Effect of Genetic Variability in the CYP4F2, CYP4F11, and CYP4F12 Genes on Liver mRNA Levels and Warfarin Response

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.

Signatures of Co-evolution and Co-regulation in the CYP3A and CYP4F Genes in Humans

Cytochromes P450 (CYP450) are hemoproteins generally involved in the detoxification of the body of xenobiotic molecules. They participate in the metabolism of many drugs and genetic polymorphisms in humans have been found to impact drug responses and metabolic functions. In this study, we investigate the genetic diversity of CYP450 genes. We found that two clusters, CYP3A and CYP4F, are notably differentiated across human populations with evidence for selective pressures acting on both clusters: we found signals of recent positive selection in CYP3A and CYP4F genes and signals of balancing selection in CYP4F genes. Furthermore, an extensive amount of unusual linkage disequilibrium is detected in this latter cluster, indicating co-evolution signatures among CYP4F genes. Several of the selective signals uncovered co-localize with expression quantitative trait loci (eQTL), which could suggest epistasis acting on co-regulation in these gene families. In particular, we detected a potential co-regulation event between CYP3A5 and CYP3A43, a gene whose function remains poorly characterized. We further identified a causal relationship between CYP3A5 expression and reticulocyte count through Mendelian randomization analyses, potentially involving a regulatory region displaying a selective signal specific to African populations. Our findings linking natural selection and gene expression in CYP3A and CYP4F subfamilies are of importance in understanding population differences in metabolism of nutrients and drugs.

Characterization of Gla proteoforms and non-Gla peptides of gamma carboxylated proteins: Application to quantification of prothrombin proteoforms in human plasma

Gamma (γ) carboxylation is an essential post-translational modification in vitamin K-dependent proteins (VKDPs), involved in maintaining critical biological homeostasis. Alterations in the abundance or activity of these proteins have pharmacological and pathological consequences. Importantly, low levels of fully γ-carboxylated clotting factors increase plasma des-γ-carboxy precursors resulting in little or no biological activity. Therefore, it is important to characterize the levels of γ-carboxylation that reflect the active state of these proteins. The conventional enzyme-linked immunosorbent assay for protein induced by vitamin K absence or antagonist II (PIVKA-II) quantification uses an antibody that is not applicable to distinguish different γ-carboxylation states. Liquid chromatography-mass spectrometry (LC-MS) approaches have been utilized to distinguish different γ-carboxylated proteoforms, however, these attempts were impeded by poor sensitivity due to spontaneous neutral loss of CO2 and simultaneous cleavage of the backbone bond in the collision cell. In this study, we utilized an alkaline mobile phase in combination with polarity switching (positive and negative ionization modes) to simultaneously identify and quantify γ-carboxylated VKDPs. The method was applied to compare Gla proteomics of prothrombin (FII) in 10 μL plasma samples of healthy control and warfarin-treated adults. We also identified surrogate non-Gla peptides for seven other VKDPs to quantify total (active plus inactive) protein levels. The total protein approach (TPA) was used to quantify absolute levels of the VKDPs in human plasma.

Whole-genome sequencing across 449 samples spanning 47 ethnolinguistic groups provides insights into genetic diversity in Nigeria

African populations have been drastically underrepresented in genomics research, and failure to capture the genetic diversity across the numerous ethnolinguistic groups (ELGs) found on the continent has hindered the equity of precision medicine initiatives globally. Here, we describe the whole-genome sequencing of 449 Nigerian individuals across 47 unique self-reported ELGs. Population structure analysis reveals genetic differentiation among our ELGs, consistent with previous findings. From the 36 million SNPs and insertions or deletions (indels) discovered in our dataset, we provide a high-level catalog of both novel and medically relevant variation present across the ELGs. These results emphasize the value of this resource for genomics research, with added granularity by representing multiple ELGs from Nigeria. Our results also underscore the potential of using these cohorts with larger sample sizes to improve our understanding of human ancestry and health in Africa.

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

Computational analysis of missense variant CYP4F2*3 (V433M) in association with human CYP4F2 dysfunction: a functional and structural impact

BACKGROUND

Cytochrome P450 4F2 (CYP4F2) enzyme is a member of the CYP4 family responsible for the metabolism of fatty acids, therapeutic drugs, and signaling molecules such as arachidonic acid, tocopherols, and vitamin K. Several reports have demonstrated that the missense variant CYP4F2*3 (V433M) causes decreased activity of CYP4F2 and inter-individual variations in warfarin dose in different ethnic groups. However, the molecular pathogenicity mechanism of missense V433M in CYP4F2 at the atomic level has not yet been completely elucidated.

METHODS AND RESULTS

In the current study, we evaluated the effect of the V433M substitution on CYP4F2 using 14 different bioinformatics tools. Further molecular dynamics (MD) simulations were performed to assess the impact of the V433M mutation on the CYP4F2 protein structure, stability, and dynamics. In addition, molecular docking was used to illustrate the effect of V433M on its interaction with vitamin K1. Based on our results, the CYP4F2*3 variant was a damaging amino acid substitution with a destabilizing nature. The simulation results showed that missense V433M affects the dynamics and stability of CYP4F2 by reducing its compactness and stability, which means that it tends to change the overall structural conformation and flexibility of CYP4F2. The docking results showed that the CYP4F2*3 variant decreased the binding affinity between vitamin K1 and CYP4F2, which reduced the activity of CYP4F2*3 compared to native CYP4F2.

CONCLUSIONS

This study determined the molecular pathogenicity mechanism of the CYP4F2*3 variant on the human CYP4F2 protein and provided new information for understanding the structure-function relationship of CYP4F2 and other CYP4 enzymes. These findings will aid in the development of effective drugs and treatment options.

Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP)

BACKGROUND

Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness.

METHOD AND RESULTS

A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation.

CONCLUSION

The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.

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.

The Relationship Among Intestinal Bacteria, Vitamin K and Response of Vitamin K Antagonist: A Review of Evidence and Potential Mechanism

The vitamin K antagonist is a commonly prescribed effective oral anticoagulant with a narrow therapeutic range, and the dose requirements for different patients varied greatly. In recent years, studies on human intestinal microbiome have provided many valuable insights into disease development and drug reactions. A lot of studies indicated the potential relationship between microbiome and the vitamin K antagonist. Vitamin K is absorbed by the gut, and the intestinal bacteria are a major source of vitamin K in human body. A combined use of the vitamin K antagonist and antibiotics may result in an increase in INR, thus elevating the risk of bleeding, while vitamin K supplementation can improve stability of anticoagulation for oral vitamin K antagonist treatment. Recently, how intestinal bacteria affect the response of the vitamin K antagonist remains unclear. In this review, we reviewed the research, focusing on the physiology of vitamin K in the anticoagulation treatment, and investigated the potential pathways of intestinal bacteria affecting the reaction of the vitamin K antagonist.

Polymorphisms in genes related to oxidative stress and inflammation: Emerging links with the pathogenesis and severity of Cerebral Cavernous Malformation disease

Cerebral Cavernous Malformation (CCM) is a cerebrovascular disease of genetic origin affecting 0.5% of the population and characterized by abnormally enlarged and leaky capillaries that predispose to seizures, neurological deficits, and intracerebral hemorrhage (ICH). CCM occurs sporadically or is inherited as dominant condition with incomplete penetrance and highly variable expressivity. Three disease genes have been identified: KRIT1 (CCM1), CCM2 and CCM3. Previous results demonstrated that loss-of-function mutations of CCM genes cause pleiotropic effects, including defective autophagy, altered reactive oxygen species (ROS) homeostasis, and enhanced sensitivity to oxidative stress and inflammatory events, suggesting a novel unifying pathogenetic mechanism, and raising the possibility that CCM disease onset and severity are influenced by the presence of susceptibility and modifier genes. Consistently, genome-wide association studies (GWAS) in large and homogeneous cohorts of patients sharing the familial form of CCM disease and identical mutations in CCM genes have led to the discovery of distinct genetic modifiers of major disease severity phenotypes, such as development of numerous and large CCM lesions, and susceptibility to ICH. This review deals with the identification of genetic modifiers with a significant impact on inter-individual variability in CCM disease onset and severity, including highly polymorphic genes involved in oxidative stress, inflammatory and immune responses, such as cytochrome P450 monooxygenases (CYP), matrix metalloproteinases (MMP), and Toll-like receptors (TLR), pointing to their emerging prognostic value, and opening up new perspectives for risk stratification and personalized medicine strategies.

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

BACKGROUND

Warfarin is the most commonly evaluated drug in pharmacogenetic-guided dosing studies. However, gaps remain regarding the influence of the genetic polymorphisms of CYP2C9, VKORC1, and CYP4F2 on specific pharmacodynamic parameters like the warfarin sensitivity index (WSI), prothrombin time international normalized ratio (PT-INR), and log-INR variability.

METHODS

A cross-sectional study was conducted in non-smoking adults receiving warfarin for at least 6 months. Their demographics, diagnoses, warfarin dosing regimen, concomitant drugs, PT-INR, and bleeding episodes were obtained. CYP2C9 (rs1057910-*3 and rs1799853-*2 alleles), CYP4F2 (rs2108622), and VKORC1 (rs9923231) polymorphisms were assessed using real-time polymerase chain reaction. Three genotype groups (I-III) were defined based on the combined genetic polymorphisms of CYP2C9 and VKORC1 from the FDA's recommendations. Key outcome measures included anticoagulation control, time spent in therapeutic range, stable warfarin dose, WSI, log-INR variability, and Warfarin Composite Measure (WCM).

RESULTS

The study recruited 236 patients; 75 (31.8%) carried a functional CYP2C9 variant allele, and, 143 (60.6%) had at least one T allele in CYP4F2 and 133 (56.4%) had at least one T allele in VKORC1. Groups' II and III CYP2C9 and VKORC1 genotypes were observed with reduced stable warfarin dose, increased WSI, higher log-INR variability, and increased bleeding risk. The presence of *2 or *3 allele in CYP2C9 was observed with reduced stable warfarin doses akin to the presence of T alleles in VKORC1; however, the doses increased with T alleles in CYP4F2.

CONCLUSION

The evaluated genetic polymorphisms significantly influenced all the pharmacodynamic parameters of warfarin. Evaluating CYP2C9, VKORC1, and CYP4F2 genetic polymorphisms prior to warfarin initiation is likely to optimize therapeutic response.

The correlation between CYP4F2 variants and chronic obstructive pulmonary disease risk in Hainan Han population

Background

Chronic obstructive pulmonary disease (COPD) is a complex pulmonary disease. Cytochrome P450 family 4 subfamily F member 2 (CYP4F2) belongs to cytochrome P450 superfamily of enzymes responsible for metabolism, its single nucleotide polymorphisms (SNPs) were reported to be involved in metabolism in the development of many diseases. The study aimed to assess the relation between CYP4F2 SNPs and COPD risk in the Hainan Han population.

Method

We genotyped five SNPs in CYP4F2 in 313 cases and 508 controls by Agena MassARRAY assay. The association between CYP4F2 SNPs and COPD risk were assessed by χ² test and genetic models. Besides, logistic regression analysis was introduced into the calculation for odds ratio (OR) and 95% confidence intervals (CIs).

Results

Allele model analysis indicated that rs3093203 A was significantly correlated with an increased risk of COPD. Also, rs3093193 G and rs3093110 G were associated with a reduced COPD risk. In the genetic models, we found that rs3093203 was related to an increased COPD risk, while rs3093193 and rs3093110 were related to a reduced risk of COPD. After gender stratification, rs3093203, rs3093193 and rs3093110 showed the association with COPD risk in males. With smoking stratification, rs3093144 was significantly associated with an increased risk of COPD in smokers. CYP4F2 SNPs were significantly associated with COPD risk.

Conclusions

Our findings illustrated potential associations between CYP4F2 polymorphisms and COPD risk. However, large-scale and well-designed studies are needed to determine conclusively the association between the CYP4F2 SNPs and COPD risk.

A Novel LC-MS/MS Assay for Quantification of Des-carboxy Prothrombin and Characterization of Warfarin-Induced Changes

Warfarin is a narrow therapeutic index anticoagulant drug and its use is associated with infrequent but significant adverse bleeding events. The international normalized ratio (INR) is the most commonly used biomarker to monitor and titrate warfarin therapy. However, INR is derived from a functional assay, which determines clotting efficiency at the time of measurement and is susceptible to technical variability. Protein induced by vitamin K antagonist-II (PIVKA-II) has been suggested as a biomarker of long-term vitamin K status, providing mechanistic insights about variation in the functional assay. However, the currently available antibody-based PIVKA-II assay does not inform on the position and number of des-carboxylation sites in prothrombin. The assay presented in this paper provides simultaneous quantification of carboxy and des-carboxy prothrombin that are essential for monitoring early changes in INR and, thus, serves as the superior tool for managing warfarin therapy. Additionally, this assay permits the quantification of total prothrombin level, which is affected by warfarin treatment. Prothrombin recovery from plasma was 95% and the liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was linear (r²  = 0.98) with a dynamic range of 1-100 µg/mL. The assay interday precision was within 20%. A des-carboxy peptide of prothrombin (GNLER) was negatively correlated with active prothrombin (Pearson r = 0.99, P < 0.0001), whereas its association was positively linked with INR values (Pearson r = 0.75, P < 0.015). This novel LC-MS/MS assay for active and inactive prothrombin quantification can be applied to titrate anticoagulant therapy and to monitor the impact of diseases, such as hepatocellular carcinoma on clotting physiology.

Effect of CYP4F2, VKORC1, and CYP2C9 in Influencing Coumarin Dose: A Single-Patient Data Meta-Analysis in More Than 15,000 Individuals

The cytochrome P450 (CYP)4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at the individual patients level to capture the possible effect of ethnicity, gene-gene interaction, or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists of 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95% confidence interval (CI) 7-10%), with a higher effect in women, in patients taking acenocoumarol, and in white patients. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived.

Precision dosing of warfarin: open questions and strategies

Warfarin has a very narrow therapeutic window and obvious interindividual variability in its effects, with many factors contributing to the body's response. Algorithms incorporating multiple genetic, environment and clinical factors have been established to select a precision dose for each patient. A number of randomized controlled trials (RCTs) were conducted to explore whether patients could benefit from these algorithms; however, the results were inconsistent. Some questions remain to be resolved. Recently, new genetic and non-genetic factors have been discovered to contribute to variability in optimal warfarin doses. The results of further RCTs have been unveiled, and guidelines for pharmacogenetically guided warfarin dosing have been updated. Based on these most recent advancements, we summarize some open questions in this field and try to propose possible strategies to resolve them.

GSTP1 rs1695 is associated with both hematological toxicity and prognosis of ovarian cancer treated with paclitaxel plus carboplatin combination chemotherapy: a comprehensive analysis using targeted resequencing of 100 pharmacogenes

Purpose

To find genetic variants that predicted toxicity and/or efficacy of paclitaxel plus carboplatin combination therapy (TC therapy).

Patients and methods

In a retrospective case-control study, we analyzed 320 patients who had received TC therapy for gynecological cancers (ovarian, fallopian tube, peritoneal, uterine, and cervical cancers) and collected their germline DNA. We performed a comprehensive pharmacogenomic analysis using a targeted resequencing panel of 100 pharmacogenes. For 1,013 variants passing QC, case-control association studies and survival analyses were conducted.

Results

GSTP1 rs1695 showed the smallest p value for hematotoxicity association, and the ¹⁰⁵Ile wild type allele had a significantly higher risk of severe hematotoxicity (neutropenia G4, thrombocytopenia ≥ G3 and anemia ≥ G3) than the ¹⁰⁵Val allele (p=0.00034, odds ratio=5.71 (95% confidence interval:1.77-18.44)). Next, we assessed 5-year progression-free survival (PFS) and overall survival (OS) in 56 advanced ovarian cancer patients who received tri-weekly TC as a first-line chemotherapy. Patients with the ¹⁰⁵Ile/¹⁰⁵Ile genotype showed significantly better PFS (p=0.00070) and OS (p=0.0012) than those with the ¹⁰⁵Ile/¹⁰⁵Val or ¹⁰⁵Val/¹⁰⁵Val genotype.

Conclusion

Our study indicates that the GSTP1 rs1695 ¹⁰⁵Ile/¹⁰⁵Ile genotype is associated with both severe hematotoxicity and high efficacy of TC therapy, identifying a possible prognostic indicator for patients with TC therapy.