Pharmacogenetic Variants Research Articles

Large-Scale Pharmacogenomics Analysis of Patients With Cancer Within the 100,000 Genomes Project Combining Whole-Genome Sequencing and Medical Records to Inform Clinical Practice.

As part of the 100,000 Genomes Project, we set out to assess the potential viability and clinical impact of reporting genetic variants associated with drug-induced toxicity for patients with cancer recruited for whole-genome sequencing (WGS) as part of a genomic medicine service. Germline WGS from 76,805 participants was analyzed for pharmacogenetic (PGx) variants in four genes (DPYD, NUDT15, TPMT, UGT1A1) associated with toxicity induced by five drugs used in cancer treatment (capecitabine, fluorouracil, mercaptopurine, thioguanine, irinotecan). Linking genomic data with prescribing and hospital incidence records, a phenome-wide association study (PheWAS) was performed to identify whether phenotypes indicative of adverse drug reactions (ADRs) were enriched in drug-exposed individuals with the relevant PGx variants. In a subset of 7,081 patients with cancer, DPYD variants were reported back to clinicians and outcomes were collected. We identified clinically relevant PGx variants across the four genes in 62.7% of participants in our cohort. Extending this to annual prescription numbers in England for the drugs affected by these PGx variants, approximately 14,540 patients per year could potentially benefit from a reduced dose or alternative drug to reduce the risk of ADRs. Validating PGx associations in a real-world data set, we found a significant association between PGx variants in DPYD and toxicity-related phenotypes in patients treated with capecitabine or fluorouracil. Reported DPYD variants were deemed informative for clinical decision making in a majority of cases. Reporting PGx variants from germline WGS relevant to patients with cancer alongside primary findings related to their cancer can be clinically informative, informing prescribing to reduce the risk of ADRs. Extending the range of actionable variants to those found in patients of non-European ancestry is important and will extend the potential clinical impact.

Afro-Latin American Pharmacogenetics of CYP2D6, CYP2C9, and CYP2C19 in Dominicans: A Study from the RIBEF-CEIBA Consortium

Background/Objectives: Research on pharmacogenetic variability in response to prescribed drugs and across ethnic groups is essential for personalized medicine, particularly in admixed and unstudied populations. For the first time, this study examines CYP2D6, CYP2C9, and CYP2C19 alleles and genotypes in 197 healthy volunteers from the Dominican Republic, as part of the RIBEF-CEIBA collaborative network. Methods: The analysis focuses on the participants’ tri-hybrid genomic ancestry, with CYP alleles determined by real-time PCR and molecular ancestry inferred using 90 AIMs. Linear regression was used to associate ancestry components with CYP frequencies. Results: The average ancestry was 23.8% European, 42.6% Native American, and 33.6% African, the latter being higher than in most Latin American populations. Native American ancestry was also higher than expected. Predicted phenotype frequencies based on genotypes were 4.2% poor metabolizers (gPMs) and 3.6% ultrarapid metabolizers (gUMs) for CYP2D6, as well as 3% gPMs, 22.8% rapid metabolizers (gRMs), and 1.5% gUMs for CYP2C19. No gPM individuals were observed for CYP2C9. Certain alleles associated with decreased CYP2D6 activity (*17 and *29) and increased CYP2C19 activity (*17 and gUMs) were positively linked with African ancestry and negatively with Native American ancestry. Rare CYP2C9 alleles (*5 and *6) with clinical relevance were additionally found. Conclusions: These findings build on previous results from the RIBEF-CEIBA collaborative network, demonstrating differences in allele frequencies of CYP2D6, CYP2C9, and CYP2C19 in relation to genomic ancestry. In summary, ethnicity must be considered in the development of pharmacogenetic guidelines for clinical application, research, and regulation to avoid widening the biotechnology gap and to allow Personalized Medicine to reach the entire world population.

The role of candidate pharmacogenetic variants in determining valproic acid efficacy, toxicity and concentrations in patients with epilepsy

BackgroundAntiseizure medications (ASM) exhibit considerable interindividual variability in terms of efficacy and adverse events. Genetic variation is thought to contribute to these differences in clinical outcomes. Specifically, the response to valproic acid (VPA), a widely used ASM, is influenced by multiple pharmacogenetic factors. However, and in contrast to other ASMs such as phenytoin and carbamazepine, there is a paucity of data on the association between VPA and various gene variants. The aim of this study was hence to evaluate the influence of candidate pharmacogenetic variants on VPA efficacy, toxicity and serum concentrations in a homogeneous cohort of patients newly diagnosed with genetic generalized epilepsies (GGE).MethodsIn this prospective cohort study, demographic, clinical and treatment outcomes of GGE patients were retrieved from their medical records. Whole exome sequencing was performed in collaboration with Epi25. Gene variants associated with VPA efficacy, metabolism and toxicities were retrieved from PharmGKB. An analysis was then conducted to explore potential associations between these gene variants and VPA clinical outcomes.ResultsOf the 166 patients included, 60 (36.1%) experienced treatment failure while 106 (63.9%) achieved treatment success. After adjusting for VPA maintenance dose, carriers of the rs3892097 (CYP2D6) variant were 2.5 times more likely to experience treatment failure compared to wildtype (p = 0.026). The rs1057910 variant (CYP2C9*3) was associated with increased serum VPA concentrations (p = 0.034). Moreover, the rs1137101 variant (LEPR gene, a metabolism regulator) was significantly associated with a higher risk of weight gain (regression coefficient of 3.430 [0.674; 6.186], p = 0.015) and a higher frequency of hair loss (OR = 3.394 [1.157; 9.956], p = 0.026), while the rs4480 variant (SOD2 gene, encoding for a mitochondrial scavenging enzyme) was correlated with a lower frequency of hair loss (OR = 0.276 [0.089; 0.858], p = 0.026).ConclusionThese findings highlight the role of genetic factors in VPA treatment and underscore the potential for developing therapeutic strategies to enhance patient outcomes and minimize adverse effects.

Drug-gene interactions in older patients with coronary artery disease

BackgroundOlder patients with coronary artery disease (CAD) are particularly vulnerable to the efficacy and adverse drug reactions, and may therefore particularly benefit from personalized medication. Drug–gene interactions (DGIs) occur when an individual’s genotype affects the pharmacokinetics and/or pharmacodynamics of a victim drug.ObjectivesThis study aimed to investigate the impact of cardiovascular-related DGIs on the clinical efficacy and safety outcomes in older patients with CAD.MethodsHospitalized older patients (≥ 65 years old) with CAD were consecutively recruited from August 2018 to May 2022. Eligible patients were genotyped for the actionable pharmacogenetic variants of CYP2C9, CYP2C19, CYP2D6, CYP3A5, and SLCO1B1, which had clinical annotations or implementation guidelines for cardiovascular drugs. Allele frequencies and DGIs were determined in the cohort for the 5 actionable PGx genes and the prescribed cardiovascular drugs. All patients were followed up for at least 1 year. The influence of DGIs on the cardiovascular drug-related efficacy outcomes (all-cause mortality and/or major cardiovascular events, MACEs) and drug response phenotypes of “drug-stop” and “dose-decrease” were evaluated.ResultsA total of 1,017 eligible older patients with CAD were included, among whom 63.2% were male, with an average age of 80.8 years old, and 87.6% were administrated with polypharmacy (≥ 5 medications). After genotyping, we found that 96.0% of the older patients with CAD patients had at least one allele of the 5 pharmacogenes associated with a therapeutic change, indicating a need for a therapeutic change in a mean of 1.32 drugs of the 19 cardiovascular-related drugs. We also identified that 79.5% of the patients had at least one DGI (range 0–6). The median follow-up interval was 39 months. Independent of age, negative association could be found between the number of DGIs and all-cause mortality (adjusted HR: 0.84, 95% CI: 0.73–0.96, P = 0.008), and MACEs (adjusted HR: 0.84, 95% CI: 0.72–0.98, P = 0.023), but positive association could be found between the number of DGIs and drug response phenotypes (adjusted OR: 1.24, 95% CI: 1.05–1.45, P = 0.011) in the elderly patients with CAD.ConclusionsThe association between cardiovascular DGIs and the clinical outcomes emphasized the necessity for the integration of genetic and clinical data to enhance the optimization of cardiovascular polypharmacy in older patients with CAD. The causal relationship between DGIs and the clinical outcomes should be established in the large scale prospectively designed cohort study.

Case report: Acute liver failure during deferasirox therapy and the potential role of pharmacogenetics

Background and aimsA number of case reports have documented the occurrence of acute hepatic and renal toxicity during treatment with deferasirox (DFX). The precise mechanisms underlying these adverse events remain unclear, with the time to toxicity varying considerably between patients—some experiencing it within weeks of treatment initiation, while others after several years. Recent studies have underscored the association of pharmacogenetic variants in genes responsible for the metabolism and clearance of DFX (ABCC2, ABCG2, and UGT1A1) in the development of toxicity. We present the case of an 8-year-old patient with beta thalassemia major who developed acute hepatic failure years after the initiation of DFX therapy. After ruling out the most likely causes, we performed a pharmacogenetic analysis, which suggested a possible link between the patient’s genotype and the development of toxicity.MethodsSanger sequencing was performed for the most extensively studied single nucleotide polymorphisms (SNPs) studied associated with changes in transporter/enzyme function: ABCC2 rs717620 (c.-24C>T), rs2273697 (c.1249G>A), rs8187710 (c.4544G>A), rs369192412 (g.99781071delG); ABCG2 rs2231142 (c.421C>A); UGT1A1 *6 rs4148323 (c.211G>A), *28 rs3064744 (g.233760235TA[8]), *36 rs3064744 (g.233760235TA[6]) and *37 rs3064744 (g.233760235TA[9]).ResultsThe patient is heterozygous for two ABCC2 variants, namely rs717620 (c.-24C>T) and rs2273697 (c.1249G>A). These variants have the potential to cause a reduction in transporter function, which could in turn result in decreased drug clearance and increased toxicity.DiscussionThe precise mechanism by which toxicity developed in this case remains unclear and is likely multifactorial. However, it is probable that the presence of SNPs in the gene ABCC2 played a substantial role. Our findings align with those of previously published reports of remarkably similar cases, where patients also exhibited genetic variants in the gene ABCC2.

Pharmacogenetic DPYD allele variant frequencies: A comprehensive analysis across an ancestrally diverse Iranian population.

Cancer treatment has improved over the past decades, but many cancer patients still experience adverse drug reactions (ADRs). Pharmacogenomics (PGx), known as personalized treatment, is a pillar of precision medicine that aims to optimize the efficacy and safety of medications by studying the germline variations. Germline variations in the DPYD lead to significant ADRs. The present cross-sectional study aims to evaluate the allele frequency of the DPYD gene variations in the Iranian population to provide insights into personalized treatment decisions in the Iranian population. The allele frequency of 51 pharmacogenetic variations in the clinically relevant DPYD was assessed in a representative sample set of 1142 unrelated Iranian individuals and subpopulations of different ethnic groups who were genotyped using the Infinium Global Screening Array-24 BeadChip. The genotyping assay revealed eight pharmacogenetic variants including DPYD rs1801265 (c.85T > C; DPYD*9A), rs2297595 (c.496A > G), rs1801158 (c.1601G > A; DPYD*4), rs1801159 (c.1627A > G; DPYD*5), rs1801160 (c.2194G > A; DPYD*6), rs17376848 (c.1896T > C), rs56038477 (c.1236G > A; HapB3), and rs75017182 (c.1129-5923C > G; HapB3) with minor allele frequency (MAF) ≥ 1%. The results of the study reveal significant genetic variations among Iranian population that could significantly influence clinical decision-making. These variants, with their potential to explain the substantial variability in drug response phenotypes among different populations, shed light on a crucial aspect of pharmacogenomics. These findings not only provide valuable insights but also inspire the design and implementation of future pharmacogenomic clinical trials, motivating further research in this crucial area.

Value of Pharmacogenetic Testing Assessed with Real-World Drug Utilization and Genotype Data.

Implementation of pharmacogenetic testing in clinical care has been slow and with few exceptions is hindered by the lack of real-world evidence on how to best target testing. In this retrospective register-based study, we analyzed a nationwide cohort of 1,425,000 patients discharged from internal medicine or surgical wards and a cohort of 2,178 university hospital patients for purchases and prescriptions of pharmacogenetically actionable drugs. Pharmacogenetic variants were obtained from whole genome genotype data for a subset (n = 930) of the university hospital patients. We investigated factors associated with receiving pharmacogenetically actionable drugs and developed a literature-based cost-benefit model for pre-emptive pharmacogenetic panel testing. In a 2-year follow-up, 60.4% of the patients in the nationwide cohort purchased at least one pharmacogenetically actionable drug, most commonly ibuprofen (25.0%) and codeine (19.4%). Of the genotyped subset, 98.8% carried at least one actionable pharmacogenetic genotype and 23.3% had at least one actionable gene-drug pair. Patients suffering from musculoskeletal or cardiovascular diseases were more prone to receive pharmacogenetically actionable drugs during inpatient episode. The cost-benefit model included frequently dispensed drugs in the university hospital cohort, comprising ondansetron (19.4%), simvastatin (7.4%), clopidogrel (5.0%), warfarin (5.1%), (es)citalopram (5.3%), and azathioprine (0.5%). For untargeted pre-emptive pharmacogenetic testing of all university hospital patients, the model indicated saving €17.49 in direct healthcare system costs per patient in 2 years without accounting for the cost of the test itself. Therefore, it might be reasonable to target pre-emptive pharmacogenetic testing to patient groups most likely to receive pharmacogenetically actionable drugs.

Metabolic Syndrome Drug Therapy: The Potential Interplay of Pharmacogenetics and Pharmacokinetic Interactions in Clinical Practice: A Narrative Review

Metabolic syndrome (MetS) presents a significant global health challenge, characterized by a cluster of metabolic alterations including obesity, hypertension, insulin resistance/dysglycemia, and atherogenic dyslipidemia. Advances in understanding and pharmacotherapy have added complexity to MetS management, particularly concerning drug interactions and pharmacogenetic variations. Limited literature exists on drug–drug–gene interactions (DDGIs) and drug–drug–transporter gene interactions (DDTGIs), which can significantly impact pharmacokinetics and pharmacodynamics, affecting treatment outcomes. This narrative review aims to address the following three key objectives: firstly, shedding a light on the PK metabolism, transport, and the pharmacogenetics (PGx) of medicines most commonly used in the MetS setting (relevant lipid-lowering drugs, antihypertensives and antihyperglycemics agents); secondly, exemplifying potential clinically relevant pharmacokinetic drug interactions, including drug–drug interactions, DDGIs, and DDTGIs; and, thirdly, describing and discussing their potential roles in clinical practice. This narrative review includes relevant information found with the use of interaction checkers, pharmacogenetic databases, clinical pharmacogenetic practice guidelines, and literature sources, guided by evidence-based medicine principles.

Patterns of pharmacogenetic variation in nine biogeographic groups.

Frequencies of pharmacogenetic (PGx) variants are known to differ substantially across populations but much of the available PGx literature focuses on one or a few population groups, often defined in nonstandardized ways, or on a specific gene or variant. Guidelines produced by the Clinical Pharmacogenetic Implementation Consortium (CPIC) provide consistent methods of literature extraction, curation, and reporting, including comprehensive curation of allele frequency data across nine defined "biogeographic groups" from the PGx literature. We extracted data from 23 CPIC guidelines encompassing 19 genes to compare the sizes of the populations from each group and allele frequencies of altered function alleles across groups. The European group was the largest in the curated literature for 16 of the 19 genes, while the American and Oceanian groups were the smallest. Nearly 200 alleles were detected in nonreference groups that were not reported in the largest (reference) group. The genes CYP2B6 and CYP2C9 were more likely to have higher frequencies of altered function alleles in nonreference groups compared to the reference group, while the genes CYP4F2, DPYD, SLCO1B1, and UGT1A1 were less likely to have higher frequencies in nonreference groups. PGx allele frequencies and function differ substantially across nine biogeographic groups, all but two of which are underrepresented in available PGx data. Awareness of these differences and increased efforts to characterize the breadth of global PGx variation are needed to ensure that implementation of PGx-guided drug selection does not further widen existing health disparities among populations currently underrepresented in PGx data.

Prevalence of actionable pharmacogenetic variants and high-risk drug prescriptions: A Swiss hospital-based cohort study.

Drug type and dosing recommendation have been designed and optimized based on average response in the general population. Yet, there is significant inter-individual variability in drug response, which results in treatment inefficacy or adverse drug reactions in a subset of patients. This is partly due to genetic factors that typically affect drug metabolism or clearance. To verify the relevance and applicability of international pharmacogenetic guidelines in the Swiss population, we genotyped 1533 patients from a hospital-based biobank who received at least 30 different drugs, as documented in their electronic health record. We then assessed the prevalence of clinically actionable variants in 13 high-risk pharmacogenes. We compared the allele frequencies obtained in the hospital-based cohort with those of a Swiss population-based cohort of 4791 individuals. The prevalence of clinically actionable variants was comparable between the two cohorts, with most study participants (97.3%) carrying at least one actionable pharmacogenetic variant. We then assessed the frequency of high-risk prescriptions due to actionable gene-drug interactions and observed that 31% of patients in the hospital-based cohort were prescribed at least one drug for which they carried a high-risk variant, and for which international guidelines recommend a change of drug or dosage. Our analysis confirms the high prevalence of actionable pharmacogenetic variants in the Swiss population. It also shows that a substantial minority of patients are exposed to drugs for which they carry potentially problematic variants. Implementing a genetically informed approach to drug prescribing could have a positive impact on the quality of healthcare delivery.

Drug metabolizing enzymes pharmacogenetic variation-informed antidepressant therapy approach for common mental disorders: A systematic review and meta-analysis

ImportanceCurrently, 30–50 % of individuals with depression and 40 % with anxiety—collectively referred to as common mental disorders (CMDs), exhibit inadequate responses to antidepressant treatments. ObjectiveTo assess the effectiveness and safety of drug-metabolizing enzyme pharmacogenetic variation informed treatment (PGxIT) versus usual antidepressant treatment (UT) in patients with CMDs. Data sourcesA literature search was conducted in the MEDLINE, Scopus, and Cochrane Library databases from inception until January 30, 2024. Study selectionStudies were selected based on CMD diagnoses, reporting on the genetic variations of drug-metabolizing enzyme (DME) genes in relation to antidepressants, involving PGxIT and UT groups with human subjects, and published in English. Data extraction and synthesisData extraction and quality assessment were performed independently by two authors. A pooled risk ratio (RR) with 95 % CI was estimated using both random and fixed-effect models, and heterogeneity was assessed using Cochran's Q test and the I2 statistic. The publication bias of eligible studies was assessed using post hoc Doi plots and the LFK index. ResultsThis systematic review included 18 studies (n = 7021). The PGxIT demonstrated greater efficacy in the remission of symptoms of depressive disorder at 8 weeks (RR 1.523 [95 % CI: 1.255–1.843]; I2 = 48 %) and 12 weeks (RR 1.631 [95 % CI: 1.001–2.657]; I2 = 86 %; p < 0.01), and symptoms of anxiety disorder compared to UT. Additionally, the risk of adverse drug events (ADEs) was significantly lower in the PGxIT group (RR = 0.65 [95 % CI: 0.52–0.82]; I2 = 0 %) than in the UT group. The certainty of evidence for both outcomes was moderate. Conclusions and relevanceThis systematic review and meta-analysis suggest that pharmacogenetically guided antidepressant treatment, based on genetic variation in drug-metabolizing enzymes, is associated with superior efficacy in the remission of symptoms for patients with depressive disorders and a reduction in ADEs compared to usual treatment and the findings of the systematic review for remission in anxiety disorders indicate that, PGx guided treatment is also associated with increased remission of symptoms in anxiety disorders compared to usual treatment.

Impact of steroid hormone levels on estradiol-mediated regulation of cytochrome P450 2B6 compared to 1B1 in breast cancer cells.

Pharmacogenetic variants of the steroid hormone-metabolizing enzyme cytochrome P450 2B6 (CYP2B6) were reported to be associated with breast cancer (BC) risk and prognosis. CYP2B6 expression is inducible by estradiol (E2) but induction was demonstrated only under steroid hormone-deprived medium conditions. Physiological conditions, however, even under endocrinological BC treatment, do not correspond to complete steroid hormone depletion. The aim of this study was to investigate the E2-mediated CYP2B6 and CYP1B1 regulation under various steroid hormone conditions, including physiological concentrations, in human oestrogen receptor positive (T47D, MCF-7) and negative (MDA-MB-231) BC cell lines. We confirm that steroid-deprived pre-cultivation led to CYP2B6 upregulation in T47D, but not in MCF-7. However, when pre-cultivated with steroid-containing medium CYP2B6 was downregulated in T47D and MCF-7, while the addition of physiological E2 concentrations to steroid-deprived medium resulted in a downregulation in T47D. In contrast, CYP1B1 was never downregulated in any culture condition. Thus, we show that E2-mediated CYP2B6 regulation in BC cells depends on steroid hormone exposure in a cell line-specific manner. Our data indicates the importance of being careful with conclusions drawn from CYP2B6 induction findings in vitro, as we demonstrate potential influences of hormonal changes on CYP2B6 expression, which could impact steroid hormone homeostasis and, consequently, BC risk.

A Pharmacogenetic Panel-Based Prediction of the Clinical Outcomes in Elderly Patients with Coronary Artery Disease.

Clinical annotations for the actionable pharmacogenetic variants affecting the efficacy of cardiovascular drugs have been collected, yet their impacts on elderly patients with coronary artery disease (CAD) undergoing polypharmacy remain uncertain. We consecutively enrolled 892 elderly patients (mean age 80.7 ± 5.2) with CAD and polypharmacy. All the included patients underwent genotyping for 13 variants in 10 pharmacogenes (CYP2C19, CYP2C9, CYP4F2, CYP2D6, VKORC1, SLCO1B1, APOE, ACE, ADRB1, and MTHFR), which have the clinical annotations for 12 drugs that are commonly prescribed for patients with CAD. We found that 80.3% of the elderly CAD patients had at least one drug-gene pair associated with a therapeutical drug change. After adjusting for covariates, the number of drug-gene pairs was independently associated with a decreased risk of both major cardiovascular events (MACEs) (adjusted hazard ratio [HR]: 0.803, 95% confidence interval [CI]: 0.683-0.945, p = 0.008) and all-cause mortality (adjusted HR: 0.848, 95% CI: 0.722-0.996, p = 0.045), but also with an increased risk of adverse drug reactions (ADRs) (adjusted HR: 1.170, 95% CI: 1.030-1.329, p = 0.016). The Kaplan-Meier survival curves showed that compared to patients without a drug-gene pair, a significantly lower risk of MACEs could be observed in patients with a drug-gene pair during a 4-year follow-up (HR: 0.556, 95% CI: 0.325-0.951, p = 0.013). In conclusion, the carrier status of the actionable drug-gene pair is predictive for the clinical outcomes in elderly patients with CAD and polypharmacy. Implementing early or preemptive pharmacogenetic panel-guided polypharmacy holds the potential to enhance clinical outcomes for these patients.

Pharmacogenetic Variants and Plasma Concentrations of Antiseizure Drugs

Precise estimation of a patient's drug metabolism capacity is important for antiseizure dose personalization. To quantify the differences in plasma concentrations for antiseizure drugs associated with variants of genes encoding drug metabolizing enzymes. PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to September 30, 2023, without language restrictions. Two reviewers performed independent study screening and assessed the following inclusion criteria: appropriate genotyping was performed, genotype-based categorization into subgroups was possible, and each subgroup contained at least 3 participants. The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for data extraction and subsequent quality, validity, and risk-of-bias assessments. The results from the included studies were pooled with random-effect meta-analysis. Plasma concentrations of antiseizure drugs were quantified with the dose-normalized area under the concentration-time curve, the dose-normalized steady state concentration, or the concentrations after a single dose at standardized dose and sampling time. The ratio of the means was calculated by dividing the mean drug plasma concentrations of carriers and noncarriers of the pharmacogenetic variant. Data from 98 studies involving 12 543 adult participants treated with phenytoin, valproate, lamotrigine, or carbamazepine were analyzed. Studies were mainly conducted within East Asian (69 studies) or White or European (15 studies) cohorts. Significant increases of plasma concentrations compared with the reference subgroup were observed for phenytoin, by 46% (95% CI, 33%-61%) in CYP2C9 intermediate metabolizers, 20% (95% CI, 17%-30%) in CYP2C19 intermediate metabolizers, and 39% (95% CI, 24%-56%) in CYP2C19 poor metabolizers; for valproate, by 12% (95% CI, 4%-20%) in CYP2C9 intermediate metabolizers, 12% (95% CI, 2%-24%) in CYP2C19 intermediate metabolizers, and 20% (95% CI, 2%-41%) in CYP2C19 poor metabolizers; and for carbamazepine, by 12% (95% CI, 3%-22%) in CYP3A5 poor metabolizers. This systematic review and meta-analysis found that CYP2C9 and CYP2C19 genotypes encoding low enzymatic capacity were associated with a clinically relevant increase in phenytoin plasma concentrations, several pharmacogenetic variants were associated with statistically significant but only marginally clinically relevant changes in valproate and carbamazepine plasma concentrations, and numerous pharmacogenetic variants were not associated with statistically significant differences in plasma concentrations of antiseizure drugs.

Drug-induced hepatotoxicity and association with slow acetylation variants NAT2*5 and NAT2*6 in Cameroonian patients with tuberculosis and HIV co-infection

BackgroundHuman immunodeficiency virus (HIV) and tuberculosis (TB) are major contributors to morbidity and mortality in sub-Saharan Africa including Cameroon. Pharmacogenetic variants could serve as predictors of drug-induced hepatotoxicity (DIH), in patients with TB co-infected with HIV. We evaluated the occurrence of DIH and pharmacogenetic variants in Cameroonian patients.MethodsTreatment-naïve patients with HIV, TB or TB/HIV co-infection were recruited at three hospitals in Cameroon, between September 2018 and November 2019. Appropriate treatment was initiated, and patients followed up for 12 weeks to assess DIH. Pharmacogenetic variants were assessed by allele discrimination TaqMan SNP assays.ResultsOf the 141 treatment naïve patients, the overall incidence of DIH was 38% (53/141). The highest incidence of DIH, 52% (32/61), was observed among HIV patients. Of 32 pharmacogenetic variants, the slow acetylation variants NAT2*5 was associated with a decreased risk of DIH (OR: 0.4; 95%CI: 0.17–0.96; p = 0.038), while NAT2*6 was found to be associated with an increased risk of DIH (OR: 4.2; 95%CI: 1.1–15.2; p = 0.017) among patients treated for TB. Up to 15 SNPs differed in ≥ 5% of allele frequencies among African populations, while 25 SNPs differed in ≥ 5% of the allele frequencies among non-African populations, respectively.ConclusionsDIH is an important clinical problem in African patients with TB and HIV. The NAT2*5 and NAT2*6 variants were found to be associated with DIH in the Cameroonian population. Prior screening for the slow acetylation variants NAT2*5 and NAT2*6 may prevent DIH in TB and HIV-coinfected patients.

Implementing pharmacogenetic testing to optimize proton-pump inhibitors use among Indian population based on CPIC-CYP2C19-PPI dosing guidelines: The need of the hour.

Proton-pump inhibitors (PPIs) are widely prescribed to decrease stomach acid and treat various acid-related Gastrointestinal tract (GIT) diseases. However, genetic variations, particularly in the CYP2C19 gene, affect PPIs metabolism and efficacy. Variants in CYP2C19 can result in different rates of PPI metabolism, influencing their effectiveness. Personalized medicine strategies, such as genotyping for CYP2C19, have the potential to enhance the effectiveness of PPI therapy and patient safety. This review aims to describe the relevance of CYP2C19 genetic profiling in the indian population, including normal function (e.g. CYP2C19*1, *11, *13, *15, *18, *28, and 38), decreased function (e.g., CYP2C19*9, *10, *16, *19, *25, and 26), loss of function (e.g., CYP2C19*2, *3, *4, *5, *6, *7, *8, *22, *24, *35, *36, and *37), and increased function (e.g., CYP2C19*17) variants. This review also examines the clinical pharmacogenomics implementation consortium (CPIC)-CYP2C19-PPI guidelines to highlight the importance of pharmacogenomics (PGx)-informed personalized PPI therapy for gastroesophageal reflux disease and peptic ulcer disease treatment. On average, each person in India possesses eight pharmacogenetic (PGx) variants that can be clinically significant, underscoring the need for preemptive testing. Implementing CYP2C19 genetic testing in India requires expanding laboratory capacity, increasing accessibility in primary care, increasing public awareness, collaboration between pharmacovigilance and PGx programs, investing in advanced sequencing technologies, data management systems, and integration with electronic health records and clinical decision support systems. Addressing challenges such as genetic diversity, socioeconomic factors, health-care access issues, and shortage of trained professionals is essential for implementation. Due to the lack of definitive country-specific policies and PGx guidelines from Indian drug regulatory agencies, guidelines from international consortia such as the Clinical Pharmacogenetics Implementation Consortium and drug labeling offer crucial foundational evidence. This evidence can be used to enhance patient outcomes and ensure the safe and effective use of PPIs in India.

Assessing the Performance of In silico Tools and Molecular Dynamics Simulations for Predicting Pharmacogenetic Variant Impact.

The ability of freely available in silico tools to predict the effect of non-synonymous single nucleotide polymorphisms (nsSNPs) in pharmacogenes on protein function is not well defined. We assessed the performance of seven sequence-based (SIFT, PolyPhen2, mutation accessor, FATHMM, PhD-SNP, MutPred2, and SNPs & Go) and five structure-based (mCSM, SDM, DDGun, CupSat, and MAESTROweb) tools in predicting the impact of 118 nsSNPs in the CYP2C19, CYP2C9, CYP2B6, CYP2D6, and DPYD genes with known function (24 normal, one increased, 42 decreased, and 51 no-function). Sequence-based tools had a higher median (IQR) positive predictive value (89% [89-94%] vs. 12% [10-15%], P < 0.001) and lower negative predictive value (30% [24-34%] vs. 90% [80-93%], P < 0.001) than structure-based tools. Accuracy did not significantly differ between sequence-based (59% [37-67%]) and structure-based (34% [23-44%]) tools (P = 0.070). Notably, the no-function CYP2C9*3 allele and decreased function CYP2C9*8 allele were predicted incorrectly as tolerated by 100% of sequenced-based tools and as stabilizing by 60% and 20% of structure-based tools, respectively. As a case study, we performed mutational analysis for the CYP2C9*1, *3 (I359L), and *8 (R150H) proteins through molecular dynamic (MD) simulations using S-warfarin as the substrate. The I359L variant increased the distance of the major metabolic site of S-warfarin to the oxy-ferryl center of CYP2C9, and I359L and R150H caused shifts in the conformation of S-warfarin to a position less favorable for metabolism. These data suggest that MD simulations may better capture the impact of nsSNPs in pharmacogenes than other tools.

Implementing DPYD/UGT1A1testing to prevent treatment related adverse events (TRAE) in patients with gastrointestinal (GI) cancer: Results of a pragmatic implementation trial.

10599 Background: Fluoropyrimidines (FP), 5-FU and capecitabine, are standard treatments for many GI cancers. Irinotecan may be used with FPs in both the curative and palliative settings. 30-40% of patients experience severe TRAEs which can lead to treatment interruption and hospitalization. TRAE risk is higher in patients with pharmacogenetic variants in DPYD and/or UGT1A1. Methods: This is a non-randomized, open-label implementation study at 3 cancer care sites within an academic health system to determine feasibility of integrating DPYD/UGT1A1 testing into clinical care (IMPACT-GI; NCT#04736472). Test ordering and discrete variant resulting were available within the Electronic Health Record. The lab detected 5 DPYD variants with reduced or no function (c.1905+1G&gt;A, c.2846A&gt;T, c.1679T&gt;G, c.1236G&gt;A, c.557A&gt;G) and 2 UGT1A1 (*6, *28) alleles. Patients with a GI cancer initiating treatment with 5-FU, capecitabine, or irinotecan underwent testing along with preemptive chemotherapy dose modifications. Carriers of 1 DPYD variant (i.e., intermediate metabolizers [IM]) and UGT1A1 homozygous carriers (i.e., poor metabolizers [PM]) were recommended a 50% and 30% dose reduction, respectively. The primary endpoints were feasibility (proportion of results available prior to cycle 1) and fidelity (genotype concordant dose modifications). Secondary endpoints included severe TRAE (requiring emergency room visit or hospitalization) comparing variant carriers vs. wildtype over the first 6 cycles. Results: From 3/2021- 12/2022, 224 patients received testing (54% male, 74% White, 18% Black, mean age 62 ±17 years. The most common diagnoses were 47% colorectal and 30% pancreatic cancers. The median lab turnaround time was 10 (IQR 9-13) calendar days with 57.2% of results available prior to cycle 1. Results available prior to cycle 1 varied by distance to lab (64.7% near sites vs. 32.7% far site, p&lt;0.001). We identified 7 (3%) DPYD intermediate metabolizers (IM) and 33 (15%) UGT1A1 poor metabolizers (PM). Four (2%) patients carried a variant in both DPYD and UGT1A1. Chemotherapies were preemptively dose reduced for 6 of 7 DPYD carriers receiving FP and 5 of 8 UGT1A1 PMs receiving irinotecan. 2 (28%) DPYD carriers vs. 71 (33%) wildtype carriers had a severe TRAE. 4 (50%) UGT1A1 PMs vs. 11 (36%) UGT1A1 wildtype carriers experienced a severe TRAE. Conclusions: DPYD/UGT1A1 testing is feasible with oncology providers following the genotype guided dose reductions when results were available prior to cycle 1. Pretreatment DPYD/UGT1A1 testing in conjunction with preemptive dose reductions resulted a similar proportion of severe TRAE as compared with wild-type patients. Further workflow modifications are required to decrease test turnaround time to ensure results are available prior to chemotherapy initiation. Clinical trial information: NCT04736472 .

APF2: an improved ensemble method for pharmacogenomic variant effect prediction

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20–30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

Landscape of TPMT and NUDT15 Pharmacogenetic Variation in a Cohort of Canadian Pediatric Inflammatory Bowel Disease Patients.

Patients with inflammatory bowel disease (IBD) exhibit considerable interindividual variability in medication response, highlighting the need for precision medicine approaches to optimize and tailor treatment. Pharmacogenetics (PGx) offers the ability to individualize dosing by examining genetic factors underlying the metabolism of medications such as thiopurines. Pharmacogenetic testing can identify individuals who may be at risk for thiopurine dose-dependent adverse reactions including myelosuppression. We aimed to evaluate PGx variation in genes supported by clinical guidelines that inform dosing of thiopurines and characterize differences in the distribution of actionable PGx variation among diverse ancestral groups. Pharmacogenetic variation in TPMT and NUDT15 was captured by genome-wide genotyping of 1083 pediatric IBD patients from a diverse Canadian cohort. Genetic ancestry was inferred using principal component analysis. The proportion of PGx variation and associated metabolizer status phenotypes was compared across 5 genetic ancestral groups within the cohort (Admixed American, African, East Asian, European, and South Asian) and to prior global estimates from corresponding populations. Collectively, 11% of the cohort was categorized as intermediate or poor metabolizers of thiopurines, which would warrant a significant dose reduction or selection of alternate therapy. Clinically actionable variation in TPMT was more prevalent in participants of European and Admixed American/Latino ancestry (8.7% and 7.5%, respectively), whereas variation in NUDT15 was more prevalent in participants of East Asian and Admixed American/Latino ancestry (16% and 15% respectively). These findings demonstrate the considerable interpopulation variability in PGx variation underlying thiopurine metabolism, which should be factored into testing diverse patient populations.