From genes to drugs: CYP2C19 and pharmacogenetics in clinical practice

The CYP2C19 gene is frequently included in different pharmacogenomic panels tested in clinical practice, due to its involvement in the metabolism of a myriad of frequently prescribed medications. Accordingly, CYP2C19 genotyping can promote precise therapeutic decisions and avoid the occurrence of significant drug-drug-gene interactions in the clinical setting. A comprehensive examination of the role of the CYP2C19 gene in real-world medical settings is presented in this review. This review summarizes the most recent information on how genetic variants in CYP2C19 affect drug metabolism and therapeutic outcomes. It goes into the wide range of CYP2C19 phenotypes, with different degrees of metabolizing activity, and their implications for customized medication response through a review of the literature. The review also analyzes the clinical significance of CYP2C19 in several medical specialties, including cardiology, psychiatry, and gastro-enterology clinics, and illuminates how it affects pharmacological efficacy, safety, and adverse effects. Finally, CYP2C19-supported clinical decision-making is outlined, highlighting the possibility of improving therapeutic outcomes and achieving more affordable treatment options, a step towards optimizing healthcare provision through precision medicine.

Pharmacogenetics in Child and Adolescent Psychiatry: Background and Evidence-Based Clinical Applications

The efficacy and tolerability of psychotropic medications can vary significantly among children and adolescents, and some of this variability relates to pharmacogenetic factors. Pharmacogenetics (PGx) in child and adolescent psychiatry can potentially improve treatment outcomes and minimize adverse drug reactions. This article reviews key pharmacokinetic and pharmacodynamic genes and principles of pharmacogenetic testing and discusses the evidence base for clinical decision-making concerning PGx testing. This article reviews current guidelines from the United States Food and Drug Administration (FDA), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) and explores potential future directions. This review discusses key clinical considerations for clinicians prescribing psychotropic medications in children and adolescents, focusing on antidepressants, antipsychotics, stimulants, norepinephrine reuptake inhibitors, and alpha-2 agonists. Finally, this review synthesizes the practical use of pharmacogenetic testing and clinical decision support systems.

Pharmacogenes that demonstrate high association evidence according to CPIC, DPWG, and PharmGKB

BACKGROUND

Different levels of evidence related to the variable responses of individuals to drug treatment have been reported in various pharmacogenomic (PGx) databases. Identification of gene-drug pairs with strong association evidence can be helpful in prioritizing the implementation of PGx guidelines and focusing on a gene panel. This study aimed to determine the pharmacogenes with the highest evidence-based association and to indicate their involvement in drug-gene interactions.

METHODOLOGY

The publicly available datasets CPIC, DPWG, and PharmGKB were selected to determine the pharmacogenes with the highest drug outcome associations. The upper two levels of evidence rated by the three scoring methods were specified (levels A-B in CPIC, 3-4 in DPWG, or 1-2 levels in PharmGKB). The identified pharmacogenes were further ranked in this study based on the number of medications they interacted with.

RESULTS

Fifty pharmacogenes, with high to moderately high evidence of associations with drug response alterations, with potential influence on the therapeutic and/or toxicity outcomes of 152 drugs were identified. CYP2D6, CYP2C9, CYP2C19, G6PD, HLA-B, SLCO1B1, CACNA1S, RYR1, MT-RNR1, and IFNL4 are the top 10 pharmacogenes, where each is predicted to impact patients' responses to ≥5 drugs.

CONCLUSION

This study identified the most important pharmacogenes based on the highest-ranked association evidence and their frequency of involvement in affecting multiple drugs. The obtained data is useful for customizing a gene panel for PGx testing. Identifying the strength of scientific evidence supporting drug-gene interactions aids drug prescribers in making the best clinical decision.

Pharmacogenomics (PGx) Patient with Mixed Levels of Actionable Variant Evidence

Objective:

To demonstrate the types of clinical recommendations a pharmacogenomics pharmacist may make to medical clinicians with regard to medication management to improve therapeutic outcomes based on varied levels of medical literature evidence.

Summary:

This case demonstrates how a common type of patient seen in a pharmacist practice may present with a varied pharmacogenomic (PGx) profile, how they may benefit from PGx analysis, and how varying levels of medical literature evidence can be used with clinical decision making.

Conclusion:

PGx testing can help avoid adverse drug reactions (ADRs) or medication inefficacy by assisting in the adjustment of current or future medication doses. It can also help predict the best medications to use or those to avoid in advance by eliminating much of the existing dosing or medication selection method of trial and error.

Discrepancies and similarities in the genome-informed guidance for psychiatric disorders amongst different regulatory bodies and research consortia using next generation sequencing-based clinical pharmacogenomics data

Undoubtedly, pharmacogenomics (PGx) aims in optimizing drug treatment responses whilst also improving the patients' quality of life, either via a reduction of adverse drug reactions and/or an enhancement of drug treatment efficacy. To achieve this, PGx guidance is provided by the two major regulatory bodies in a worldwide level, specifically the U.S. Food and Drug Administration (FDA) and the European Medicine Agency (EMA), and occasionally some research consortia, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) or the Dutch Pharmacogenomics Working Group (DPWG). However, so far, there is a limited number of studies focusing on the delineation of the similarities and more importantly, the discrepancies in the PGx guidance by the different regulatory bodies and consortia. Herein, we use real-life clinical PGx data to highlight such discrepancies and similarities for genome-guided interventions in psychiatric disorders, thus demonstrating the need for harmonization of the guidelines and recommendations. More precisely, we used the PharmCAT genome-informed drug treatment reports from 304 Greek individuals with psychiatric disorders in order to emphasize on the discrepancies in the PGx guidance/guidelines between FDA vs EMA and CPIC vs DPWG, respectively. For example, CYP2D6-pimozide pair is characterized as 'Testing Required' according to FDA and is accompanied by a DPWG PGx guideline, whilst no EMA or CPIC PGx guidance is found for this drug-gene pair. Moreover, discrepancies are observed regarding the type of PGx guidance for CYP2C19-doxepin pair, with 89 individuals from our study cohort requiring a dose prescribing change based on FDA, whilst only 5 individuals have to receive genome-guided treatment adjustment according to CPIC. To our knowledge, this is the first study, in which discrepancies regarding the type of PGx guidance and the number of actionable drug-gene pairs amongst FDA and EMA, as well as CPIC and DPWG, are brought to light with an emphasis on psychiatric disorders.

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Variant Interpretation in Current Pharmacogenetic Testing

In the current marketplace, there are now more than a dozen commercial companies providing pharmacogenetic tests. Each company varies in the panel of genes they test and the variants they are able to screen for. The reports generated by these companies provide phenotypic interpretations of pharmacogenes and clinically actionable gene–drug interactions based on internally curated data and proprietary algorithms. The freedom to choose the types of evidence to include versus exclude in interpreting genomics has created reporting discrepancies in the industry. The case report presented here reveals the discordant phenotype analysis provided by two pharmacogenetic testing companies. The uncertainty and unnecessary distress experienced by the patient highlights the need for consensus in phenotype reporting within the industry.

Unveiling the guidance heterogeneity for genome-informed drug treatment interventions among regulatory bodies and research consortia

Pharmacogenomics and personalized medicine interventions hold promise to optimize drug treatment modalities and hence, improve the quality of life of the patients by minimizing the occurrence of adverse drug reactions and/or maximizing drug treatment efficacy. To this end, proper guidance for accurately prescribing the correct drug at the right dose is empowered by major regulatory bodies, namely the U.S. Food and Drug Administration (FDA) and the European Medicine Agency (EMA), and well-recognized research consortia, like the Clinical Pharmacogenetics Implementation Consortium (CPIC), that propose therapeutic recommendations after the thorough evaluation of the existing scientific evidence base. In this context, the consistency of these recommendations is crucial for smoothly integrating pharmacogenomics into the clinic. Here, we collected all of the important and clinically actionable pharmacogenomics information provided by the aforementioned renowned sources and documented it in order to assess potential similarities and, most importantly, differences. Our data show that the level of concordance regarding the guidance provided for the same drug-gene association pairs varies significantly, despite the fact that it all derives from a single evidence base. In particular, apart from the expected similarities in a number of association pairs, especially the ones related to cancer genomics, there are still major discrepancies that create confusion as to which guidance should be followed in order to properly inform drug prescribing. This regulatory deficiency calls for the fruitful engagement of the regulatory agencies involved with the contribution of other experts engaged in the field of pharmacogenomics in an effort to harmonize the existing arsenal of guidance for genome-informed drug prescription. The achievement of harmonization would in turn expedite bringing personalized medicine closer to clinical fruition.

Tailored therapy in patients treated with fluoropyrimidines: focus on the role of dihydropyrimidine dehydrogenase

Fluoropyrimidines are widely used in the treatment of solid tumors, mainly gastrointestinal, head and neck and breast cancer. Dihydropyrimidine dehydrogenase (DPD) is the rate-limiting enzyme for catabolism of 5-FU and it is encoded by DPYD gene. To date, many known polymorphisms cause DPD deficiency and subsequent increase of 5-FU toxicity. In addition, reduced inactivation of 5-FU could lead to increased 5-FU intracellular concentration and augmented efficacy of this drugs. Therefore DPD expression, particularly intratumoral, has been investigated as predictive and prognostic marker in 5-FU treated patients. There also seems to be a tendency to support the correlation between DPD expression and response/survival in patients treated with fluoropyrimidine even if definitive conclusions cannot be drawn considering that some studies are conflicting. Therefore, the debate on intratumoral DPD expression as a potential predictor and prognostic marker in patients treated with fluoropyrimidines is still open. Four DPD-polymorphisms are the most relevant for their frequency in population and clinical relevance. Many studies demonstrate that treating a carrier of one of these polymorphisms with a full dose of fluoropyrimidine can expose patient to a severe, even life-threatening, toxicity. Severe toxicity is reduced if this kind of patients received a dose-adjustment after being genotyped. CPIC (Clinical Pharmacogenetics Implementation Consortium) is an International Consortium creating guidelines for facilitating use of pharmacogenetic tests for patient care and helps clinicians ensuring a safer drug delivery to the patient. Using predictive DPD deficiency tests in patients receiving 5FU-based chemotherapy, in particular for colorectal cancer, has proven to be a cost-effective strategy.

Maintaining Internal Validity in Community Partnered Participatory Research: Experience from the Community Partners in Care Study

Objective

With internal validity being a central goal of designed experiments, we seek to elucidate how community partnered participatory research (CPPR) impacts the internal validity of public health comparative-effectiveness research.

Methods

Community Partners in Care (CPIC), a study comparing a community-coalition intervention to direct technical assistance for disseminating depression care to vulnerable populations, is used to illustrate design choices developed with attention to core CPPR principles. The study-design process is reviewed retrospectively and evaluated based on the resulting covariate balance across intervention arms and on broader peer-review assessments. Contributions of the CPIC Council and the study's design committee are highlighted.

Results

CPPR principles contributed to building consensus around the use of randomization, creating a sampling frame, specifying geographic boundaries delimiting the scope of the investigation, grouping similar programs into pairs or other small blocks of units, collaboratively choosing random-number-generator seeds to determine randomized intervention assignments, and addressing logistical constraints in field operations. Study protocols yielded samples that were well-balanced on background characteristics across intervention arms. CPIC has been recognized for scientific merit, has drawn attention from policymakers, and has fueled ongoing research collaborations.

Conclusions

Creative and collaborative fulfillment of CPPR principles reinforced the internal validity of CPIC, strengthening the study's scientific rigor by engaging complementary areas of knowledge and expertise among members of the investigative team.

Standardization can accelerate the adoption of pharmacogenomics: current status and the path forward

Successfully implementing pharmacogenomics into routine clinical practice requires an efficient process to order genetic tests and report the results to clinicians and patients. Lack of standardized approaches and terminology in clinical laboratory processes, ordering of the test and reporting of test results all impede this workflow. Expert groups such as the Association for Molecular Pathology and the Clinical Pharmacogenetics Implementation Consortium have published recommendations for standardizing laboratory genetic testing, reporting and terminology. Other resources such as PharmGKB, ClinVar, ClinGen and PharmVar have established databases of nomenclature for pharmacogenetic alleles and variants. Opportunities remain to develop new standards and further disseminate existing standards which will accelerate the implementation of pharmacogenomics.

Evidence and resources to implement pharmacogenetic knowledge for precision medicine

PURPOSE

The current state of pharmacogenetic data curation and dissemination is described, and evidence-based resources for applying pharmacogenetic data in clinical practice are reviewed.

SUMMARY

Implementation of pharmacogenetics in clinical practice has been relatively slow despite substantial scientific progress in understanding linkages between genetic variation and variability of drug response and effect. One factor that has inhibited the adoption of genetic data to guide medication use is a lack of knowledge of how to translate genetic test results into clinical action based on currently available evidence. Other implementation challenges include controversy over selection of appropriate evidentiary thresholds for routine clinical implementation of pharmacogenetic data and the difficulty of compiling scientific data to support clinical recommendations given that large randomized controlled trials to demonstrate the utility of pharmacogenetic testing are not feasible or are not considered necessary to establish clinical utility. Organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Pharmacogenomics Knowledgebase (PharmGKB) systematically evaluate emerging evidence of pharmacogenomic linkages and publish evidence-based prescribing recommendations to inform clinical practice. Both CPIC and PharmGKB provide online resources that facilitate the interpretation of genetic test results and provide prescribing recommendations for specific gene-drug pairs.

CONCLUSION

Resources provided by organizations such as CPIC and PharmGKB, which use standardized approaches to evaluate the literature and provide clinical guidance for a growing number of gene-drug pairs, are essential for the implementation of pharmacogenetics into routine clinical practice.