Technologies for Pharmacogenomics: A Review

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.

Geny: A Genotyping Tool for Allelic Decomposition of Killer Cell Immunoglobulin-Like Receptor Genes

Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the currently available genotyping methods are unable to accurately infer copy numbers, genotypes and haplotypes of individual KIR genes from next-generation sequencing data. Here we introduce Geny, a new computational tool for precise genotyping of KIR genes. Geny utilizes available KIR haplotype databases and proposes a novel combination of expectation-maximization filtering schemes and integer linear programming-based combinatorial optimization models to resolve ambiguous reads, provide accurate copy number estimation and estimate the haplotype of each copy for the genes within the KIR region. We evaluated Geny on a large set of simulated short-read datasets covering the known validated KIR region assemblies and a set of Illumina short-read samples sequenced from 25 validated samples from the Human Pangenome Reference Consortium collection and showed that it outperforms the existing genotyping tools in terms of accuracy, precision and recall. We envision Geny becoming a valuable resource for understanding immune system response and consequently advancing the field of patient-centric medicine.

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Implementation of pharmacogenomics testing for precision medicine

Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.

Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology

Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.

A call for increased inclusivity and global representation in pharmacogenetic testing

Commercial pharmacogenetic testing panels capture a fraction of the genetic variation underlying medication metabolism and predisposition to adverse reactions. In this study we compared variation in six pharmacogenes detected by whole genome sequencing (WGS) to a targeted commercial panel in a cohort of 308 individuals with family history of pediatric heart disease. In 1% of the cohort, WGS identified rare variants that altered the interpretation of metabolizer status and would thus prevent potential errors in gene-based dosing.

Integrative analysis reveals that SLC38A1 promotes hepatocellular carcinoma development via PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism

Although hepatocellular carcinoma (HCC) is rather frequent, little is known about the molecular pathways underlying its development, progression, and prognosis. In the current study, we comprehensively analyzed the deferentially expressed metabolism-related genes (MRGs) in HCC based on TCGA datasets attempting to discover the potentially prognostic genes in HCC. The up-regulated MRGs were further subjected to analyze their prognostic values and protein expressions. Twenty-seven genes were identified because their high expressions were significant in OS, PFS, DFS, DSS, and HCC tumor samples. They were then used for GO, KEGG, methylation, genetics changes, immune infiltration analyses. Moreover, we established a prognostic model in HCC using univariate assays and LASSO regression based on these MRGs. Additionally, we also found that SLC38A1, an amino acid metabolism closely related transporter, was a potential prognostic gene in HCC, and its function in HCC was further studied using experiments. We found that the knockdown of SLC38A1 notably suppressed the growth and migration of HCC cells. Further studies revealed that SLC38A1 modulated the development of HCC cells by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism. In conclusion, this study identified the potentially prognostic MRGs in HCC and uncovered that SLC38A1 regulated HCC development and progression by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism, which might provide a novel marker and potential therapeutic target in HCC.

Pharmacogenomic variation in the Malagasy population: implications for the antimalarial drug primaquine metabolism

Aim: Antimalarial primaquine (PQ) eliminates liver hypnozoites of Plasmodium vivax. CYP2D6 gene variation contributes to PQ therapeutic failure. Additional gene variation may contribute to PQ efficacy. Information on pharmacogenomic variation in Madagascar, with vivax malaria and a unique population admixture, is scanty. Methods: The authors performed genome-wide genotyping of 55 Malagasy samples and analyzed data with a focus on a set of 28 pharmacogenes most relevant to PQ. Results: Mainly, the study identified 110 coding or splicing variants, including those that, based on previous studies in other populations, may be implicated in PQ response and copy number variation, specifically in chromosomal regions that contain pharmacogenes. Conclusion: With this pilot information, larger genome-wide association analyses with PQ metabolism and response are substantially more feasible.

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.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing

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

Pharmacogenomic profile of actionable molecular variants related to drugs commonly used in anesthesia: WES analysis reveals new mutations

Background: Genetic interindividual variability is associated with adverse drug reactions (ADRs) and affects the response to common drugs used in anesthesia. Despite their importance, these variants remain largely underexplored in Latin-American countries. This study describes rare and common variants found in genes related to metabolism of analgesic and anaesthetic drug in the Colombian population. Methods: We conducted a study that included 625 Colombian healthy individuals. We generated a subset of 14 genes implicated in metabolic pathways of common medications used in anesthesia and assessed them by whole-exome sequencing (WES). Variants were filtered using two pipelines: A) novel or rare (minor allele frequency-MAF <1%) variants including missense, loss-of-function (LoF, e.g., frameshift, nonsense), and splice site variants with potential deleterious effect and B) clinically validated variants described in the PharmGKB (categories 1, 2 and 3) and/or ClinVar databases. For rare and novel missense variants, we applied an optimized prediction framework (OPF) to assess the functional impact of pharmacogenetic variants. Allelic, genotypic frequencies and Hardy-Weinberg equilibrium were calculated. We compare our allelic frequencies with these from populations described in the gnomAD database. Results: Our study identified 148 molecular variants potentially related to variability in the therapeutic response to 14 drugs commonly used in anesthesiology. 83.1% of them correspond to rare and novel missense variants classified as pathogenic according to the pharmacogenetic optimized prediction framework, 5.4% were loss-of-function (LoF), 2.7% led to potential splicing alterations and 8.8% were assigned as actionable or informative pharmacogenetic variants. Novel variants were confirmed by Sanger sequencing. Allelic frequency comparison showed that the Colombian population has a unique pharmacogenomic profile for anesthesia drugs with some allele frequencies different from other populations. Conclusion: Our results demonstrated high allelic heterogeneity among the analyzed sampled, enriched by rare (91.2%) variants in pharmacogenes related to common drugs used in anesthesia. The clinical implications of these results highlight the importance of implementation of next-generation sequencing data into pharmacogenomic approaches and personalized medicine.

From gene to dose: Long-read sequencing and *-allele tools to refine phenotype predictions of CYP2C19

Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual's drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.

The Influence of Structural Variants of the CES1 Gene on the Pharmacokinetics of Enalapril, Presumably Due to Linkage Disequilibrium with the Intronic rs2244613

Variants in the CES1 gene encoding carboxylesterase 1 may affect the metabolism of enalapril to the active metabolite enalaprilat. It was shown that the A allele of rs71647871 and the C allele of rs2244613 led to a decrease in plasma enalaprilat concentrations. This study aimed to estimate the effect of structural haplotypes of CES1 containing the pseudogene CES1P1, or a hybrid of the gene and the pseudogene CES1A2, on the pharmacokinetics of enalapril. We included 286 Caucasian patients with arterial hypertension treated with enalapril. Genotyping was performed using real-time PCR and long-range PCR. Peak and trough plasma enalaprilat concentrations were lower in carriers of CES1A2. The studied haplotypes were in linkage disequilibrium with rs2244613: generally, the A allele was in the haplotype containing the CES1P1, and the C allele was in the haplotype with the CES1A2. Thus, carriers of CES1A2 have reduced CES1 activity against enalapril. Linkage disequilibrium of the haplotype containing the CES1P1 or CES1A2 with rs2244613 should be taken into account when genotyping the CES1 gene.

Implementation of pharmacogenomics: Where are we now?

Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre-emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches.

An Investigation of O-Demethyl Tramadol/Tramadol Ratio for Cytochrome P450 2D6 Phenotyping: The CYTRAM Study

Cytochrome P450 2D6 (CYP2D6) gene polymorphisms influence the exposure to tramadol (T) and its pharmacologically active metabolite, O-demethyl tramadol (O-dT). Tramadol has been considered as a candidate probe drug for CYP2D6 phenotyping. The objective of the CYTRAM study was to investigate the value of plasma O-dT/T ratio for CYP2D6 phenotyping. European adult patients who received IV tramadol after surgery were included. CYP2D6 genotyping was performed and subjects were classified as extensive (EM), intermediate (IM), poor (PM), or ultra-rapid (UM) CYP2D6 metabolizers. Plasma concentrations of tramadol and O-dT were determined at 24 h and 48 h. The relationship between O-dT/T ratio and CYP2D6 phenotype was examined in both a learning and a validation group. Genotype data were obtained in 301 patients, including 23 PM (8%), 117 IM (39%), 154 EM (51%), and 7 UM (2%). Tramadol trough concentrations at 24 h were available in 297 patients. Mean value of O-dT/T ratio was significantly lower in PM than in non-PM individuals (0.061 ± 0.031 versus 0.178 ± 0.09, p < 0.01). However, large overlap was observed in the distributions of O-dT/T ratio between groups. Statistical models based on O-dT/T ratio failed to identify CYP2D6 phenotype with acceptable sensitivity and specificity. Those results suggest that tramadol is not an adequate probe drug for CYP2D6 phenotyping.

Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing

In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches

Head and neck cancers (HNCs) represent the sixth most widespread malignancy worldwide. Surgery, radiotherapy, chemotherapeutic and immunotherapeutic drugs represent the main clinical approaches for HNC patients. Moreover, HNCs are characterised by an elevated mutational load; however, specific genetic mutations or biomarkers have not yet been found. In this scenario, personalised medicine is showing its efficacy. To study the reliability and the effects of personalised treatments, preclinical research can take advantage of next-generation sequencing and innovative technologies that have been developed to obtain genomic and multi-omic profiles to drive personalised treatments. The crosstalk between malignant and healthy components, as well as interactions with extracellular matrices, are important features which are responsible for treatment failure. Preclinical research has constantly implemented in vitro and in vivo models to mimic the natural tumour microenvironment. Among them, 3D systems have been developed to reproduce the tumour mass architecture, such as biomimetic scaffolds and organoids. In addition, in vivo models have been changed over the last decades to overcome problems such as animal management complexity and time-consuming experiments. In this review, we will explore the new approaches aimed to improve preclinical tools to study and apply precision medicine as a therapeutic option for patients affected by HNCs.

Keeping pace with CYP2D6 haplotype discovery: innovative methods to assign function

The discovery of haplotypes with unknown or uncertain function in the CYP2D6 pharmacogene is outpacing the capabilities of traditional in vitro and in vivo approaches to characterize their function. This challenge will undoubtedly grow as pharmacogenomic research becomes more inclusive of globally diverse populations. As accurate phenotypic assignment is paramount to the utility of pharmacogenomics, high-throughput technologies are needed for this complex pharmacogene. We describe the evolving landscape of innovative approaches to assign function to CYP2D6 haplotypes and possibilities for adopting these technologies into cohesive processes. Promising approaches include ADME-optimized prediction frameworks, machine learning algorithms, deep mutational scanning and phenoconversion predictions. Implementing these approaches will lead to improved personalization of treatment for patients.

Pharmacogenetics research in Brazil: a systematic review

Aim: Pharmacogenomics (PGx) is a rising scientific area in many countries, such as Brazil. Objectives: To identify biomarkers, therapeutic areas, probe drugs and regions/ethnicities most studied in the country in order to guide future studies. Materials & methods: Systematic review of 1060 studies (from 1968 to 2020) comprising 80 genes, six probe drugs and 3,819,233 individuals. Results: MTHFR and HLA-A/B were the most studied genes and metoprolol and dextromethorphan the most studied probe drugs. Oncology was the most studied therapeutic area considering PGx biomarkers. The country’s regions and ethnic groups were studied unevenly, with south/southeast and White people over-represented in respect to their demographic relevance, in detriment of the center-west/northeast/north and Black/mixed individuals. Conclusion: Many of the gaps and possible paths to be covered to reach even PGx data are pointed out by this review.

Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data

Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.

Substrate specificity of CYP2D6 genetic variants

Genetic variation in the gene encoding CYP2D6 is used to guide drug prescribing in clinical practice. However, genetic variants in CYP2D6 show substrate-specific effects that are currently not accounted for. With a systematic literature, we retrieved 22 original studies describing in vitro experiments focusing on CYP2D6 alleles (CYP2D6*1, *2, *10 and *17) and substrates. Allele activity (clearance of the allele of interest divided by the clearance of the wildtype) was extracted. The results support the hypothesis of the existence of substrate specificity of the CYP2D6*17-allele (higher debrisoquine clearance), a subtle effect of the CYP2D6*10-allele (lower dextromethorphan clearance) but no substrate-specific effect of the CYP2D6*2-allele. Although our results support substrate specificity, for most substrates data are too sparse and require further studies.

Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice

Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.

Cytogenetic and Biochemical Genetic Techniques for Personalized Drug Therapy in Europe

For many authorized drugs, accumulating scientific evidence supports testing for predictive biomarkers to apply personalized therapy and support preventive measures regarding adverse drug reactions and treatment failure. Here, we review cytogenetic and biochemical genetic testing methods that are available to guide therapy with drugs centrally approved in the European Union (EU). We identified several methods and combinations of techniques registered in the Genetic Testing Registry (GTR), which can be used to guide therapy with drugs for which pharmacogenomic-related information is provided in the European public assessment reports. Although this registry provides information on genetic tests offered worldwide, we identified limitations regarding standard techniques applied in clinical practice and the information on test validity rarely provided in the according sections.