Influence of CYP2C9, VKORC1, and CYP4F2 polymorphisms on the pharmacodynamic parameters of warfarin: a cross-sectional study

Association between gene polymorphisms and initial warfarin therapy in patients after heart valve surgery

BACKGROUND

Warfarin is widely used for the prevention and treatment of thrombotic events. This study aimed to examine the influence of gene polymorphisms on the early stage of warfarin therapy in patients following heart valve surgery.

METHODS

Nine single nucleotide polymorphisms were genotyped using microarray chips, categorizing patients into three groups: normal responders (Group I), sensitive responders (Group II), and highly sensitive responders (Group III). The primary clinical outcomes examined were time in therapeutic range (TTR) and international normalized ratio (INR) variability. To investigate potential influencing factors, a generalized linear regression model was employed.

RESULTS

Among 734 patients, the prevalence of CYP2C9*3-1075A > C, CYP2C19*3-636G > A, and CYP2C19*17-806C > T variants were 11.2%, 9.9%, and 1.9% of patients, respectively. VKORC1-1639G > A or the linked -1173C > T variant was observed in 99.0% of the patients. Generalized linear model analysis revealed an impact of sensitivity grouping on INR variability. Compared to Group I, Group II showed higher TTR values (p = 0.023), while INR variability was poorer in Group II (p < 0.001) and Group III (p < 0.001). Individual gene analysis identified significant associations between CYP2C9*3-1075A > C (p < 0.001), VKORC1-1639G > A or the linked -1173 C > T (p = 0.009) and GGCX-3261G > A (p = 0.019) with INR variability.

CONCLUSION

The genotypes of CYP2C9, VKORC1, and GGCX were found to have a significant impact on INR variability during the initial phase of warfarin therapy. However, no significant association was observed between TTR and gene polymorphisms. These findings suggest that focusing on INR variability is crucial in clinical practice, and preoperative detection of gene polymorphisms should be considered to assist in the initiation of warfarin therapy.

Functional Characterization of 29 Cytochrome P450 4F2 Variants Identified in a Population of 8380 Japanese Subjects and Assessment of Arachidonic Acid ω-Hydroxylation

Cytochrome P450 4F2 (CYP4F2) is an enzyme that is involved in the metabolism of arachidonic acid (AA), vitamin E and K, and xenobiotics including drugs. CYP4F2*3 polymorphism (rs2108622; c.1297G>A; p.Val433Met) has been associated with hypertension, ischemic stroke, and variation in the effectiveness of the anticoagulant drug warfarin. In this study, we characterized wild-type CYP4F2 and 28 CYP4F2 variants, including a Val433Met substitution, detected in 8380 Japanese subjects. The CYP4F2 variants were heterologously expressed in 293FT cells to measure the concentrations of CYP4F2 variant holoenzymes using carbon monoxide-reduced difference spectroscopy, where the wild type and 18 holoenzyme variants showed a peak at 450 nm. Kinetic parameters [Vmax , substrate concentration producing half of Vmax (S50 ), and intrinsic clearance (CL int ) as Vmax /S50 ] of AA ω-hydroxylation were determined for the wild type and 21 variants with enzyme activity. Compared with the wild type, two variants showed significantly decreased CL int values for AA ω-hydroxylation. The values for seven variants could not be determined because no enzymatic activity was detected at the highest substrate concentration used. Three-dimensional structural modeling was performed to determine the reason for reduced enzymatic activity of the CYP4F2 variants. Our findings contribute to a better understanding of CYP4F2 variant-associated diseases and possible future therapeutic strategies. SIGNIFICANCE STATEMENT: CYP4F2 is involved in the metabolism of arachidonic acid and vitamin K, and CYP4F2*3 polymorphisms have been associated with hypertension and variation in the effectiveness of the anticoagulant drug warfarin. This study presents a functional analysis of 28 CYP4F2 variants identified in Japanese subjects, demonstrating that seven gene polymorphisms cause loss of CYP4F2 function, and proposes structural changes that lead to altered function.

Evaluation of a warfarin dosing algorithm including CYP2C9, VKORC1, and CYP4F2 polymorphisms and non-genetic determinants for the Iranian population

BACKGROUND

The response to warfarin, as an oral anticoagulant agent, varies widely among patients from different ethnic groups. In this study, we tried to ascertain and determine the relationship between non-genetic factors and genetic polymorphisms with warfarin therapy; we then proposed a new warfarin dosing prediction algorithm for the estimation of drug sensitivity and resistance in the Iranian population.

METHODS

Overall, 200 warfarin-treated patients with stable doses were recruited, the demographic and clinical characteristics were documented, and genotyping was done using a sequencing assay.

RESULTS

The outcomes of our investigation showed that the genetic polymorphisms of VKORC1(-1639 G > A), CYP2C9*3, CYP2C9*2, amiodarone use, and increasing age were found to be related to a significantly lower mean daily warfarin dose. In contrast, the CYP4F2*3 variant and increased body surface area were linked with an increased dose of warfarin in the Iranians. Our descriptive model could describe 56.5% of the variability in response to warfarin. This population-specific dosing model performed slightly better than other previously published warfarin algorithms for our patient's series. Furthermore, our findings provided the suggestion that incorporating the CYP4F2*3 variant into the dosing algorithm could result in a more precise calculation of warfarin dose requirements in the Iranian population.

CONCLUSIONS

We proposed and validated a population-specific dosing algorithm based on genetic and non-genetic determinants for Iranian patients and evaluated its performance. Accordingly, by using this newly developed algorithm, prescribers could make more informed decisions regarding the treatment of Iranian patients with warfarin.

Warfarin-Rifampin-Gene (WARIF-G) Interaction: A Retrospective, Genetic, Case-Control Study

Warfarin is extensively metabolized by cytochrome P450 2C9 (CYP2C9). Concomitant use with the potent CYP2C9 inducer, rifampin, requires close monitoring and dosage adjustments. Although, in theory, warfarin dose increase should overcome this interaction, most reported cases over the last 50 years have not responded even to high warfarin doses, but some have responded to modest doses. To investigate the genetic polymorphisms' impact on this unexplained interpatient variability, we performed genotyping of CYP2C9, VKORC1, and CYP4F2 for warfarin and rifampin concomitant receivers from 2016 to 2022 at Hamad Medical Corporation, Doha, Qatar. We identified and included 36 patients: 22 responders and 14 nonresponders. Warfarin-responders were significantly more likely to have one or more warfarin-sensitizing CYP2C9/VKORC1 alleles than nonresponders (odds ratio = 23.2, 95% confidence interval = 3.2-195.6; P = 0.0001). The mean genetic-based pre-interaction calculated dose was significantly lower for responders than for nonresponders (P < 0.001); and was negatively correlated with warfarin sensitivity index (WSI) (r = -0.58; P = 0.0002). The median percentage time in therapeutic range and mean WSI were significantly higher in the warfarin-sensitizing CYP2C9/VKORC1 alleles carriers than noncarriers (P = 0.017 and 0.0004, respectively). Whereas the warfarin-sensitizing CYP2C9/VKORC1 genotypes were associated with modest on-rifampin warfarin dose requirements, the noncarriers would have required more than double these doses to respond. Warfarin-sensitizing CYP2C9/VKORC1 genotypes and low genetic-based warfarin calculated doses were associated with higher warfarin sensitivity and better anticoagulation quality in patients receiving rifampin concomitantly.

Evaluation of supervised machine learning algorithms in predicting the poor anticoagulation control and stable weekly doses of warfarin

BACKGROUND

Machine learning algorithms (MLAs) carry a huge potential in identifying predicting factors and are being explored for their utility in the field of personalized medicine.

AIM

We aimed to investigate MLAs for identifying predictors (clinical and genetic) of poor anticoagulation status (ACS) and stable weekly warfarin dose (SWWD).

METHOD

Clinical factors, in addition to the CYP2C9, VKORC1, and CYP4F2 genotypes, were obtained for patients receiving warfarin for at least the previous six months. The C5.0 decision tree classification algorithm was used to predict poor ACS while classification and regression tree analysis (CART), in addition to the Chi-square automatic interaction detector (CHAID), was used to predict SWWD. The percentage of patients within 20% of the actual dose, root mean squared error (RMSE), and area under the receiver-operating characteristics curve (AUROC) were identified as performance indicators of the models.

RESULTS

In the C5.0 classification decision tree, the CYP4F2 genotype was the strongest predictor of ACS (AUROC = 0.53). In the CART analysis of SWWD, VKORC1 polymorphisms were the most significant predictor, followed by the CYP2C9 genotype (percentage of patients within 20% of the actual dose = 38.2%, RMSE = 13.6). For the CHAID algorithm, the percentage of patients within 20% of the actual dose was 49%, while the RMSE was found to be 13.4.

CONCLUSION

Genetic and non-genetic predictive factors were identified by the MLAs for ACS and SWWD. Further, the need to externally validate the MLAs in a prospective study was highlighted.

Polymorphisms in common antihypertensive targets: Pharmacogenomic implications for the treatment of cardiovascular disease

The idea of personalized medicine came to fruition with sequencing the human genome; however, aside from a few cases, the genetic revolution has yet to materialize. Cardiovascular diseases are the leading cause of death globally, and hypertension is a common prelude to nearly all cardiovascular diseases. Thus, hypertension is an ideal candidate disease to apply tenants of personalized medicine to lessen cardiovascular disease. Herein is a survey that visually depicts the polymorphisms in the top eight antihypertensive targets. Although there are numerous genome-wide association studies regarding cardiovascular disease, few studies look at the effects of receptor polymorphisms on drug treatment. With 17,000+ polymorphisms in the combined target proteins examined, it is expected that some of the clinical variability in the treatment of hypertension is due to polymorphisms in the drug targets. Recent advances in techniques and technology, such as high throughput examination of single mutations, structure prediction, computational power for modeling, and CRISPR models of point mutations, allow for a relatively rapid and comprehensive examination of the effects of known and future polymorphisms on drug affinity and effects. As hypertension is easy to measure and has a plethora of clinically viable ligands, hypertension makes an excellent disease to study pharmacogenomics in the lab and the clinic. If the promises of personalized medicine are to materialize, a concerted effort to examine the effects polymorphisms have on drugs is required. A clinician with the knowledge of a patient's genotype can then prescribe drugs that are optimal for treating that specific patient.

Evaluation of Pharmacogenetics of Drug-Metabolizing Enzymes and Drug Efflux Transporter in Renal Transplants Receiving Immunosuppressants

Cytochrome P450 (CYP) enzymes, such as CYP3A4, and CYP3A5, P450 oxidoreductase (POR), peroxisome proliferator activated receptor alpha (PPAR-alpha), and drug transporter (ABCB1) were observed to influence concentrations of immunosuppressants (cyclosporine, everolimus, sirolimus, and tacrolimus) and outcomes in renal transplants. We carried out the present study to evaluate the prevalence and impact of these single nucleotide polymorphisms (SNPs) in adult renal transplants. SNPs were evaluated using commercial TaqMan^® assays. Serum drug concentrations were estimated using immunoassays. One hundred and forty-six patients were recruited. SNPs in CYP3A5*3 were significantly associated with greater dose-adjusted cyclosporine and tacrolimus concentrations. SNPs in POR*28 were observed with significantly lower dose-adjusted concentrations, particularly with cyclosporine and tacrolimus. ABCB1 homozygous polymorphisms were observed with significantly lower time spent in the therapeutic range with cyclosporine and everolimus/sirolimus. Cyclosporine was observed in a significantly greater proportion of patients with elevated GGT, and SNPs in PPAR-alpha were significantly associated with an increased risk of this adverse event. Hypertriglyceridemia with everolimus was significantly associated with POR*28 polymorphisms. There is a need to validate the influence of these SNPs in a prospective study and develop an algorithm predicting the achievement of target concentrations.

The importance of including African populations in pharmacogenetics studies of warfarin response

Tweetable abstract Warfarin will remain in use for a long time to come, thus inclusion of African populations in pharmacogenomics is essential to be able to identify all possible biomarkers that are potential predictors for warfarin drug response.