Next-generation sequencing of pharmacogenes: a critical analysis focusing on schizophrenia treatment

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.

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

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

Investigating aberrantly expressed microRNAs in peripheral blood mononuclear cells from patients with treatment‑resistant schizophrenia using miRNA sequencing and integrated bioinformatics

Treatment-resistant schizophrenia (TRS) is a common phenotype of schizophrenia that places a considerable burden on patients as well as on society. TRS is known for its tendency to relapse and uncontrollable nature, with a poor response to antipsychotics other than clozapine. Therefore, it is urgent to identify objective biological markers, so as to guide its treatment and associated clinical work. In the present study, the peripheral blood mononuclear cells (PBMCs) of patients with TRS and a healthy control group, which were gender-, age- and ethnicity-matched, were subjected to microRNA (miRNA/miR) sequencing to screen out the top three miRNAs with the highest fold change values. These were then validated in the TRS (n=34) and healthy control (n=31) groups by reverse transcription-quantitative PCR. For two of the top three miRNAs, the PCR results were in accordance with the sequencing result (P<0.01), while the third miRNA exhibited the opposite trend (P<0.01). To elucidate the functions of these two miRNAs, Homo sapiens (hsa)-miR-218-5p and hsa-miR-1262 and their regulatory network, target gene prediction was first performed using online TargetScan and Diana-micro T software. Bioinformatics analysis was then performed using functional enrichment analysis to determine the Gene Ontology terms in the category biological process and the Kyoto Encyclopedia of Genes and Genomes pathways. It was revealed that these target genes were markedly associated with the nervous system and brain function, and it was obvious that the differentially expressed miRNAs most likely participated in the pathogenesis of TRS. A receiver operating characteristic curve was generated to confirm the distinct diagnostic value of these two miRNAs. It was concluded that aberrantly expressed miRNAs in PMBCs may be implicated in the pathogenesis of TRS and may serve as specific peripheral blood-based biomarkers for the early diagnosis of TRS.

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.

Targeted next generation sequencing as a tool for precision medicine

BACKGROUND

Targeted next-generation sequencing (NGS) enables rapid identification of common and rare genetic variation. The detection of variants contributing to therapeutic drug response or adverse effects is essential for implementation of individualized pharmacotherapy. Successful application of short-read based NGS to pharmacogenes with high sequence homology, nearby pseudogenes and complex structure has been previously shown despite anticipated technical challenges. However, little is known regarding the utility of such panels to detect copy number variation (CNV) in the highly polymorphic cytochrome P450 (CYP) 2D6 gene, or to identify the promoter (TA)₇ TAA repeat polymorphism UDP glucuronosyltransferase (UGT) 1A1*28. Here we developed and validated PGxSeq, a targeted exome panel for pharmacogenes pertinent to drug disposition and/or response.

METHODS

A panel of capture probes was generated to assess 422 kb of total coding region in 100 pharmacogenes. NGS was carried out in 235 subjects, and sequencing performance and accuracy of variant discovery validated in clinically relevant pharmacogenes. CYP2D6 CNV was determined using the bioinformatics tool CNV caller (VarSeq). Identified SNVs were assessed in terms of population allele frequency and predicted functional effects through in silico algorithms.

RESULTS

Adequate performance of the PGxSeq panel was demonstrated with a depth-of-coverage (DOC) ≥ 20× for at least 94% of the target sequence. We showed accurate detection of 39 clinically relevant gene variants compared to standard genotyping techniques (99.9% concordance), including CYP2D6 CNV and UGT1A1*28. Allele frequency of rare or novel variants and predicted function in 235 subjects mirrored findings from large genomic datasets. A large proportion of patients (78%, 183 out of 235) were identified as homozygous carriers of at least one variant necessitating altered pharmacotherapy.

CONCLUSIONS

PGxSeq can serve as a comprehensive, rapid, and reliable approach for the detection of common and novel SNVs in pharmacogenes benefiting the emerging field of precision medicine.

The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics

Inherited genetic variations in pharmacogenetic loci are widely acknowledged as important determinants of phenotypic differences in drug response, and may be actionable in the clinic. However, recent studies suggest that a considerable number of novel rare variants in pharmacogenes likely contribute to a still unexplained fraction of the observed interindividual variability. Next-generation sequencing (NGS) represents a rapid, relatively inexpensive, large-scale DNA sequencing technology with potential relevance as a comprehensive pharmacogenetic genotyping platform to identify genetic variation related to drug therapy. However, many obstacles remain before the clinical use of NGS-based test results, including technical challenges, functional interpretation, and strict requirements for diagnostic tests. Advanced computational analyses, high-throughput screening methodologies, and generation of shared resources with cell-based and clinical information will facilitate the integration of NGS data into candidate genotyping approaches, likely enhancing future drug phenotype predictions in patients.

CYP2D6 as a treatment decision aid for ER-positive non-metastatic breast cancer patients: a systematic review with accompanying clinical practice guidelines

PURPOSE

Tamoxifen is one of the principal treatments for estrogen receptor (ER)-positive breast cancer. Unfortunately, between 30 and 50% of patients receiving this hormonal therapy relapse. Since CYP2D6 genetic variants have been reported to play an important role in survival outcomes after treatment with tamoxifen, this study sought to summarize and critically appraise the available scientific evidence on this topic.

METHODS

A systematic literature review was conducted to identify studies investigating associations between CYP2D6 genetic variation and survival outcomes after tamoxifen treatment. Critical appraisal of the retrieved scientific evidence was performed, and recommendations were developed for CYP2D6 genetic testing in the context of tamoxifen therapy.

RESULTS

Although conflicting literature exists, the majority of the current evidence points toward CYP2D6 genetic variation affecting survival outcomes after tamoxifen treatment. Of note, review of the CYP2D6 genotyping assays used in each of the studies revealed the importance of comprehensive genotyping strategies to accurately predict CYP2D6 metabolizer phenotypes.

CONCLUSIONS AND RECOMMENDATIONS

Critical appraisal of the literature provided evidence for the value of comprehensive CYP2D6 genotyping panels in guiding treatment decisions for non-metastatic ER-positive breast cancer patients. Based on this information, it is recommended that alternatives to standard tamoxifen treatments may be considered in CYP2D6 poor or intermediate metabolizers.

New findings in pharmacogenetics of schizophrenia

PURPOSE OF REVIEW

This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects.

RECENT FINDINGS

Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications.

SUMMARY

The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.

Modification of the association between antipsychotic treatment response and childhood adversity by MMP9 gene variants in a first-episode schizophrenia cohort

Antipsychotics remain the most effective, and wide used option for ameliorating the symptoms of schizophrenia. However, inter-individual differences in treatment outcome are vast and suggest a role for genetic and environmental factors in affording favourable outcomes. A notable epigenetic relationship which has gained considerable traction in recent literature is the way in which the severity of childhood trauma can modify associations seen between genetic variation and antipsychotic treatment response. A potential mechanism of action which may facilitate this relationship is synaptic plasticity. This study investigated the role of variants in matrix metallopeptidase 9 (MMP9), a gene involved in synaptic plasticity, with treatment outcome considering the severity of childhood trauma as an interacting variable. The cohort comprised South African first episode schizophrenia patients treated with a single injectable antipsychotic, flupenthixol decanoate, monitored over 12 months. Relationships between novel and previously described variants, and haplotypes, with antipsychotic treatment response were found to be modified when considering childhood trauma as an interacting variable. This study provides the first evidence for the involvement of polymorphisms within MMP9 and the severity of childhood trauma in antipsychotic treatment response, and warrants further investigation into the role gene-environment interactions may play in the betterment of antipsychotic treatment strategies.

The global spectrum of protein-coding pharmacogenomic diversity

Differences in response to medications have a strong genetic component. By leveraging publically available data, the spectrum of such genomic variation can be investigated extensively. Pharmacogenomic variation was extracted from the 1000 Genomes Project Phase 3 data (2504 individuals, 26 global populations). A total of 12 084 genetic variants were found in 120 pharmacogenes, with the majority (90.0%) classified as rare variants (global minor allele frequency <0.5%), with 52.9% being singletons. Common variation clustered individuals into continental super-populations and 23 pharmacogenes contained highly differentiated variants (FST>0.5) for one or more super-population comparison. A median of three clinical variants (PharmGKB level 1A/B) was found per individual, and 55.4% of individuals carried loss-of-function variants, varying by super-population (East Asian 60.9%>African 60.1%>South Asian 60.3%>European 49.3%>Admixed 39.2%). Genome sequencing can therefore identify clinical pharmacogenomic variation, and future studies need to consider rare variation to understand the spectrum of genetic diversity contributing to drug response.

Genetic variation in human drug-related genes

Background

Variability in drug efficacy and adverse effects are observed in clinical practice. While the extent of genetic variability in classic pharmacokinetic genes is rather well understood, the role of genetic variation in drug targets is typically less studied.

Methods

Based on 60,706 human exomes from the ExAC dataset, we performed an in-depth computational analysis of the prevalence of functional variants in 806 drug-related genes, including 628 known drug targets. We further computed the likelihood of 1236 FDA-approved drugs to be affected by functional variants in their targets in the whole ExAC population as well as different geographic sub-populations.

Results

We find that most genetic variants in drug-related genes are very rare (f < 0.1%) and thus will likely not be observed in clinical trials. Furthermore, we show that patient risk varies for many drugs and with respect to geographic ancestry. A focused analysis of oncological drug targets indicates that the probability of a patient carrying germline variants in oncological drug targets is, at 44%, high enough to suggest that not only somatic alterations but also germline variants carried over into the tumor genome could affect the response to antineoplastic agents.

Conclusions

This study indicates that even though many variants are very rare and thus likely not observed in clinical trials, four in five patients are likely to carry a variant with possibly functional effects in a target for commonly prescribed drugs. Such variants could potentially alter drug efficacy.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0502-5) contains supplementary material, which is available to authorized users.

Flexible and Scalable Full-Length CYP2D6 Long Amplicon PacBio Sequencing

Cytochrome P450 2D6 (CYP2D6) is among the most important genes involved in drug metabolism. Specific variants are associated with changes in the enzyme's amount and activity. Multiple technologies exist to determine these variants, like the AmpliChip CYP450 test, Taqman qPCR, or Second‐Generation Sequencing, however, sequence homology between cytochrome P450 genes and pseudogene CYP2D7 impairs reliable CYP2D6 genotyping, and variant phasing cannot accurately be determined using these assays. To circumvent this, we sequenced CYP2D6 using the Pacific Biosciences RSII and obtained high‐quality, full‐length, phased CYP2D6 sequences, enabling accurate variant calling and haplotyping of the entire gene‐locus including exonic, intronic, and upstream and downstream regions. Unphased diplotypes (Roche AmpliChip CYP450 test) were confirmed for 24 of the 25 samples, including gene duplications. Cases with gene deletions required additional specific assays to resolve. In total, 61 unique variants were detected, including variants that had not previously been associated with specific haplotypes. To further aid genomic analysis using standard reference sequences, we have established an LOVD‐powered CYP2D6 gene‐variant database, and added all reference haplotypes and data reported here. We conclude that our CYP2D6 genotyping approach produces reliable CYP2D6 diplotypes and reveals information about additional variants, including phasing and copy‐number variation.

Genetic variation in the human cytochrome P450 supergene family

OBJECTIVES

Single nucleotide variations (SNVs) in the cytochrome P450 (CYP) gene family are a primary cause of interindividual differences in therapeutic effects and adverse reactions to drugs. However, we still lack important information on the extent of CYP polymorphisms at the population level. Here, we developed a comprehensive data set of SNVs in all 57 human CYP genes by integrating data from two extensive population sequencing projects and analyzed the distribution of SNVs in different subpopulations.

MATERIALS AND METHODS

CYP genetic variants derived from the NHLBI and 1000 Genomes project were classified by variant type, frequency, and ethnic origins. The genetic variability of CYP genes was normalized on the basis of nonlinear regression and the total number of genetic variations was estimated by the derived formulas.

RESULTS

In total, we detected 6165 SNVs, of which many were novel. The vast majority (83.2%) of all SNVs in coding regions were very rare (minor allele frequency <0.1%). On the basis of the regression analysis, the total number of genetic variations in human CYP genes was calculated to be 3.4 × 10 and 4.8 × 10 for a population size of one million in Europeans and Africans, respectively.

CONCLUSION

Our results suggest that the variant spectrum of human CYP genes is extensive and only a fraction of SNVs has been characterized to date. Moreover, the multitude of very rare novel sequence variants indicates that the commonly used SNV platforms are not satisfactory for determining the true genotype, which is critical information for personalized treatment with drugs influenced by CYP polymorphisms.

Cross-Comparison of Exome Analysis, Next-Generation Sequencing of Amplicons, and the iPLEX(®) ADME PGx Panel for Pharmacogenomic Profiling

Whole-exome sequencing (WES) has been widely used for analysis of human genetic diseases, but its value for the pharmacogenomic profiling of individuals is not well studied. Initially, we performed an in-depth evaluation of the accuracy of WES variant calling in the pharmacogenes CYP2D6 and CYP2C19 by comparison with MiSeq(®) amplicon sequencing data (n = 36). This analysis revealed that the concordance rate between WES and MiSeq(®) was high, achieving 99.60% for variants that were called without exceeding the truth-sensitivity threshold (99%), defined during variant quality score recalibration (VQSR). Beyond this threshold, the proportion of discordant calls increased markedly. Subsequently, we expanded our findings beyond CYP2D6 and CYP2C19 to include more genes genotyped by the iPLEX(®) ADME PGx Panel in the subset of twelve samples. WES performed well, agreeing with the genotyping panel in approximately 99% of the selected pass-filter variant calls. Overall, our results have demonstrated WES to be a promising approach for pharmacogenomic profiling, with an estimated error rate of lower than 1%. Quality filters, particularly VQSR, are important for reducing the number of false variants. Future studies may benefit from examining the role of WES in the clinical setting for guiding drug therapy.

Constellation: a tool for rapid, automated phenotype assignment of a highly polymorphic pharmacogene, CYP2D6, from whole-genome sequences

An important component of precision medicine-the use of whole-genome sequencing (WGS) to guide lifelong healthcare-is electronic decision support to inform drug choice and dosing. To achieve this, automated identification of genetic variation in genes involved in drug absorption, distribution, metabolism, excretion and response (ADMER) is required. CYP2D6 is a major enzyme for drug bioactivation and elimination. CYP2D6 activity is predominantly governed by genetic variation; however, it is technically arduous to haplotype. Not only is the nucleotide sequence of CYP2D6 highly polymorphic, but the locus also features diverse structural variations, including gene deletion, duplication, multiplication events and rearrangements with the nonfunctional, neighbouring CYP2D7 and CYP2D8 genes. We developed Constellation, a probabilistic scoring system, enabling automated ascertainment of CYP2D6 activity scores from 2×100 paired-end WGS. The consensus reference method included TaqMan genotyping assays, quantitative copy-number variation determination and Sanger sequencing. When compared with the consensus reference Constellation had an analytic sensitivity of 97% (59 of 61 diplotypes) and analytic specificity of 95% (116 of 122 haplotypes). All extreme phenotypes, i.e., poor and ultrarapid metabolisers were accurately identified by Constellation. Constellation is anticipated to be extensible to functional variation in all ADMER genes, and to be performed at marginal incremental financial and computational costs in the setting of diagnostic WGS.

Applicability of gene expression and systems biology to develop pharmacogenetic predictors; antipsychotic-induced extrapyramidal symptoms as an example

Pharmacogenetics has been driven by a candidate gene approach. The disadvantage of this approach is that is limited by our current understanding of the mechanisms by which drugs act. Gene expression could help to elucidate the molecular signatures of antipsychotic treatments searching for dysregulated molecular pathways and the relationships between gene products, especially protein-protein interactions. To embrace the complexity of drug response, machine learning methods could help to identify gene-gene interactions and develop pharmacogenetic predictors of drug response. The present review summarizes the applicability of the topics presented here (gene expression, network analysis and gene-gene interactions) in pharmacogenetics. In order to achieve this, we present an example of identifying genetic predictors of extrapyramidal symptoms induced by antipsychotic.

Genomic analysis in the clinic: benefits and challenges for health care professionals and patients in Brazil

Despite significant advances in the diagnosis and treatment of genetic diseases in the last two decades, there is still a significant proportion where a causative mutation cannot be identified and a definitive genetic diagnosis remains elusive. New genome-wide or high-throughput multiple gene tests have brought new hope to the field, since they can offer fast, cost-effective and comprehensive analysis of genetic variation. This is particularly interesting in disorders with high genetic heterogeneity. There are, however, limitations and concerns regarding the implementation of genomic analysis in everyday clinical practice, including some particular to emerging and developing economies, as Brazil. They include the limited number of actionable genetic variants known to date, difficulties in determining the clinical validity and utility of novel variants, growth of direct-to-consumer genetic testing using a genomic approach and lack of proper training of health care professionals to adequately request, interpret and use genetic information. Despite all these concerns and limitations, the availability of genomic tests has grown at an extremely rapid pace and commercially available services include initiatives in almost all areas of clinical genetics, including newborn and carrier screening. We discuss the benefits and limitations of genomic testing, as well as the ethical implications and the challenges for genetic education and enough available and qualified health care professionals, to ensure the adequate process of informed consent, meaningful interpretation and use of genomic data and definition of a clear regulatory framework in the particular context of Brazil.

Personalized pharmacogenomics profiling using whole-genome sequencing

AIM

Pharmacogenomics holds promise to rationalize drug use by minimizing drug toxicity and at the same time increase drug efficacy. There are currently several assays to screen for known pharmacogenomic biomarkers for the most commonly prescribed drugs. However, these genetic screening assays cannot account for other known or novel pharmacogenomic markers.

MATERIALS & METHODS

We analyzed whole-genome sequences of 482 unrelated individuals of various ethnic backgrounds to obtain their personalized pharmacogenomics profiles.

RESULTS

Bioinformatics analysis revealed 408,964 variants in 231 pharmacogenes, from which 26,807 were residing on exons and proximal regulatory sequences, whereas 16,487 were novel. In silico analyses indicated that 1012 novel pharmacogene-related variants possibly abolish protein function. We have also performed whole-genome sequencing analysis in a seven-member family of Greek origin in an effort to explain the variable response rate to acenocoumarol treatment in two family members.

CONCLUSION

Overall, our data demonstrate that whole-genome sequencing, unlike conventional genetic screening methods, is necessary to determine an individual's pharmacogenomics profile in a more comprehensive manner, which, combined with the gradually decreasing whole-genome sequencing costs, would expedite bringing personalized medicine closer to reality.

Unravelling the transcriptomic landscape of the major phase II UDP-glucuronosyltransferase drug metabolizing pathway using targeted RNA sequencing

A comprehensive view of the human UDP-glucuronosyltransferase (UGT) transcriptome is a prerequisite to the establishment of an individual's UGT metabolic glucuronidation signature. Here, we uncover the transcriptome landscape of the 10 human UGT gene loci in normal and tumoral metabolic tissues by targeted RNA next-generation sequencing. Alignment on the human hg19 reference genome identifies 234 novel exon-exon junctions. We recover all previously known UGT1 and UGT2 enzyme-coding transcripts and identify over 130 structurally and functionally diverse novel UGT variants. We further expose a revised genomic structure of UGT loci and provide a comprehensive repertoire of transcripts for each UGT gene. Data also uncover a remodelling of the UGT transcriptome occurring in a tissue- and tumor-specific manner. The complex alternative splicing program regulating UGT expression and protein functions is likely critical in determining detoxification capacity of an organ and stress-related responses, with significant impact on drug responses and diseases.

Whole genome sequencing in pharmacogenomics

Pharmacogenomics aims to shed light on the role of genes and genomic variants in clinical treatment response. Although, several drug-gene relationships are characterized to date, many challenges still remain toward the application of pharmacogenomics in the clinic; clinical guidelines for pharmacogenomic testing are still in their infancy, whereas the emerging high throughput genotyping technologies produce a tsunami of new findings. Herein, the potential of whole genome sequencing on pharmacogenomics research and clinical application are highlighted.

Considerations for rare variants in drug metabolism genes and the clinical implications

INTRODUCTION

Large-scale whole genome and exome resequencing studies have revealed that humans have a high level of deleterious rare variation, which has important implications for the design of future pharmacogenetics studies.

AREAS COVERED

Current pharmacogenetic guidelines focus on the implementation of common variation into dosing guidelines. However, it is becoming apparent that rare variation may also play an important role in differential drug response. Current sequencing technologies offer the opportunity to examine rare variation, but there are many challenges associated with such analyses. Nonetheless, if a comprehensive picture of the role that genetic variants play in treatment outcomes is to be obtained, it will be necessary to include the entire spectrum of variation, including rare variants, into pharmacogenetic research.

EXPERT OPINION

In order to implement pharmacogenetics in the clinic, patients should be genotyped for clinically actionable pharmacogenetic variants and patients responding unfavourably to treatment after pharmacogenetics-based dosing should be identified and resequenced to identify additional functionally relevant variants, including rare variants. All derived information should be added to a central database to allow for the updating of existing dosing guidelines. By routinely implementing such strategies, pharmacogenetics-based treatment guidelines will continue to improve.