The Pharmacogene Variation (PharmVar) Consortium: Incorporation of the Human Cytochrome P450 (CYP) Allele Nomenclature Database

Molecular Mechanisms Underlying Single Nucleotide Polymorphism-Induced Reactivity Decrease in CYP2D6

Cytochrome P450 2D6 (CYP2D6) is one of the most important enzymes involved in drug metabolism. Genetic polymorphism can influence drug metabolism by CYP2D6 such that a therapy is seriously affected by under- or overdosing of drugs. However, a general explanation at the atomistic level for poor activity is missing so far. Here we show for the 20 most common single nucleotide polymorphisms (SNPs) of CYP2D6 that poor metabolism is driven by four mechanisms. We found in extensive all-atom molecular dynamics simulations that the rigidity of the I-helix (central helix), distance between central phenylalanines (stabilizing bound substrate), availability of basic residues on the surface of CYP2D6 (binding of cytochrome P450 reductase), and position of arginine 132 (electron transfer to heme) are essential for an extensive function of the enzyme. These results were applied to SNPs with unknown effects, and potential SNPs that may lead to poor drug metabolism were identified. The revealed molecular mechanisms might be important for other drug-metabolizing cytochrome P450 enzymes.

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.

Phenoconversion Due to Drug-Drug Interactions in CYP2C19 Genotyped Healthy Volunteers

To compensate for drug response variability, drug metabolism phenotypes are determined based on the results of genetic testing, and if necessary, drug dosages are adjusted. In some cases, discrepancies between predicted and observed phenotypes (phenoconversion) may occur due to drug-drug interactions caused by concomitant medications. We conducted a prospective, exploratory study to evaluate the risk of CYP2C19 phenoconversion in genotyped healthy volunteers exposed to CYP2C19 inhibitors. Three groups of volunteers were enrolled: CYP2C19 g-RM, g-NM, and g-IM (g- for genetically predicted). All volunteers received as CYP2C19 phenotyping substrate 10 mg omeprazole (OME) alone at the control session and in co-administration with CYP2C19 inhibitors: voriconazole 400 mg and fluvoxamine 50 mg in second and third study sessions, respectively. Phenoconversion occurred in over 80% of healthy volunteers, with variations among genotypic groups, revealing distinct proportions in response to fluvoxamine and voriconazole. Statistically significant differences were observed in mean metabolic ratios between CYP2C19 intermediate metabolizers (g-IMs) with *1/*2 and *2/*17 genotypes, with the *2/*17 group exhibiting lower ratios, and distinctions were noted between genotypic groups, emphasizing the impact of genetic variations on drug metabolism. When reclassified according to CYP2C19 baseline-measured phenotype into p-RM, p-NM, and p-IM (p- for measured phenotype), we observed 100% phenoconversion of p-RMs and a significant phenotype switch in p-NMs, p-IMs, and p-PMs after fluvoxamine and voriconazole, and complete phenoconversion of p-IMs to p-PMs on both inhibitors, emphasizing the impact of genetic variations on the vulnerability to CYP2C19 phenoconversion and the importance of considering both genotyping and phenotyping in predicting drug response.

Frequency of pharmacogenomic variation and medication exposures among All of Us Participants

Pharmacogenomics promises improved outcomes through individualized prescribing. However, the lack of diversity in studies impedes clinical translation and equitable application of precision medicine. We evaluated the frequencies of PGx variants, predicted phenotypes, and medication exposures using whole genome sequencing and EHR data from nearly 100k diverse All of Us Research Program participants. We report 100% of participants carried at least one pharmacogenomics variant and nearly all (99.13%) had a predicted phenotype with prescribing recommendations. Clinical impact was high with over 20% having both an actionable phenotype and a prior exposure to an impacted medication with pharmacogenomic prescribing guidance. Importantly, we also report hundreds of alleles and predicted phenotypes that deviate from known frequencies and/or were previously unreported, including within admixed American and African ancestry groups.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Designing cytochrome P450 enzymes for use in cancer gene therapy

Cancer is a significant global socioeconomic burden, as millions of new cases and deaths occur annually. In 2020, almost 10 million cancer deaths were recorded worldwide. Advancements in cancer gene therapy have revolutionized the landscape of cancer treatment. An approach with promising potential for cancer gene therapy is introducing genes to cancer cells that encode for chemotherapy prodrug metabolizing enzymes, such as Cytochrome P450 (CYP) enzymes, which can contribute to the effective elimination of cancer cells. This can be achieved through gene-directed enzyme prodrug therapy (GDEPT). CYP enzymes can be genetically engineered to improve anticancer prodrug conversion to its active metabolites and to minimize chemotherapy side effects by reducing the prodrug dosage. Rational design, directed evolution, and phylogenetic methods are some approaches to developing tailored CYP enzymes for cancer therapy. Here, we provide a compilation of genetic modifications performed on CYP enzymes aiming to build highly efficient therapeutic genes capable of bio-activating different chemotherapeutic prodrugs. Additionally, this review summarizes promising preclinical and clinical trials highlighting engineered CYP enzymes' potential in GDEPT. Finally, the challenges, limitations, and future directions of using CYP enzymes for GDEPT in cancer gene therapy are discussed.

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.

ursaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.

Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism

BACKGROUND

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes.

METHODS

Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8 weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants.

RESULTS

Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel.

CONCLUSION

In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

Leveraging in Vitro Models for Clinically Relevant Rare CYP2D6 Variants in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of up to 20% of small-molecule drugs and therefore, may impact the safety and efficacy of medicines in broad therapeutic areas. CYP2D6 is highly polymorphic, and the frequency of variants can differ across racial and ethnic populations, significantly affecting enzymatic function and drug metabolism. However, rare variants of CYP2D6 present a unique challenge for academia, industry, and regulatory agencies alike due to the lack of feasibility of characterizing their clinical relevance in clinical trials, particularly in variants that exhibit population-specific frequencies in racial and ethnic groups that are poorly represented in clinical trials. Despite significant advancement in pharmacogenomics, the substrate specificity and related clinical relevance of these CYP2D6 rare variants remain largely unclear, and further efforts are warranted to characterize the burden of these variants on adverse drug reactions and drug efficacy. Thus, cell-based in vitro systems can be used to inform substrate-specific effects and the overall relevance of a rare variant. Liver microsomes, cell-based expression systems, ex vivo primary samples, and purified variant protein have all been used with various substrates to potentially predict the clinical impact of new substrates. In this review, we identify rare variants of CYP2D6 that demonstrate differences across races in prevalence and thus are often unassessed in clinical trials. Accordingly, we examine current pharmacogenomic in vitro models used to analyze the functional impact of these rare variants in a substrate-specific manner. SIGNIFICANCE STATEMENT: Variants of CYP2D6 play a clinically relevant role in drug metabolism, leading to potential safety and efficacy concerns. Although the influence of prevalent variants is often well characterized, rare variants are traditionally not included in clinical trials. This review captures the clinical relevance of rare variants in CYP2D6 by highlighting in vitro models that analyze their impact on the metabolism of CYP2D6 substrates.

Haplotype phasing of CYP2D6: an allelic ratio method using Agena MassARRAY data

Pharmacogenomics aims to use the genetic information of an individual to personalize drug prescribing. There is evidence that pharmacogenomic testing before prescription may prevent adverse drug reactions, increase efficacy, and reduce cost of treatment. CYP2D6 is a key pharmacogene of relevance to multiple therapeutic areas. Indeed, there are prescribing guidelines available for medications based on CYP2D6 enzyme activity as deduced from CYP2D6 genetic data. The Agena MassARRAY system is a cost-effective method of detecting genetic variation that has been clinically applied to other genes. However, its clinical application to CYP2D6 has to date been limited by weaknesses such as the inability to determine which haplotype was present in more than one copy for individuals with more than two copies of the CYP2D6 gene. We report application of a new protocol for CYP2D6 haplotype phasing of data generated from the Agena MassARRAY system. For samples with more than two copies of the CYP2D6 gene for which the prior consensus data specified which one was present in more than one copy, our protocol was able to conduct CYP2D6 haplotype phasing resulting in 100% concordance with the prior data. In addition, for three reference samples known to have more than two copies of CYP2D6 but for which the exact number of CYP2D6 genes was unknown, our protocol was able to resolve the number for two out of the three of these, and estimate the likely number for the third. Finally, we demonstrate that our method is applicable to CYP2D6 hybrid tandem configurations.

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

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

Solanidine is a sensitive and specific dietary biomarker for CYP2D6 activity

BACKGROUND

Individual assessment of CYP enzyme activities can be challenging. Recently, the potato alkaloid solanidine was suggested as a biomarker for CYP2D6 activity. Here, we aimed to characterize the sensitivity and specificity of solanidine as a CYP2D6 biomarker among Finnish volunteers with known CYP2D6 genotypes.

RESULTS

Using non-targeted metabolomics analysis, we identified 9152 metabolite features in the fasting plasma samples of 356 healthy volunteers. Machine learning models suggested strong association between CYP2D6 genotype-based phenotype classes with a metabolite feature identified as solanidine. Plasma solanidine concentration was 1887% higher in genetically poor CYP2D6 metabolizers (gPM) (n = 9; 95% confidence interval 755%, 4515%; P = 1.88 × 10-11), 74% higher in intermediate CYP2D6 metabolizers (gIM) (n = 89; 27%, 138%; P = 6.40 × 10-4), and 35% lower in ultrarapid CYP2D6 metabolizers (gUM) (n = 20; 64%, - 17%; P = 0.151) than in genetically normal CYP2D6 metabolizers (gNM; n = 196). The solanidine metabolites m/z 444 and 430 to solanidine concentration ratios showed even stronger associations with CYP2D6 phenotypes. Furthermore, the areas under the receiver operating characteristic and precision-recall curves for these metabolic ratios showed equal or better performances for identifying the gPM, gIM, and gUM phenotype groups than the other metabolites, their ratios to solanidine, or solanidine alone. In vitro studies with human recombinant CYP enzymes showed that solanidine was metabolized mainly by CYP2D6, with a minor contribution from CYP3A4/5. In human liver microsomes, the CYP2D6 inhibitor paroxetine nearly completely (95%) inhibited the metabolism of solanidine. In a genome-wide association study, several variants near the CYP2D6 gene associated with plasma solanidine metabolite ratios.

CONCLUSIONS

These results are in line with earlier studies and further indicate that solanidine and its metabolites are sensitive and specific biomarkers for measuring CYP2D6 activity. Since potato consumption is common worldwide, this biomarker could be useful for evaluating CYP2D6-mediated drug-drug interactions and to improve prediction of CYP2D6 activity in addition to genotyping.

The genomic landscape of CYP2D6 variation in the Indian population

Aim: The CYP2D6 gene is highly polymorphic, causing large interindividual variability in the metabolism of several clinically important drugs. Materials & methods: The authors investigated the diversity and distribution of CYP2D6 alleles in Indians using whole genome sequences (N = 1518). Functional consequences were assessed using pathogenicity scores and molecular dynamics simulations. Results: The analysis revealed population-specific CYP2D6 alleles (*86, *7, *111, *112, *113, *99) and remarkable differences in variant and phenotype frequencies with global populations. The authors observed that one in three Indians could benefit from a dose alteration for psychiatric drugs with accurate CYP2D6 phenotyping. Molecular dynamics simulations revealed large conformational fluctuations, confirming the predicted reduced function of *86 and *113 alleles. Conclusion: The findings emphasize the utility of comprehensive CYP2D6 profiling for aiding precision public health.

Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens

Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.

Genetic variation of CYP2C9 gene and its correlation with cardiovascular disease risk factors

BACKGROUND

The major enzyme that is responsible for Sulfonylureas (SUs) metabolism is hepatic cytochrome P-450 2C9 (CYP2C9). It is encoded by the polymorphic gene CYP2C9, which has many allelic variants, among those the CYP2C9*2 and CYP2C9*3 are the most common and clinically significant allelic variations. People with diabetes mellitus type 2 (T2DM) are more likely to develop cardiovascular disease (CVD), and their risk of dying from it is more than two times higher than that of people without the condition. The purpose of this study was to evaluate the association of genetic variations in the CYP2C9 gene with cardiovascular risk factors by investigating CYP2C9*1, *2, *3, *5, *11, and *13 allelic variants.

METHODS AND RESULTS

A total of 226 participants were enrolled in the current case-control study. Allele-specific amplification- PCR (ASA-PCR) was used to determine the allele of different variations and the results were confirmed by sequencing. The findings of this study showed the presence of the CYP2C9*2 allele in the T2DM group does not differ from its percentage in the control group. Also, CYP2C9*3 allele frequencies identified by Hardy-Weinberg equilibrium (HWE) analysis law were not significant, p = 0.6593 and 0.5828 in T2DM and control groups. There is no statistically significant difference between the control and diabetes groups involving the distribution of CYP2C9 alleles and CYP2C9*5, *11, and *13 polymorphisms were absent in the Iraqi population. No carrier for the CYP2C9*3 homozygous state was found in both groups.

CONCLUSIONS

According to these results T2DM patients with the CYP2C9*2 and *3 variants have an increased risk of developing hypertension.

Pharmacogenetic Variation in Neanderthals and Denisovans and Implications for Human Health and Response to Medications

Modern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes-genes responsible for the processing of exogenous substances such as food, pollutants, and medications-as these can relate to changing environmental effects, and beneficial variants may have been retained as modern humans encountered new environments. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remain understudied. Here, we explore 11 key cytochrome P450 genes (CYP450) involved in 75% of all drug metabolizing reactions in three Neanderthal and one Denisovan individuals and examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these 11 CYP450 genes in archaic individuals and find important predicted phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaic CYP450 genes, which may result in altered metabolism in living people carrying these variants. We also identified several variants in the archaic CYP450 genes that are novel and unique to archaic humans as well as one gene, CYP2B6, that shows evidence for a gene duplication found only in Neanderthals and modern Africans. Finally, we highlight CYP2A6, CYP2C9, and CYP2J2, genes which show evidence for archaic introgression into modern humans and posit evolutionary hypotheses that explain their allele frequencies in modern populations.

Effects of pharmacogenetic profiles on pediatric pain relief and adverse events with ibuprofen and oxycodone

Introduction

Individual genetic variation may influence clinical effects for pain medications. Effects of CYP2C9, CYP3A4, and CYP2D6 polymorphisms on clinical effectiveness and safety for ibuprofen and oxycodone were studied.

Objective

Primary objectives were to AU2 evaluate if allelic variations would affect clinical effectiveness and adverse events (AEs) occurrence.

Methods

This pragmatic prospective, observational cohort included children aged 4 to 16 years who were seen in a pediatric emergency department with an acute fracture and prescribed ibuprofen or oxycodone for at-home pain management. Saliva samples were obtained for genotyping of allelic variants, and daily telephone follow-up was conducted for 3 days. Pain was measured using the Faces Pain Scale-Revised.

Results

We included 210 children (n = 140 ibuprofen and n = 70 oxycodone); mean age was 11.1 (±SD 3.5) years, 33.8% were female. Median pain reduction on day 1 was similar between groups [ibuprofen 4 (IQR 2,4) and oxycodone 4 (IQR 2,6), P = 0.69]. Over the 3 days, the oxycodone group experienced more AE than the ibuprofen group (78.3% vs 53.2%, P < 0.001). Those with a CYP2C9*2 reduced function allele experienced less adverse events with ibuprofen compared with those with a normal functioning allele CYP2C9*1 (P = 0.003). Neither CYP3A4 variants nor CYP2D6 phenotype classification affected clinical effect or AE.

Conclusion

Although pain relief was similar, children receiving oxycodone experienced more AE, overall, than those receiving ibuprofen. For children receiving ibuprofen or oxycodone, pain relief was not affected by genetic variations in CYP2C9 or CYP3A4/CYP2D6, respectively. For children receiving ibuprofen, the presence of CYP2C9*2 was associated with less adverse events.

Study on the association between adverse drug reactions to opioids and gene polymorphisms: a case-case-control study

OBJECTIVE

Adverse drug reactions (ADRs) caused by opioid drugs show individual differences. Our objective was to explore the association between gene polymorphism and ADRs induced by opioid drugs.

METHODS

Evidence-based medical data analysis was conducted for genes related to ADRs induced by opioid drugs to select target genes. Sixty patients with cancer pain who had ADRs after taking opioid drugs (morphine, codeine, oxycodone) and 60 patients without ADRs after taking opioid drugs were used as the experimental group and control group, respectively. Then, we used polymerase chain reaction (PCR) or in situ hybridization to detect target genes. By combining with clinical data such as age, sex, dosage and duration of medication, the effect of gene polymorphism on the ADR of patients after taking opioid drugs was statistically analysed.

RESULTS

Based on a database search and evidence-based medical data, we identified CYP2D6*10, CYP3A5*3, ABCB1, and OPRM1 as target genes for detection. The results of statistical analysis showed no significant difference in genotype distribution between the experimental group and the control group (p > 0.05). However, if 32 patients with ADRs after taking oxycodone and 32 controls were selected for comparison, the SPSS22.0 and SNPStats genetic models showed that the ABCB1 (062rs1045642) CT and TT genotypes correlated with the occurrence of ADRs (p < 0.05): the total number of CT + TT genotypes in the experimental group was 29 (90.62%), with 11 (34.37%) CT + TT genotypes types in the control group.

CONCLUSION

Polymorphism of ABCB1 (062rs1045642) is related to ADRs caused by oxycodone, and the incidence of ADRs is higher with the allele T. Polymorphism of ABCB1 is expected to become a clinical predictor of ADRs to oxycodone, and attention should be given to the occurrence of serious ADRs in patients with ABCB1 (062rs1045642) CT and TT genotypes.

Targeted haplotyping in pharmacogenomics using Oxford Nanopore Technologies' adaptive sampling

Pharmacogenomics (PGx) studies the impact of interindividual genomic variation on drug response, allowing the opportunity to tailor the dosing regimen for each patient. Current targeted PGx testing platforms are mainly based on microarray, polymerase chain reaction, or short-read sequencing. Despite demonstrating great value for the identification of single nucleotide variants (SNVs) and insertion/deletions (INDELs), these assays do not permit identification of large structural variants, nor do they allow unambiguous haplotype phasing for star-allele assignment. Here, we used Oxford Nanopore Technologies' adaptive sampling to enrich a panel of 1,036 genes with well-documented PGx relevance extracted from the Pharmacogenomics Knowledge Base (PharmGKB). By evaluating concordance with existing truth sets, we demonstrate accurate variant and star-allele calling for five Genome in a Bottle reference samples. We show that up to three samples can be multiplexed on one PromethION flow cell without a significant drop in variant calling performance, resulting in 99.35% and 99.84% recall and precision for the targeted variants, respectively. This work advances the use of nanopore sequencing in clinical PGx settings.

Pharmacogenomics of Dementia: Personalizing the Treatment of Cognitive and Neuropsychiatric Symptoms

Dementia is a syndrome of global and progressive deterioration of cognitive skills, especially memory, learning, abstract thinking, and orientation, usually affecting the elderly. The most common forms are Alzheimer's disease, vascular dementia, and other (frontotemporal, Lewy body disease) dementias. The etiology of these multifactorial disorders involves complex interactions of various environmental and (epi)genetic factors and requires multiple forms of pharmacological intervention, including anti-dementia drugs for cognitive impairment, antidepressants, antipsychotics, anxiolytics and sedatives for behavioral and psychological symptoms of dementia, and other drugs for comorbid disorders. The pharmacotherapy of dementia patients has been characterized by a significant interindividual variability in drug response and the development of adverse drug effects. The therapeutic response to currently available drugs is partially effective in only some individuals, with side effects, drug interactions, intolerance, and non-compliance occurring in the majority of dementia patients. Therefore, understanding the genetic basis of a patient's response to pharmacotherapy might help clinicians select the most effective treatment for dementia while minimizing the likelihood of adverse reactions and drug interactions. Recent advances in pharmacogenomics may contribute to the individualization and optimization of dementia pharmacotherapy by increasing its efficacy and safety via a prediction of clinical outcomes. Thus, it can significantly improve the quality of life in dementia patients.

Introduction to pharmacogenetics

There is considerable interindividual variability in the effectiveness and safety of medicines. Although the reasons for this are multifactorial, it is well recognised that genetic changes impacting the absorption or metabolism of these drugs play a significant contributory role. Understanding how these pharmacogenetic variants impact response to medicines, and leveraging this knowledge to guide prescribing, could have significant benefits for patients and health services. This article provides an introduction to the field of pharmacogenetics, including its nomenclature, the existing evidence base and the current state of implementation globally. We discuss the challenges in translating pharmacogenetic research into clinical practice and highlight the considerable benefits which can emerge in those health services where implementation is successful.

Genetic variations of CYP3A4 on the metabolism of itraconazole in vitro

Itraconazole is a triazole anti-infective drug that has been proven to prevent and treat a variety of fungal and viral infections and has been considered to be a potential therapeutic remedy for COVID-19 treatment. In this study, we aimed to completely evaluate the impacts of Cytochrome P450 3A4 (CYP3A4) variant proteins and drug interactions on the metabolism of itraconazole in recombinant insect microsomes, and to characterize the potential mechanism of substrate selectivity. Incubations with itraconazole (0.2-15 μM) in the presence/absence of lopinavir or darunavir were assessed by CYP3A4 variants, and the metabolite hydroxyitraconazole concentrations were measured by UPLC-MS/MS. Our data showed that when compared with CYP3A4.1, 4 variants (CYP3A4.9, .10, .28 and .34) displayed no significant differences, and 3 variants (CYP3A4.14, .15 and .19) exhibited increased intrinsic clearance (CLint), whereas the remaining 17 variant proteins showed decreased enzyme activities for the catalysis of itraconazole. Moreover, the inhibitory effects of lopinavir and darunavir on itraconazole metabolism varied in different degrees. Furthermore, different changed trend of the kinetic parameters in ten variants (CYP3A4.5, .9, .10, .16, .19, .24, .28, .29, .31, and .33) were observed, especially CYP3A4.5 and CYP3A4.16, and this may be related to the metabolic site-heme iron atom distance. In the present study, we functionally analyzed the effects of 25 CYP3A4 protein variants on itraconazole metabolism for the first time, and provided comprehensive data on itraconazole metabolism in vitro. This may help to better assess the metabolism and elimination of itraconazole in clinic to improve the safety and efficacy of its clinical treatment and also provide new possibilities for the treatment of COVID-19.

Hydrocodone, Oxycodone, and Morphine Metabolism and Drug-Drug Interactions

Awareness of drug interactions involving opioids is critical for patient treatment as they are common therapeutics used in numerous care settings, including both chronic and disease-related pain. Not only do opioids have narrow therapeutic indexes and are extensively used, but they have the potential to cause severe toxicity. Opioids are the classical pain treatment for patients who suffer from moderate to severe pain. More importantly, opioids are often prescribed in combination with multiple other drugs, especially in patient populations who typically are prescribed a large drug regimen. This review focuses on the current knowledge of common opioid drug-drug interactions (DDIs), focusing specifically on hydrocodone, oxycodone, and morphine DDIs. The DDIs covered in this review include pharmacokinetic DDI arising from enzyme inhibition or induction, primarily due to inhibition of cytochrome p450 enzymes (CYPs). However, opioids such as morphine are metabolized by uridine-5'-diphosphoglucuronosyltransferases (UGTs), principally UGT2B7, and glucuronidation is another important pathway for opioid-drug interactions. This review also covers several pharmacodynamic DDI studies as well as the basics of CYP and UGT metabolism, including detailed opioid metabolism and the potential involvement of metabolizing enzyme gene variation in DDI. Based upon the current literature, further studies are needed to fully investigate and describe the DDI potential with opioids in pain and related disease settings to improve clinical outcomes for patients. SIGNIFICANCE STATEMENT: A review of the literature focusing on drug-drug interactions involving opioids is important because they can be toxic and potentially lethal, occurring through pharmacodynamic interactions as well as pharmacokinetic interactions occurring through inhibition or induction of drug metabolism.

Selective Serotonin Reuptake Inhibitors and Other Treatment Modalities for Deep Space Missions

INTRODUCTION: As humankind ventures further into the depths of space, planning is already underway for long-duration exploration missions that will test the bounds of human performance. Deep space travel will include added risk related to stressors from the isolated, confined, and extreme environment that lies outside the boundaries of low Earth orbit. Currently, selective serotonin reuptake inhibitors (SSRIs) are considered the standard of care for many mental health diagnoses, including anxiety and depression; however, SSRIs are also associated with several undesired side effects. The utility of nonpharmacological therapies for the management of behavioral health conditions has not yet been fully explored.METHODS: A comprehensive literature search was performed using PubMed. Relevant articles pertaining to the psychological impacts of isolated, confined, and extreme environments, use of SSRIs in spaceflight, side effects associated with SSRIs, and nonpharmacological treatments for anxiety and depression were reviewed. Over 70 studies were reviewed in total.RESULTS: Reduced bone mineral density, impaired hemostatic function, significant individual variability resulting from gene polymorphisms, and drug-drug interactions are well described adverse effects of SSRIs that may complicate their operational use in the deep space environment. Four alternative therapies for the treatment of anxiety and depression may show promise for long duration missions.DISCUSSION: Although SSRIs have long been considered standard of care treatment for many behavioral health conditions, we cannot trivialize the risk that prolonged pharmacological therapy may pose. The need to mitigate these risks by exploring alternative therapies has never been more relevant.El-Khoury BB, Ray KL, Altchuler SI, Reichard JF, Dukes CH. Selective serotonin reuptake inhibitors and other treatment modalities for deep space missions. Aerosp Med Hum Perform. 2023; 94(11):843-851.

G-quadruplex forming sequences in the genes coding for cytochrome P450 enzymes and their potential roles in drug metabolism

The majority of drugs are metabolized by cytochrome P450 (CYP) enzymes, primarily belonging to the CYP1, CYP2 and CYP3 families. Genetic variations are the main cause of inter-individual differences in drug response, which constitutes a major concern in pharmacotherapy. G-quadruplexes (G4s), are non-canonical DNA and RNA secondary structures formed by guanine-rich sequences. G4s have been implicated in cancer and gene regulation. In this study, we investigated putative G4-forming sequences (PQSs) in the CYP genes. Our findings reveal a high density of PQSs in the full genes of CYP family 2. Moreover, we observe an increased density of PQSs in the promoters of CYP family 1 genes compared to non-CYP450 genes. Importantly, stable PQSs were also identified in all studied CYP genes. Subsequently, we assessed the impact of the most frequently reported genetic mutations in the selected genes and the possible effect of these mutations on G4 formation as well as on the thermodynamic stability of predicted G4s. We found that 4 SNPs overlap G4 sequences and lead to mutated DNA and RNA G4 forming sequences in their context. Notably, the mutation in the CYP2C9 gene, which is associated with impaired (S)-warfarin metabolism in patients, alters a G4 sequence. We then demonstrated that at least 10 of the 13 chosen cytochrome P450 G4 candidates form G-quadruplex structures in vitro, using a combination of spectroscopic methods. In conclusion, our findings indicate the potential role of G-quadruplexes in the regulation of cytochrome genes, and emphasize the importance of G-quadruplexes in drug metabolism.

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.

Psychiatric mental health nurse practitioner student knowledge and perceptions of pharmacogenetic testing

Psychotropic medications are typically prescribed in a trial-and-error fashion, and some providers are beginning to utilize pharmacogenetic testing (PGx) as a supplemental prescribing tool in treatment decision making. PGx testing shows potential in enhancing provider insights into personalized prescribing for patients by examining genetic information related to drug metabolism. Literature points to providers' lack of knowledge in PGx interpretation as a main barrier, including psychiatric mental health nurse practitioners (PMHNPs). The aim of this study was to measure a difference, if any, in the knowledge and perceptions of PGx after implementation using a pre-post design. This study implemented an educational intervention on graduate nursing students (n = 15). Data were collected by using a pre- and post-interventional questionnaire. Results demonstrated a significant difference in findings related to students' knowledge (p < 0.001), students' skills related to pharmacogenetics, (p < 0.001), as well as students' perceived ability to implement pharmacogenetics into their practice, (p = 0.028). The authors propose that the knowledge gained from the study demonstrates the importance of introducing PGx education into the PMHNP curricula and to prepare future PMHNPs to confidently utilize PGx in their clinical practice.

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.

Current Practices in Pharmacogenomics

Pharmacogenomics, where genomic information is used to tailor medication management, is a strategy to maximize drug efficacy and minimize toxicity. Although pediatric evidence is less robust than for adults, medications influenced by pharmacogenomics are prescribed to children and adolescents. Evidence-based guidelines and drug label annotations are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Pharmacogenomics Knowledgebase (PharmGKB). Some pediatric health care facilities use pharmacogenomics to provide dosing recommendations to pediatricians. Herein, we use a case-based approach to illustrate the use of pharmacogenomic data in pediatric clinical care and provide resources for finding and using pharmacogenomic guidelines.

Utility of pharmacogenetic testing to optimise antidepressant pharmacotherapy in youth: a narrative literature review

Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals' genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current "one-size-fits-all" approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.

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.

Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

Distribution of pharmacogene allele and phenotype frequencies in Brazilian psychiatric patients

Purpose: This work was designed to identify the pharmacogenetic profile of Brazilian psychiatric patients receiving psychoactive drug treatment according to ethnicity. Methods: Based on the GnTech® database, this cross-sectional study analyzed data from self-reported sociodemographic and genetic results from the next-generation sequencing panel composed of 26 pharmacogenes from 359 psychotropic drug users. Results: Variant frequencies of multiple pharmacogenes presented differences between ethnicities (CYP3A5, CYP2D6, CYP1A2, CYP2B6, CYP3A4, UGT1A4, UGT2B15, ABCB1 rs1045642, ADRA2A rs1800544, COMT rs4680, GRIK4 rs1954787, GSK3B rs334558, GSK3B rs6438552, HTR1A rs6295, HTR2A rs7997012, HTR2C rs1414334, MTHFR rs1801131, OPRM1 rs1799971 and 5-HTTLPR), endorsing the necessity of individual-level analyses in drug treatment. Conclusion: A discussion of pharmacogenomic test implementation in psychiatric clinical practice is needed to improve treatment choices, especially in Brazil, a multiethnic country.

Updated benchmarking of variant effect predictors using deep mutational scanning

The assessment of variant effect predictor (VEP) performance is fraught with biases introduced by benchmarking against clinical observations. In this study, building on our previous work, we use independently generated measurements of protein function from deep mutational scanning (DMS) experiments for 26 human proteins to benchmark 55 different VEPs, while introducing minimal data circularity. Many top-performing VEPs are unsupervised methods including EVE, DeepSequence and ESM-1v, a protein language model that ranked first overall. However, the strong performance of recent supervised VEPs, in particular VARITY, shows that developers are taking data circularity and bias issues seriously. We also assess the performance of DMS and unsupervised VEPs for discriminating between known pathogenic and putatively benign missense variants. Our findings are mixed, demonstrating that some DMS datasets perform exceptionally at variant classification, while others are poor. Notably, we observe a striking correlation between VEP agreement with DMS data and performance in identifying clinically relevant variants, strongly supporting the validity of our rankings and the utility of DMS for independent benchmarking.

Pilot Study: Personalized Medicine in Endoscopy, Can Pharmacogenomics Predict Response to Conscious Sedation?

BACKGROUND

Adequate response to moderate (conscious) sedation varies significantly between individuals. Polymorphisms in genes encoding drug metabolizing enzymes can lead to inter-individual variability in drug efficacy, potentially influencing sedation requirements during endoscopic procedures.

OBJECTIVES

The aim of this study was to assess the potential role of inter-individual variation in inherited polymorphisms of drug-metabolizing enzymes, cytochrome P450 (CYP450), specifically CYP3A4 and CYP3A5, in sedation requirements for outpatient endoscopic procedures.

METHODS

A retrospective analysis of sedation requirements and pharmacogenomics data in 106 unique patients who received outpatient esophagogastroduodenoscopy (EGD), colonoscopy, or both between December 2011 and February 2019 was conducted. Patients were divided into two groups based on their sedation requirements during endoscopy (high vs. normal sedation).

RESULTS

Patients with reduced a CYP2C19 metabolism (poor + intermediate metabolizers) (odds ratio [OR] = 0.38, 95% confidence interval [CI]: 0.16-0.91, p = 0.03), poor CYP3A5 metabolism (OR = 0.25, 95% CI: 0.095-0.65, p = 0.0046), and poor UGT1A1 (OR = 2.76, 95% CI: 1.07-7.13, p = 0.08) had higher odds of requiring normal sedation compared to those with CYP2C19 increased metabolism, CYP3A5 intermediate metabolism, and UGT1A1 intermediate metabolism.

CONCLUSION

Information about inter-individual variation in (CYP450) genes may be useful for determining the sedation requirements for outpatient endoscopic procedures. We found that patients with reduced CYP2C19 metabolism, poor CYP3A5 metabolism, and poor UGT1A1 metabolism were more likely to require normal sedation requirements during outpatient endoscopic procedures.

CYP4F12 is a potential biomarker and inhibits cell migration of head and neck squamous cell carcinoma via EMT pathway

Head and neck squamous cell carcinoma (HNSC) is the most common malignant tumor of head and neck. Due to the insidious nature of HNSC and the lack of effective early diagnostic indicators, the development of novel biomarkers to improve patient prognosis is particularly urgent. In this study, we explored and validated the correlation between cytochrome P450 family 4 subfamily F member 12 (CYP4F12) expression levels and HNSC progression using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets and collected patient samples. We analyzed the association of CYP4F12 expression with clinicopathological features, immune correlation and prognosis. Finally, we analyzed the correlation between CYP4F12 and pathways, and verified by experiments. The results showed that CYP4F12 was low expressed in tumor tissues, participated in a variety of phenotypic changes of HNSC and affected immune cell infiltration. Pathway analysis indicated that CYP4F12 may play a key role in tumor cell migration and apoptosis. Experimental results showed that over-expression of CYP4F12 inhibited cell migration and enhanced the adhesion between cells and matrix by inhibiting epithelial-mesenchymal transition (EMT) pathway in HNSC cells. In conclusion, our study provided insights into the role of CYP4F12 in HNSC and revealed that CYP4F12 may be a potential therapeutic target for HNSC.

Characterizing the combined effects of cytochrome P450 missense variation within star allele definitions

Background: Cytochrome P450 (CYP) genetic variation largely impacts drug response. However, many CYP star alleles (haplotypes) lack functional annotation, impeding our understanding of drug metabolism mechanisms. We aimed to investigate the impact of missense variant combinations on CYP protein structures. Methods: Normal mode analysis was conducted on 261 missense variants within 91 CYP haplotypes. CYP2D6*2 and CYP2D6*17 were prioritized for molecular dynamics simulation. Results: Normal mode analysis and molecular dynamics highlight the effects of known CYP missense variants on protein stability and conformational dynamics. Missense variants within haplotypes may have intermodulating effects on protein structure and function. Conclusion: This study highlights the utility of multiscale modeling in interpreting CYP missense variants and particularly their combinations within various star alleles.

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.

Characterization of complex structural variation in the CYP2D6-CYP2D7-CYP2D8 gene loci using single-molecule long-read sequencing

Complex regions in the human genome such as repeat motifs, pseudogenes and structural (SVs) and copy number variations (CNVs) present ongoing challenges to accurate genetic analysis, particularly for short-read Next-Generation-Sequencing (NGS) technologies. One such region is the highly polymorphic CYP2D loci, containing CYP2D6, a clinically relevant pharmacogene contributing to the metabolism of >20% of common drugs, and two highly similar pseudogenes, CYP2D7 and CYP2D8. Multiple complex SVs, including CYP2D6/CYP2D7-derived hybrid genes are known to occur in different configurations and frequencies across populations and are difficult to detect and characterize accurately. This can lead to incorrect enzyme activity assignment and impact drug dosing recommendations, often disproportionally affecting underrepresented populations. To improve CYP2D6 genotyping accuracy, we developed a PCR-free CRISPR-Cas9 based enrichment method for targeted long-read sequencing that fully characterizes the entire CYP2D6-CYP2D7-CYP2D8 loci. Clinically relevant sample types, including blood, saliva, and liver tissue were sequenced, generating high coverage sets of continuous single molecule reads spanning the entire targeted region of up to 52 kb, regardless of SV present (n = 9). This allowed for fully phased dissection of the entire loci structure, including breakpoints, to accurately resolve complex CYP2D6 diplotypes with a single assay. Additionally, we identified three novel CYP2D6 suballeles, and fully characterized 17 CYP2D7 and 18 CYP2D8 unique haplotypes. This method for CYP2D6 genotyping has the potential to significantly improve accurate clinical phenotyping to inform drug therapy and can be adapted to overcome testing limitations of other clinically challenging genomic regions.

Mining of molecular insights of CYP2A6 and its variants complex with coumarin (CYP2A6*-coumarin) using molecular dynamics simulation

CYP2A6 is a very important enzyme that plays a crucial role in nicotine compounds and is responsible for the metabolism of more than 3% drugs of total metabolized drugs by the CYP family and reported as one of very important pharmacogenes. CYP2A6 is highly polymorphic in nature and reported with more than 40 variants, most of these variants are SNPs originated and population specific. It has been well observed and reported that the presence of these population-specific non-synonymous SNPs in CYP2A6 alters the rate of drug metabolism and as a functional consequence, drugs produce an abnormal response. Though genomics and pharmacogenomics studies are there, very less is known about the structural effects of these SNPs on molecular-interaction and folding of CYP2A6. To fill the knowledge gap, SNPs based four variants, i.e., CYP2A6*2, CYP2A6*18, CYP2A6*21, and CYP2A6*35, which are frequently reported in the South Asian population, were considered for the study. Coumarin (DB04665), a well reported drug, is considered as a model substance, and the effect of all four variants on 'CYP2A6*-coumarin' complex was studied. MD simulation-based analysis (at 200 ns) was performed and comparative analysis with respect to wild type 'CYP2A6-coumarin' complex was done. Though observation didn't find any global effect on complete complex but found some crucial minor-local alteration in interaction and folding process. It is assumed that the change due to SNPs in the single amino acid did not bring global change in physiochemical properties of CYP2A6* but caused local-trivial changes which are very crucial for its metabolic activity.Communicated by Ramaswamy H. Sarma.

Efficient and accurate KIR and HLA genotyping with massively parallel sequencing data

Killer cell immunoglobulin like receptor (KIR) genes and human leukocyte antigen (HLA) genes play important roles in innate and adaptive immunity. They are highly polymorphic and cannot be genotyped with standard variant calling pipelines. Compared with HLA genes, many KIR genes are similar to each other in sequences and may be absent in the chromosomes. Therefore, although many tools have been developed to genotype HLA genes using common sequencing data, none of them work for KIR genes. Even specialized KIR genotypers could not resolve all the KIR genes. Here we describe T1K, a novel computational method for the efficient and accurate inference of KIR or HLA alleles from RNA-seq, whole-genome sequencing, or whole-exome sequencing data. T1K jointly considers alleles across all genotyped genes, so it can reliably identify present genes and distinguish homologous genes, including the challenging KIR2DL5A/KIR2DL5B genes. This model also benefits HLA genotyping, where T1K achieves high accuracy in benchmarks. Moreover, T1K can call novel single-nucleotide variants and process single-cell data. Applying T1K to tumor single-cell RNA-seq data, we found that KIR2DL4 expression was enriched in tumor-specific CD8+ T cells. T1K may open the opportunity for HLA and KIR genotyping across various sequencing applications.

Determination of the Duplicated CYP2D6 Allele Using Real-Time PCR Signal: An Alternative Approach

CYP2D6 duplication has important pharmacogenomic implications. Reflex testing with long-range PCR (LR-PCR) can resolve the genotype when a duplication and alleles with differing activity scores are detected. We evaluated whether visual inspection of plots from real-time-PCR-based targeted genotyping with copy number variation (CNV) detection could reliably determine the duplicated CYP2D6 allele. Six reviewers evaluated QuantStudio OpenArray CYP2D6 genotyping results and the TaqMan Genotyper plots for seventy-three well-characterized cases with three copies of CYP2D6 and two different alleles. Reviewers blinded to the final genotype visually assessed the plots to determine the duplicated allele or opt for reflex sequencing. Reviewers achieved 100% accuracy for cases with three CYP2D6 copies that they opted to report. Reviewers did not request reflex sequencing in 49-67 (67-92%) cases (and correctly identified the duplicated allele in each case); all remaining cases (6-24) were marked by at least one reviewer for reflex sequencing. In most cases with three copies of CYP2D6, the duplicated allele can be determined using a combination of targeted genotyping using real-time PCR with CNV detection without need for reflex sequencing. In ambiguous cases and those with >3 copies, LR-PCR and Sanger sequencing may still be necessary for determination of the duplicated allele.

Characterization of 15 CYP2J2 variants identified in the Chinese Han population on the metabolism of ebastine and terfenadine in vitro

Genetic polymorphism of the cytochrome P450 (CYP) gene can significantly influence the metabolism of endogenous and xenobiotic compounds. However, few studies have focused on the polymorphism of CYP2J2 and its impact on drug catalytic activity, especially in the Chinese Han population. In this study, we sequenced the promoter and exon regions of CYP2J2 in 1,163 unrelated healthy Chinese Han individuals using the multiplex PCR amplicon sequencing method. Then, the catalytic activities of the detected CYP2J2 variants were evaluated after recombinant expression in S. cerevisiae microsomes. As a result, CYP2J2*7, CYP2J2*8, 13 variations in the promoter region and 15 CYP2J2 nonsynonymous variants were detected, of which V15A, G24R, V68A, L166F and A391T were novel missense variations. Immunoblotting results showed that 11 of 15 CYP2J2 variants exhibited lower protein expression than wild-type CYP2J2.1. In vitro functional analysis results revealed that the amino acid changes of 14 variants could significantly influence the drug metabolic activity of CYP2J2 toward ebastine or terfenadine. Specifically, 4 variants with relatively higher allele frequencies, CYP2J2.8, 173_173del, K267fs and R446W, exhibited extremely low protein expression and defective catalytic activities for both substrates. Our results indicated that a high genetic polymorphism of CYP2J2 could be detected in the Chinese Han population, and most genetic variations in CYP2J2 could influence the expression and catalytic activity of CYP2J2. Our data significantly enrich the knowledge of genetic polymorphisms in CYP2J2 and provide new theoretical information for corresponding individualized medication in Chinese and other Asian populations.

Pharmacogenomics in practice: a review and implementation guide

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

A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact

The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.

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.

A retrospective analysis of preemptive pharmacogenomic testing in 22,918 individuals from China

BACKGROUND

Pharmacogenomics (PGx) examines the influence of genetic variation on drug responses. With more and more Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines published, PGx is gradually shifting from the reactive testing of single gene toward the preemptive testing of multiple genes. But the profile of PGx genes, especially for the intra-country diversity, is not well understood in China.

METHODS

We retrospectively collected preemptive PGx testing data of 22,918 participants from 20 provinces of China, analyzed frequencies of alleles, genotypes and phenotypes of pharmacogenes, predicted drug responses for each participant, and performed comparisons between different provinces.

RESULTS AND CONCLUSION

After analyzing 15 pharmacogenes from CPIC guidelines of 31 drugs, we found that 99.97% of individuals may have an atypical response to at least one drug; the participants carry actionable genotypes leading to atypical dosage recommendation for a median of eight drugs. Over 99% of the participants were recommended a decreased warfarin dose based on genetic factors. There were 20 drugs with high-risk ratios from 0.18% to 58.25%, in which clopidogrel showed the highest high-risk ratio. In addition, the high-risk ratio of rasburicase in GUANGDONG (risk ratio (RR) = 13.17, 95%CI:4.06-33.22, p < 0.001) and GUANGXI (RR = 23.44, 95%CI:8.83-52.85, p < 0.001) were significantly higher than that in all provinces. Furthermore, the diversity we observed among 20 provinces suggests that preemptive PGx testing in different geographical regions in China may need to pay more attention to specific genes. These results emphasize the importance of preemptive PGx testing and provide essential evidence for promoting clinical implementation in China.