A Novel CYP2C-Haplotype Associated With Ultrarapid Metabolism of Escitalopram

Novel genetic structures associated with adverse response to chemotherapy in breast cancer

Introduction: The role of genetic variants in response to chemotherapy has been investigated in several studies. This study aimed to investigate genetic variants associated with response to chemotherapy in breast cancer (BC) patients. Methods: Significant variants (p < 5 × 10-8) associated with response to chemotherapy were obtained from GWA studies. Candidate variants were identified by haplotype analysis (r2 ≥ 0.9, D'≥0.9) using 1000Genome LD data. To determine the effects of the variants on gene expression, expression quantitative trait loci (eQTL) were evaluated. To compare the expression of the identified genes in tumor samples, expression levels were compared between TCGA tumor types and adjacent normal tissues. Results: Six rs3820706, rs147451859, rs4784750, rs17587029, rs16830728, and rs16972207 variants were significantly associated with response to chemotherapy in BC patients (p < 5 × 10-8). Seven novel haplotypic structures were identified to be associated with adverse response to chemotherapy in BC patients. These haplotypes formed two genetic structures associated with neutropenia, leukopenia, chemotherapy-induced cytotoxicity (GAG-TTAT), and chemotherapy-induced alopecia (CC-CAACTCCCGTTGCGG). These variants are located on PPCDC, NLRC5, STAM2, and TNFSF13B genes, and the expression of these genes significantly changed in BC tissues than normal tissues (P ≤ 0.05), also showing gene-gene correlation (P ≤ 0.05). Conclusions: These genetic variants and their associated novel haplotypic structures can predict adverse response to chemotherapy in BC patients and could potentially form BC-associated genetic panel for adverse response to chemotherapy.

Phenotype-Genotype Correlation Applying a Cocktail Approach and an Exome Chip Analysis Reveals Further Variants Contributing to Variation of Drug Metabolism

Although great progress has been made in the fine-tuning of diplotypes, there is still a need to further improve the predictability of individual phenotypes of pharmacogenetically relevant enzymes. The aim of this study was to analyze the additional contribution of sex and variants identified by exome chip analysis to the metabolic ratio of five probe drugs. A cocktail study applying dextromethorphan, losartan, omeprazole, midazolam, and caffeine was conducted on 200 healthy volunteers. CYP2D6, 2C9, 2C19, 3A4/5, and 1A2 genotypes were analyzed and correlated with metabolic ratios. In addition, an exome chip analysis was performed. These SNPs correlating with metabolic ratios were confirmed by individual genotyping. The contribution of various factors to metabolic ratios was assessed by multiple regression analysis. Genotypically predicted phenotypes defined by CPIC discriminated very well the log metabolic ratios with the exception of caffeine. There were minor sex differences in the activity of CYP2C9, 2C19, 1A2, and CYP3A4/5. For dextromethorphan (CYP2D6), IP6K2 (rs61740999) and TCF20 (rs5758651) affected metabolic ratios, but only IP6K2 remained significant after multiple regression analysis. For losartan (CYP2C9), FBXW12 (rs17080138), ZNF703 (rs79707182), and SLC17A4 (rs11754288) together with CYP diplotypes, and sex explained 50% of interindividual variability. For omeprazole (CYP2C19), no significant influence of CYP2C:TG haplotypes was observed, but CYP2C19 rs12777823 improved the predictability. The comprehensive genetic analysis and inclusion of sex in a multiple regression model significantly improved the explanation of variability of metabolic ratios, resulting in further improvement of algorithms for the prediction of individual phenotypes of drug-metabolizing enzymes.

Combined effect of CYP2C19 and CYP2D6 genotypes on escitalopram serum concentration and its metabolic ratio in a European patient population

AIMS

The aim of the present study was to investigate the impact of CYP2D6 genotype on exposure and metabolism of escitalopram in patients stratified by CYP2C19 genotype in a large real-world population.

METHODS

Patients were included from a therapeutic drug monitoring service if they had measured serum concentration of escitalopram and the metabolite, N-desmethyl escitalopram, and performed CYP2C19 and CYP2D6 genotyping. Patients were divided into 16 combined genotype-predicted phenotype subgroups (poor [PM], intermediate [IM], normal [NM] and ultrarapid metabolizers [UM]) of CYP2C19/CYP2D6. The concentration-to-dose (CD) ratio and metabolite-to-parent ratio (metabolic ratio) of escitalopram were compared across subgroups using the Kruskal-Wallis test followed by Dunn's test with CYP2D6 NMs as the reference group.

RESULTS

A total of 5067 patients were included in the study. A stepwise increase in escitalopram CD ratio by decreasing CYP2D6 activity was observed in all CYP2C19 subgroups, except for in CYP2C19 UMs. The percentage differences in escitalopram CD ratio between CYP2D6 PMs and NMs were 24% in CYP2C19 NMs (P < .001), 28% in CYP2C19 IMs (P < .001) and 31% in CYP2C19 PMs (P = .04). As for the CD ratio, CYP2D6 genotype effect on metabolic ratio increased stepwise by decreasing CYP2C19 metabolism.

CONCLUSIONS

CYP2D6 genotype is of significant importance for the individual variation in escitalopram pharmacokinetics. The most relevant increase in escitalopram concentration is seen in individuals with decreased and/or absent CYP2C19 activity. By combining CYP2C19 and CYP2D6 genotypes, the optimal dose for patients may be predicted with greater precision than for CYP2C19 genotype alone.

Pharmacogenomic insights in psychiatric care: uncovering novel actionability, allele-specific CYP2D6 copy number variation, and phenoconversion in 15,000 patients

Pharmacogenomic testing has emerged as an aid in clinical decision making for psychiatric providers, but more data is needed regarding its utility in clinical practice and potential impact on patient care. In this cross-sectional study, we determined the real-world prevalence of pharmacogenomic actionability in patients receiving psychiatric care. Potential actionability was based on the prevalence of CYP2C19 and CYP2D6 phenotypes, including CYP2D6 allele-specific copy number variations (CNVs). Combined actionability additionally incorporated CYP2D6 phenoconversion and the novel CYP2C-TG haplotype in patients with available medication data. Across 15,000 patients receiving clinical pharmacogenomic testing, 65% had potentially actionable CYP2D6 and CYP2C19 phenotypes, and phenotype assignment was impacted by CYP2D6 allele-specific CNVs in 2% of all patients. Of 4114 patients with medication data, 42% had CYP2D6 phenoconversion from drug interactions and 20% carried a novel CYP2C haplotype potentially altering actionability. A total of 87% had some form of potential actionability from genetic findings and/or phenoconversion. Genetic variation detected via next-generation sequencing led to phenotype reassignment in 22% of individuals overall (2% in CYP2D6 and 20% in CYP2C19). Ultimately, pharmacogenomic testing using next-generation sequencing identified potential actionability in most patients receiving psychiatric care. Early pharmacogenomic testing may provide actionable insights to aid clinicians in drug prescribing to optimize psychiatric care.

Is CYP2C Haplotype Relevant for Efficacy and Bleeding Risk in Clopidogrel-Treated Patients?

A recently discovered haplotype-CYP2C:TG-determines the ultrarapid metabolism of several CYP2C19 substrates. The platelet inhibitor clopidogrel requires CYP2C19-mediated activation: the risk of ischemic events is increased in patients with a poor (PM) or intermediate (IM) CYP2C19 metabolizer phenotype (vs. normal, NM; rapid, RM; or ultrarapid, UM). We investigated whether the CYP2C:TG haplotype affected efficacy/bleeding risk in clopidogrel-treated patients. Adults (n = 283) treated with clopidogrel over 3-6 months were classified by CYP2C19 phenotype based on the CYP2C19*2*17 genotype, and based on the CYP2C19/CYP2C cluster genotype, and regarding carriage of the CYP2:TG haplotype, and were balanced on a number of covariates across the levels of phenotypes/haplotype carriage. Overall, 45 (15.9%) patients experienced ischemic events, and 49 (17.3%) experienced bleedings. By either classification, the incidence of ischemic events was similarly numerically higher in PM/IM patients (21.6%, 21.8%, respectively) than in mutually similar NM, RM, and UM patients (13.2-14.8%), whereas the incidence of bleeding events was numerically lower (13.1% vs. 16.6-20.5%). The incidence of ischemic events was similar in CYP2C:TG carries and non-carries (14.1% vs. 16.1%), whereas the incidence of bleedings appeared mildly lower in the former (14.9% vs. 20.1%). We observed no signal to suggest a major effect of the CYP2C19/CYP2C cluster genotype or CYP2C:TG haplotype on the clinical efficacy/safety of clopidogrel.

Proton-Pump Inhibitors in Eosinophilic Esophagitis: A Review Focused on the Role of Pharmacogenetics

Proton-pump inhibitors (PPIs) are the most administered first-line treatment for eosinophilic esophagitis (EoE). However, only around half of EoE patients respond histologically to a double dosage of PPI. In addition, 70% of responders maintain EoE in remission after tapering the PPI dose. In order to avoid endoscopy with biopsies-the only accurate method of assessing PPI response-efforts have been made to identify PPI responder patients. The clinical or endoscopic features and biomarkers evaluated so far, however, have not proven to be sufficient in predicting PPI response. Although new approaches based on omics technologies have uncovered promising biomarkers, the specialized and complex procedures required are difficult to implement in clinical settings. Alternatively, PPI pharmacogenetics based on identifying variations in CYP2C19 and STAT6 genes have shown promising results in EoE, and could easily be performed in most laboratories. Other genetic variations have also been associated with PPI response and may explain those cases not related to CYP2C19 or STAT6. Here, we provide an overview of PPI treatment in EoE and evidence of how genetic variations in CYP2C19 and other genes could affect PPI effectiveness, and also discuss studies evaluating the role of pharmacogenetics in predicting PPI response in patients with EoE.

Influence of novel CYP2C-haplotype on proton pump inhibitor pharmacokinetics in children

In this brief report, we provide an analysis of the influence of a novel CYP2C haplotype (CYP2C:TG) on proton pump inhibitor (PPI) pharmacokinetics (PK) in children. The CYP2C:TG haplotype has been proposed to be associated with increased CYP2C19 activity. We sought to determine if this CYP2C:TG haplotype resulted in similar alterations in metabolism for proton pump inhibitors, which are primarily metabolized by CYP2C19. In a cohort of 41 children aged 6-21 participating in a PPI pharmacokinetic study, effects of the CYP2C:TG allele were assessed by fitting two linear regression models for each of the six PK outcomes assessed, the second of which accounted for the presence of the CYP2C:TG allele. The difference in R2 values between the two models was computed to quantify the variability in the outcome that could be accounted for by the CYP2C:TG allele after adjustment for the CYP2C19 genotype. We found the CYP2C:TG haplotype to have no measurable additive impact on CYP2C19-mediated metabolism of PPIs in vivo in older children and adolescents. The findings of this study do not support the clinical utility of routine testing for the CYP2C:TG haplotype to guide PPI dose adjustments in children.

Exploratory focused pharmacogenetic testing reveals novel markers associated with risperidone pharmacokinetics in Saudi children with autism

Background: Autism spectrum disorders (ASDs) encompass a broad range of phenotypes characterized by diverse neurological alterations. Genomic studies have revealed considerable overlap between the molecular mechanisms implicated in the etiology of ASD and genes involved in the pharmacokinetic (PK) and pharmacodynamic (PD) pathways of antipsychotic drugs employed in ASD management. Given the conflicting data originating from candidate PK or PD gene association studies in diverse ethnogeographic ASD populations, dosage individualization based on "actionable" pharmacogenetic (PGx) markers has limited application in clinical practice. Additionally, off-label use of different antipsychotics is an ongoing practice, which is justified given the shortage of approved cures, despite the lack of satisfactory evidence for its safety according to precision medicine. This exploratory study aimed to identify PGx markers predictive of risperidone (RIS) exposure in autistic Saudi children. Methods: This prospective cohort study enrolled 89 Saudi children with ASD treated with RIS-based antipsychotic therapy. Plasma levels of RIS and 9-OH-RIS were measured using a liquid chromatography-tandem mass spectrometry system. To enable focused exploratory testing, genotyping was performed with the Axiom PharmacoFocus Array, which included a collection of probe sets targeting PK/PD genes. A total of 720 PGx markers were included in the association analysis. Results: A total of 27 PGx variants were found to have a prominent impact on various RIS PK parameters; most were not located within the genes involved in the classical RIS PK pathway. Specifically, 8 markers in 7 genes were identified as the PGx markers with the strongest impact on RIS levels (p < 0.01). Four PGx variants in 3 genes were strongly associated with 9-OH-RIS levels, while 5 markers in 5 different genes explained the interindividual variability in the total active moiety. Notably, 6 CYP2D6 variants exhibited strong linkage disequilibrium; however, they significantly influenced only the metabolic ratio and had no considerable effects on the individual estimates of RIS, 9-OH-RIS, or the total active moiety. After correction for multiple testing, rs78998153 in UGT2B17 (which is highly expressed in the brain) remained the most significant PGx marker positively adjusting the metabolic ratio. For the first time, certain human leukocyte antigen (HLA) markers were found to enhance various RIS exposure parameters, which reinforces the gut-brain axis theory of ASD etiology and its suggested inflammatory impacts on drug bioavailability through modulation of the brain, gastrointestinal tract and/or hepatic expression of metabolizing enzymes and transporters. Conclusion: Our hypothesis-generating approach identified a broad spectrum of PGx markers that interactively influence RIS exposure in ASD children, which indicated the need for further validation in population PK modeling studies to define polygenic scores for antipsychotic efficacy and safety, which could facilitate personalized therapeutic decision-making in this complex neurodevelopmental condition.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

Impact of CYP2C:TG Haplotype on CYP2C19 Substrates Clearance In Vivo, Protein Content, and In Vitro Activity

A novel haplotype composed of two non-coding variants, CYP2C18 NM_000772.3:c.*31T (rs2860840) and NM_000772.2:c.819+2182G (rs11188059), referred to as "CYP2C:TG," was recently associated with ultrarapid metabolism of various CYP2C19 substrates. As the underlying mechanism and clinical relevance of this effect remain uncertain, we analyzed existing in vivo and in vitro data to determine the magnitude of the CYP2C:TG haplotype effect. We assessed variability in pharmacokinetics of CYP2C19 substrates, including citalopram, sertraline, voriconazole, omeprazole, pantoprazole, and rabeprazole in 222 healthy volunteers receiving one of these six drugs. We also determined its impact on CYP2C8, CYP2C9, CYP2C18, and CYP2C19 protein abundance in 135 human liver tissue samples, and on CYP2C18/CYP2C19 activity in vitro using N-desmethyl atomoxetine formation. No effects were observed according to CYP2C:TG haplotype or to CYP2C19*1+TG alleles (i.e., CYP2C19 alleles containing the CYP2C:TG haplotype). In contrast, CYP2C19 intermediate (e.g., CYP2C19*1/*2) and poor metabolizers (e.g., CYP2C19*2/*2) showed significantly higher exposure in vivo, lower CYP2C19 protein abundance in human liver microsomes, and lower activity in vitro compared with normal, rapid (i.e., CYP2C19*1/*17), and ultrarapid metabolizers (i.e., CYP2C19*17/*17). Moreover, a tendency toward lower exposure was observed in ultrarapid metabolizers compared with rapid metabolizers and normal metabolizers. Furthermore, when the CYP2C19*17 allele was present, CYP2C18 protein abundance was increased suggesting that genetic variation in CYP2C19 may be relevant to the overall metabolism of certain drugs by regulating not only its expression levels, but also those of CYP2C18. Considering all available data, we conclude that there is insufficient evidence supporting clinical CYP2C:TG testing to inform drug therapy.

Pharmacogenetic and clinical predictors of voriconazole concentration in hematopoietic stem cell transplant recipients receiving CYP2C19-guided dosing

CYP2C19-guided voriconazole dosing reduces pharmacokinetic variability, but many patients remain subtherapeutic. The aim of this study was to evaluate the effect of candidate genes and a novel CYP2C haplotype on voriconazole trough concentrations in patients receiving CYP2C19-guided dosing. This is a retrospective candidate gene study in allogeneic hematopoietic cell transplant (HCT) patients receiving CYP2C19-guided voriconazole dosing. Patients were genotyped for ABCB1, ABCG2, CYP2C9, CYP3A4, CYP3A5, and the CYP2C haplotype. Of 185 patients, 36% were subtherapeutic (of which 79% were normal or intermediate metabolizers). In all patients, CYP2C19 (p < 0.001), age (p = 0.018), and letermovir use (p = 0.001) were associated with voriconazole concentrations. In the subset receiving 200 mg daily (non-RM/UMs), CYP2C19 (p = 0.004) and ABCG2 (p = 0.015) were associated with voriconazole concentrations; CYP2C19 (p = 0.028) and letermovir use (p = 0.001) were associated with subtherapeutic status. CYP2C19 phenotype and letermovir use were significantly associated with subtherapeutic voriconazole concentrations and may be used to improve voriconazole precision dosing, while further research is needed to clarify the role of ABCG2 in voriconazole dosing.

A Pharmacogenetics-Based Approach to Managing Gastroesophageal Reflux Disease: Current Perspectives and Future Steps

Proton pump inhibitors (PPIs) are commonly used medications to treat acid-related conditions, including gastro-esophageal reflux disease (GERD). Gastroenterology guidelines mention the importance of CYP2C19 in PPI metabolism and the influence of CYP2C19 genetic variations on variable responses to PPIs, but do not currently recommend the genotyping of CYP2C19 prior to prescribing PPIs. There are strong data to support the influence of CYP2C19 genetic variations on the pharmacokinetics of PPIs and clinical outcomes. Existing pharmacogenetic guideline recommendations for dose increases focus on H. pylori and erosive esophagitis indications, but PPIs are also the main therapy for treating GERD. Recent data suggest GERD patients being treated with a PPI may also benefit from genotype-guided dosing. We summarize the literature supporting this contention and highlight future directions for improved management of patients with GERD through precision medicine approaches.

Pharmacogenomics in allogeneic hematopoietic stem cell transplantation: Implications on supportive therapies and conditioning regimens

Allogeneic hematopoietic stem cell transplantation mortality has declined over the years, though prevention and management of treatment-related toxicities and post-transplant complications remains challenging. Applications of pharmacogenomic testing can potentially mitigate adverse drug outcomes due to interindividual variability in drug metabolism and response. This review summarizes clinical pharmacogenomic applications relevant to hematopoietic stem cell transplantation, including antifungals, immunosuppressants, and supportive care management, as well as emerging pharmacogenomic evidence with conditioning regimens.

Pharmacogenomics in practice: a review and implementation guide

Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.

Distribution of a novel CYP2C haplotype in Native American populations

The CYP2C19 gene, located in the CYP2C cluster, encodes the major drug metabolism enzyme CYP2C19. This gene is highly polymorphic and no-function (CYP2C19*2 and CYP2C19*3), reduced function (CYP2C19*9) and increased function (CYP2C19*17) star alleles (haplotypes) are commonly used to predict CYP2C19 metabolic phenotypes. CYP2C19*17 and the genotype-predicted rapid (RM) and ultrarapid (UM) CYP2C19 metabolic phenotypes are absent or rare in several Native American populations. However, discordance between genotype-predicted and pharmacokinetically determined CYP2C19 phenotypes in Native American cohorts have been reported. Recently, a haplotype defined by rs2860840T and rs11188059G alleles in the CYP2C cluster has been shown to encode increased rate of metabolism of the CYP2C19 substrate escitalopram, to a similar extent as CYP2C19*17. We investigated the distribution of the CYP2C:TG haplotype and explored its potential impact on CYP2C19 metabolic activity in Native American populations. The study cohorts included individuals from the One Thousand Genomes Project AMR superpopulation (1 KG_AMR), the Human Genome Diversity Project (HGDP), and from indigenous populations living in Brazil (Kaingang and Guarani). The frequency range of the CYP2C:TG haplotype in the study cohorts, 0.469 to 0.598, is considerably higher than in all 1 KG superpopulations (range: 0.014-to 0.340). We suggest that the high frequency of the CYP2C:TG haplotype might contribute to the reported discordance between CYP2C19-predicted and pharmacokinetically verified CYP2C19 metabolic phenotypes in Native American cohorts. However, functional studies involving genotypic correlations with pharmacokinetic parameters are warranted to ascertain the importance of the CYP2C:TG haplotype.

Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder

Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005-2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04-1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05-2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.

Pharmacogenetic Dose Modeling Based on CYP2C19 Allelic Phenotypes

Pharmacogenetic variability in drug metabolism leads to patient vulnerability to side effects and to therapeutic failure. Our purpose was to introduce a systematic statistical methodology to estimate quantitative dose adjustments based on pharmacokinetic differences in pharmacogenetic subgroups, addressing the concerns of sparse data, incomplete information on phenotypic groups, and heterogeneity of study design. Data on psychotropic drugs metabolized by the cytochrome P450 enzyme CYP2C19 were used as a case study. CYP2C19 activity scores were estimated, while statistically assessing the influence of methodological differences between studies, and used to estimate dose adjustments in genotypic groups. Modeling effects of activity scores in each substance as a population led to prudential predictions of adjustments when few data were available ('shrinkage'). The best results were obtained with the regularized horseshoe, an innovative Bayesian approach to estimate coefficients viewed as a sample from two populations. This approach was compared to modeling the population of substance as normally distributed, to a more traditional "fixed effects" approach, and to dose adjustments based on weighted means, as in current practice. Modeling strategies were able to assess the influence of study parameters and deliver adjustment levels when necessary, extrapolated to all phenotype groups, as well as their level of uncertainty. In addition, the horseshoe reacted sensitively to small study sizes, and provided conservative estimates of required adjustments.

Pharmacogenomics in treatment of depression and psychosis: an update

Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.

Rates of Divergent Pharmacogenes in a Psychiatric Cohort of Inpatients with Depression-Arguments for Preemptive Testing

Background: The international drug agencies annotate pharmacogenes for many years. Pharmacogenetic testing is thus far only established in few settings, assuming that only few patients are actually affected by drug-gene interactions. Methods: 108 hospitalized patients with major depressive disorder were genotyped for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NAT2, DPYD; VKORC1 and TMTP. Results: We found 583 (mean 5.4, median 5) divergent phenotypes (i.e., divergent from the common phenotypes considered normal, e.g., extensive metabolizer) in the 12 analyzed pharmacokinetic genes. The rate for at least one divergent phenotype was 100% in our cohort for CYP, but also for all 12 important pharmacogenes: patients had at least two divergent phenotypes. Compared to a large Danish cohort, CYP2C9 NM and IM status, CYP2C19 UM, CYP2D6 UM and DYPD (GAS 0, 1, 2) genotypes differed statistical significantly. For CYP2D6 and CYP2C19, 13% of the patients were normal metabolizers for both enzymes in our cohort, but this value was 27.3% in the Danish cohort, which is a highly significant difference (p < 0.0001). Conclusion: Divergent phenotypes in pharmacogenes are not the exception, but the rule. Patients with divergent phenotypes seem more prone for hospitalization, emphasizing the need for pre-emptive testing to avoid inefficacy and adverse drug effects in all patients.

Impact of the novel CYP2C:TG haplotype and CYP2B6 variants on sertraline exposure in a large patient population

Sertraline is a commonly used SSRI antidepressant drug, metabolized by CYP2C19 and CYP2B6, that exhibits a substantial interindividual variation in clinical response, of which only a part can be attributed to known genetic variants. In the current study we have examined the role of a newly discovered ultrarapid CYP2C:TG haplotype and CYP2B6 variants in order to identify the possible missing heritability for such variation in sertraline response in a large patient population (n = 840). Compared to the reference group (CYP2C19*1/*1, n = 160), sertraline exposure was increased by 128% in CYP2C19 PMs (n = 29, p < 0.001) but decreased by about 20% in CYP2C19 ultrarapid metabolizers (Ums) (homozygous carriers of CYP2C19*17 and/or CYP2C:TG haplotype) with the diplotypes CYP2C19*17/*17, CYP2C:TG/TG, or CYP2C19*17/CYP2C:TG (n = 135, p < 0.003, p = 0.022, p < 0.003, respectively). Interestingly, in patients carrying the increased function CYP2B6*4 allele, and also carrying the CYP2C19*17 and CYP2C:TG alleles (n = 10), sertraline exposure was 35.4% lower compared to the reference group, whereas in subjects being poor metabolizers (PM) in both the CYP2C19 and CYP2B6 gene, the sertraline concentrations were raised by 189%. In summary, the CYP2C19 variants including the CYP2C:TG haplotype had a significant impact on sertraline metabolism, as well as the CYP2B6*4, *6, and *9 alleles. Knowing the CYP2B6 and CYP2C19 genotype, including the CYP2C:TG haplotype status, can prospectively be useful to clinicians in making more appropriate sertraline dosing decisions.

Challenges and opportunities associated with rare-variant pharmacogenomics

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Pharmacogenetics of the cytochromes P450: Selected pharmacological and toxicological aspects

With the availability of detailed genomic data on all 57 human cytochrome P450 genes, it is clear that there is substantial variability in gene product activity with functionally significant polymorphisms reported across almost all isoforms. This article is concerned mainly with 13 P450 isoforms of particular relevance to xenobiotic metabolism. After brief review of the extent of polymorphism in each, the relevance of selected P450 isoforms to both adverse drug reaction and disease susceptibility is considered in detail. Bleeding due to warfarin and other coumarin anticoagulants is considered as an example of a type A reaction with idiosyncratic adverse drug reactions affecting the liver and skin as type B. It is clear that CYP2C9 variants contribute significantly to warfarin dose requirement and also risk of bleeding, with a minor contribution from CYP4F2. In the case of idiosyncratic adverse drug reactions, CYP2B6 variants appear relevant to both liver and skin reactions to several drugs with CYP2C9 variants also relevant to phenytoin-related skin rash. The relevance of P450 genotype to disease susceptibility is also considered but detailed genetic studies now suggest that CYP2A6 is the only P450 relevant to risk of lung cancer with alleles associated with low or absent activity clearly protective against disease. Other cytochrome P450 genotypes are generally not predictors for risk of cancer or other complex disease development.

Cytochrome P450 polymorphism: From evolution to clinical use

The cytochromes P450s can be divided in two groups, those of high importance for endogenous functions being evolutionary quite stable and those participating in detoxification of drugs and other xenobiotics having less important endogenous functions. In the latter group extensive genetic diversity has been allowed and in addition this is of high importance for survival in different environments. The genetic polymorphisms in these genes have evolved to some extent based on dietary restrictions and environmental factors and have not been subject of conservation due to less importance for survival. In cases of high dietary selection events, gene multiplication and amplification events have been seen. The different variants in genes encoding drug metabolizing enzymes can be used as genetic biomarkers (pharmacogenomic labels) for adjustment of drug treatment leading to less adverse drug reactions and better response. Indeed, this has improved the use of personalized medicine, although the missing heredity seen based on twin studies indicates that there are indeed many more genetic variants to be discovered before one can achieve a satisfactory relationship between genotype and phenotype with respect to drug metabolism and toxicity.

Epigenetic signatures in antidepressant treatment response: a methylome-wide association study in the EMC trial

Although the currently available antidepressants are well established in the treatment of the major depressive disorder (MDD), there is strong variability in the response of individual patients. Reliable predictors to guide treatment decisions before or in an early stage of treatment are needed. DNA-methylation has been proven a useful biomarker in different clinical conditions, but its importance for mechanisms of antidepressant response has not yet been determined. 80 MDD patients were selected out of >500 participants from the Early Medication Change (EMC) cohort with available genetic material based on their antidepressant response after four weeks and stratified into clear responders and age- and sex-matched non-responders (N = 40, each). Early improvement after two weeks was analyzed as a secondary outcome. DNA-methylation was determined using the Illumina EPIC BeadChip. Epigenome-wide association studies were performed and differentially methylated regions (DMRs) identified using the comb-p algorithm. Enrichment was tested for hallmark gene-sets and in genome-wide association studies of depression and antidepressant response. No epigenome-wide significant differentially methylated positions were found for treatment response or early improvement. Twenty DMRs were associated with response; the strongest in an enhancer region in SORBS2, which has been related to cardiovascular diseases and type II diabetes. Another DMR was located in CYP2C18, a gene previously linked to antidepressant response. Results pointed towards differential methylation in genes associated with cardiac function, neuroticism, and depression. Linking differential methylation to antidepressant treatment response is an emerging topic and represents a step towards personalized medicine, potentially facilitating the prediction of patients' response before treatment.

Omeprazole Treatment Failure in Gastroesophageal Reflux Disease and Genetic Variation at the CYP2C Locus

Omeprazole is extensively used to manage gastroesophageal reflux disease (GERD). It is primarily metabolized by CYP2C19. The CYP2C19*17 (rs12248560) allele and the recently described CYP2C:TG haplotype (rs11188059 and rs2860840) are associated with increased enzymatic activity, and may reduce omeprazole exposure. This observational study aimed to investigate the association between these genetic variants and omeprazole treatment failure in GERD. We recruited predominantly New Zealand European GERD patients who either did not respond to omeprazole or experienced breakthrough heartburn symptoms despite at least 8 weeks of omeprazole (≥40 mg/day). The GerdQ score was used to gauge symptomatic severity. A total of 55 cases were recruited with a median age (range) of 56 years (19–82) and GerdQ score of 11 (5–17). Of these, 19 (34.5%) were CYP2C19*17 heterozygotes and two (3.6%) were CYP2C19*17 homozygotes. A total of 30 (27.3%) CYP2C:TG haplotypes was identified in our cohort, with seven (12.7%) CYP2C:TG homozygotes, and 16 (29%) CYP2C:TG heterozygotes. No significant differences were observed for overall CYP2C19*17 alleles, CYP2C19*17/*17, overall CYP2C:TG haplotypes, and CYP2C:TG heterozygotes (p &gt; 0.05 for all comparisons). Gastroscopy and 24-h esophageal pH/impedance tests demonstrated objective evidence of GERD in a subgroup of 39 (71%) cases, in which the CYP2C:TG/TG was significantly enriched (p = 0.03) when compared with the haplotype frequencies in a predominantly (91%) New Zealand European reference population, but not the CYP2C19*17/*17 (p &gt; 0.99), when compared with the allele frequencies for the non-Finnish European subset of gnomAD. We conclude that omeprazole treatment failure in GERD is associated with CYP2C:TG/TG, but not CYP2C19*17.

Systematic review and meta-analysis on the therapeutic reference range for escitalopram: Blood concentrations, clinical effects and serotonin transporter occupancy

INTRODUCTION

A titration within a certain therapeutic reference range presupposes a relationship between the blood concentration and the therapeutic effect of a drug. However, this has not been systematically investigated for escitalopram. Furthermore, the recommended reference range disagrees with mean steady state concentrations (11-21 ng/ml) that are expected under the approved dose range (10-20 mg/day). This work systematically investigated the relationships between escitalopram dose, blood levels, clinical effects, and serotonin transporter occupancy.

METHODS

Following our previously published methodology, relevant articles were systematically searched and reviewed for escitalopram.

RESULTS

Of 1,032 articles screened, a total of 30 studies met the eligibility criteria. The included studies investigated escitalopram blood levels in relationship to clinical effects (9 studies) or moderating factors on escitalopram metabolism (12 studies) or serotonin transporter occupancy (9 studies). Overall, the evidence for an escitalopram concentration/effect relationship is low (level C).

CONCLUSION

Based on our findings, we propose a target range of 20-40 ng/ml for antidepressant efficacy of escitalopram. In maintenance treatment, therapeutic response is expected, when titrating patients above the lower limit. The lower concentration threshold is strongly supported by findings from neuroimaging studies. The upper limit for escitalopram's reference range rather reflects a therapeutic maximum than a tolerability threshold, since the incidence of side effects in general is low. Concentrations above 40 ng/ml should not necessarily result in dose reductions in case of good clinical efficacy and tolerability. Dose-related escitalopram concentrations in different trials were more than twice the expected concentrations from guideline reports.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=215873], identifier [CRD42020215873].

Cardiovascular Pharmacogenomics: An Update on Clinical Studies of Antithrombotic Drugs in Brazilian Patients

Anticoagulant and antiplatelet drugs effectively prevent thrombotic events in patients with cardiovascular diseases, ischemic stroke, peripheral vascular diseases, and other thromboembolic diseases. However, genetic and non-genetic factors affect the response to antithrombotic therapy and can increase the risk of adverse events. This narrative review discusses pharmacogenomic studies on antithrombotic drugs commonly prescribed in Brazil. Multiple Brazilian studies assessed the impact of pharmacokinetic (PK) and pharmacodynamic (PD) gene variants on warfarin response. The reduced function alleles CYP2C9*2 and CYP2C9*3, and VKORC1 rs9923231 (c.-1639G>A) are associated with increased sensitivity to warfarin and a low dose requirement to prevent bleeding episodes, whereas CYP4F2 rs2108622 (p.Val433Met) carriers have higher dose requirements (warfarin resistance). These deleterious variants and non-genetic factors (age, gender, body weight, co-administered drugs, food interactions, and others) account for up to 63% of the warfarin dose variability. Few pharmacogenomics studies have explored antiplatelet drugs in Brazilian cohorts, finding associations between CYP2C19*2, PON1 rs662 and ABCC3 rs757421 genotypes and platelet responsiveness or clopidogrel PK in subjects with coronary artery disease (CAD) or acute coronary syndrome (ACS), whereas ITGB3 contributes to aspirin PK but not platelet responsiveness in diabetic patients. Brazilian guidelines on anticoagulants and antiplatelets recommend the use of a platelet aggregation test or genotyping only in selected cases of ACS subjects without ST-segment elevation taking clopidogrel, and also suggest CYP2C9 and VKORC1 genotyping before starting warfarin therapy to assess the risk of bleeding episodes or warfarin resistance.

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability

Interindividual differences in drug response are a common concern in both drug development and across layers of care. While genetics clearly influences drug response and toxicity of many drugs, a substantial fraction of the heritable pharmacological and toxicological variability remains unexplained by known genetic polymorphisms. In recent years, population-scale sequencing projects have unveiled tens of thousands of coding and noncoding pharmacogenetic variants with unclear functional effects that might explain at least part of this missing heritability. However, translating these personalized variant signatures into drug response predictions and actionable advice remains challenging and constitutes one of the most important frontiers of contemporary pharmacogenomics. Conventional prediction methods are primarily based on evolutionary conservation, which drastically reduces their predictive accuracy when applied to poorly conserved pharmacogenes. Here, we review the current state-of-the-art of computational variant effect predictors across variant classes and critically discuss their utility for pharmacogenomics. Besides missense variants, we discuss recent progress in the evaluation of synonymous, splice, and noncoding variations. Furthermore, we discuss emerging possibilities to assess haplotypes and structural variations. We advocate for the development of algorithms trained on pharmacogenomic instead of pathogenic data sets to improve the predictive accuracy in order to facilitate the utilization of next-generation sequencing data for personalized clinical decision support and precision pharmacogenomics.