Standardized Biogeographic Grouping System for Annotating Populations in Pharmacogenetic Research

Semi-physiological Pharmacokinetic Model of Clozapine and Norclozapine in Healthy, Non-smoking Volunteers: The Impact of Race and Genetics

BACKGROUND AND OBJECTIVES: Clozapine is the medication of choice for treatment-resistant schizophrenia. However, it has a complex metabolism and unexplained interindividual variability. The current work aims to develop a pharmacokinetic model of clozapine and norclozapine in non-smokers and assess the impact of demographic and genetic predictors.

METHODS

Healthy volunteers were recruited in a population pharmacokinetic study. Blood samples were collected at 30 min and 1, 2, 3, 5 and 8 h following a single flat dose of clozapine (12.5 mg). The clozapine and norclozapine concentrations were measured via high-performance liquid chromatography-ultraviolet method. A semi-physiological pharmacokinetic model of clozapine and norclozapine was developed using nonlinear mixed-effects modeling. Clinical and genetic predictors were evaluated, including CYP1A2 (rs762551) and ABCB1 (rs2032582), using restriction fragment length polymorphism.

RESULTS

A total of 270 samples were collected from 33 participants. The data were best described using a two-compartment model for clozapine and a two-compartment model for norclozapine with first-order absorption and elimination and pre-systemic metabolism. The estimated (relative standard error) clearance of clozapine and norclozapine were 27 L h-1 (31.5 %) and 19.6 L h-1 (30%), respectively. Clozapine clearance was lower in sub-Saharan Africans (n = 4) and higher in Caucasians (n = 9) than Asians (n = 20). Participants with CYP1A2 (rs762551) (n = 18) and ABCB1 (rs2032582) (n = 12) mutant alleles had lower clozapine clearance in the univariate analysis.

CONCLUSIONS

This is the first study to develop a semi-physiological pharmacokinetic model of clozapine and norclozapine accounting for the pre-systemic metabolism. Asians required lower doses of clozapine as compared with Caucasians, while clozapine pharmacokinetics in sub-Saharan Africans should be further investigated in larger trials.

Genetic variation in UGT1A1 is not associated with altered liver biochemical parameters in healthy volunteers participating in bioequivalence trials

Introduction: Bioequivalence clinical trials are conducted in healthy volunteers whose blood tests should be within normal limits; individuals with Gilbert syndrome (GS) are excluded from these studies on suspicion of any liver disease, even if the change is clinically insignificant. GS is a benign genetic disorder characterized by elevated bilirubin levels, the primary cause of which is the presence of polymorphisms in UGT1A1 gene. In this work, subjects with UGT1A1 intermediate (IM) or poor (PM) metabolizer genotype-informed phenotypes were investigated to determine whether they have a higher incidence of liver disease or other biochemical parameters. Methods: The study population comprised 773 healthy volunteers who underwent biochemical analysis at baseline and at the end of the study which were genotyped for UGT1A1*80 (rs887829), as an indicator of UGT1A1*80+*28 (rs887829 and rs3064744), and UGT1A1*6 (rs4148323). Results: Bilirubin levels were higher in subjects IMs and PMs compared to normal metabolizers (NMs). Decreased uric acid levels was observed in PMs compared to NMs. No associations were observed in liver enzyme levels according to UGT1A1 phenotype. Discussion: Considering that there is no hepatic toxicity in subjects with UGT1A1 IM or PM phenotype, who are more likely to develop GS, this study suggests that they could be included in bioequivalence clinical trials as their biochemical parameters are not affected outside normal ranges.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol

BACKGROUND

Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD.

METHODS AND ANALYSIS

Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep.

CONCLUSION

SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank

Importance

Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings.

Objective

To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings.

Design, Setting, and Participants

This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023.

Main Outcomes and Measures

A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression.

Results

The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis.

Conclusions and Relevance

Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

Estimation of the benefit from pre-emptive genotyping based on the nationwide cohort data in South Korea

Genetic variants affect drug responses, making pre-emptive genotyping crucial for averting serious adverse events (SAEs) and treatment failure. However, assessing the benefits of pre-emptive genotyping based on genetic distribution, drug exposure, and demographics is challenging. This study aimed to estimate the population-level benefits of pre-emptive genotyping in the Korean population using nationwide cohort data. We reviewed actionable gene-drug combinations recommended by both the Clinical Pharmacogenomics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) as of February 2022, identifying high-risk phenotypes. We collected reported risk reduction from genotyping and standardized it into population attributable risks. Healthcare reimbursement costs for SAEs and treatment failures were obtained from the Health Insurance Review and Assessment Service Statistics in 2021. The benefits of pre-emptive genotyping for a specific group were determined by multiplying drug exposure from nationwide cohort data by individual genotyping benefits. We identified 31 gene-drug-event pairs, with CYP2D6 and CYP2C19 demonstrating the greatest benefits for both male and female patients. Individuals aged 65-70 years had the highest individual benefit from pre-emptive genotyping, with $84.40 for men and $100.90 for women. Pre-emptive genotyping, particularly for CYP2D6 and CYP2C19, can provide substantial benefits.

Addressing Ancestry and Sex Bias in Pharmacogenomics

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcaseCYP2D6, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

The Intersection between Pharmacogenomics and Health Equity: A Case Example

Pharmacogenomics (PGx) and the study of precision medicine has substantial power to either uplift health equity efforts or further widen the gap of our already existing health disparities. In either occurrence, the medication experience plays an integral role within this intersection on an individual and population level. Examples of this intertwined web are highlighted through a case discussion. With these perspectives in mind, several recommendations for the research and clinical communities are highlighted to promote equitable healthcare with PGx integrated.

The Frequency of CYP2D6 and CYP3A4/5 Genotypes and The Impact of Their Allele Translation and Phenoconversion-Predicted Enzyme Activity on Risperidone Pharmacokinetics in Saudi Children with Autism

Data on the role of CYP2D6 and CYP3A4/5 polymorphisms in relation to risperidone (RIS) pharmacokinetics (PK) in children are relatively limited and inconsistent. This is partially attributable to the limited coverage of CYP2D6 and CYP3A4/5 metabolizer phenotypes, particularly those of poor and ultrarapid metabolizers (PMs and UMs), which has led to calls for studies of populations with a non-European background that may carry variants that are less frequent in Europeans. Children ≤ 18 years old with at least 8 weeks of a RIS-based regimen were recruited from three autism centers in Riyadh, Saudi Arabia. The primary outcomes measured were plasma concentrations of RIS and 9-hydroxyrisperidone (9-OH-RIS) and their dose-adjusted (C/D) ratios as a function of phenotypes and activity score (AS). For accurate DNA genotyping, targeted pharmacogenomic testing with the Axiom PharmacoFocus Array was performed via examination of a broad collection of probesets targeting CYP2D6 and CYP3A4/5 variants. The frequency of genotypes/phenotypes and the impact of their allele translation and phenoconversion-predicted enzyme activity were examined. The final cohort included 83 individuals. The most common CYP2D6 phenotype in our population was normal metabolizers (NMs, 66.3%). Inconsistent with some previous studies, the three phenotypes of intermediate metabolizers (IMs), NMs, and UMs were significantly different in terms of RIS concentration, the RIS/9-OH-RIS ratio, the RIS C/D ratio and the 9-OH-RIS C/D ratio. According to AS analyses, there were statistically significant differences in the RIS concentration (P = 0.013), RIS/9-OH-RIS ratio (P < 0.001) and RIS C/D ratio (P = 0.030) when patients were categorized into AS ≤ 1 vs. AS > 1. None of the CYP3A4/5 star allele translated phenotypes revealed a significant influence on any of the RIS PK parameters. Notably, neither CYP2D6 nor CYP3A4/5 phenotyping demonstrated a significant impact on the total active moiety, suggesting that other gene variants could modulate RIS PK. The study confirmed the previously reported partial impact of the CYP2D6 gene on RIS PK. However, future studies using contemporary genotyping techniques targeting a wide range of variants in other candidate genes must be conducted to further examine their interactive effects on RIS PK and the clinical response.

Ethnopsychopharmacology: Clinical and scientific writing pearls

The concept of ethnopsychopharmacology aims to predict or explain the pharmacologic response to psychiatric medications based on the influence of biologic and nonbiologic factors. Interactions involving these factors are complex and influence patient outcomes in health care. Pharmacists and other clinicians working in patient care environments, research, or medical education should engage in lifelong learning to enhance ethnopsychopharmacologic knowledge gaps, which ultimately may improve and individualize care across diverse populations. Through two cases, this paper provides pearls on how biogeographical ancestry and cytochrome P450 status may influence pharmacotherapy selection, dosing, or response. A third scenario highlights a publication, like many other published works, with deficiencies in how data on ancestry, race, and ethnicity are collected or reported. Current recommendations on the use of inclusive language in scientific writing are reviewed, with attention to specific examples.

CYP2D6 and CYP2C19 Variant Coverage of Commercial Antidepressant Pharmacogenomic Testing Panels Available in Victoria, Australia

Pharmacogenomic (PGx) testing to inform antidepressant medication selection and dosing is gaining attention from healthcare professionals, patients, and payors in Australia. However, there is often uncertainty regarding which test is most suitable for a particular patient. Here, we identified and evaluated the coverage of CYP2D6 and CYP2C19 variants in commercial antidepressant PGx testing panels in Victoria, a large and ethnically diverse state of Australia. Test characteristics and star alleles tested for both genes were obtained directly from pathology laboratories offering PGx testing and compared against the Association of Molecular Pathology's recommended minimum (Tier 1) and extended (Tier 2) allele sets. Although all tests covered the minimum recommended alleles for CYP2C19, this was not the case for CYP2D6. This study emphasizes that PGx tests might not be suitable for all individuals in Australia due to the limited range of star alleles assessed. Inadequate haplotype coverage may risk misclassification of an individual's predicted metabolizer phenotype, which has ramifications for depression medication selection and dosage. This study underscores the urgent need for greater standardization in PGx testing and emphasizes the importance of considering genetic ancestry when choosing a PGx testing panel to ensure optimal clinical applicability.

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.

NAT2 phenotype alters pharmacokinetics of rivaroxaban in healthy volunteers

Rivaroxaban is a direct inhibitor of factor Xa, a member of direct oral anticoagulant group of drugs (DOACs). Despite being a widely extended alternative to vitamin K antagonists (i.e., acenocoumarol, warfarin) the interindividual variability of DOACs is significant, and may be related to adverse drug reaction occurrence or drug inefficacy, namely hemorrhagic or thromboembolic events. Since there is not a consistent analytic practice to monitor the anticoagulant activity of DOACs, previously reported polymorphisms in genes coding for proteins responsible for the activation, transport, or metabolism of DOACs were studied. The study population comprised 60 healthy volunteers, who completed two randomized, crossover bioequivalence clinical trials between two different rivaroxaban formulations. The effect of food, sex, biogeographical origin and 55 variants (8 phenotypes and 47 single nucleotide polymorphisms) in drug metabolizing enzyme genes (such as CYP2D6, CYP2C9, NAT2) and transporters (namely, ABCB1, ABCG2) on rivaroxaban pharmacokinetics was tested. Individuals dosed under fasting conditions presented lower tmax (2.21 h vs 2.88 h, β = 1.19, R2 =0.342, p = 0.012) compared to fed volunteers. NAT2 slow acetylators presented higher AUC∞ corrected by dose/weight (AUC∞/DW; 8243.90 vs 7698.20 and 7161.25 h*ng*mg /ml*kg, β = 0.154, R2 =0.250, p = 0.044), higher Cmax/DW (1070.99 vs 834.81 and 803.36 ng*mg /ml*kg, β = 0.245, R2 =0.320, p = 0.002), and lower tmax (2.63 vs 3.19 and 4.15 h, β = -0.346, R2 =0.282, p = 0.047) than NAT2 rapid and intermediate acetylators. No other association was statistically significant. Thus, slow NAT2 appear to have altered rivaroxaban pharmacokinetics, increasing AUC∞ and Cmax. Nonetheless, further research should be conducted to verify NAT2 involvement on rivaroxaban pharmacokinetics and to determine its clinical significance.

CYP3A4 and CYP3A5 Genotyping Recommendations: A Joint Consensus Recommendation of the Association for Molecular Pathology, Clinical Pharmacogenetics Implementation Consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document will focus on clinical CYP3A4 and CYP3A5 PGx testing that may be applied to all CYP3A4- and CYP3A5-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.

CYP2C19 Genotype Prevalence and Association With Recurrent Myocardial Infarction in British-South Asians Treated With Clopidogrel

Background

Cytochrome P450 family 2 subfamily C member 19 (CYP2C19) is a hepatic enzyme involved in the metabolism of clopidogrel from a prodrug to its active metabolite. Prior studies of genetic polymorphisms in CYP2C19 and their relationship with clinical efficacy have not included South Asian populations.

Objectives

The objective of this study was to assess prevalence of common CYP2C19 genotype polymorphisms in a British-South Asian population and correlate these with recurrent myocardial infarction risk in participants prescribed clopidogrel.

Methods

The Genes & Health cohort of British Bangladeshi and Pakistani ancestry participants were studied. CYP2C19 diplotypes were assessed using array data. Multivariable logistic regression was used to test for association between genetically inferred CYP2C19 metabolizer status and recurrent myocardial infarction, controlling for known cardiovascular disease risk factors, percutaneous coronary intervention, age, sex, and population stratification.

Results

Genes & Health cohort participants (N = 44,396) have a high prevalence (57%) of intermediate or poor CYP2C19 metabolizers, with at least 1 loss-of-function CYP2C19 allele. The prevalence of poor metabolizers carrying 2 CYP2C19 loss-of-function alleles is 13%, which is higher than that in previously studied European (2.4%) and Central/South Asian populations (8.2%). Sixty-nine percent of the cohort who were diagnosed with an acute myocardial infarction were prescribed clopidogrel. Poor metabolizers were significantly more likely to have a recurrent myocardial infarction (OR: 3.1; P = 0.019).

Conclusions

A pharmacogenomic-driven approach to clopidogrel prescribing has the potential to impact significantly on clinical management and outcomes in individuals of Bangladeshi and Pakistani ancestry.

A Genetics-Focused Lens on Social Constructs in Pharmacy Education

OBJECTIVE

Incorporating diversity, equity, inclusion, and anti-racism principles into clinical and didactic education is essential because each influence cognitive and affective attitudes in pharmacy practice. Educators must learn from the past to enlighten the future. For example, race is a social construct, not a biological construct. However, it persistently acts as a surrogate for determining medical diagnoses and treatment.

FINDINGS

Precision medicine and pharmacogenomics can serve as a basis for deconstructing social constructs surrounding race and other social determinants of health.

SUMMARY

In this review, the authors highlight why using race in health education will lead to less-than-optimal clinical decisions and discuss best practices for incorporating diversity, equity, inclusion, and anti-racism into health education from a pharmacogenomic-based perspective.

Pharmacogenomic implications of the differential distribution of CYP2C9 metabolic phenotypes among Latin American populations

The CYP2C9 gene encodes the major drug metabolism enzyme CYP2C9. This gene is highly polymorphic, and no-function (CYP2C9*3) plus decreased function (CYP2C9*2, *5, *8 and *11) star alleles (haplotypes) are commonly used to predict CYP2C9 metabolic phenotypes. This study explores the pharmacogenomic implications of the differential distribution of genotype-predicted CYP2C9 phenotypes across Latin American populations. Data from 1,404 individuals from the South American countries Brazil, Colombia and Peru, from Puerto Rico in the Caribbean and from persons with Mexican ancestry living in North America were analysed. The results showed that the distribution of CYP2C9 alleles and diplotypes, and diplotype-predicted CYP2C9 phenotypes vary significantly across the distinct country cohorts, as well as among self-identified White, Brown and Black Brazilians. Differences in average proportions of biogeographical ancestry across the study groups, especially Native American and African ancestry, are the likely explanation for these results. The differential distribution of genotype-predicted CYP2C9 phenotypes has potentially clinically-relevant pharmacogenomic implications, through its influence on the proportion of individuals at high risk for adverse response to medications that are CYP2C9 substrates, the proportion on individuals with CPIC therapeutic recommendations for dosing and choice of nonsteroidal antinflammatory drugs (NSAIDs) and the number of individuals that need to be genotyped in order to prevent adverse effects of NSAIDs. Collectively, these findings are likely to impact the perceived benefits, cost-effectiveness and clinical adoption of pharmacogenomic screening for drugs that are predominantly metabolized by CYP2C9.

The Value of Pharmacogenomics for White and Indigenous Americans after Kidney Transplantation

BACKGROUND

There is a paucity of evidence to inform the value of pharmacogenomic (PGx) results in patients after kidney transplant and how these results differ between Indigenous Americans and Whites. This study aims to identify the frequency of recommended medication changes based on PGx results and compare the pharmacogenomic (PGx) results and patients' perceptions of the findings between a cohort of Indigenous American and White kidney transplant recipients.

METHODS

Thirty-one Indigenous Americans and fifty White kidney transplant recipients were studied prospectively. Genetic variants were identified using the OneOme RightMed PGx test of 27 genes. PGx pharmacist generated a report of the genetic variation and recommended changes. Pre- and post-qualitative patient surveys were obtained.

RESULTS

White and Indigenous American subjects had a similar mean number of medications at the time of PGx testing (mean 13 (SD 4.5)). In the entire cohort, 53% received beta blockers, 30% received antidepressants, 16% anticoagulation, 47% pain medication, and 25% statin therapy. Drug-gene interactions that warranted a clinical action were present in 21.5% of patients. In 12.7%, monitoring was recommended. Compared to the Whites, the Indigenous American patients had more normal CYP2C19 (p = 0.012) and CYP2D6 (p = 0.012) activities. The Indigenous American patients had more normal CYP4F2 (p = 0.004) and lower VKORC (p = 0.041) activities, phenotypes for warfarin drug dosing, and efficacy compared to the Whites. SLC6A4, which affects antidepressant metabolism, showed statistical differences between the two cohorts (p = 0.017); specifically, SLC6A4 had reduced expression in 45% of the Indigenous American patients compared to 20% of the White patients. There was no significant difference in patient perception before and after PGx.

CONCLUSIONS

Kidney transplant recipients had several drug-gene interactions that were clinically actionable; over one-third of patients were likely to benefit from changes in medications or drug doses based on the PGx results. The Indigenous American patients differed in the expression of drug-metabolizing enzymes and drug transporters from the White patients.

Race, Ethnicity, and Pharmacogenomic Variation in the United States and the United Kingdom

The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Isavuconazole Exposure in Critically Ill Patients Treated with Extracorporeal Membrane Oxygenation: Two Case Reports and a Narrative Literature Review

Effective dosing of isavuconazole in patients supported by extracorporeal membrane oxygenation (ECMO) is important due to the role of isavuconazole as a first-line treatment in patients with influenza- and COVID-19-associated pulmonary aspergillosis. To date, robust pharmacokinetic data in patients supported by ECMO are limited. Therefore, it is unknown whether ECMO independently impacts isavuconazole exposure. We measured isavuconazole plasma concentrations in two patients supported by ECMO and estimated individual pharmacokinetic parameters using non-compartmental analysis and two previously published population pharmacokinetic models. Furthermore, a narrative literature review on isavuconazole exposure in adult patients receiving ECMO was performed. The 24 h areas under the concentration-time curve and trough concentrations of isavuconazole were lower in both patients compared with exposure values published before. In the literature, highly variable isavuconazole concentrations have been documented in patients with ECMO support. The independent effect of ECMO versus critical illness itself on isavuconazole exposure cannot be deduced from our and previously published (case) reports. Pending additional data, therapeutic drug monitoring is recommended in critically ill patients, regardless of ECMO support.

Interdisciplinary Collaboration Among Nursing and Computer Science to Refine a Pharmacogenetics Clinical Decision Support Tool Via Mobile Application

In previous work, a prototype clinical decision support mobile application was created that accepts a patient's genomic profile information and provides information and rationale for the prescription of certain oncology medications. The response to the instrument was overwhelmingly positive by healthcare providers in the oncology field who tested the instrument. This article reports on the interdisciplinary collaboration among nursing and computer science to redesign and reimplement a new version of the instrument with expanded functionality and improved usability. This article describes the functionality, usability considerations, and usability evaluation of the instrument over three versions. The current version is Web-based and responsive to different screen sizes (desktop, tablet, mobile), features improved usability, and expands the number of gene-drug recommendations provided based on Clinical Pharmacogenetics Implementation Consortium dosing guidelines. This project represents a successful new collaboration between the nursing and computer science disciplines.

The Evaluation of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 Phenoconversion in Post-Mortem Casework: The Challenge of Forensic Toxicogenetics

In toxicogenetics, an integrative approach including the prediction of phenotype based on post-mortem genotyping of drug-metabolising enzymes might help explain the cause of death (CoD) and manner of death (MoD). The use of concomitant drugs, however, might lead to phenoconversion, a mismatch between the phenotype based on the genotype and the metabolic profile actually observed after phenoconversion. The aim of our study was to evaluate the phenoconversion of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 drug-metabolising enzymes in a series of autopsy cases tested positive for drugs that are substrates, inducers, or inhibitors of these enzymes. Our results showed a high rate of phenoconversion for all enzymes and a statistically significant higher frequency of poor and intermediate metabolisers for CYP2D6, CYP2C9, and CYP2C19 after phenoconversion. No association was found between phenotypes and CoD or MoD, suggesting that, although phenoconversion might be useful for a forensic toxicogenetics approach, more research is needed to overcome the challenges arising from the post-mortem setting.

The frequency of major ABCG2, SLCO1B1 and CYP2C9 variants in Asian, Native Hawaiian and Pacific Islander women subgroups: implications for personalized statins dosing

Aim: The frequencies of SLCO1B1*5 and CYP2C9*2 and *3 in specific Asian, Native Hawaiian and Pacific Islander (NHPI) subgroups are unknown. Patients & methods: Repository DNA samples from 1064 women self-identifying as Filipino, Korean, Japanese, Native Hawaiian, Marshallese or Samoan and aged 18 years or older were used for targeted sequencing of three genetic variants (rs4149056, rs1799853 and rs1057910). Results: SLCO1B1*5 was significantly less frequent in NHPI women (0.5-6%) than in Europeans (16%). Except for Koreans, CYP2C9*2 (0-1.4%) and *3 (0.5-3%) were significantly less frequent in all subgroups than in Europeans (8 and 12.7%, respectively). Prior reports showed that Asian and NHPI individuals have significantly higher ABCG2 Q141K allele frequency (13-46%) than Europeans (9.4%). Combined phenotype rates for rosuvastatin and fluvastatin revealed that Filipinos and Koreans had the highest frequencies of statin-associated myopathy symptoms risk alleles. Conclusion: Differences in ABCG2, SLCO1B1 and CYP2C9 allele frequencies among different racial and ethnic subgroups highlight the need for increased diversity in pharmacogenetic research. Risk alleles for statin-associated myopathy symptoms are more prevalent in Filipinos, underscoring the importance of genotype-based statin dosing.

PharmVar GeneFocus: SLCO1B1

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Identification of Transporter Polymorphisms Influencing Metformin Pharmacokinetics in Healthy Volunteers

For patients with type 2 diabetes, metformin is the most often recommended drug. However, there are substantial individual differences in the pharmacological response to metformin. To investigate the effect of transporter polymorphisms on metformin pharmacokinetics in an environment free of confounding variables, we conducted our study on healthy participants. This is the first investigation to consider demographic characteristics alongside all transporters involved in metformin distribution. Pharmacokinetic parameters of metformin were found to be affected by age, sex, ethnicity, and several polymorphisms. Age and SLC22A4 and SLC47A2 polymorphisms affected the area under the concentration-time curve (AUC). However, after adjusting for dose-to-weight ratio (dW), sex, age, and ethnicity, along with SLC22A3 and SLC22A4, influenced AUC. The maximum concentration was affected by age and SLC22A1, but after adjusting for dW, it was affected by sex, age, ethnicity, ABCG2, and SLC22A4. The time to reach the maximum concentration was influenced by sex, like half-life, which was also affected by SLC22A3. The volume of distribution and clearance was affected by sex, age, ethnicity and SLC22A3. Alternatively, the pharmacokinetics of metformin was unaffected by polymorphisms in ABCB1, SLC2A2, SLC22A2, or SLC47A1. Therefore, our study demonstrates that a multifactorial approach to all patient characteristics is necessary for better individualization.

A review of pharmacogenetic studies in the Bangladeshi population

Pharmacogenetics (PGx)-guided prescribing is an evidence-based precision medicine strategy. Although the past two decades have reported significant advancements in both the quality and quantity of PGx research studies, they are seldom done in developing countries like Bangladesh. This review identified and summarized PGx studies conducted in the Bangladeshi population by searching PubMed and Google Scholar. Additionally, a quality evaluation of the identified studies was also carried out. Eleven PGx studies were identified that looked at the effects of genetic variants on blood thinners (CYP2C9, VKORC1, and ITGB3), cancer drugs (TPMT, MTHFR, DPYD, ERCC1, GSTP1, XPC, XRCC1, TP53, XPD, and ABCC4), statins (COQ2, CYP2D6, and CYP3A5), and prednisolone (ABCB1, CYP3A5, and NR3C1) in the Bangladeshi population. Most studies were of low to moderate quality. Although the identified studies demonstrated the potential for PGx testing, the limited PGx literature in the Bangladeshi population poses a significant challenge in the widespread implementation of PGx testing in Bangladesh.

Reductionist methodology and the ambiguity of the categories of race and ethnicity in biomedical research: an exploratory study of recent evidence

In this article, we analyse how researchers use the categories of race and ethnicity with reference to genetics and genomics. We show that there is still considerable conceptual "messiness" (despite the wide-ranging and popular debate on the subject) when it comes to the use of ethnoracial categories in genetics and genomics that among other things makes it difficult to properly compare and interpret research using ethnoracial categories, as well as draw conclusions from them. Finally, we briefly reconstruct some of the biases of reductionism to which geneticists (as well as other researchers referring to genetic methods and explanations) are particularly exposed to, and we analyse the problem in the context of the biologization of ethnoracial categories. Our work constitutes a novel, in-depth contribution to the debate about reporting race and ethnicity in biomedical and health research. First, we reconstruct the theoretical background assumptions about racial ontology which researchers implicitly presume in their studies with the aid of a sample of recent papers published in medical journals about COVID-19. Secondly, we use the typology of the biases of reductionism to the problem of biologization of ethnoracial categories with reference to genetics and genomics.

Genetic Variants Associated with Opioid Use Disorder

Genetics are presumed to contribute 30-40% to opioid use disorder (OUD), allowing for the possibility that genetic markers could be used to identify personal risk for developing OUD. We aimed to test the potential association among 180 candidate single nucleotide polymorphisms (SNPs), 120 of which were related to the dopamine reward pathway and 60 related to pharmacokinetics. Participants were randomly recruited in 2020-2021 in a cross-sectional genetic association study. Self-reported health history including Diagnostic and Statistical Manual of Mental Disorders (DSM-5) OUD criteria and buccal swabs were collected. A total of 1,301 participants were included in the analyses for this study. Of included participants, 250 met the DSM-5 criteria for ever having OUD. Logistic regression, adjusting for age and biologic sex, was used to characterize the association between each SNP and DSM-5 criteria consistent with OUD. Six SNPs found in 4 genes were associated with OUD: increased odds with CYP3A5 (rs15524 and rs776746) and DRD3 (rs324029 and rs2654754), and decreased odds with CYP3A4 (rs2740574) and CYP1A2 (rs2069514). Homozygotic CYP3A5 (rs15524 and rs776746) had the highest adjusted odds ratio of 2.812 (95% confidence interval (CI) 1.737, 4.798) and 2.495 (95% CI 1.670, 3.835), respectively. Variants within the dopamine reward and opioid metabolism pathways have significant positive (DRD3 and CYP3A5) and negative (CYP3A4 and CYP1A2) associations with OUD. Identification of these variants provides promising possibilities for genetic prognostic and therapeutic targets for future investigation.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

Towards the multileveled and processual conceptualisation of racialised individuals in biomedical research

In this paper, we discuss the processes of racialisation on the example of biomedical research. We argue that applying the concept of racialisation in biomedical research can be much more precise, informative and suitable than currently used categories, such as race and ethnicity. For this purpose, we construct a model of the different processes affecting and co-shaping the racialisation of an individual, and consider these in relation to biomedical research, particularly to studies on hypertension. We finish with a discussion on the potential application of our proposition to institutional guidelines on the use of racial categories in biomedical research.

“Black race”, “Schwarze Hautfarbe”, “Origine africaine”, or “Etnia nera”? The absent presence of race in European pharmaceutical regulation

Current scholarship on race in Europe has described race as an “absent presence”. However, little is known about the dynamics of the absentness and presentness of race, including how various social processes operating at distinct levels (e.g. supranational and national) influence the uses of race and ethnicity concepts. We begin addressing this gap by examining racialised pharmaceutical regulation in the EU and its operationalisation in European countries. We analysed patterns of English-language uses of race and ethnicity terms at the EU level for all new drugs approved in 2014–2018, and systematically compared official translations into 24 languages. We found that “race” was promoted in plain sight and often retained when translated, albeit with much inconsistency across languages, creating peculiar patterns of presentness and absentness of race. Finnish, French, Swedish, and German stood out, as “race” was often translated into ethnicity terms, but even in those languages, “race” lingered despite claims that these countries vehemently opposed “race”. Our findings should inform scholarly and political debates about race, ethnicity, and medicine in Europe that tend to assume, incorrectly, an anti-racialist consensus. There are also policy implications, because prescribers may interpret regulator-approved information about race and ethnicity differently because of inconsistent translations.

PharmVar GeneFocus: CYP3A5

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Allelic diversity of the pharmacogene CYP2D6 in New Zealand Māori and Pacific peoples

The enzyme cytochrome P450 2D6 (CYP2D6) metabolises approximately 25% of commonly prescribed drugs, including analgesics, anti-hypertensives, and anti-depressants, among many others. Genetic variation in drug metabolising genes can alter how an individual responds to prescribed drugs, including predisposing to adverse drug reactions. The majority of research on the CYP2D6 gene has been carried out in European and East Asian populations, with many Indigenous and minority populations, such as those from Oceania, greatly underrepresented. However, genetic variation is often population specific and analysis of diverse ethnic groups can reveal differences in alleles that may be of clinical significance. For this reason, we set out to examine the range and frequency of CYP2D6 variants in a sample of 202 Māori and Pacific people living in Aotearoa (New Zealand). We carried out long PCR to isolate the CYP2D6 region before performing nanopore sequencing to identify all variants and alleles in these samples. We identified twelve variants which have previously not been reported in the PharmVar CYP2D6 database, three of which were exonic missense variations. Six of these occurred in single samples and one was found in 19 samples (9.4% of the cohort). The remaining five variants were identified in two samples each. Identified variants formed twelve new CYP2D6 suballeles and four new star alleles, now recorded in the PharmVar database. One striking finding was that CYP2D6*71, an allele of uncertain functional status which has been rarely observed in previous studies, occurs at a relatively high frequency (8.9%) within this cohort. These data will help to ensure that CYP2D6 genetic analysis for pharmacogenetic purposes can be carried out accurately and effectively in this population group.

Comparison of the Warfarin Dosing and Outcomes in Hmong Versus East Asians Patients: Real-World Data From an Integrated Healthcare System

Background

Previous research predicted that Hmong, an understudied East Asian subpopulation, might require significantly lower warfarin doses than East Asian patients partially due to their unique genetic and clinical factors. However, such findings have not been corroborated using real-world data.

Methods

This was a retrospective cohort study of Hmong and East Asian patients receiving warfarin. Warfarin stable doses (WSD) and time to the composite outcome, including international normalized ratio (INR) greater than four incidences or major bleeding within six months of warfarin initiation, were compared.

Results

This cohort study included 55 Hmong and 100 East Asian patients. Compared to East Asian patients, Hmong had a lower mean WSD (14.5 vs. 20.4 mg/week, p<0.05). In addition, Hmong had a 3.1-fold (95% CI: 1.1-9.3, p<0.05) higher hazard of the composite outcome.

Conclusion

Using real-world data, significant differences in warfarin dosing and hazard for the composite outcome of INR>4 and major bleeding were observed between Hmong and East Asian patients. These observations further underscore the importance of recognizing subpopulation-based differences in warfarin dosing and outcomes.

Pharmacogenomic Profile of Amazonian Amerindians

Given the role of pharmacogenomics in the large variability observed in drug efficacy/safety, an assessment about the pharmacogenomic profile of patients prior to drug prescription or dose adjustment is paramount to improve adherence to treatment and prevent adverse drug reaction events. A population commonly underrepresented in pharmacogenomic studies is the Native American populations, which have a unique genetic profile due to a long process of geographic isolation and other genetic and evolutionary processes. Here, we describe the pharmacogenetic variability of Native American populations regarding 160 pharmacogenes involved in absorption, distribution, metabolism, and excretion processes and biological pathways of different therapies. Data were obtained through complete exome sequencing of individuals from 12 different Amerindian groups of the Brazilian Amazon. The study reports a total of 3311 variants; of this, 167 are exclusive to Amerindian populations, and 1183 are located in coding regions. Among these new variants, we found non-synonymous coding variants in the DPYD and the IFNL4 genes and variants with high allelic frequencies in intronic regions of the MTHFR, TYMS, GSTT1, and CYP2D6 genes. Additionally, 332 variants with either high or moderate (disruptive or non-disruptive impact in protein effectiveness, respectively) significance were found with a minimum of 1% frequency in the Amazonian Amerindian population. The data reported here serve as scientific basis for future design of specific treatment protocols for Amazonian Amerindian populations as well as for populations admixed with them, such as the Northern Brazilian population.

Transmembrane protease serine 2 (TMPRSS2) rs75603675, comorbidity, and sex are the primary predictors of COVID-19 severity

The TMPRSS2 rs75603675 genotype (OR = 0.586), dyslipidemia (OR = 2.289), sex (OR = 0.586), and the Charlson Comorbidity Index (OR = 1.126) were identified as the main predictors of COVID-19 severity in 817 patients who attended Hospital Universitario de La Princesa during March and April 2020.

By the end of December 2021, coronavirus disease 2019 (COVID-19) produced more than 271 million cases and 5.3 million deaths. Although vaccination is an effective strategy for pandemic control, it is not yet equally available in all countries. Therefore, identification of prognostic biomarkers remains crucial to manage COVID-19 patients. The aim of this study was to evaluate predictors of COVID-19 severity previously proposed. Clinical and demographic characteristics and 120 single-nucleotide polymorphisms were analyzed from 817 patients with COVID-19, who attended the emergency department of the Hospital Universitario de La Princesa during March and April 2020. The main outcome was a modified version of the 7-point World Health Organization (WHO) COVID-19 severity scale (WHOCS); both in the moment of the first hospital examination (WHOCS-1) and of the severest WHOCS score (WHOCS-2). The TMPRSS2 rs75603675 genotype (OR = 0.586), dyslipidemia (OR = 2.289), sex (OR = 0.586), and the Charlson Comorbidity Index (OR = 1.126) were identified as the main predictors of disease severity. Consequently, these variables might influence COVID-19 severity and could be used as predictors of disease development.

Pharmacogenetic and clinical predictors of ondansetron failure in a diverse pediatric oncology population

PURPOSE

Chemotherapy-induced nausea and vomiting (CINV) is a frequently seen burdensome adverse event of cancer therapy. The 5-HT3 receptor antagonist ondansetron has improved the rates of CINV but, unfortunately, up to 30% of patients do not obtain satisfactory control. This study examined whether genetic variations in a relevant drug-metabolizing enzyme (CYP2D6), transporter (ABCB1), or receptor (5-HT3) were associated with ondansetron failure.

METHODS

DNA was extracted from blood and used to genotype: ABCB1 (3435C > T (rs1045642) and G2677A/T (rs2032582)), 5-HT3RB (rs3758987 T > C and rs45460698 (delAAG/dupAAG)), and CYP2D6 variants. Ondansetron failure was determined by review of the medical records and by patient-reported outcomes (PROs).

RESULTS

One hundred twenty-nine patients were approached; 103 consented. Participants were less than 1 to 33 years (mean 6.85). A total of 39.8% was female, 58.3% was White (22.3% Black, 19.4% other), and 24.3% was Hispanic. A majority had leukemia or lymphoma, and 41 (39.8%) met the definition of ondansetron failure. Of variants tested, rs45460698 independently showed a significant difference in risk of ondansetron failure between a mutant (any deletion) and normal allele (p = 0.0281, OR 2.67). Age and BMI were both predictive of ondansetron failure (age > 12 (OR 1.12, p = 0.0012) and higher BMI (OR 1.13, p = 0.0119)). In multivariate analysis, age > 12 was highly predictive of ondansetron failure (OR 7.108, p = 0.0008). rs45460698 was predictive when combined with an increased nausea phenotype variant of rs1045642 (OR 3.45, p = 0.0426).

CONCLUSION

Select phenotypes of 5-HT3RB and ABCB1, age, and potentially BMI can help predict increased risk for CINV in a diverse pediatric oncology population.

Psychotropic prescribing rates and pharmacogenomic testing implications for autism in the Canadian primary care sentinel surveillance network

OBJECTIVE

To estimate prescribing rates of psychotropic drugs to individuals with autism and the proportion of these individuals who could benefit from pharmacogenetic testing.

METHODS

Prescribing data for 92 psychotropic drugs, including 31 antidepressants, 22 antipsychotics, 14 mood stabilizer/antiepileptics, 17 anxiolytic/hypnotics and eight antiadrenergic/psychostimulant were retrieved from medical records of 787 (613 males) autistic individuals who sought treatment from a primary care office enrolled in the Canadian Primary Care Sentinel Surveillance Network between 2012 and 2014. Each prescribed drug was cross-referenced with pharmacogenomic-based prescribing guidelines published by the Clinical Pharmacogenetics Implementation Consortium, the Dutch Pharmacogenetics Working Group, and the Canadian Pharmacogenomics Network for Drug Safety.

RESULTS

More than half (58%) of the participants were prescribed a psychotropic drug and 37% were prescribed two or more psychotropic drugs concurrently. Among the 83 psychotropic drugs examined, 54 (65%) were prescribed to one or more participants during the study's observation period. The ten most frequently prescribed psychotropics were methylphenidate (16.3%), risperidone (12.8%), lorazepam (12.1%), fluoxetine (7.9%), sertraline (7.1%), quetiapine (6.9%), aripiprazole (6.1%), lisdexamfetamine (5.8%), citalopram (5.6%) and clonazepam (4.8%). Seventeen (32%) of the 54 psychotropic drugs prescribed were linked to a pharmacogenomic-based prescribing guideline, including risperidone, sertraline, aripiprazole and citalopram.

CONCLUSIONS

Our findings suggest primary care providers in Canada prescribe a wide range of psychotropics to their patients with autism, some of which may benefit from the integration of pharmacogenomic information into their treatment planning.

Integration of liquid biopsy and pharmacogenomics for precision therapy of EGFR mutant and resistant lung cancers

The advent of molecular profiling has revolutionized the treatment of lung cancer by comprehensively delineating the genomic landscape of the epidermal growth factor receptor (EGFR) gene. Drug resistance caused by EGFR mutations and genetic polymorphisms of drug metabolizing enzymes and transporters impedes effective treatment of EGFR mutant and resistant lung cancer. This review appraises current literature, opportunities, and challenges associated with liquid biopsy and pharmacogenomic (PGx) testing as precision therapy tools in the management of EGFR mutant and resistant lung cancers. Liquid biopsy could play a potential role in selection of precise tyrosine kinase inhibitor (TKI) therapies during different phases of lung cancer treatment. This selection will be based on the driver EGFR mutational status, as well as monitoring the development of potential EGFR mutations arising during or after TKIs treatment, since some of these new mutations may be druggable targets for alternative TKIs. Several studies have identified the utility of liquid biopsy in the identification of EGFR driver and acquired resistance with good sensitivities for various blood-based biomarkers. With a plethora of sequencing technologies and platforms available currently, further evaluations using randomized controlled trials (RCTs) in multicentric, multiethnic and larger patient cohorts could enable optimization of liquid-based assays for the detection of EGFR mutations, and support testing of CYP450 enzymes and drug transporter polymorphisms to guide precise dosing of EGFR TKIs.

African Genomic Medicine Portal: A Web Portal for Biomedical Applications

Genomics data are currently being produced at unprecedented rates, resulting in increased knowledge discovery and submission to public data repositories. Despite these advances, genomic information on African-ancestry populations remains significantly low compared with European- and Asian-ancestry populations. This information is typically segmented across several different biomedical data repositories, which often lack sufficient fine-grained structure and annotation to account for the diversity of African populations, leading to many challenges related to the retrieval, representation and findability of such information. To overcome these challenges, we developed the African Genomic Medicine Portal (AGMP), a database that contains metadata on genomic medicine studies conducted on African-ancestry populations. The metadata is curated from two public databases related to genomic medicine, PharmGKB and DisGeNET. The metadata retrieved from these source databases were limited to genomic variants that were associated with disease aetiology or treatment in the context of African-ancestry populations. Over 2000 variants relevant to populations of African ancestry were retrieved. Subsequently, domain experts curated and annotated additional information associated with the studies that reported the variants, including geographical origin, ethnolinguistic group, level of association significance and other relevant study information, such as study design and sample size, where available. The AGMP functions as a dedicated resource through which to access African-specific information on genomics as applied to health research, through querying variants, genes, diseases and drugs. The portal and its corresponding technical documentation, implementation code and content are publicly available.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Pharmacogenetic differentiation across Latin America

Aim: To explore the pharmacogenetic differentiation across Latin American populations, using the fixation index statistics (F_ST). Materials & methods: F_ST analyses were applied to 1519 pharmacogenetic markers in the 1000 Genomes Admixed American superpopulation (1KG_AMR) and an admixed Brazilian sample. Results: Allele-specific F_ST values for the overall cohort point to little overall pharmacogenetic differentiation (average F_ST = 0.017); however, moderate differentiation (F_ST = 0.05-0.15) was observed for 83 markers, while large differentiation (F_ST = 0.15-0.25) was restricted to three markers. Pairwise F_ST analysis identified three markers with very large differentiation (F_ST >0.25). Conclusion: The present study verifies and extends previous reports of little overall pharmacogenetic divergence across Latin America, although a number of markers display substantial differentiation.

Health equality, race and pharmacogenomics

Pharmacogenomics is increasingly moving into mainstream clinical practice. Careful consideration must be paid to inclusion of diverse populations in research, translation and implementation, in the historical and social context of population stratification, to ensure that this leads to improvements in healthcare for all rather than increased health disparities. This review takes a broad and critical approach to the current role of diversity in pharmacogenomics and addresses potential pitfalls in order to raise awareness for prescribers. It also emphasizes evidence gaps and suggests approaches that may minimize negative consequences and promote health equality.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Evolving use of ancestry, ethnicity, and race in genetics research-A survey spanning seven decades

To inform continuous and rigorous reflection about the description of human populations in genomics research, this study investigates the historical and contemporary use of the terms "ancestry," "ethnicity," "race," and other population labels in The American Journal of Human Genetics from 1949 to 2018. We characterize these terms' frequency of use and assess their odds of co-occurrence with a set of social and genetic topical terms. Throughout The Journal's 70-year history, "ancestry" and "ethnicity" have increased in use, appearing in 33% and 26% of articles in 2009-2018, while the use of "race" has decreased, occurring in 4% of articles in 2009-2018. Although its overall use has declined, the odds of "race" appearing in the presence of "ethnicity" has increased relative to the odds of occurring in its absence. Forms of population descriptors "Caucasian" and "Negro" have largely disappeared from The Journal (<1% of articles in 2009-2018). Conversely, the continental labels "African," "Asian," and "European" have increased in use and appear in 18%, 14%, and 42% of articles from 2009-2018, respectively. Decreasing uses of the terms "race," "Caucasian," and "Negro" are indicative of a transition away from the field's history of explicitly biological race science; at the same time, the increasing use of "ancestry," "ethnicity," and continental labels should serve to motivate ongoing reflection as the terminology used to describe genetic variation continues to evolve.

Clozapine-induced myocarditis and patient outcomes after drug rechallenge following myocarditis: A systematic case review

Clozapine is underutilized due, in part, to concerns about rare but severe adverse drug reactions, including cardiac inflammation and injury (myocarditis). Risk factors for clozapine-induced myocarditis are limited and predictors for the successful rechallenge of clozapine after an episode of myocarditis are even more poorly understood. We conducted a systematic review, in accordance with the PRISMA recommendation, of published case reports to describe demographic and clinical characteristics of patients with clozapine-induced myocarditis and identify potential markers of clozapine rechallenge success. A total of 180 cases from 88 articles were evaluated. Male cases of clozapine-associated myocarditis were more frequently reported than female cases by a ratio of 6:1. Less than half of patients reported the presence of chest pain (35%) or flu-like symptoms (43%) but increases in troponin or C-reactive protein were present in 87% of cases. Clozapine rechallenge was carried out in 34 (2 female) cases, with successful reintroduction in 22 (2 female) cases (64.7%) and one fatality (2.9%). No demographic or clinical markers were significantly associated with rechallenge success after correction for multiple testing. Standardized reporting of clozapine-induced myocarditis cases is needed to facilitate the identification of factors associated with successful rechallenge.

Validation of a multi-gene qPCR-based pharmacogenomics panel across major ethnic groups in Singapore and Indonesia

Aim: The clinical utility of pharmacogenomics (PGx) has been gaining traction alongside growing evidence that adverse drug reactions (ADRs) have significant genetic associations. Nala PGx Core^® is a multi-gene qPCR-based panel of 20 allele variants, comprising 18 SNPs and two CYP2D6 copy number markers across four pharmacogenes - CYP2C9, CYP2C19, CYP2D6 and SLCO1B1. Methods: In this study, we validated the performance of Nala PGx Core^® against benchmark methods, on the Singaporean and Indonesian populations. Results & conclusion: Nala PGx Core^® demonstrated robust and accurate genotyping when compared with other established benchmarks. Furthermore, the panel successfully characterized alleles of clinical relevance, such as CYP2D6*10 and CYP2D6*36, across major ethnic groups present of Singapore and Indonesia, suggesting its potential for adoption in clinical workflows regionally.

Pharmacogenomics: A road ahead for precision medicine in psychiatry

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

African Global Representation in Biomedical Sciences

African populations are diverse in their ethnicity, language, culture, and genetics. Although plagued by high disease burdens, until recently the continent has largely been excluded from biomedical studies. Along with limitations in research and clinical infrastructure, human capacity, and funding, this omission has resulted in an underrepresentation of African data and disadvantaged African scientists. This review interrogates the relative abundance of biomedical data from Africa, primarily in genomics and other omics. The visibility of African science through publications is also discussed. A challenge encountered in this review is the relative lack of annotation of data on their geographical or population origin, with African countries represented as a single group. In addition to the abovementioned limitations,the global representation of African data may also be attributed to the hesitation to deposit data in public repositories. Whatever the reason, the disparity should be addressed, as African data have enormous value for scientists in Africa and globally.