CYP2C9

The CYP2C family of enzymes is the second most abundant of the CYP enzymes represented in the hepatocyte. The commonest is CYP3A4/5. Correspondingly they are also the second most important enzymes involved in drug metabolism.

There are 4 members of this family, 2C8, 2C9, 2C19 and 2C18, whose genes are all located on chromosome 10. The 2 members of this family that are of greatest importance for us are CYP2C9 and CYP2C10. CYP2C8 came into prominence initially in an association with the cerivastatin induced rhabdomyolysis and later in association with irinotecan metabolism. There has not been a lot of discussions about it lately because of the limited range of substrates linked with it. There is also little known about drug substrates associated with CYP2C18.

CYP2C9, originally known as tolbutamide hydroxylase, has been shown to be involved extensively in the metabolism of many pharmaceuticals. Of topical interest is its involvement with the metabolism with warfarin, particularly the S-isomer.

The Pharmacogenomics Journal (2005) 5, 193–202

The S:R isomeric ration of warfarin concentrations is routinely used as a convenient way of phenotyping the 2C9 activity. The common loss of function genetic variants are the *2 and *3 variants. These variants are much more common among Caucasian populations as compared to East Asians, e.g. Chinese, Japanese and Koreans. In Singapore, the ethnic group which had the highest frequencies of the *2 and *3 variants are the Indians, who had similar frequencies to the Caucasian populations.

CYP2C19 is much more of a preoccupation for us as the *2 and *3 variants are much more common among Chinese than Caucasians. The *2 alleleic variants is particularly common at about 25%. The CYP2C19 was earlier known by the original studied substrate, mephenytoin hydroxylase. The CYP2C19 genetic polymorphism has been discussed largely because if the association of the enzyme with the metabolism of proton pump inhibitors, and lately with the

antiplatelet drug clopidogrel.

Comparison of prasugrel 60 mg and clopidogrel 600 mg loading dose exposure of active metabolite by CYP2C19 genetic classification. Box represents median, 25th, and 75th percentiles and whiskers represent the most extreme values within 1.5 times inter-quartile range of the box. AUC, area under the concentration–time curve; EM, extensive metabolizer; RM, reduced metabolizer.

Eur Heart J (2009) 30 (14): 1744-1752

Warfarin - variability in response

Frequency distribution of warfarin daily dose requirement

Pharmacogenomics. 2009, 10 (12) :1955-1965

Warfarin presents a very good case study with respect to drug response variability, and the management of the uncertainty that surrounds the therapeutic use of warfarin.

Warfarin inhibits the reductase that recycles warfarin epoxide (Vit K epoxide reductase C1) so that it can be used again in the production of the Vit K dependent clotting factors. Conceptually very simple, but a number of things complicate this schematic. Firstly warfarin is optically active, and the two isomers, R and S warfarin, have different potencies and PK characteristics. The S warfarin has 5 times the potency of R warfarin and so often has been taken to represent the active ingredient of racemic warfarin. This is a convenient over-simplification, and it is by no means true that all warfarin activity is accounted for by only the S isomer. This is further

complicated by the fact that the isomers are metabolized preferentially by different CYP450 enzymes and have different elimination halflives.

S warfarin has quite a long halflife - an average of 40 hours. In some individuals it may be up to or longer than 60 hours. This means that after initiation of dosing, S warfarin doesn't achieve steady-state concentrations until about a week of dosing. Using a loading dose will get you closer to the steady-state concentrations, but will still need 5 halflives to settle into 'steady-state'. To make it worse, this does not even mean that warfarin's anticoagulant effects stabilize after one week. In fact the anticoagulant effects are not just dependent on warfarin kinetics but also on the kinetics of the clotting factors, which have their own halflives of elimination. This means that after warfarin steady-state is reached, some more time is required for the clotting factors, and consequently the fully anticoagulant effect, to settle into 'steady-state'. Simulations suggest that the whole process of anticoagulation may take up to about 2 weeks to reach steady-state.

Practically this means that the sooner you can settle into the correct maintenance dose, the sooner the patient will be at a stable level of anticoagulation. Every time you tweak the dose, it will require another 2 weeks to settle down. This makes dosage optimization particularly problematic.

The main sources of variability for warfarin response may be anticipated to relate to the following:

a] body weight

b] diet (Vit K supply, inhibitors.inducers of CYP enzymes),

c] smoking

d] genetics of CYP enzymes

-particularly CYP2C9 for S-warfarin, but cannot ignore other CYP enzymes involved with R warfarin.

e] genetics of CYP4F2 involved in breakdown of Vit K

f] genetics of Vit epoxide reductase complex 1 (VKORC1)

g] drug interaction with CYP enzymes

What saves the situation for warfarin is that it has an excellent direct measurement of drug response, - the INR (International Normalized Ratio) which directly measures the state of anticoagulation produced by warfarin. The INR allows a very convenient way to adjust warfarin dosages according to a 'target' level of response. This is called a target response strategy. For warfarin, drug level monitoring is of little use because of i) the delay in response because of the clotting factors halflives, ii) the presence of 2 active warfarin isomers, and iii) because there are different sensitivities to warfarin effects because of genetic variants affecting VKORC1.

Though the INR is a useful 'direct' measure of warfarin response, it is in reality only a 'surrogate' measure of the true warfarin efficacy, which is the eventual effect warfarin has in reducing morbidity and mortality associated with thromboembolism, strokes etc. These can only be assessed through monitoring therapeutic outcomes. However, these outcome measures, do not help us in the day to day optimization of the patient's warfarin dose.

CYP4F2

The CYP4F2 is involved in the synthesis of a number of sterols and lipids. Because it was involved in the production of 20-hydroxyeicosatetraenoic acid (20-HETE), it was postulated to be involved in the pathophysiology of hypertension. It is now thought to be also involved in the breakdown of Vit K1. Correspondingly, the V433M variant is thought to result in decreased breakdown of VitK1 and an leading an excess of VitK1, leading to relative warfarin resistance. Recent studies have suggested that the polymorphism contributes 1-2% of the variability in warfarin dosage requirements.

The frequency of the polymorphism in Caucasians and 'Asians' is approximately 30%. There isn't any more specific population frequencies than these, and I have no breakdown of Chinese, Malay and Indian frequncies.

Rat poison and the F1 driver - the warfarin story

The anticoagulant warfarin actually started life as rat poison. Chemically, it is derived from a natural plant product, coumarin. The way it acts is by inhibiting the enzyme Vitamin K epoxide reductase, and in so doing reduce formation of various Vit K dependent clotting factors.

So what's the deal about F1 drivers?

Well... like F1 drivers, the physician using warfarin needs to keep his eye on the road. Too little warfarin, and there is inadequate therapeutic anticoagulation; too much warfarin and the patient may suffer a catastrophic bleed. Fortunately, he has a way to do this. The Prothrombin Time and other derived measures such as the International Normalized Ratio (INR) provide a heads up to the physician about how much anticoagulation has been provided for the patient. By keeping his eye on the INR, the physician can adjust the dose of warfarin to provide just the right range on anticoagulation the patient needs. This is important, because the warfarin requirements for every patient differ, and the warfarin dose needs to be 'individualized'.

More recently, various other biomarkers enable the physician to make educated guesses about the dosage requirement for the patient. These are genetic markers related to the rate of metabolic degradation of warfarin through cytochrome P450 2C9 (not many such problems in our Chinese population) and the genetically reduced sensitivity of the Vitamin K epoxide reductase C1 subunit (VKORC1). However, using these genetic biomarkers only provide an improved starting dose. Once the race car engine starts, the F1 driver will still have to manage the therapeutic process through keeping a close eye on the INR.

There have been many discussions about the genotyping of patients prior to dosing with warfarin. I have no doubt to its usefulness in helping us to understand the patient a lot better. But becasue there is already a good efficacy marker (the INR) for us to titrate the patients dosing against, the improved starting point may only be of theoretical benefit. I think most of the benefit will come in situations when you need to deliver very fast anticoagulation. Where time is not on an essence, genotyping would likely not be a cost effective option.

Highlighted report: Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose

Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose: a prospective study in Chinese patients.

Huang, Sheng-Wen, Chen, Hai-Sheng, Wang, Xian-Qun, Huang, Ling, Xu, Ding-Li, Hu, Xiao-Jia, Huang, Zhi-Hui, He, Yong, Chen, Kai-Ming, Xiang, Dao-Kang, Zou, Xiao-Ming, Li, Qiang, Ma, Li-Qin, Wang, Hao-Fei, Chen, Bao-Lin, Li, Liang, Jia, Yan-Kai, Xu, Xiang-Min

Objectives: To develop a warfarin-dosing algorithm that could be combined with pharmacogenomic and demographic factors, and to evaluate its effectiveness in a randomized prospective controlled clinical trial.

Methods: A pharmacogenetics-based dosing model was derived using retrospective data from 266 Chinese patients and multiple linear regression analysis. To prospectively validate this model, 156 patients with an operation of heart valve replacement were enrolled and randomly assigned to the group of pharmacogenetics-guided or traditional dosing for warfarin therapy. All patients were followed up for 50 days after initiation of warfarin therapy. The log-rank test was compared with the time-to-event (Kaplan-Meier) curves. Cox proportional hazards-regression model was used to assess the hazard ratio of the time to reach stable dose.

Results: The linear regression model derived from the pharmacogenomic model correlated with 54.1% of warfarin dosing variance. The final multiple linear regression model included age, body surface area, VKORC1, and CYP2C9 genotype. The study showed that the hazard ratio for the time to reach stable dose was 1.932 for the traditional dosing group versus the model-based group and a close and highly significant relationship was observed to exist between the predicted and the actual warfarin dose (R2=0.454).

Conclusion: A pharmacogenetics-based dosing algorithm has been developed for improvement in the time to reach the stable dosing of warfarin. This model may be useful in helping the clinicians to prescribe warfarin with greater safety and efficiency.

See also:

Estimation of the Warfarin Dose with Clinical and Pharmacogenetic Data.
The International Warfarin Pharmacogenetics Consortium.

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,>/=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.

Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation.
Eckman MH, Rosand J, Greenberg SM, Gage BF.
University of Cincinnati Medical Center, Cincinnati, OH 45267-0535, USA. mark.eckman@uc.edu

BACKGROUND: Variants in genes involved in warfarin metabolism and sensitivity affect individual warfarin requirements and the risk for bleeding. Testing for these variant alleles might allow more personalized dosing of warfarin during the induction phase. In 2007, the U.S. Food and Drug Administration changed the labeling for warfarin (Coumadin, Bristol-Myers Squibb, Princeton, New Jersey), suggesting that clinicians consider genetic testing before initiating therapy. OBJECTIVE: To examine the cost-effectiveness of genotype-guided dosing versus standard induction of warfarin therapy for patients with nonvalvular atrial fibrillation. DESIGN: Markov state transition decision model. DATA SOURCES: MEDLINE searches and bibliographies from relevant articles of literature published in English. TARGET POPULATION: Outpatients or inpatients requiring initiation of warfarin therapy. The base case was a man age 69 years with newly diagnosed nonvalvular atrial fibrillation and no contraindications to warfarin therapy. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTION: Genotype-guided dosing consisting of genotyping for CYP2C9*2, CYP2C9*3, and/or VKORC1 versus standard warfarin induction. OUTCOME MEASURES: Effectiveness was measured in quality-adjusted life-years (QALYs), and costs were in 2007 U.S. dollars. RESULTS: In the base case, genotype-guided dosing resulted in better outcomes, but at a relatively high cost. Overall, the marginal cost-effectiveness of testing exceeded $170 000 per QALY. On the basis of current data and cost of testing (about $400), there is only a 10% chance that genotype-guided dosing is likely to be cost-effective (that is, <$50 000 per QALY). Sensitivity analyses revealed that for genetic testing to cost less than $50 000 per QALY, it would have to be restricted to patients at high risk for hemorrhage or meet the following optimistic criteria: prevent greater than 32% of major bleeding events, be available within 24 hours, and cost less than $200. LIMITATION: Few published studies describe the effect of genotype-guided dosing on major bleeding events, and although these studies show a trend toward decreased bleeding, the results are not statistically significant. CONCLUSION: Warfarin-related genotyping is unlikely to be cost-effective for typical patients with nonvalvular atrial fibrillation, but may be cost-effective in patients at high risk for hemorrhage who are starting warfarin therapy.