Impact of CYP2C9-Interacting Drugs on Warfarin Pharmacogenomics

Abstract

Precise dosing of warfarin is important to achieve therapeutic benefit without adverse effects. Pharmacogenomics explains some interindividual variability in warfarin response, but less attention has been paid to drug-drug interactions in the context of genetic factors. We investigated retrospectively the combined effects of cytochrome P450 (CYP)2C9 and vitamin K epoxide reductase complex (VKORC)1 genotypes and concurrent exposure to CYP2C9-interacting drugs on long-term measures of warfarin anticoagulation. Study participants predicted to be sensitive responders to warfarin based on CYP2C9 and VKORC1 genotypes, had significantly greater international normalized ratio (INR) variability over time. Participants who were concurrently taking CYP2C9-interacting drugs were found to have greater INR variability and lesser time in therapeutic range. The associations of INR variability with genotype were driven by the subgroup not exposed to interacting drugs, whereas the effect of interacting drug exposure was driven by the subgroup categorized as normal responders. Our findings emphasize the importance of considering drug interactions in pharmacogenomic studies.

Figure 1

Flow diagram illustrating inclusion and exclusion criteria. ^aThe study period is the interval between 30 days after the first warfarin prescription start date and the last warfarin prescription end date. Ninety‐six participants were excluded because there were < 14 international normalized ratio (INR) measurements recorded. Three participants were excluded because genotyping for cytochrome P450 (CYP)2C9 and vitamin K epoxide reductase complex (VKORC)1 was unsuccessful. eMERGE, Electronic Medical Records and Genomics Network; NMEDW, Northwestern Medicine Enterprise Data Warehouse.

Figure 2

Associations of outcome measures with genotype‐predicted warfarin response. Bounds of the box‐and‐whisker plots are discussed in the Methods section. Each P value corresponds to a one‐way analysis of variance test for an international normalized ratio (INR) outcome measure against the three combined cytochrome P450 (CYP)2C9/vitamin K epoxide reductase complex (VKORC)1 genotype‐predicted responder categories (Table 2 ). Post hoc pairwise comparisons were made using Tukey’s HSD. *Indicates a significant pairwise comparison at the P < 0.05 level. HS, highly sensitive; NL, normal; SN, sensitive; TTR, time in therapeutic range.

Figure 3

Associations of outcome measures with cytochrome P450 (CYP)2C9‐interacting drugs. Box‐and‐whisker plots are shown. Each P value corresponds to a one‐way analysis of variance test for an international normalized ratio (INR) outcome measure against the three categories of CYP2C9‐interacting drugs (Table 3 ). Post hoc pairwise comparisons were made using Tukey’s HSD. *Indicates a significant pairwise comparison at the P < 0.05 level. TTR, time in therapeutic range.

Figure 4

International normalized ratio (INR) differences before and after cytochrome P450 (CYP)2C9‐interacting drug exposure. Mean values with 95% confidence intervals are shown superimposed on the individual data. Maximum change in INR refers to the magnitude of maximum perturbation from the baseline INR after initiating an interacting drug. The baseline INR is defined by average INR in a study period prior to exposure to an interacting drug. The maximum perturbation is defined by peak INR after initiation of a CYP2C9 inhibitor, and by trough INR after initiation of a CYP2C9 inducer. Change in average INR refers to the difference between baseline INR as described above and the average INR in a time period shortly after initiation of an interacting drug. Tabulated data are presented in Table S11 . For each listed mean INR difference, the P value corresponds to a t‐test comparing the two sets of INRs included in the difference. *Indicates statistical significance at the P < 0.05 level. AMIO, amiodarone; INB, CYP2C9‐inhibitors; IND, CYP2C9‐inducers; MET, metronidozole; SMX, suflamethoxazole.