Pharmacogenomic allele coverage of genome-wide genotyping arrays: a comparative analysis

The use of genome-wide genotyping arrays in pharmacogenomics (PGx) research and clinical implementation applications is increasing but it is unclear which arrays are best suited for these applications. Here, we conduct a comparative coverage analysis of PGx alleles included on genome-wide genotyping arrays, with an emphasis on alleles in genes with PGx-based prescribing guidelines. Genomic manifest files for seven arrays including the Axiom Precision Medicine Diversity Array (PMDA), Axiom PMDA Plus, Axiom PangenomiX, Axiom PangenomiX Plus, Infinium Global Screening Array, Infinium Global Diversity Array (GDA) and Infinium GDA with enhanced PGx (GDA-PGx) Array, were evaluated for coverage of 523 star alleles across 19 pharmacogenes included in prescribing guidelines developed by the Clinical Pharmacogenetic Implementation Consortium and Dutch Pharmacogenomics Working Group. Specific attention was given to coverage of the Association of Molecular Pathology's Tier 1 and Tier 2 allele sets for CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NUDT15, TPMT and VKORC1 . Coverage of the examined PGx alleles was highest for the Infinium GDA-PGx (88%), Axiom PangenomiX Plus (77%), Axiom PangenomiX (72%) and Axiom PMDA Plus (70%). Three arrays (Infinium GDA-PGx, Axiom PangenomiX Plus and Axiom PMDA Plus) fully covered the Tier 1 alleles and the Axiom PangenomiX array provided full coverage of Tier 2 alleles. In conclusion, PGx allele coverage varied by gene and array. A superior array for all PGx applications was not identified. Future comparative analyses of genotype data produced by these arrays are needed to determine the robustness of the reported coverage estimates.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

Pharmacogenomics of Drugs Used in β-Thalassemia and Sickle-Cell Disease: From Basic Research to Clinical Applications

In this short review we have presented and discussed studies on pharmacogenomics (also termed pharmacogenetics) of the drugs employed in the treatment of β-thalassemia or Sickle-cell disease (SCD). This field of investigation is relevant, since it is expected to help clinicians select the appropriate drug and the correct dosage for each patient. We first discussed the search for DNA polymorphisms associated with a high expression of γ-globin genes and identified this using GWAS studies and CRISPR-based gene editing approaches. We then presented validated DNA polymorphisms associated with a high HbF production (including, but not limited to the HBG2 XmnI polymorphism and those related to the BCL11A, MYB, KLF-1, and LYAR genes). The expression of microRNAs involved in the regulation of γ-globin genes was also presented in the context of pharmacomiRNomics. Then, the pharmacogenomics of validated fetal hemoglobin inducers (hydroxyurea, butyrate and butyrate analogues, thalidomide, and sirolimus), of iron chelators, and of analgesics in the pain management of SCD patients were considered. Finally, we discuss current clinical trials, as well as international research networks focusing on clinical issues related to pharmacogenomics in hematological diseases.

Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Documentation of results and medication prescribing after combinatorial psychiatric pharmacogenetic testing: A case for discrete results

PURPOSE

Combinatorial pharmacogenetic (PGx) panels intended to aid psychiatric prescribing are available to clinicians. Here, we evaluated the documentation of PGx panel results and subsequent prescribing patterns within a tertiary health care system.

METHODS

We performed a query of psychiatry service note text in our electronic health record using 71 predefined PGx terms. Patients who underwent combinatorial PGx testing were identified, and documentation of test results was analyzed. Prescription data following testing were examined for the frequency of prescriptions influenced by genes on the panel along with the medical specialties involved.

RESULTS

A total of 341 patients received combinatorial PGx testing, and documentation of results was found to be absent or incomplete for 198 patients (58%). The predominant method of documentation was through portable document formats uploaded to the electronic health record's "Media" section. Among patients with at least 1 year of follow-up, a large majority (194/228, 85%) received orders for medications affected by the tested genes, including 132 of 228 (58%) patients receiving at least 1 non-psychiatric medication influenced by the test results.

CONCLUSION

Results from combinatorial PGx testing were poorly documented. Medications affected by these results were often prescribed after testing, highlighting the need for discrete results and clinical decision support.

Utilizing Pharmacogenomics Results to Improve Statin-Associated Muscle Symptoms

The objective of this aims to demonstrate the advantage of a pharmacogenomics (PGx)-informed medication review in mitigating adverse drug events (ADEs) and optimizing therapeutic outcomes. PGx testing and PGx-informed medication reviews assist in mitigating ADEs. PGx testing was performed on a 68-year-old male presenting with uncontrolled chronic pain. The PGx results highlighted a drug-gene interaction, aiding in identification of the increased risk of statin-associated muscle symptoms (SAMS) attributing to uncontrolled chronic pain. This patient case report illustrates how incorporating PGx results can help improve chronic pain and mitigate ADEs, such as SAMS.

Cost-utility analysis of pharmacogenomics-guided tacrolimus treatment in Austrian kidney transplant recipients participating in the U-PGx PREPARE study

Chronic kidney disease (CKD) is a global health issue. Kidney failure patients may undergo a kidney transplantation (KTX) and prescribed an immunosuppressant medication i.e., tacrolimus. Tacrolimus' efficacy and toxicity varies among patients. This study investigates the cost-utility of pharmacogenomics (PGx) guided tacrolimus treatment compared to the conventional approach in Austrian patients undergone KTX, participating in the PREPARE UPGx study. Treatment's effectiveness was determined by mean survival, and utility values were based on a Visual Analog Scale score. Incremental Cost-Effectiveness Ratio was also calculated. PGx-guided treatment arm was found to be cost-effective, resulting in reduced cost (3902 euros less), 6% less hospitalization days and lower risk of adverse drug events compared to the control arm. The PGx-guided arm showed a mean 0.900 QALYs (95% CI: 0.862-0.936) versus 0.851 QALYs (95% CI: 0.814-0.885) in the other arm. In conclusion, PGx-guided tacrolimus treatment represents a cost-saving option in the Austrian healthcare setting.

Genetic-Guided Pharmacotherapy for Coronary Artery Disease: A Systematic and Critical Review of Economic Evaluations

BACKGROUND

Genetic-guided pharmacotherapy (PGx) is not recommended in clinical guidelines for coronary artery disease (CAD). We aimed to examine the extent and quality of evidence from economic evaluations of PGx in CAD and to identify variables influential in changing conclusions on cost-effectiveness.

METHODS AND RESULTS

From systematic searches across 6 databases, 2 independent reviewers screened, included, and rated the methodological quality of economic evaluations of PGx testing to guide pharmacotherapy for patients with CAD. Of 35 economic evaluations included, most were model-based cost-utility analyses alone, or alongside cost-effectiveness analyses of PGx testing to stratify patients into antiplatelets (25/35), statins (2/35), pain killers (1/35), or angiotensin-converting enzyme inhibitors (1/35) to predict CAD risk (8/35) or to determine the coumadin doses (1/35). To stratify patients into antiplatelets (96/151 comparisons with complete findings of PGx versus non-PGx), PGx was more effective and more costly than non-PGx clopidogrel (28/43) but less costly than non-PGx prasugrel (10/15) and less costly and less effective than non-PGx ticagrelor (22/25). To predict CAD risk (51/151 comparisons), PGx using genetic risk scores was more effective and less costly than clinical risk score (13/17) but more costly than no risk score (16/19) or no treatment (9/9). The remaining comparisons were too few to observe any trend. Mortality risk was the most common variable (47/294) changing conclusions.

CONCLUSIONS

Economic evaluations to date found PGx to stratify patients with CAD into antiplatelets or to predict CAD risk to be cost-effective, but findings varied based on the non-PGx comparators, underscoring the importance of considering local practice in deciding whether to adopt PGx.

Pharmacogenomics for Prader-Willi syndrome: caregiver interest and planned utilization

Aim: The study aim was to determine caregiver interest and planned utilization of pharmacogenomic (PGx) results for their child with Prader-Willi syndrome. Methods: Caregivers consented to PGx testing for their child and completed a survey before receiving results. Results: Of all caregivers (n = 48), 93.8% were highly interested in their child's upcoming PGx results. Most (97.9%) planned to share results with their child's medical providers. However, only 47.9% of caregivers were confident providers would utilize the PGx results. Conclusion: Caregivers are interested in utilizing PGx but are uncertain providers will use these results in their child's care. More information about provider comfort with PGx utilization is needed to understand how PGx education would benefit providers and ultimately patients with PGx results.

[The pharmacogenetics as integral part of personalized medicine: problems and prospects]

The article considers issues of implementation into clinical practice the principles of 5P medicine in its part of individualization of therapeutic tactics considering genetic characteristics of patients. The analysis of studies concerning influence of allelic variations on metabolism, safety and tolerance of the most often prescribed medicinal preparations was implemented. The main assumptions of pharmacogenomics were considered. Despite broad perspective of applying obtained data in clinical practice, there are a number of unresolved problems related to accessibility of genetic testing to population, ambiguity of approaches to interpretation of obtaining results, ethical issues and legal regulation.

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity

Variability in genes involved in drug pharmacokinetics or drug response can be responsible for suboptimal treatment efficacy or predispose to adverse drug reactions. In addition to common genetic variations, large-scale sequencing studies have uncovered multiple rare genetic variants predicted to cause functional alterations in genes encoding proteins implicated in drug metabolism, transport and response. To understand the functional importance of rare genetic variants in DPYD, a pharmacogene whose alterations can cause severe toxicity in patients exposed to fluoropyrimidine-based regimens, massively parallel sequencing of the exonic regions and flanking splice junctions of the DPYD gene was performed in a series of nearly 3000 patients categorized according to pre-emptive DPD enzyme activity using the dihydrouracil/uracil ([UH2]/[U]) plasma ratio as a surrogate marker of DPD activity. Our results underscore the importance of integrating next-generation sequencing-based pharmacogenomic interpretation into clinical decision making to minimize fluoropyrimidine-based chemotherapy toxicity without altering treatment efficacy.

Interrogating Pharmacogenetics Using Next-Generation Sequencing

BACKGROUND

Pharmacogenetics or pharmacogenomics (PGx) is the study of the role of inherited or acquired sequence change in drug response. With the rapid evolution of molecular techniques, bioinformatic tools, and increased throughput of functional genomic studies, the discovery of PGx associations and clinical implementation of PGx test results have now moved beyond a handful variants in single pharmacogenes and multi-gene panels that interrogate a few pharmacogenes to whole-exome and whole-genome scales. Although some laboratories have adopted next-generation sequencing (NGS) as a testing platform for PGx and other molecular tests, most clinical laboratories that offer PGx tests still use targeted genotyping approaches.

CONTENT

This article discusses primarily the technical considerations for clinical laboratories to develop NGS-based PGx tests including whole-genome and whole-exome sequencing analyses and highlights the challenges and opportunities in test design, content selection, bioinformatic pipeline for PGx allele and diplotype assignment, rare variant classification, reporting, and briefly touches a few additional areas that are important for successful clinical implementation of PGx results.

SUMMARY

The accelerated speed of technology development associated with continuous cost reduction and enhanced ability to interrogate complex genome regions makes it inevitable for most, if not all, clinical laboratories to transition PGx testing to an NGS-based platform in the near future. It is important for laboratories and relevant professional societies to recognize both the potential and limitations of NGS-based PGx profiling, and to work together to develop a standard and consistent practice to maximize the variant or allele detection rate and utility of PGx testing.

Implementing pharmacogenetics in clinical trials: considerations about current methodological, ethical, and regulatory challenges

INTRODUCTION

The implementation of pharmacogenetic analysis within clinical trials faces methodological, ethical, and regulatory challenges, as well as tackling the difficulty in obtaining actionable information with a sufficient level of evidence to enable its integration into routine clinical practice.

AREAS COVERED

We discuss the current status of pharmacogenetics integration in clinical trials, underscore the associated challenges, and make some suggestions on the aspects to address in any clinical trial including a pharmacogenetic evaluation. We conducted a literature review, thoroughly reviewed the applicable regulations and available guidelines, and assessed the application dossiers submitted for evaluation to the Ethics committee of Hospital La Paz (Madrid, Spain) to extract information related to inclusion of pharmacogenetics evaluations.

EXPERT OPINION

The integration of pharmacogenetics into clinical trials is becoming increasingly common. However, several regulatory, methodological and ethical aspects involved are insufficiently addressed. There is a need for specific and transparent guidelines that establish unified and compliant criteria for methodology, proper handling of samples in compliance with regulations, and the protection of data privacy and confidentiality. Participants should receive complete and appropriate information regarding the purpose, handling, storage, and transfer of their samples and data, and should have the right to decide about their processing.

Pharmacogenetics to prevent hypersensitivity reactions to antiepileptic drugs: is testing performed when indicated?

Extensive scientific evidence consistently demonstrates the clinical validity and utility of HLA-B*15:02 pre-screening in averting severe cutaneous adverse reactions (SCARs), namely Stevens-Johnson syndrome and toxic epidermal necrolysis, associated with carbamazepine or oxcarbazepine usage. Current practice guidelines and drug labeling actively advocate for pharmacogenetic pre-screening before initiating these antiepileptic drugs (AED), with particular emphasis on patients of Asian descent. However, there is a potential need to strengthen compliance with these recommendations. This retrospective study aimed to describe the pharmacogenetic pre-screening, documentation, and SCARs incidence for patients of Asian ancestry initiated on carbamazepine or oxcarbazepine at a large Northeastern USA healthcare system. Between 1 July 2016 and August 1, 2021, 27 patients with documented Asian heritage in the electronic health record (EHR) were included. The overall rate of HLA-B*15:02 pre-screening before carbamazepine or oxcarbazepine initiation was 4%. None who underwent pharmacogenetic pre-screening carried the associated HLA-B risk allele, and no SCARs were reported. Notably, pharmacogenetic results were not discretely entered into the EHR, and the results were only found as attached documents in the miscellaneous section of the EHR. There remains a significant opportunity for improving HLA-B*15:02 pre-screening for patients starting carbamazepine and oxcarbazepine to prevent SCARs in the USA.

Assessing the utility of measurement methods applied in economic evaluations of pharmacogenomics applications

An increasing number of economic evaluations are published annually investigating the economic effectiveness of pharmacogenomic (PGx) testing. This work was designed to provide a comprehensive summary of the available utility methods used in cost-effectiveness/cost-utility analysis studies of PGx interventions. A comprehensive review was conducted to identify economic analysis studies using a utility valuation method for PGx testing. A total of 82 studies met the inclusion criteria. A majority of studies were from the USA and used the EuroQol-5D questionnaire, as the utility valuation method. Cardiovascular disorders was the most studied therapeutic area while discrete-choice studies mainly focused on patients' willingness to undergo PGx testing. Future research in applying other methodologies in PGx economic evaluation studies would improve the current research environment and provide better results.

PharmoCo: a graph-based visualization of pharmacogenomic plausibility check reports for clinical decision support systems

The first approaches in recent years for the integration of pharmacogenomic plausibility checks into clinical practice show both a promising improvement in the drug therapy safety, but also difficulties in application. One of the difficulties is the meaningful interpretation of the text-based results by the medical practitioner. We propose here as an appropriate and sensible solution to avoid misunderstandings and to include evidence-based, pharmacogenomic recommendations in prescriptions, which should be the graph-based visualization of the reports. This allows for a plausible interpretation and relate complex, even contradictory guidelines. The improved overview over the pharmacogenomics (PGx) guidelines using the graphical visualization makes the medical practitioner's choice of dose and medication more patient-specific, improves the treatment outcome and thus, increases the drug therapy safety.

Pre-emptive pharmacogenomics implementation among polypharmacy patients 65 years old and older: a clinical pilot

Aim: Pre-emptive testing of pharmacogenomic (PGx) variations has potential to improve medication safety and effectiveness; however, testing is not routine. Given the newfound payor coverage of multigene testing and the potential value of testing within aging patients, it is imperative to test local PGx testing capabilities, report results to patients and providers, and determine the value of testing. Materials & methods: We designed a randomized clinical pilot of a pre-emptive PGx testing process using the electronic health record compared with usual care among an aging primary care population. Results & conclusion: The impact of the program on prescribing patterns, healthcare utilization and costs of care will be evaluated. We hypothesize that implementation of a pre-emptive multigene PGx panel is feasible among elderly, polypharmacy, primary care patients, measured by the number of enrolled patients with PGx results entered in the medical record. Health system wide PGx implementation, including capacity needed to integrate these valuable results, is also described.

Pharmacists' role in supporting the return of over 10,000 preemptive pharmacogenomics results: The Mayo Clinic experience

PURPOSE

To develop a pharmacist-driven, exploratory pharmacogenomics implementation model with the goal of creating a process for pharmacists to interpret pharmacogenomics results from RIGHT 10K Study samples and provide electronic consults to providers.

SUMMARY

A train-the-trainer model program was initiated whereby pharmacogenomics pharmacists developed a documentation template and a quick reference guide as a standard guide to train other pharmacists. Pharmacists completed electronic consults (e-consults) reviewing pharmacogenomics results, with reference to drug-gene interactions, for patients with "semi-urgent" and "clinically actionable" results, defined as those indicating a potential for gene-drug interactions to cause major harm and those indicating a potential for an adverse drug reaction or reduced efficacy, respectively. Outcomes measured included the number of consults over time, number and role of pharmacists involved, average time to complete e-consults over time, and gene-drug pairs for semi-urgent consults per month. A total of 395 pharmacists were trained. The total number of e-consults completed was 2,843: 61 semi-urgent and 2,782 clinically actionable consults. The average time spent per consult was 24 minutes, and the average number of e-consults per pharmacist was 7. CYP2C19-clopidogrel was the most common gene-drug pair targeted in semi-urgent consults.

CONCLUSION

Pharmacy leaders planning to implement similar pharmacogenomics programs can utilize this data to estimate hiring needs for future pharmacogenomics implementation, while also considering the potential additional cost of developing resources.

Current status of the analytical validation of next generation sequencing applications for pharmacogenetic profiling

BACKGROUND

Analytical validity is a prerequisite to use a next generation sequencing (NGS)-based application as an in vitro diagnostic test or a companion diagnostic in clinical practice. Currently, in the United States and the European Union, the intended use of such NGS-based tests does not refer to guided drug therapy on the basis of pharmacogenetic profiling of drug metabolizing enzymes, although the value of pharmacogenetic testing has been reported. However, in research, a large variety of NGS-based tests are used and have been confirmed to be at least comparable to array-based testing.

METHODS AND RESULTS

A systematic evaluation was performed screening and assessing published literature on analytical validation of NGS applications for pharmacogenetic profiling of CYP2C9, CYP2C19, CYP2D6, VKORC1 and/or UGT1A1. Although NGS applications are also increasingly used for implementation assessments in clinical practice, we show in the present systematic literature evaluation that published information on the current status of analytical validation of NGS applications targeting drug metabolizing enzymes is scarce. Furthermore, a comprehensive performance evaluation of whole exome and whole genome sequencing with the intended use for pharmacogenetic profiling has not been published so far.

CONCLUSIONS

A standard in reporting on analytical validation of NGS-based tests is not in place yet. Therefore, many relevant performance criteria are not addressed in published literature. For an appropriate analytical validation of an NGS-based qualitative test for pharmacogenetic profiling at least accuracy, precision, limit of detection and specificity should be addressed to facilitate the implementation of such tests in clinical use.

Assessing pharmacogenomic literacy in China through validation of the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy

Pharmacogenomics (PGx) implementation into clinical care is rapidly increasing in China. However, the extent to which the public understands PGx testing and important knowledge domains requiring patient education or counseling remains unclear. To address this, we created and validated the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy (MAPL-CTM ). The MAPL-C was developed by translating the English MAPL to Chinese following cross-cultural translation guidelines. An online survey validated the MAPL-C and assessed Chinese individuals' PGx literacy. Validation analyses were performed and associations of PGx literacy with participants' characteristics were quantified. Of 959 high-quality responses, the majority of respondents were Han Chinese (96.3%), men (54.5%), aged 18-29 years (70.9%), residing in China (97.3%), and had received college or higher education (95.0%). Out of 15 starting items developed to query specific predefined knowledge domains, two uninformative items were excluded, resulting in a 13-item MAPL-C. Chinese participants' MAPL-C performance was best explained by a three-factor model, encompassing PGx concepts and function, testing limitations, and privacy. Higher MAPL-C performance was associated with younger age, higher education, and previous genetic testing experience. Correct response rates for questions related to testing limitations were lower than those in other domains. The creation and validation of the MAPL-C fills a gap in determining PGx knowledge among Chinese speakers, quantifying PGx literacy within a Chinese cohort, and identifying response patterns and knowledge gaps. The MAPL-C can be useful in clinical practice to guide patient counseling, assess PGx education interventions, and quantify PGx knowledge in relation to outcomes in research studies involving Chinese participants.

Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank

Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry

Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.

Lack of exposure to pharmacogenomics education among the health care providing students in the West Bank of Palestine

OBJECTIVES

Evaluating the knowledge in pharmacogenomics (PGx) is the first step toward the implementation of PGx testing in clinical practice. This survey aimed to evaluate the knowledge of PGx testing among healthcare providing students at the top-ranked university in the West Bank of Palestine.

METHODS

First an online questionnaire consisting of 30 questions regarding the demographic, knowledge, and attitude toward pharmacogenomics testing was structured and validated. Then the questionnaire was distributed to 1,000 current students from different fields.

RESULTS

696 responses was received. The results showed that almost half of the participants (n=355, 51.1%) have never took any courses about PGx during their university training. Only 81 (11.7%) of the students who took the PGx course stated that it helped them understanding how genetic variations affect drug response. The majority of the students were uncertain (n=352, 50.6%) or disagreed (n=143, 20.6%) that the lectures during university education described the effects of genetic variants on drug response. Although most of the students (70-80%) answered that genetic variants can indeed affect the drug's response, only 162 students (23.3%) responded that VKORC1 and CYP2C9 genotypes influence the response to warfarin. In addition, only 94 (13.5%) students were aware that many medicine labels include clinical information about PGx testing provided by the FDA.

CONCLUSIONS

It is concluded from the results of this survey that there is a lack of exposure to PGx education associated with poor knowledge of PGx testing among the healthcare providing students in the West Bank of Palestine. It is recommended to include and improve the lectures and courses regarding PGx as this will have a major impact on precision medicine.

Warfarin pharmacogenetics in a black Zimbabwean cohort: an observational prospective study

Aim: A prospective observational study was conducted to evaluate the feasibility of implementing clinical guidelines for warfarin dosing in black Zimbabwean patients. Methods: CYP2C9*5, CYP2C9*6, CYP2C9*8 and CYP2C9*11 and VKORC1 c. 1639 G>A variations were observed in 62 study patients. Results & Conclusion: Overall, 39/62 (62.90%) participants did not receive a warfarin starting dose as would have been recommended by Clinical Pharmacogenetics Implementation Consortium guidelines. US FDA and Dutch Pharmacogenetics Working Group guidelines are based on CYP2C9*2 and CYP2C9*3 only, hence, unlikely useful in this cohort, where such variants were not detected. Clinical Pharmacogenetics Implementation Consortium guidelines, on the other hand, have a specific recommendation on the African-specific variants CYP2C9*5, CYP2C9*6 and CYP2C9*11, and are hence suitable for implementation in Zimbabwe and would help optimize warfarin doses in patients in the study cohort.

Implementation of CYP2D6-guided opioid therapy at Cincinnati Children's Hospital Medical Center

PURPOSE

We describe the implementation of CYP2D6-focused pharmacogenetic testing to guide opioid prescribing in a quaternary care, nonprofit pediatric academic medical center.

SUMMARY

Children are often prescribed oral opioids after surgeries, for cancer pain, and occasionally for chronic pain. In 2004, Cincinnati Children's Hospital Medical Center implemented pharmacogenetic testing for CYP2D6 metabolism phenotype to inform codeine prescribing. The test and reports were updated to align with changes over time in the testing platform, the interpretation of genotype to phenotype, the electronic health record, and Food and Drug Administration (FDA) guidance. The use of the test increased when a research project required testing and decreased as prescribing of oxycodone increased due to FDA warnings about codeine. Education about the opioid-focused pharmacogenetic test was provided to prescribers (eg, the pain and sickle cell teams) as well as patients and families. Education and electronic health record capability increased provider compliance with genotype-guided postsurgical prescribing of oxycodone, although there was a perceived lack of utility for oxycodone prescribing.

CONCLUSION

The implementation of pharmacogenetic testing to inform opioid prescribing for children has evolved with accumulating evidence and guidelines, requiring changes in reporting of results and recommendations.

Congruence rates for pharmacogenomic noninterruptive alerts

Meaningful clinical decision support (CDS) recommendations are vital for implementation of pharmacogenomics (PGx) into routine clinical care. PGx CDS alerts include interruptive and noninterruptive alerts. The objective of this study was to evaluate provider ordering behavior after noninterruptive alerts are displayed. A retrospective manual chart review was conducted from the time of noninterruptive alert implementation to the time of data analysis to determine congruence with CDS recommendations. The congruence rate for noninterruptive alerts was 89.8% across all drug-gene interactions. The drug-gene interaction with the most alerts for analysis included metoclopramide (n = 138). The high rate of medication order congruence after noninterruptive alerts were deployed suggests this modality may be appropriate for PGx CDS as a method for best practice adherence.

Pharmacogenetics: ethnicity, treatment and health in Latin American populations

The Ibero-American Network of Pharmacogenetics and Pharmacogenomics (RIBEF) studies Latin American populations to benefit from the implementation of personalized medicine. Since 2006, it has studied ethnicity to apply pharmacogenetics knowledge in autochthonous populations of Latin America, considering ancestral medicine. The meeting 'Pharmacogenetics: ethnicity, Treatment and Health in Latin American Populations' was held in Mexico City, Mexico, and presented the relevance of RIBEF collaboration with Latin American researchers and the governments of Mexico, Spain and the Autonomous Community of Extremadura. The results of 17 years of uninterrupted work by RIBEF, the Declaration of Mérida/T'Hó and the call for the Dr José María Cantú Award for studies focused on the pharmacogenetics of native populations in Latin America were presented.

Prescription medications with actionable pharmacogenomic recommendations in Veterans Health Administration patients

Aim: To evaluate the prevalence of medications with actionable pharmacogenomic (PGx) safety and efficacy recommendations in patients receiving care from the Veterans Health Administration. Materials & methods: Outpatient prescription data from 2011 to 2021 and any documented adverse drug reactions (ADRs) were reviewed for those who received PGx testing at one Veterans Administration location between November 2019 and October 2021. Results: Among the reviewed prescriptions, 381 (32.8%) were associated with an actionable recommendation based on the Clinical Pharmacogenetics Implementation Consortium (CPIC) prescribing guidelines, with 205 (17.7%) for efficacy concerns and 176 (15.2%) for safety concerns. Among those with a documented ADR for a PGx-impacted medication, 39.1% had PGx results that aligned with CPIC recommendations. Conclusion: Medications with actionable PGx recommendations for safety and efficacy concerns are received with similar frequency, and most patients who have undergone PGx testing at the Phoenix Veterans Administration have received medications that may be impacted by PGx testing.

Potential Impact of Pharmacogenomic Single Nucleotide Variants in a Rural Caucasian Population

BACKGROUND

In the US adverse drug reactions (ADRs) are estimated to cause 100 000 fatalities and cost over $136 billion annually. A patient's genes play a significant role in their response to a drug. Pharmacogenomics aims to optimize drug choice and dose for individual patients by characterizing patients' pharmacologically relevant genes to identify variants of known impact.

METHODS

DNA was extracted from randomly selected remnant whole blood samples from Caucasian patients with previously performed complete blood counts. Samples were genotyped by mass spectrometry using a customized pharmacogenomics panel. A third-party result interpretation service used genotypic results to predict likely individual responses to frequently prescribed drugs.

RESULTS

Complete genotypic and phenotypic calls for all tested Cytochrome P450 isoenzymes and other genes were obtained from 152 DNA samples. Of these 152 unique genomic DNA samples, 140 had genetic variants suggesting dose adjustment for at least one drug. Cardiovascular and psychiatry drugs had the highest number of recommendations, which included United States Food and Drug Administration warnings for highly prescribed drugs metabolized by CYP2C19, CYP2C9, CYP2D6, HLA-A, and VKORC1.

CONCLUSIONS

Risk for each drug:gene pairing primarily depends upon the degree of predicted enzyme impairment or activation, width of the therapeutic window, and whether parent compound or metabolite is pharmacologically active. The resulting metabolic variations range from risk of toxicity to therapeutic failure. Pharmacogenomic profiling likely reduces ADR potential by allowing up front drug/dose selection to fit a patient's unique drug-response profile.

Evaluation of pharmacogenomic evidence for drugs related to ADME genes in CPIC database

OBJECTIVES

Clinical Pharmacogenetics Implementation Consortium (CPIC) is a platform that advances the pharmacogenomics (PGx) practice by developing evidence-based guidelines. The purpose of this study was to analyze the CPIC database for ADME related genes and their corresponding drugs, and evidence level for drug-gene pairs; and to determine the presence of these drug-gene pairs in the highest mortality diseases in the United States.

METHODS

CPIC database was evaluated for drug-gene pairs related to absorption, distribution, metabolism, and excretion (ADME) properties. National Vital Statistics from Centers for Disease Control and Prevention was used to identify the diseases with the highest mortality. CPIC levels are assigned to different drug-gene pairs based on varying levels of evidence as either A, B, C, or D. All drug-gene pairs assigned with A/B, B/C, or C/D mixed levels were excluded from this study. A stepwise exclusion process was followed to determine the prevalence of various ADME drug-gene pairs among phase I/II enzymes or transporters and stratify the drug-gene pairs relevant to different disease conditions most commonly responsible for death in the United States.

RESULTS

From a total of 442 drug-gene pairs in the CPIC database, after exclusion of 86 drug-gene pairs with levels A/B, B/C, or C/D, and 211 non-ADME related genes, 145 ADME related drug-gene pairs resulted. From the 145 ADME related drug-genes pairs, the following were the distribution of levels: Level A: 43 (30%), Level B: 22 (15%), Level C: 59 (41%), Level D: 21 (14%). The most prevalent ADME gene with CPIC level A classification was cytochrome P450 2C9 (CYP2C9) (26%) and overall, the most prevalent ADME gene in the CPIC database was CYP2D6 (30%). The most prevalent diseases related to the CPIC evidence related drugs were cancer and depression.

CONCLUSIONS

We found that there is an abundance of ADME related genes in the CPIC database, including in the high mortality disease states of cancer and depression. There is a differential level of pharmacogenomic evidence in drug-gene pairs enlisted in CPIC where levels A and D having the greatest number of drug-gene pairs. CYP2D6 was the most common ADME gene with CPIC evidence for drug-gene pairs. Pharmacogenomic applications of CPIC evidence can be leveraged to individualize patient therapy and lower adverse effect events.

Polygenic Pharmacogenomic Markers as Predictors of Toxicity Phenotypes in the Treatment of Acute Lymphoblastic Leukemia: A Single-Center Study

PURPOSE

Acute lymphoblastic leukemia (ALL) is the most prevalent cause of childhood cancer and requires a long course of therapy consisting of three primary phases with interval intensification blocks. Although these phases are necessary to achieve remission, the primary chemotherapeutic agents have potentially serious toxicities, which may lead to delays or discontinuations of therapy. The purpose of this study was to perform a comprehensive pharmacogenomic evaluation of common antileukemic agents and develop a polygenic toxicity risk score predictive of the most common toxicities observed during ALL treatment.

METHODS

This cross-sectional study included 75 patients with pediatric ALL treated between 2012 and 2020 at the University of Florida. Toxicity data were collected within 100 days of initiation of therapy using CTCAE v4.0 for toxicity grading. For pharmacogenomic evaluation, single-nucleotide polymorphisms (SNPs) and genes were selected from previous reports or PharmGKB database. 116 unique SNPs were evaluated for incidence of various toxicities. A multivariable multi-SNP modeling for up to 3-SNP combination was performed to develop a polygenic toxicity risk score of prognostic value.

RESULTS

We identified several SNPs predictive of toxicity phenotypes in univariate analysis. Further multivariable SNP-SNP combination analysis suggest that susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. For 3-SNPscore models, patients with high scores experienced increased risk of GI (P = 2.07E-05, 3 SNPs: TYMS-rs151264360/FPGS-rs1544105/GSTM1-GSTM5-rs3754446), neurologic (P = .0005, 3 SNPs: DCTD-rs6829021/SLC28A3-rs17343066/CTPS1-rs12067645), endocrine (P = 4.77E-08, 3 SNPs: AKR1C3-rs1937840/TYMS-rs2853539/CTH-rs648743), and heme toxicities (P = .053, 3 SNPs: CYP3A5-rs776746/ABCB1-rs4148737/CTPS1-rs12067645).

CONCLUSION

Our results imply that instead of a single-SNP approach, SNP-SNP combinations in multiple genes in drug pathways increases the robustness of prediction of toxicity. These results further provide promising SNP models that can help establish clinically relevant biomarkers allowing for greater individualization of cancer therapy to maximize efficacy and minimize toxicity for each patient.

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network

Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of external validation, lack of assessment for clinical utility, and high risk of bias. Moreover, given the high degree of heterogeneity across different datasets used to develop these algorithms, it is unsurprising that prediction errors remain high, and dosing accuracy is dependent on specific ethnic populations. To circumvent these challenges, deep neural models are increasingly used to improve the precision and accuracy of warfarin dose predictions. Hence, this study sought to develop a deep learning-based model using a well-established curated dataset of over 6000 patients from the International Warfarin Pharmacogenomics Consortium (IWPC). Clinically-relevant input data such as physical attributes, medical conditions, concomitant medications, genotype status of functional warfarin genetic polymorphisms, and therapeutic INR were entered followed by applying a unique and robust training and validation method. The deep model yielded a low average mean absolute error (MAE) of 7.6 mg/week and a relatively low mean percentage of error of 40.9% in Asians, 14.2 mg/week MAE and 36.9% in African Americans, and 12.7 mg/week MAE and 45.4% mean percentage of error in White Caucasians. This model also resulted in 36.4% of all patients with a predicted dose within 20% of the administered dose. Hence, our proposed deep model provides an alternative to predicting warfarin dose in the clinical setting upon validation in ethnically-similar datasets.

Genomic medicine in Africa: a need for molecular genetics and pharmacogenomics experts

The large-scale implementation of genomic medicine in Africa has not been actualized. This overview describes how routine molecular genetics and advanced protein engineering/structural biotechnology could accelerate the implementation of genomic medicine. By using data-mining and analysis approaches, we analyzed relevant information obtained from public genomic databases on pharmacogenomics biomarkers and reviewed published studies to discuss the ideas. The results showed that only 68 very important pharmacogenes currently exist, while 867 drug label annotations, 201 curated functional pathways, and 746 annotated drugs have been catalogued on the largest pharmacogenomics database (PharmGKB). Only about 5009 variants of the reported ∼25,000 have been clinically annotated. Predominantly, the genetic variants were derived from 43 genes that contribute to 2318 clinically relevant variations in 57 diseases. Majority (∼60%) of the clinically relevant genetic variations in the pharmacogenes are missense variants (1390). The enrichment analysis showed that 15 pharmacogenes are connected biologically and are involved in the metabolism of cardiovascular and cancer drugs. The review of studies showed that cardiovascular diseases are the most frequent non-communicable diseases responsible for approximately 13% of all deaths in Africa. Also, warfarin pharmacogenomics is the most studied drug on the continent, while CYP2D6, CYP2C9, DPD, and TPMT are the most investigated pharmacogenes with allele activities indicated in African and considered to be intermediate metaboliser for DPD and TPMT (8.4% and 11%). In summary, we highlighted a framework for implementing genomic medicine starting from the available resources on ground.

Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy

Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.

Pharmacogenomics-a New Frontier for Individualized Treatment of Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disease with a significant public health burden. It is characterized by the gradual degeneration of dopamine neurons in the central nervous system. Although symptomatic pharmacological management remains the primary therapeutic method for PD, clinical experience reveals significant inter-individual heterogeneity in treatment effectiveness and adverse medication responses. The mechanisms behind the observed interindividual variability may be elucidated by investigating the role of genetic variation in human-to-human variances in medication responses and adverse effects.

OBJECTIVE

This review aims to explore the impact of gene polymorphism on the efficacy of antiparkinsonian drugs. The identification of factors associated with treatment effectiveness variability might assist the creation of a more tailored pharmacological therapy with higher efficacy, fewer side outcomes, and cheaper costs.

METHODS

In this review, we conducted a thorough search in databases such as PubMed, Web of Science, and Google Scholar, and critically examined current discoveries on Parkinson's disease pharmacogenetics. The ethnicity of the individuals, research methodologies, and potential bias of these studies were thoroughly compared, with the primary focus on consistent conclusions.

RESULTS

This review provides a summary of the existing data on PD pharmacogenetics, identifies its limitations, and offers insights that may be beneficial for future research. Previous studies have investigated the impact of gene polymorphism on the effectiveness and adverse effects of levodopa. The trendiest genes are the COMT gene, DAT gene, and DRD2 gene. However, limited study on other anti-Parkinson's drugs has been conducted.

CONCLUSION

Therefore, In order to develop an individualized precision treatment for PD, it is an inevitable trend to carry out multi-center, prospective, randomized controlled clinical trials of PD pharmacogenomics covering common clinical anti-PD drugs in large, homogeneous cohorts.

[The relationship of cytochrome P450 isoforms with the efficacy and safety of antipsychotic and antidepressant therapy]

Cytochrome P450 (CYP450) is the leading enzyme in the biotransformation of most psychotropic drugs. CYP450 gene polymorphisms determine a patient's endophenotype with respect to the activity of enzymes of the family and affect the metabolism of prescribed antipsychotics and antidepressants. Categorizing patients by endophenotype during genotyping is likely to help simplify the selection of therapy in clinical practice. Co-prescribing drugs that may be inhibitors or inducers of CYP450 isoforms, in turn, may lead to adverse reactions or no effect of therapy. The article presents a compilation of known pharmacogenetic recommendations regarding the four major endophenotypes of metabolizers.

Pharmacogenomic and Statistical Analysis

Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.

Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts

Thoughtful integration of interruptive clinical decision support (CDS) alerts within the electronic health record is essential to guide clinicians on the application of pharmacogenomic results at point of care. St. Jude Children's Research Hospital implemented a preemptive pharmacogenomic testing program in 2011 in a multidisciplinary effort involving extensive education to clinicians about pharmacogenomic implications. We conducted a retrospective analysis of clinicians' adherence to 4783 pharmacogenomically guided CDS alerts that triggered for 12 genes and 60 drugs. Clinicians adhered to the therapeutic recommendations provided in 4392 alerts (92%). In our population of pediatric patients with catastrophic illnesses, the most frequently presented gene/drug CDS alerts were TPMT/NUDT15 and thiopurines (n = 3850), CYP2D6 and ondansetron (n = 667), CYP2D6 and oxycodone (n = 99), G6PD and G6PD high-risk medications (n  = 51), and CYP2C19 and proton pump inhibitors (omeprazole and pantoprazole; n = 50). The high adherence rate was facilitated by our team approach to prescribing and our collaborative CDS design and delivery.

Leveraging a pharmacogenomics knowledgebase to formulate a drug response phenotype terminology for genomic medicine

MOTIVATION

Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships. In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic variants and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for 'Genes and Gene Products' and 'Treatments'.

RESULTS

Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18 653 sentences that contained both 'Genes and Gene Products' and 'Treatments', 3011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829) and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic variants and treatments. In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Role of Genetic Polymorphisms in Drug-Metabolizing Enzyme-Mediated Toxicity and Pharmacokinetic Resistance to Anti-Cancer Agents: A Review on the Pharmacogenomics Aspect

The inter-individual differences in cancer susceptibility are somehow correlated with the genetic differences that are caused by the polymorphisms. These genetic variations in drug-metabolizing enzymes/drug-inactivating enzymes may negatively or positively affect the pharmacokinetic profile of chemotherapeutic agents that eventually lead to pharmacokinetic resistance and toxicity against anti-cancer drugs. For instance, the CYP1B1*3 allele is associated with CYP1B1 overexpression and consequent resistance to a variety of taxanes and platins, while 496T>G is associated with lower levels of dihydropyrimidine dehydrogenase, which results in severe toxicities related to 5-fluorouracil. In this context, a pharmacogenomics approach can be applied to ascertain the role of the genetic make-up in a person's response to any drug. This approach collectively utilizes pharmacology and genomics to develop effective and safe medications that are devoid of resistance problems. In addition, recently reported genomics studies revealed the impact of many single nucleotide polymorphisms in tumors. These studies emphasized the importance of single nucleotide polymorphisms in drug-metabolizing enzymes on the effect of anti-tumor drugs. In this review, we discuss the pharmacogenomics aspect of polymorphisms in detail to provide an insight into the genetic manipulations in drug-metabolizing enzymes that are responsible for pharmacokinetic resistance or toxicity against well-known anti-cancer drugs. Special emphasis is placed on different deleterious single nucleotide polymorphisms and their effect on pharmacokinetic resistance. The information provided in this report may be beneficial to researchers, especially those who are working in the field of biotechnology and human genetics, in rationally manipulating the genetic information of patients with cancer who are undergoing chemotherapy to avoid the problem of pharmacokinetic resistance/toxicity associated with drug-metabolizing enzymes.

Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial

BACKGROUND

Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care.

METHODS

The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers.

RESULTS

Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow.

CONCLUSIONS

Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.

Attitudes on pharmacogenomic results as secondary findings among medical geneticists

OBJECTIVES

As evidence mounts supporting the utility of pharmacogenomic-guided medication management, incorporating pharmacogenomic genes into secondary finding results from sequencing panels is increasingly under consideration. We studied medical geneticists' attitudes on receiving pharmacogenomic results as secondary finding.

METHODS

Four focus groups with 16 medical geneticists total were conducted followed by thematic analysis.

RESULTS

All participants ordered genetic sequencing tests; however, the majority had rarely or never ordered pharmacogenomic tests (10/16) or prescribed medications with established response variability (11/16). In total 81.3% expressed low comfort interpreting pharmacogenomic results without appropriate clinical resources (13/16). The positives of receiving pharmacogenomic results as secondary finding included prevention of adverse drug reactions in adults, grateful information-seeking patients, the ability to rapidly prescribe more effective treatments and appreciation of the recent advances in both pharmacogenomic knowledge and available guidelines. Negatives included laboratory reporting issues, exclusivity of pharmacogenomic results to certain populations, lengthy reports concealing pharmacogenomic results in patient charts and laboratories marketing to individuals without prior pharmacogenomic knowledge or targeting inappropriate populations. The most desirable pharmacogenomic resources included a universal electronic health record clinical decision support tool to assist identifying and implementing pharmacogenomic results, a specialized pharmacist as part of the care team, additional pharmacogenomic training during medical/graduate school, and a succinct interpretation of pharmacogenomic results included on laboratory reports.

CONCLUSIONS

The majority of participants agreed that adding certain actionable pharmacogenomic genes to the American College of Medical Genetics and Genomics SF list is reasonable; however, this was qualified with a need for additional resources to support implementation.

Fetal pharmacogenomics: A promising addition to complex neonatal care

OBJECTIVE

Pharmacogenomics (PGx) characterizes genetic variation in medication response. 85-95% of the population carries actionable PGx variants. No prior studies have demonstrated the application and feasibility of PGx in prenatal testing. We assessed parental desire for PGx findings from fetal exome sequencing (ES), evaluated PGx variants, and reviewed implications for medically complex neonates.

METHODS

A prospective cohort undergoing ES for nonimmune hydrops fetalis were offered PGx results as a secondary finding. Seven pharmacogenes with Level A evidence, defined by Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, were tested and reported to patients and referring providers. Medication administration records were reviewed.

RESULTS

Most participants (36/40, 90%) desired PGx testing. 32/36 (89%) had potentially actionable PGx diplotypes in six genes: CYP2C19 (20/36, 56%), CYP2C9 (16/36, 44%), CYP2D6 (10/36, 28%), SLCO1B1 (13/36, 36%), TPMT (6/36, 17%), UGT1A1 (4/36, 11%). 12/13 (92%) live births had PGx variants. Neonatal chart review indicated that three medications with CPIC Level A evidence were administered to four neonates. None of the patients received a medication that aligned with an actionable pharmacogenetic variant as defined by Level A CPIC guidance.

CONCLUSION

Most participants opted to receive PGx results. 89% had actionable variants, consistent with population estimates. Obtaining fetal PGx data is feasible for medically complex neonates. Further studies are needed for broad clinical application of PGx in fetuses with major congenital abnormalities. Our study demonstrates the potential of PGx as useful preemptive clinical information that could be obtained at the time of fetal exome sequencing for other indications.

CLINICALTRIALS

gov Registration: NCT03911531.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

Population genetic polymorphisms of pharmacogenes in Zimbabwe, a potential guide for the safe and efficacious use of medicines in people of African ancestry

OBJECTIVE

Pharmacogenomics (PGx) is a clinically significant factor in the safe and efficacious use of medicines. While PGx knowledge is abundant for other populations, there are scarce PGx data on African populations and is little knowledge on drug-gene interactions for medicines used to treat diseases common in Africa. The aim of this study was to use a custom-designed open array to genotype clinically actionable variants in a Zimbabwean population. This study also identified some of the commonly used drugs in Zimbabwe and the associated genes involved in their metabolism.

METHODS

A custom-designed open array that covers 120 genetic variants was used to genotype 522 black Zimbabwean healthy volunteers using TaqMan-based single nucleotide polymorphism genotyping. Data were also accessed from Essential Drugs' List in Zimbabwe (EDLIZ), and the medicines were grouped into the associated biomarker groups based on their metabolism. We also estimated the national drug procurement levels for medicines that could benefit from PGx-guided use based on the data obtained from the national authorities in Zimbabwe.

RESULTS

The results demonstrate the applicability of an open-array chip in simultaneously determining multiple genetic variants in an individual, thus significantly reducing cost and time to generate PGx data. There were significantly high frequencies of African-specific variants, such as the CYP2D6*17 and *29 variants and the CYP2B6*18 variant. The data obtained showed that the Zimbabwean population exhibits PGx variations in genes important for the safe and efficacious use of drugs approved by the EDLIZ and are procured at significantly large amounts annually. The study has established a cohort of genotyped healthy volunteers that can be accessed and used in the conduct of clinical pharmacogenetic studies for drugs entering a market of people of predominantly African ancestry.

CONCLUSION

Our study demonstrated the potential benefit of integrating PGx in Zimbabwe for the safe and efficacious use of drugs that are commonly used.

Anesthesia providers as stakeholders to adoption of pharmacogenomic information in perioperative care

OBJECTIVES

Integration of pharmacogenomics into clinical care is being studied in multiple disciplines. We hypothesized that understanding attitudes and perceptions of anesthesiologists, critical care and pain medicine providers would uncover unique considerations for future implementation within perioperative care.

METHODS

A survey (multiple choice and Likert-scale) was administered to providers within our Department of Anesthesia and Critical Care prior to initiation of a department-wide prospective pharmacogenomics implementation program. The survey addressed knowledge, perceptions, experiences, resources and barriers.

RESULTS

Of 153 providers contacted, 149 (97%) completed the survey. Almost all providers (92%) said that genetic results influence drug therapy, and few (22%) were skeptical about the usefulness of pharmacogenomics. Despite this enthusiasm, 87% said their awareness about pharmacogenomic information is lacking. Feeling well-informed about pharmacogenomics was directly related to years in practice/experience: only 38% of trainees reported being well-informed, compared to 46% of those with 1-10 years of experience, and nearly two-thirds with 11+ years (P < 0.05). Regarding barriers, providers reported uncertainty about availability of testing, turnaround time and whether testing is worth financial costs.

CONCLUSIONS

Anesthesiology, critical care and pain medicine providers are optimistic about the potential clinical utility of pharmacogenomics, but are uncertain about practical aspects of testing and desire clear guidelines on the use of results. These findings may inform future institutional efforts toward greater integration of genomic results to improve medication-related outcomes.

Role of Pharmacogenomics in Individualizing Treatment for Alzheimer's Disease

The development of Alzheimer's disease therapeutics has been challenging, with 99% of clinical trials failing to find a significant difference between drug and placebo. While the quest continues for more effective treatments, there is emerging evidence that pharmacogenetic considerations are important factors in regard to metabolism, efficacy, and toxicity of drugs. Currently, there are five US Food and Drug Administration-approved drugs for the treatment of Alzheimer's disease; three acetylcholinesterase inhibitors, memantine, and aducanumab. Introducing a limited genetic panel consisting of APOE4, CYP2D6*10, and BChE*K would optimize acetylcholinesterase inhibitor therapy, facilitate immunotherapy risk assessment, and inform an amyloid-related imaging abnormality surveillance schedule. In view of the genetic heterogeneity of Alzheimer's disease identified in genome-wide association studies, pharmacogenetics is expected to play an increasing role in mechanism-specific treatment strategies and personalized medicine.