Human liver microsomal metabolism of the enantiomers of warfarin and acenocoumarol: P450 isozyme diversity determines the differences in their pharmacokinetics

Abstract

1 To explain the large differences in (the stereoselectivity of) the clearances of the enantiomers of warfarin and acenocoumarol (4'-nitrowarfarin) their human liver microsomal metabolism has been studied and enzyme kinetic parameters determined. The effects of cimetidine, propafenone, sulphaphenazole, and omeprazole on their metabolism has been investigated. 2 The 4-hydroxycoumarins follow similar metabolic routes and are mainly hydroxylated at the 6-and 7-position (accounting for 63 to 99% of the metabolic clearances).3 Due to the lower Km values of R-and S-acenocoumarol and higher Vma. values of S-acenocoumarol, the overall metabolic clearances of R/S acenocoumarol exceed those of R/S warfarin 6 and 66 times respectively. 4 The metabolism of both compounds is stereoselective for the S-enantiomers, which is 10 times more pronounced in the case of acenocoumarol.5 Except for the 7-hydroxylation of the R-enantiomers (r = 0.90; P <0.025), the 6-and 7-hydroxylation rates of R/S warfarin do not correlate with those of R/S acenocoumarol. 6 Sulphaphenazole competitively inhibits the 7-and in some samples partly (up to 50%) the 6-hydroxylation of S-warfarin as well as the 7-hydroxylation of R-and S-acenocoumarol and the 6-hydroxylation of S-acenocoumarol (Kis ranging from 0.5-1.3 JAM).7 Omeprazole partly (40-80%) inhibits the 6-and 7-hydroxylation of R-warfarin (Ki = 99 and 117 pM) and of R-(Ki = 219 and 7.2 jAM) and S-acenocoumarol (Ki = 6.1 and 7.7 JiM) but not S-warfarin in a competitive manner. 8 Differences in the partial (up to 40%) inhibition of the metabolism of the enantiomers of the 4-hydroxycoumarins were also observed for the relatively weak inhibitors, propafenone and cimetidine. 9 The results suggest that the coumarin ring hydroxylations of both compounds are catalysed by different combinations of P450 isozymes. The 7-hydroxylation of R/S acenocoumarol and the 6-hydroxylation of S-acenocoumarol are at least partly conducted by (a) P450 isozyme(s) of the 2C subfamily different from P450 2C9 (the main S-warfarin 7-and 6-hydroxylase).

Main comedications associated with major bleeding during anticoagulant therapy with coumarins

“…The difference in structure of acenocoumarol and phenprocoumon, although small, may have implications on the relative contribution of CYP enzymes to their metabolism [6]. Therefore, the risk of bleeding associated with the start of inhibitors of CYP1A2, 2C19, and 2C9 possibly differs with the type of anticoagulant used.…”

“…First, pharmacodynamic interactions with one anticoagulant may well apply to another anticoagulant [18]. Second, PIDs that interact by inhibiting CYP2C9 will affect both acenocoumarol and warfarin [6]. Third, PIDs that do not influence the intensity of the anticoagulant effect of coumarin anticoagulants, but increase the risk of bleeding by interfering with hemostasis or by their ulcerogenic effect, will exert their effect regardless of the type of coumarin used.…”

Lack of Effect of Gemifloxacin on the Steady-State Pharmacodynamics of Warfarin in Healthy Volunteers

“…In addition, warfarin is eliminated almost entirely by hepatic metabolism, mainly through cytochrome P450 isoenzymes. S-warfarin is hydroxylated by CYP2C9, whereas R-warfarin is metabolized mainly through the CYP1A2 enzyme [2]. As the S-enantiomer is the more potent of the two, interactions with the CYP2C9 isoenzyme may result in a clinically significant interaction [3].…”

VKORC1 and CYP2C9 genotypic data-based dose prediction alone does not accurately predict warfarin dose requirements in some Malaysian patients

“…Research has shown that cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex 1 (VKORC1) gene polymorphisms are significantly associated with warfarin sensitivity (2)(3)(4)(5), including among Asian patients. Several dosing guidelines and algorithms based on genetic data have been proposed in response to reports that the addition of genetic data into a nongenetic dosing model may increase the predictability of the model by up to 16% (6)(7)(8)(9).…”