This study has contributed samples to the NINDS Human Genetics Resource Center DNA and Cell Line Repository (http://ccr.coriell.org/ninds), NINDS Repository sample numbers corresponding to the samples used are ND04466, ND04556, ND04604, ND04605, ND04626, ND04869, ND04907, ND04934, ND04951, ND05036, ND05108, ND05175, ND05176, ND05239, ND05605, ND05606, ND05701, ND05702, ND05735, ND06147, ND06207, ND06385, ND06424, ND06480, ND06706, ND06814, ND06871, ND06983, ND07057, ND07234, ND07304, ND07494, ND07602, ND07711, ND07712, ND08065, ND08596, ND08864, ND08932, ND09079, ND09172, ND09760, ND09761, ND09809.
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