Accurately genotyping CYP2D6: not for the faint of heart

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Implementing a pragmatic clinical trial to tailor opioids for chronic pain on behalf of the IGNITE ADOPT PGx investigators

Chronic pain is a prevalent condition with enormous economic burden. Opioids such as tramadol, codeine, and hydrocodone are commonly used to treat chronic pain; these drugs are activated to more potent opioid receptor agonists by the hepatic CYP2D6 enzyme. Results from clinical studies and mechanistic understandings suggest that CYP2D6-guided therapy will improve pain control and reduce adverse drug events. However, CYP2D6 is rarely used in clinical practice due in part to the demand for additional clinical trial evidence. Thus, we designed the ADOPT-PGx (A Depression and Opioid Pragmatic Trial in Pharmacogenetics) chronic pain study, a multicenter, pragmatic, randomized controlled clinical trial, to assess the effect of CYP2D6 testing on pain management. The study enrolled 1048 participants who are taking or being considered for treatment with CYP2D6-impacted opioids for their chronic pain. Participants were randomized to receive immediate or delayed (by 6 months) genotyping of CYP2D6 with clinical decision support (CDS). CDS encouraged the providers to follow the CYP2D6-guided trial recommendations. The primary study outcome is the 3-month absolute change in the composite pain intensity score assessed using Patient-Reported Outcomes Measurement Information System (PROMIS) measures. Follow-up will be completed in July 2024. Herein, we describe the design of this trial along with challenges encountered during enrollment.

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.

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.

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 CYP2D6 Pharmacogenetic Variation in Sub-Saharan African Populations

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora.

Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan

The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.

Characterization of Novel CYP2D6 Alleles across Sub-Saharan African Populations

The CYP2D6 gene has been widely studied to characterize variants and/or star alleles, which account for a significant portion of variability in drug responses observed within and between populations. However, African populations remain under-represented in these studies. The increasing availability of high coverage genomes from African populations has provided the opportunity to fill this knowledge gap. In this study, we characterized computationally predicted novel CYP2D6 star alleles in 30 African subjects for whom DNA samples were available from the Coriell Institute. CYP2D6 genotyping and resequencing was performed using a variety of commercially available and laboratory-developed tests in a collaborative effort involving three laboratories. Fourteen novel CYP2D6 alleles and multiple novel suballeles were identified. This work adds to the growing catalogue of validated African ancestry CYP2D6 allelic variation in pharmacogenomic databases, thus laying the foundation for future functional studies and improving the accuracy of CYP2D6 genotyping, phenotype prediction, and the refinement of clinical pharmacogenomic implementation guidelines in African and global settings.

Cas9 targeted nanopore sequencing with enhanced variant calling improves CYP2D6-CYP2D7 hybrid allele genotyping

CYP2D6 is a very important pharmacogene as it is responsible for the metabolization or bioactivation of 20 to 30% of the clinically used drugs. However, despite its relatively small length of only 4.4 kb, it is one of the most challenging pharmacogenes to genotype due to the high similarity with its neighboring pseudogenes and the frequent occurrence of CYP2D6-CYP2D7 hybrids. Unfortunately, most current genotyping methods are therefore not able to correctly determine the complete CYP2D6-CYP2D7 sequence. Therefore, we developed a genotyping assay to generate complete allele-specific consensus sequences of complex regions by optimizing the PCR-free nanopore Cas9-targeted sequencing (nCATS) method combined with adaptive sequencing, and developing a new comprehensive long read genotyping (CoLoRGen) pipeline. The CoLoRGen pipeline first generates consensus sequences of both alleles and subsequently determines both large structural and small variants to ultimately assign the correct star-alleles. In reference samples, our genotyping assay confirms the presence of CYP2D6-CYP2D7 large structural variants, single nucleotide variants (SNVs), and small insertions and deletions (INDELs) that go undetected by most current assays. Moreover, our results provide direct evidence that the CYP2D6 genotype of the NA12878 DNA should be updated to include the CYP2D6-CYP2D7 *68 hybrid and several additional single nucleotide variants compared to existing references. Ultimately, the nCATS-CoLoRGen genotyping assay additionally allows for more accurate gene function predictions by enabling the possibility to detect and phase de novo mutations in addition to known large structural and small variants.

During the last decades, the usefulness of personalized medicine has become increasingly apparent. Directly linked to that is the need for accurate genotyping assays to determine the pharmacogenetic profile of patients. Continuing research has led to the development of genotyping assays that perform quite robustly. However, complex genes remain an issue when it comes to determining the complete sequence correctly. An example of such a complex but very important pharmacogene is CYP2D6. Therefore, we developed a genotyping assay in an attempt to generate complete allele-specific consensus sequences of CYP2D6, by optimizing a targeted amplification-free long-read sequencing method and developing a new analysis pipeline. In reference samples, we showed that our genotyping assay performed accurately and confirmed the presence of variants that go undetected by most current assays. However, the implementation of this assay in practice is still hampered as the selected enrichment strategies inherently lead to a low percentage of on-target reads, resulting in low on-target sequencing depths. Further optimization and validation of the assay is thus needed, but definitely worth considering for follow-up research as we already demonstrated the added value for generating more complete genotypes, which on its turn will result in more accurate gene function predictions.

Methodology for clinical genotyping of CYP2D6 and CYP2C19

Many antidepressants, atomoxetine, and several antipsychotics are metabolized by the cytochrome P450 enzymes CYP2D6 and CYP2C19, and guidelines for prescribers based on genetic variants exist. Although some laboratories offer such testing, there is no consensus regarding validated methodology for clinical genotyping of CYP2D6 and CYP2C19. The aim of this paper was to cross-validate multiple technologies for genotyping CYP2D6 and CYP2C19 against each other, and to contribute to feasibility for clinical implementation by providing an enhanced range of assay options, customizable automated translation of data into haplotypes, and a workflow algorithm. AmpliChip CYP450 and some TaqMan single nucleotide variant (SNV) and copy number variant (CNV) data in the Genome-based therapeutic drugs for depression (GENDEP) study were used to select 95 samples (out of 853) to represent as broad a range of CYP2D6 and CYP2C19 genotypes as possible. These 95 included a larger range of CYP2D6 hybrid configurations than have previously been reported using inter-technology data. Genotyping techniques employed were: further TaqMan CNV and SNV assays, xTAGv3 Luminex CYP2D6 and CYP2C19, PharmacoScan, the Ion AmpliSeq Pharmacogenomics Panel, and, for samples with CYP2D6 hybrid configurations, long-range polymerase chain reactions (L-PCRs) with Sanger sequencing and Luminex. Agena MassARRAY was also used for CYP2C19. This study has led to the development of a broader range of TaqMan SNV assays, haplotype phasing methodology with TaqMan adaptable for other technologies, a multiplex genotyping method for efficient identification of some hybrid haplotypes, a customizable automated translation of SNV and CNV data into haplotypes, and a clinical workflow algorithm.

Recommendations for Clinical CYP2D6 Genotyping Allele Selection: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, and the European Society for Pharmacogenomics and Personalized Therapy

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 to determine a minimal set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations on a minimal panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories in designing assays for PGx testing. When developing these recommendations, the Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations with regard to PGx testing. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document is focused on clinical CYP2D6 PGx testing that may be applied to all cytochrome P450 2D6-metabolized medications. These recommendations are not meant to be interpreted as prescriptive but to provide a reference guide for clinical laboratories that may be either implementing PGx testing or reviewing and updating their existing platform.

Resolving discordant CYP2D6 genotyping results in Thai subjects: platform limitations and novel haplotypes

Aim: Several CYP2D6 Luminex xTAG genotype calls were identified as inconsistent or suspicious among Thai subjects and further characterized to identify the root causes. Material & methods: Forty-eight subjects were followed-up with long-range-PCR, quantitative copy number assays and/or Sanger sequencing. Results: Most of the Luminex-duplication calls were either negative or had hybrid structures involving CYP2D6*36 in various configurations. Ten samples were inaccurately called as CYP2D6*2, *29 or *35 alleles. Sequencing revealed three novel haplotypes, CYP2D6*142, *143 and *144 of which two are nonfunctional. Conclusion: The Luminex platform produced a relatively high number of false genotype calls for Thai subjects. Our findings underscore the need for the systematic characterization of the CYP2D6 locus in diverse populations and rigorous platform validation.

StellarPGx: A Nextflow Pipeline for Calling Star Alleles in Cytochrome P450 Genes

Bioinformatics pipelines for calling star alleles (haplotypes) in cytochrome P450 (CYP) genes are important for the implementation of precision medicine. Genotyping CYP genes using high throughput sequencing data is complicated, e.g., by being highly polymorphic, not to mention the structural variations especially in CYP2D6, CYP2A6, and CYP2B6. Genome graph-based variant detection approaches have been shown to be reliable for genotyping HLA alleles. However, their application to enhancing star allele calling in CYP genes has not been extensively explored. We present StellarPGx, a Nextflow pipeline for accurately genotyping CYP genes by combining genome graph-based variant detection, read coverage information from the original reference-based alignments, and combinatorial diplotype assignments. The implementation of StellarPGx using Nextflow facilitates its portability, reproducibility, and scalability on various user platforms. StellarPGx is currently able to genotype 12 important pharmacogenes belonging to the CYP1, 2, and 3 families. For purposes of validation, we use CYP2D6 as a model gene owing to its high degree of polymorphisms (over 130 star alleles defined to date, including complex structural variants) and clinical importance. We applied StellarPGx and three existing callers to 109 whole genome sequenced samples for which the Genetic Testing Reference Material Coordination Program (GeT-RM) has recently provided consensus truth CYP2D6 diplotypes. StellarPGx had the highest CYP2D6 diplotype concordance (99%) with GeT-RM compared with Cyrius (98%), Aldy (82%), and Stargazer (84%). This exemplifies the high accuracy of StellarPGx and highlights its importance for both research and clinical pharmacogenomics applications. The StellarPGx pipeline is open-source and available from https://github.com/SBIMB/StellarPGx.

Identification of CYP2D6 Haplotypes that Interfere with Commonly Used Assays for Copy Number Variation Characterization

Cytochrome P450 2D6 (CYP2D6) copy number (CN) variation affects the metabolism of numerous prescribed drugs. Sequence variation within primer or probe target regions of hydrolysis probe CN assays can generate false-positive calls for CN loss. Furthermore, CYP2D6-CYP2D7 hybrids and gene conversions can cause difficult to interpret discordant CN calls. The identification of haplotypes with CN variations and structural arrangements is important to predict phenotype accurately. During clinical testing with hydrolysis probe assays targeting three CYP2D6 regions (intron 2, intron 6, and exon 9), samples with haplotypes causing inconsistent CN calls were identified. To resolve these cases, next-generation sequencing and allele-specific Sanger sequencing was performed. Sequence analysis of 16 samples, all but one from subjects of African descent, identified six novel suballeles containing single-nucleotide polymorphisms, which cause false-positive calls for CN loss in introns 2 and 6. Five samples with an exon 9 CN loss contained CYP2D6/CYP2D7 hybrids (∗13 or ∗36) and one sample was found to have a novel haplotype, CYP2D6∗141. Interestingly, CYP2D6∗141 contains a CYP2D7-derived exon 9 conversion and core single-nucleotide polymorphisms that are otherwise found in CYP2D6∗17 and ∗27. Although these variants are rare, they can cause inconsistent CN calls that typically are reported as no calls or indeterminant, and thus may deprive patients, particularly those of African descent, from taking full benefit of pharmacogenetic testing.

Potential of whole-genome sequencing-based pharmacogenetic profiling

Pharmacogenetics represents a major driver of precision medicine, promising individualized drug selection and dosing. Traditionally, pharmacogenetic profiling has been performed using targeted genotyping that focuses on common/known variants. Recently, whole-genome sequencing (WGS) is emerging as a more comprehensive short-read next-generation sequencing approach, enabling both gene diagnostics and pharmacogenetic profiling, including rare/novel variants, in a single assay. Using the example of the pharmacogene CYP2D6, we demonstrate the potential of WGS-based pharmacogenetic profiling as well as emphasize the limitations of short-read next-generation sequencing. In the near future, we envision a shift toward long-read sequencing as the predominant method for gene diagnostics and pharmacogenetic profiling, providing unprecedented data quality and improving patient care.

Cyrius: accurate CYP2D6 genotyping using whole-genome sequencing data

Responsible for the metabolism of ~21% of clinically used drugs, CYP2D6 is a critical component of personalized medicine initiatives. Genotyping CYP2D6 is challenging due to sequence similarity with its pseudogene paralog CYP2D7 and a high number and variety of common structural variants (SVs). Here we describe a novel bioinformatics method, Cyrius, that accurately genotypes CYP2D6 using whole-genome sequencing (WGS) data. We show that Cyrius has superior performance (96.5% concordance with truth genotypes) compared to existing methods (84–86.8%). After implementing the improvements identified from the comparison against the truth data, Cyrius’s accuracy has since been improved to 99.3%. Using Cyrius, we built a haplotype frequency database from 2504 ethnically diverse samples and estimate that SV-containing star alleles are more frequent than previously reported. Cyrius will be an important tool to incorporate pharmacogenomics in WGS-based precision medicine initiatives.

Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

BACKGROUND

Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment.

METHODS

We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health).

RESULTS

CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples.

LIMITATIONS

lack of validation in large samples from the general population.

CONCLUSIONS

Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

Review and Consensus on Pharmacogenomic Testing in Psychiatry

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Ambele M, S. Pepper M. Barriers to Implementing Clinical Pharmacogenetics Testing in Sub-Saharan Africa. A Critical Review

Clinical research in high-income countries is increasingly demonstrating the cost- effectiveness of clinical pharmacogenetic (PGx) testing in reducing the incidence of adverse drug reactions and improving overall patient care. Medications are prescribed based on an individual’s genotype (pharmacogenes), which underlies a specific phenotypic drug response. The advent of cost-effective high-throughput genotyping techniques coupled with the existence of Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines for pharmacogenetic “actionable variants” have increased the clinical applicability of PGx testing. The implementation of clinical PGx testing in sub-Saharan African (SSA) countries can significantly improve health care delivery, considering the high incidence of communicable diseases, the increasing incidence of non-communicable diseases, and the high degree of genetic diversity in these populations. However, the implementation of PGx testing has been sluggish in SSA, prompting this review, the aim of which is to document the existing barriers. These include under-resourced clinical care logistics, a paucity of pharmacogenetics clinical trials, scientific and technical barriers to genotyping pharmacogene variants, and socio-cultural as well as ethical issues regarding health-care stakeholders, among other barriers. Investing in large-scale SSA PGx research and governance, establishing biobanks/bio-databases coupled with clinical electronic health systems, and encouraging the uptake of PGx knowledge by health-care stakeholders, will ensure the successful implementation of pharmacogenetically guided treatment in SSA.

Determination of novel CYP2D6 haplotype using the targeted sequencing followed by the long-read sequencing and the functional characterization in the Japanese population

Next-generation sequencing (NGS) has identified variations in cytochrome P450 (CYP) 2D6 associated with drug responses. However, determination of novel haplotypes is difficult because of the short reads generated by NGS. We aimed to identify novel CYP2D6 variants in the Japanese population and predict the CYP2D6 phenotype based on in vitro metabolic studies. Using a targeted NGS panel (PKSeq), 990 Japanese genomes were sequenced, and then novel CYP2D6 haplotypes were determined. K_m, V_max, and intrinsic clearance (V_max/K_m) of N-desmethyl-tamoxifen 4-hydroxylation were calculated by in vitro metabolic studies using cDNA-expressed CYP2D6 proteins. After determination of the CYP2D6 diplotypes, phenotypes of the individuals were predicted based on the in vitro metabolic activities. Targeted NGS identified 14 CYP2D6 variants not registered in the Pharmacogene Variation Consortium (PharmVar) database. Ten novel haplotypes were registered as CYP2D6*128 to *137 alleles in the PharmVar database. Based on the V_max/K_m value of each allele, *128, *129, *130, *131, *132, and *133 were predicted to be nonfunctional alleles. According to the results of the present study, six normal metabolizers (NM) and one intermediate (IM) metabolizers were designated as IM and poor metabolizers (PM), respectively. Our findings provide important insights into novel haplotypes and haplotypes of CYP2D6 and the effects on in vitro metabolic activities.

A systematic comparison of pharmacogene star allele calling bioinformatics algorithms: a focus on CYP2D6 genotyping

Genetic variation in genes encoding cytochrome P450 enzymes has important clinical implications for drug metabolism. Bioinformatics algorithms for genotyping these highly polymorphic genes using high-throughput sequence data and automating phenotype prediction have recently been developed. The CYP2D6 gene is often used as a model during the validation of these algorithms due to its clinical importance, high polymorphism, and structural variations. However, the validation process is often limited to common star alleles due to scarcity of reference datasets. In addition, there has been no comprehensive benchmark of these algorithms to date. We performed a systematic comparison of three star allele calling algorithms using 4618 simulations as well as 75 whole-genome sequence samples from the GeT-RM project. Overall, we found that Aldy and Astrolabe are better suited to call both common and rare diplotypes compared to Stargazer, which is affected by population structure. Aldy was the best performing algorithm in calling CYP2D6 structural variants followed by Stargazer, whereas Astrolabe had limitations especially in calling hybrid rearrangements. We found that ensemble genotyping, characterised by taking a consensus of genotypes called by all three algorithms, has higher haplotype concordance but it is prone to ambiguities whenever complete discrepancies between the tools arise. Further, we evaluated the effects of sequencing coverage and indel misalignment on genotyping accuracy. Our account of the strengths and limitations of these algorithms is extremely important to clinicians and researchers in the pharmacogenomics and precision medicine communities looking to haplotype CYP2D6 and other pharmacogenes using high-throughput sequencing data.

Nanopore sequencing of the pharmacogene CYP2D6 allows simultaneous haplotyping and detection of duplications

Aim: Long read sequencing offers the promise of overcoming some of the challenges in accurate genotyping of complex genes, along with the advantage of straightforward variant phasing. We have established methods for sequencing and haplotyping of the whole CYP2D6 gene using nanopore sequencing. Materials and methods: 32 samples covering various haplotypes including gene duplication were sequenced on the GridION platform. Results: Haplotypes of 52 alleles matched accurately to known star (*) allele subvariants, with the remaining 12 being assigned as new alleles, or new subvariants of known alleles. Duplicated alleles could be detected by analyzing the allelic balance. Conclusion: Nanopore sequencing of CYP2D6 offers a high throughput method for accurate haplotyping, detection of new variants and determination of duplicated alleles.

Interrogation of CYP2D6 Structural Variant Alleles Improves the Correlation Between CYP2D6 Genotype and CYP2D6-Mediated Metabolic Activity

The cytochrome P450 2D6 (CYP2D6) gene locus is challenging to accurately genotype due to numerous single nucleotide variants and complex structural variation. Our goal was to determine whether the CYP2D6 genotype‐phenotype correlation is improved when diplotype assignments incorporate structural variation, identified by the bioinformatics tool Stargazer, with next‐generation sequencing data. Using CYP2D6 activity measured with substrates dextromethorphan and metoprolol, activity score explained 40% and 34% of variability in metabolite formation rates, respectively, when diplotype calls incorporated structural variation, increasing from 36% and 31%, respectively, when diplotypes did not incorporate structural variation. We also investigated whether the revised Clinical Pharmacogenetics Implementation Consortium (CPIC) recommendations for translating genotype to phenotype improve CYP2D6 activity predictions over the current system. Although the revised recommendations do not improve the correlation between activity score and CYP2D6 activity, perhaps because of low frequency of the CYP2D6*10 allele, the correlation with metabolizer phenotype group was significantly improved for both substrates. We also measured the function of seven rare coding variants: one (A449D) exhibited decreased (44%) and another (R474Q) increased (127%) activity compared with reference CYP2D6.1 protein. Allele‐specific analysis found that A449D is part of a novel CYP2D6*4 suballele, CYP2D6*4.028. The novel haplotype containing R474Q was designated CYP2D6*138 by PharmVar; another novel haplotype containing R365H was designated CYP2D6*139. Accuracy of CYP2D6 phenotype prediction is improved when the CYP2D6 gene locus is interrogated using next‐generation sequencing coupled with structural variation analysis. Additionally, revised CPIC genotype to phenotype translation recommendations provides an improvement in assigning CYP2D6 activity.

Characterization of Reference Materials for Genetic Testing of CYP2D6 Alleles: A GeT-RM Collaborative Project

Pharmacogenetic testing increasingly is available from clinical and research laboratories. However, only a limited number of quality control and other reference materials currently are available for the complex rearrangements and rare variants that occur in the CYP2D6 gene. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Cell Repositories (Camden, NJ), has characterized 179 DNA samples derived from Coriell cell lines. Testing included the recharacterization of 137 genomic DNAs that were genotyped in previous Genetic Testing Reference Material Coordination Program studies and 42 additional samples that had not been characterized previously. DNA samples were distributed to volunteer testing laboratories for genotyping using a variety of commercially available and laboratory-developed tests. These publicly available samples will support the quality-assurance and quality-control programs of clinical laboratories performing CYP2D6 testing.

Prediction of drug response and adverse drug reactions: From twin studies to Next Generation Sequencing

Understanding and predicting inter-individual differences related to the success of drug therapy is of tremendous importance, both during drug development and for clinical applications. Importantly, while seminal twin studies indicate that the majority of inter-individual differences in drug disposition are driven by hereditary factors, common genetic polymorphisms explain only less than half of this genetically encoded variability. Recent progress in Next Generation Sequencing (NGS) technologies has for the first time allowed to comprehensively map the genetic landscape of human pharmacogenes. Importantly, these projects have unveiled vast numbers of rare genetic variants, which are estimated to contribute substantially to the missing heritability of drug metabolism phenotypes. However, functional interpretation of these rare variants remains challenging and constitutes one of the important frontiers of contemporary pharmacogenomics. Furthermore, NGS technologies face challenges in the interrogation of genes residing in complex genomic regions, such as CYP2D6 and HLA genes. We here provide an update of the implementation of pharmacogenomic variations in the clinical setting and present emerging strategies that facilitate the translation of NGS data into clinically useful information. Importantly, we anticipate that these developments will soon result in a paradigm shift of pre-emptive genotyping away from the interrogation to candidate variants and towards the comprehensive profiling of an individuals genotype, thus allowing for a true individualization of patient drug treatment regimens.

The 9th Santorini Conference: Systems Medicine, Personalised Health and Therapy. "The Odyssey from Hope to Practice", Santorini, Greece, 30 September⁻3 October 2018

The 9th traditional biannual conference on Systems Medicine, Personalised Health & Therapy—“The Odyssey from Hope to Practice”, inspired by the Greek mythology, was a call to search for practical solutions in cardio-metabolic diseases and cancer, to resolve and overcome the obstacles in modern medicine by creating more interactions among disciplines, as well as between academic and industrial research, directed towards an effective ‘roadmap’ for personalised health and therapy. The 9th Santorini Conference, under the Presidency of Sofia Siest, the director of the INSERM U1122; IGE-PCV (www.u1122.inserm.fr), University of Lorraine, France, offered a rich and innovative scientific program. It gathered 34 worldwide distinguished speakers, who shared their passion for personalised medicine with 160 attendees in nine specific sessions on the following topics: First day: The Odyssey from hope to practice: Personalised medicine—landmarks and challenges Second day: Diseases to therapeutics—genotype to phenotype an “-OMICS” approach: focus on personalised therapy and precision medicine Third day: Gene-environment interactions and pharmacovigilance: a pharmacogenetics approach for deciphering disease “bench to clinic to reality” Fourth day: Pharmacogenomics to drug discovery: a big data approach and focus on clinical data and clinical practice. In this article we present the topics shared among the participants of the conference and we highlight the key messages.

Integrated CYP2D6 interrogation for multiethnic copy number and tandem allele detection

AIM

To comprehensively interrogate CYP2D6 by integrating genotyping, copy number analysis and novel strategies to identify CYP2D6*36 and characterize CYP2D6 duplications.

METHODS

Genotyping of 16 CYP2D6 alleles, multiplex ligation-dependent probe amplification (MLPA) and CYP2D6*36 and duplication allele-specific genotyping were performed on 427 African-American, Asian, Caucasian, Hispanic, and Ashkenazi Jewish individuals.

RESULTS

A novel PCR strategy determined that almost half of all CYP2D6*10 (100C>T) alleles are actually *36 (isolated or in tandem with *10) and all identified duplication alleles were characterized. Integrated results from all testing platforms enabled the refinement of genotype frequencies across all studied populations.

CONCLUSION

The polymorphic CYP2D6 gene requires comprehensive interrogation to characterize allelic variation across ethnicities, which was enabled in this study by integrating multiplexed genotyping, MLPA copy number analysis, novel PCR strategies and duplication allele-specific genotyping.