Precision Medicine and Rare Genetic Variants

Non-additivity of the functional properties of individual P450 species and its manifestation in the effects of alcohol consumption on the metabolism of ketamine and amitriptyline

To explore functional interconnections between multiple P450 enzymes and their manifestation in alcohol-induced changes in drug metabolism, we implemented a high-throughput study of correlations between the composition of the P450 pool and the substrate saturation profiles (SSP) of amitriptyline and ketamine demethylation in a series of 23 individual human liver microsomes preparations from donors with a known history of alcohol consumption. The SSPs were approximated with linear combinations of three Michaelis-Menten equations with globally optimized KM (substrate affinity) values. This analysis revealed a strong correlation between the rate of ketamine metabolism and alcohol exposure. For both substrates, alcohol consumption caused a significant increase in the role of the low-affinity enzymes. The amplitudes of the kinetic components and the total rate were further analyzed for correlations with the abundance of 11 major P450 enzymes assessed by global proteomics. The maximal rate of metabolism of both substrates correlated with the abundance of CYP3A4, their predicted principal metabolizer. However, except for CYP2D6 and CYP2E1, responsible for the low-affinity metabolism of ketamine and amitriptyline, respectively, none of the other potent metabolizers of the drugs revealed a positive correlation. Instead, in the case of ketamine, we observed negative correlations with the abundances of CYP1A2, CYP2C9, and CYP3A5. For amitriptyline, the data suggest inhibitory effects of CYP1A2 and CYP2A6. Our results demonstrate the importance of functional interactions between multiple P450 species and their decisive role in the effects of alcohol exposure on drug metabolism.

Functional Characterization of Six SLCO1B1 (OATP1B1) Variants Observed in Finnish Individuals with a Psychotic Disorder

Variants in the SLCO1B1 (solute carrier organic anion transporter family member 1B1) gene encoding the OATP1B1 (organic anion transporting polypeptide 1B1) protein are associated with altered transporter function that can predispose patients to adverse drug effects with statin treatment. We explored the effect of six rare SLCO1B1 single nucleotide variants (SNVs) occurring in Finnish individuals with a psychotic disorder on expression and functionality of the OATP1B1 protein. The SUPER-Finland study has performed exome sequencing on 9381 individuals with at least one psychotic episode during their lifetime. SLCO1B1 SNVs were annotated with PHRED-scaled combined annotation-dependent (CADD) scores and the Ensembl variant effect predictor. In vitro functionality studies were conducted for the SNVs with a PHRED-scaled CADD score of >10 and predicted to be missense. To estimate possible changes in transport activity caused by the variants, transport of 2',7'-dichlorofluorescein (DCF) in OATP1B1-expressing HEK293 cells was measured. According to the findings, additional tests with rosuvastatin and estrone sulfate were conducted. The amount of OATP1B1 in crude membrane fractions was quantified using a liquid chromatography tandem mass spectrometry-based quantitative targeted absolute proteomics analysis. Six rare missense variants of SLCO1B1 were identified in the study population, located in transmembrane helix 3: c.317T>C (p.106I>T), intracellular loop 2: c.629G>T (p.210G>V), c.633A>G (p.211I>M), c.639T>A (p.213N>L), transmembrane helix 6: 820A>G (p.274I>V), and the C-terminal end: 2005A>C (p.669N>H). Of these variants, SLCO1B1 c.629G>T (p.210G>V) resulted in the loss of in vitro function, abolishing the uptake of DCF, estrone sulfate, and rosuvastatin and reducing the membrane protein expression to 31% of reference OATP1B1. Of the six rare missense variants, SLCO1B1 c.629G>T (p.210G>V) causes a loss of function of OATP1B1 transport in vitro and severely decreases membrane protein abundance. Carriers of SLCO1B1 c.629G>T might be susceptible to altered pharmacokinetics of OATP1B1 substrate drugs and might have increased likelihood of adverse drug effects such as statin-associated musculoskeletal symptoms.

CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis: A GeT-RM Collaborative Project

Pharmacogenetic tests typically target selected sequence variants to identify haplotypes that are often defined by star (∗) allele nomenclature. Due to their design, these targeted genotyping assays are unable to detect novel variants that may change the function of the gene product and thereby affect phenotype prediction and patient care. In the current study, 137 DNA samples that were previously characterized by the Genetic Testing Reference Material (GeT-RM) program using a variety of targeted genotyping methods were recharacterized using targeted and whole genome sequencing analysis. Sequence data were analyzed using three genotype calling tools to identify star allele diplotypes for CYP2C8, CYP2C9, and CYP2C19. The genotype calls from next-generation sequencing (NGS) correlated well to those previously reported, except when novel alleles were present in a sample. Six novel alleles and 38 novel suballeles were identified in the three genes due to identification of variants not covered by targeted genotyping assays. In addition, several ambiguous genotype calls from a previous study were resolved using the NGS and/or long-read NGS data. Diplotype calls were mostly consistent between the calling algorithms, although several discrepancies were noted. This study highlights the utility of NGS for pharmacogenetic testing and demonstrates that there are many novel alleles that are yet to be discovered, even in highly characterized genes such as CYP2C9 and CYP2C19.

Identification and functional validation of novel pharmacogenomic variants using a next-generation sequencing-based approach for clinical pharmacogenomics

Inter-individual variability in pharmacokinetics and drug response is heavily influenced by single-nucleotide variants (SNVs) and copy-number variations (CNVs) in genes with importance for drug disposition. Nowadays, a plethora of studies implement next generation sequencing to capture rare and novel pharmacogenomic (PGx) variants that influence drug response. To address these issues, we present a comprehensive end-to-end analysis workflow, beginning from targeted PGx panel re-sequencing to in silico analysis pipelines and in vitro validation assays. Specifically, we show that novel pharmacogenetic missense variants that are predicted or putatively predicted to be functionally deleterious, significantly alter protein activity levels of CYP2D6 and CYP2C19 proteins. We further demonstrate that variant priorization pipelines tailored with functional in vitro validation assays provide supporting evidence for the deleterious effect of novel PGx variants. The proposed workflow could provide the basis for integrating next-generation sequencing for PGx testing into routine clinical practice.

Assembling the P450 puzzle: on the sources of nonadditivity in drug metabolism

There is an increasing number of indications of an oversimplification in the premise that the cumulative properties of the human drug-metabolizing ensemble represent a simple aggregate of the properties of the constituting enzymes. Recent studies of the functional effects of hetero-association of multiple cytochrome P450 species and their interactions with metabolically related enzymes revealed a tight integration in the drug-metabolizing ensemble. In our opinion, the sources of interindividual variability in drug metabolism can be elucidated only when considering this ensemble as a multienzyme system, the functional parameters of which are determined by interactions between its constituents. In this article, we present a conceptual model providing a mechanistic explanation for the functional effects of the interactions between multiple P450 species and propose a clue to understanding the nonadditive behavior of the drug-metabolizing ensemble.

Probing functional interactions between cytochromes P450 with principal component analysis of substrate saturation profiles and targeted proteomics

We investigated the correspondence between drug metabolism routes and the composition of the P450 ensemble in human liver microsomes (HLM). As a probe, we used Coumarin 152 (C152), a fluorogenic substrate metabolized by multiple P450 species. Studying the substrate-saturation profiles (SSP) in seven pooled HLM preparations, we sought to correlate them with the P450 pool's composition characterized by targeted proteomics. This analysis, complemented with the assays with specific inhibitors of CYP3A4 and CYP2C19, the primary C152 metabolizers, demonstrated a significant contrast between different HLM samples. To unveil the source of these differences, we implemented Principal Component Analysis (PCA) of the SSP series obtained with HLM samples with a known composition of the P450 pool. Our analysis revealed that the parameters of C152 metabolism are primarily determined by the content of CYP2A6, CYP2B6, CYP2C8, CYP2E1, and CYP3A5 of those only CYP2B6 and CYP3A5 can metabolize C152. To validate this finding, we studied the effect of enriching HLM with CYP2A6, CYP2E1, and CYP3A5. The incorporation of CYP3A5 into HLM decreases the rate of C152 metabolism while increasing the role of CYP2B6 in its turnover. In contrast, incorporation of CYP2A6 and CYP2E1 reroutes the C152 demethylation towards some P450 enzyme with a moderate affinity to the substrate, most likely CYP3A4. Our results reveal a sharp non-additivity of the individual P450 properties and suggest a pivotal role of P450-P450 interactions in determining drug metabolism routes. This study demonstrates the high potential of our new PCA-based approach in unveiling functional interrelationships between different P450 species.

Understanding thiopurine methyltransferase polymorphisms for the targeted treatment of hematologic malignancies

INTRODUCTION

Thiopurine methyltransferase (TPMT) catalyzes the S-methylation of thiopurines (mercaptopurine (MP) and tioguanine (TG)), chemotherapeutic agents used in the treatment of acute lymphoblastic leukemia (ALL). Polymorphisms in TPMT gene encode diminished activity enzyme, enhancing accumulation of active metabolites, and partially explaining the inter-individual differences in patients' clinical response.

AREAS COVERED

This review gives an overview on TPMT gene and function, and discusses the pharmacogenomic implications of TPMT variants in the prevention of severe thiopurine-induced hematological toxicities and the less known implication on TG-induced sinusoidal obstruction syndrome. Additional genetic and non-genetic factors impairing TPMT activity are considered. Literature search was done in PubMed for English articles published since1990, and on PharmGKB.

EXPERT OPINION

To titrate thiopurines safely and effectively, achieve the right degree of lymphotoxic effect and avoid excessive myelosuppression, the optimal management will combine a preemptive TPMT genotyping to establish a safe initial dose with a close phenotypic monitoring of TPMT activity and/or of active metabolites during long-term treatment. Compared to current ALL protocols, replacement of TG by MP during reinduction phase in TPMT heterozygotes and novel individualized TG regimens in maintenance for TPMT wild-type subjects could be investigated to improve outcomes while avoiding risk of severe hepatotoxicity.

Pharmacogene Sequencing of a Gabonese Population with Severe Plasmodium falciparum Malaria Reveals Multiple Novel Variants with Putative Relevance for Antimalarial Treatment

Malaria remains one of the deadliest diseases in Africa, particularly for children. While successful in reducing morbidity and mortality, antimalarial treatments are also a major cause of adverse drug reactions (ADRs). Host genetic variation in genes involved in drug disposition or toxicity constitutes an important determinant of ADR risk and can prime for parasite drug resistance. Importantly, however, the genetic diversity in Africa is substantial, and thus, genetic profiles in one population cannot be reliably extrapolated to other ethnogeographic groups. Gabon is considered a high-transmission country, with more than 460,000 malaria cases per year. Yet the pharmacogenetic landscape of the Gabonese population or its neighboring countries has not been analyzed. Using targeted sequencing, here, we profiled 21 pharmacogenes with importance for antimalarial treatment in 48 Gabonese pediatric patients with severe Plasmodium falciparum malaria. Overall, we identified 347 genetic variants, of which 18 were novel, and each individual was found to carry 87.3 ± 9.2 (standard deviation [SD]) variants across all analyzed genes. Importantly, 16.7% of these variants were population specific, highlighting the need for high-resolution pharmacogenomic profiling. Between one in three and one in six individuals harbored reduced-activity alleles of CYP2A6, CYP2B6, CYP2D6, and CYP2C8 with important implications for artemisinin, chloroquine, and amodiaquine therapy. Furthermore, one in three patients harbored at least one G6PD-deficient allele, suggesting a considerably increased risk of hemolytic anemia upon exposure to aminoquinolines. Combined, our results reveal the unique genetic landscape of the Gabonese population and pinpoint the genetic basis for interindividual differences in antimalarial drug responses and toxicity.

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability

Interindividual differences in drug response are a common concern in both drug development and across layers of care. While genetics clearly influences drug response and toxicity of many drugs, a substantial fraction of the heritable pharmacological and toxicological variability remains unexplained by known genetic polymorphisms. In recent years, population-scale sequencing projects have unveiled tens of thousands of coding and noncoding pharmacogenetic variants with unclear functional effects that might explain at least part of this missing heritability. However, translating these personalized variant signatures into drug response predictions and actionable advice remains challenging and constitutes one of the most important frontiers of contemporary pharmacogenomics. Conventional prediction methods are primarily based on evolutionary conservation, which drastically reduces their predictive accuracy when applied to poorly conserved pharmacogenes. Here, we review the current state-of-the-art of computational variant effect predictors across variant classes and critically discuss their utility for pharmacogenomics. Besides missense variants, we discuss recent progress in the evaluation of synonymous, splice, and noncoding variations. Furthermore, we discuss emerging possibilities to assess haplotypes and structural variations. We advocate for the development of algorithms trained on pharmacogenomic instead of pathogenic data sets to improve the predictive accuracy in order to facilitate the utilization of next-generation sequencing data for personalized clinical decision support and precision pharmacogenomics.

Pharmacogenomics in the era of next generation sequencing - from byte to bedside

Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.

Impact of variants in ATP-binding cassette transporters on breast cancer treatment

There has been substantial interest in the impact of ATP-binding cassette (ABC) transporter variability on breast cancer drug resistance. Here, we provide a systematic review of ABC variants in breast cancer therapy. Notably, most studies used small heterogeneous cohorts and their identified associations lack statistical stringency, replication and mechanistic support. We conclude that commonly studied ABC polymorphisms are not suitable to accurately predict therapy response or toxicity in breast cancer patients and cannot guide treatment decisions. However, recent research shows that ABC transporters harbor a plethora of rare variants with individually small effect sizes, and we argue that a shift in strategy from target variant interrogation to comprehensive profiling might hold promise to drastically improve the predictive power of outcome models.

Evaluation of Phenotypic and Genotypic Variations of Drug Metabolising Enzymes and Transporters in Chronic Pain Patients Facing Adverse Drug Reactions or Non-Response to Analgesics: A Retrospective Study

This retrospective study evaluates the link between an adverse drug reaction (ADR) or a non-response to treatment and cytochromes P450 (CYP), P-glycoprotein (P-gp) or catechol-O-methyltransferase (COMT) activity in patients taking analgesic drugs for chronic pain. Patients referred to a pain center for an ADR or a non-response to an analgesic drug between January 2005 and November 2014 were included. The genotype and/or phenotype was obtained for assessment of the CYPs, P-gp or COMT activities. The relation between the event and the result of the genotype and/or phenotype was evaluated using a semi-quantitative scale. Our analysis included 243 individual genotypic and/or phenotypic explorations. Genotypes/phenotypes were mainly assessed because of an ADR (n = 145, 59.7%), and the majority of clinical situations were observed with prodrug opioids (n = 148, 60.9%). The probability of a link between an ADR or a non-response and the genotypic/phenotypic status of the patient was evaluated as intermediate to high in 40% and 28.2% of all cases, respectively. The drugs in which the probability of an association was the strongest were the prodrug opioids, with an intermediate to high link in 45.6% of the cases for occurrence of ADRs and 36.0% of the cases for non-response. This study shows that the genotypic and phenotypic approach is useful to understand ADRs or therapeutic resistance to a usual therapeutic dosage, and can be part of the evaluation of chronic pain patients.

Population-scale predictions of DPD and TPMT phenotypes using a quantitative pharmacogene-specific ensemble classifier

BACKGROUND

Inter-individual differences in dihydropyrimidine dehydrogenase (DPYD encoding DPD) and thiopurine S-methyltransferase (TPMT) activity are important predictors for fluoropyrimidine and thiopurine toxicity. While several variants in these genes are known to decrease enzyme activities, many additional genetic variations with unclear functional consequences have been identified, complicating informed clinical decision-making in the respective carriers.

METHODS

We used a novel pharmacogenetically trained ensemble classifier to analyse DPYD and TPMT genetic variability based on sequencing data from 138,842 individuals across eight populations.

RESULTS

The algorithm accurately predicted in vivo consequences of DPYD and TPMT variants (accuracy 91.4% compared to 95.3% in vitro). Further analysis showed high genetic complexity of DPD deficiency, advocating for sequencing-based DPYD profiling, whereas genotyping of four variants in TPMT was sufficient to explain >95% of phenotypic TPMT variability. Lastly, we provided population-scale profiles of ethnogeographic variability in DPD and TPMT phenotypes, and revealed striking interethnic differences in frequency and genetic constitution of DPD and TPMT deficiency.

CONCLUSION

These results provide the most comprehensive data set of DPYD and TPMT variability published to date with important implications for population-adjusted genetic profiling strategies of fluoropyrimidine and thiopurine risk factors and precision public health.

Ethnogeographic and inter-individual variability of human ABC transporters

ATP-binding cassette (ABC) transporters constitute a superfamily of 48 structurally similar membrane transporters that mediate the ATP-dependent cellular export of a plethora of endogenous and xenobiotic substances. Importantly, genetic variants in ABC genes that affect gene function have clinically important effects on drug disposition and can be predictors of the risk of adverse drug reactions and efficacy of chemotherapeutics, calcium channel blockers, and protease inhibitors. Furthermore, loss-of-function of ABC transporters is associated with a variety of congenital disorders. Despite their clinical importance, information about the frequencies and global distribution of functionally relevant ABC variants is limited and little is known about the overall genetic complexity of this important gene family. Here, we systematically mapped the genetic landscape of the entire human ABC superfamily using Next-Generation Sequencing data from 138,632 individuals across seven major populations. Overall, we identified 62,793 exonic variants, 98.5% of which were rare. By integrating five computational prediction algorithms with structural mapping approaches using experimentally determined crystal structures, we found that the functional ABC variability is extensive and highly population-specific. Every individual harbored between 9.3 and 13.9 deleterious ABC variants, 76% of which were found only in a single population. Carrier rates of pathogenic variants in ABC transporter genes associated with autosomal recessive congenital diseases, such as cystic fibrosis or pseudoxanthoma elasticum, closely mirrored the corresponding population-specific disease prevalence, thus providing a novel resource for rare disease epidemiology. Combined, we provide the most comprehensive, systematic, and consolidated overview of ethnogeographic ABC transporter variability with important implications for personalized medicine, clinical genetics, and precision public health.

Pharmacogenomic network analysis of the gene-drug interaction landscape underlying drug disposition

In recent decades the identification of pharmacogenomic gene-drug associations has evolved tremendously. Despite this progress, a major fraction of the heritable inter-individual variability remains elusive. Higher-dimensional phenomena, such as gene-gene-drug interactions, in which variability in multiple genes synergizes to precipitate an observable phenotype have been suggested to account at least for part of this missing heritability. However, the identification of such intricate relationships remains difficult partly because of analytical challenges associated with the complexity explosion of the problem. To facilitate the identification of such combinatorial pharmacogenetic associations, we here propose a network analysis strategy. Specifically, we analyzed the landscape of drug metabolizing enzymes and transporters for 100 top selling drugs as well as all compounds with pharmacogenetic germline labels or dosing guidelines. Based on this data, we calculated the posterior probabilities that gene i is involved in metabolism, transport or toxicity of a given drug under the condition that another gene j is involved for all pharmacogene pairs (i, j). Interestingly, these analyses revealed significant patterns between individual genes and across pharmacogene families that provide insights into metabolic interactions. To visualize the gene-drug interaction landscape, we use multidimensional scaling to collapse this similarity matrix into a two-dimensional network. We suggest that Euclidian distance between nodes can inform about the likelihood of epistatic interactions and thus might provide a useful tool to reduce the search space and facilitate the identification of combinatorial pharmacogenomic associations.

The genetic landscape of the human solute carrier (SLC) transporter superfamily

The human solute carrier (SLC) superfamily of transporters is comprised of over 400 membrane-bound proteins, and plays essential roles in a multitude of physiological and pharmacological processes. In addition, perturbation of SLC transporter function underlies numerous human diseases, which renders SLC transporters attractive drug targets. Common genetic polymorphisms in SLC genes have been associated with inter-individual differences in drug efficacy and toxicity. However, despite their tremendous clinical relevance, epidemiological data of these variants are mostly derived from heterogeneous cohorts of small sample size and the genetic SLC landscape beyond these common variants has not been comprehensively assessed. In this study, we analyzed Next-Generation Sequencing data from 141,456 individuals from seven major human populations to evaluate genetic variability, its functional consequences, and ethnogeographic patterns across the entire SLC superfamily of transporters. Importantly, of the 204,287 exonic single-nucleotide variants (SNVs) which we identified, 99.8% were present in less than 1% of analyzed alleles. Comprehensive computational analyses using 13 partially orthogonal algorithms that predict the functional impact of genetic variations based on sequence information, evolutionary conservation, structural considerations, and functional genomics data revealed that each individual genome harbors 29.7 variants with putative functional effects, of which rare variants account for 18%. Inter-ethnic variability was found to be extensive, and 83% of deleterious SLC variants were only identified in a single population. Interestingly, population-specific carrier frequencies of loss-of-function variants in SLC genes associated with recessive Mendelian disease recapitulated the ethnogeographic variation of the corresponding disorders, including cystinuria in Jewish individuals, type II citrullinemia in East Asians, and lysinuric protein intolerance in Finns, thus providing a powerful resource for clinical geneticists to inform about population-specific prevalence and allelic composition of Mendelian SLC diseases. In summary, we present the most comprehensive data set of SLC variability published to date, which can provide insights into inter-individual differences in SLC transporter function and guide the optimization of population-specific genotyping strategies in the bourgeoning fields of personalized medicine and precision public health.

Targeted ultra-deep sequencing of a South African Bantu-speaking cohort to comprehensively map and characterize common and novel variants in 65 pharmacologically-related genes

BACKGROUND

African populations are characterised by high genetic diversity, which provides opportunities for discovering and elucidating novel variants of clinical importance, especially those affecting therapeutic outcome. Significantly more knowledge is however needed before such populations can take full advantage of the advances in precision medicine. Coupled with the need to concisely map and better understand the pharmacological implications of genetic diversity in populations of sub-Sharan African ancestry, the aim of this study was to identify and characterize known and novel variants present within 65 important absorption, distribution, metabolism and excretion genes.

PATIENTS AND METHODS

Targeted ultra-deep next-generation sequencing was used to screen a cohort of 40 South African individuals of Bantu ancestry.

RESULTS

We identified a total of 1662 variants of which 129 are novel. Moreover, out of the 1662 variants 22 represent potential loss-of-function variants. A high level of allele frequency differentiation was observed for variants identified in this study when compared with other populations. Notably, on the basis of prior studies, many appear to be pharmacologically important in the pharmacokinetics of a broad range of drugs, including antiretrovirals, chemotherapeutic drugs, antiepileptics, antidepressants, and anticoagulants. An in-depth analysis was undertaken to interrogate the pharmacogenetic implications of this genetic diversity.

CONCLUSION

Despite the new insights gained from this study, the work illustrates that a more comprehensive understanding of population-specific differences is needed to facilitate the development of pharmacogenetic-based interventions for optimal drug therapy in patients of African ancestry.

Frequencies of clinically important CYP2C19 and CYP2D6 alleles are graded across Europe

CYP2C19 and CYP2D6 are important drug-metabolizing enzymes that are involved in the metabolism of around 30% of all medications. Importantly, the corresponding genes are highly polymorphic and these genetic differences contribute to interindividual and interethnic differences in drug pharmacokinetics, response, and toxicity. In this study we systematically analyzed the frequency distribution of clinically relevant CYP2C19 and CYP2D6 alleles across Europe based on data from 82,791 healthy individuals extracted from 79 original publications and, for the first time, provide allele confidence intervals for the general population. We found that frequencies of CYP2D6 gene duplications showed a clear South-East to North-West gradient ranging from <1% in Sweden and Denmark to 6% in Greece and Turkey. In contrast, an inverse distribution was observed for the loss-of-function alleles CYP2D6*4 and CYP2D6*5. Similarly, frequencies of the inactive CYP2C19*2 allele were graded from North-West to South-East Europe. In important contrast to previous work we found that the increased activity allele CYP2C19*17 was most prevalent in Central Europe (25–33%) with lower prevalence in Mediterranean-South Europeans (11–24%). In summary, we provide a detailed European map of common CYP2C19 and CYP2D6 variants and find that frequencies of the most clinically relevant alleles are geographically graded reflective of Europe’s migratory history. These findings emphasize the importance of generating pharmacogenomic data sets with high spatial resolution to improve precision public health across Europe.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

Computational Methods for the Pharmacogenetic Interpretation of Next Generation Sequencing Data

Up to half of all patients do not respond to pharmacological treatment as intended. A substantial fraction of these inter-individual differences is due to heritable factors and a growing number of associations between genetic variations and drug response phenotypes have been identified. Importantly, the rapid progress in Next Generation Sequencing technologies in recent years unveiled the true complexity of the genetic landscape in pharmacogenes with tens of thousands of rare genetic variants. As each individual was found to harbor numerous such rare variants they are anticipated to be important contributors to the genetically encoded inter-individual variability in drug effects. The fundamental challenge however is their functional interpretation due to the sheer scale of the problem that renders systematic experimental characterization of these variants currently unfeasible. Here, we review concepts and important progress in the development of computational prediction methods that allow to evaluate the effect of amino acid sequence alterations in drug metabolizing enzymes and transporters. In addition, we discuss recent advances in the interpretation of functional effects of non-coding variants, such as variations in splice sites, regulatory regions and miRNA binding sites. We anticipate that these methodologies will provide a useful toolkit to facilitate the integration of the vast extent of rare genetic variability into drug response predictions in a precision medicine framework.

Genetic variation in the Estonian population: pharmacogenomics study of adverse drug effects using electronic health records

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.

Genetic variability and population diversity of the human SLCO (OATP) transporter family

Organic anion transporting polypeptides (OATP) encoded by the SLCO gene family constitute clinically important transporters involved in the disposition of endogenous compounds and many commonly prescribed drugs, including statins, methotrexate and antihypertensive medications. Common genetic polymorphisms in SLCO genes are known to affect OATP function and modulate efficacy and safety of OATP substrates. However, current frequency data of these variants and haplotypes is generally based on few rather heterogenous populations of relatively small sample size. Furthermore, the genetic variability beyond these selected pharmacogenetic biomarkers has not been systematically analyzed. Here, we provide a global consolidated map of SLCO variability by leveraging fully compatible Next Generation Sequencing data from 138,632 unrelated individuals across seven major human populations. Overall, we find 9811 exonic single nucleotide variants and 155 copy number variations of which 99.3% were rare with frequencies <1%. Using orthogonal computational functionality predictors optimized for pharmacogenetic assessments, we find that four out of five individuals carry at least one deleterious variant in an SLCO transporter gene and rare variants contribute 23% to the genetically encoded functional variability. Moreover, 74.9% of all variants were found to be population-specific with important consequences for population-specific genotyping strategies and precision public health approaches. Combined, our analyses provide the most comprehensive data set of SLCO variability published to date and incentivize the integration of comprehensive NGS-based genotyping into personalized predictions of OATP substrate disposition.

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions

PURPOSE

Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations.

METHODS

We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.

RESULTS

Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.

CONCLUSION

We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

Human cytochrome P450 expression in bacteria: Whole-cell high-throughput activity assay for CYP1A2, 2A6 and 3A4

Cytochrome P450s (CYPs) are key enzymes involved in drug and xenobiotic metabolism. A wide array of in vitro methodologies, including recombinant sources, are currently been used to assess CYP catalysis, to identify the metabolic profile of compounds, potential drug-drug interactions, protein-protein interactions in the CYP enzyme complex and the role of polymorphic enzymes. We report here on a bacterial whole-cells high-throughput method for the activity evaluation of human CYP1A2, 2A6, and 3A4, when sustained by NADPH cytochrome P450 oxidoreductase (CPR), in the absence or presence of cytochrome b₅ (CYB5). This new assay consists of a microplate real-time fluorometric method, with direct measurement of metabolite formation, in a suspension of Escherichia coli BTC-CYP bacteria, a human CYP competent tester strain when incubated with specific fluorogenic substrates. Overall, the maximum turnover (k_cat) velocities of the three human CYPs resulting from the whole-BTC cells assays were similar to those obtained when applying the corresponding standard reference membrane fractions assays. CYP activity screening with co-expression of CYB5 suggests an enhancing effect of CYB5 on the k_cat of specific isoforms, when using the whole-BTC cells assay. Our results demonstrate that this new approach can offer an efficient high-throughput method for screening of CYP1A2, 2A6 and 3A4 activity and can be potentially applicable for other human CYPs. This can be of particular use for timely and efficient screening of chemical libraries or mutant libraries of CYP enzyme complex proteins, without the necessity for labor intensive isolation of subcellular fractions.

An optimized prediction framework to assess the functional impact of pharmacogenetic variants

Prediction of phenotypic consequences of mutations constitutes an important aspect of precision medicine. Current computational tools mostly rely on evolutionary conservation and have been calibrated on variants associated with disease, which poses conceptual problems for assessment of variants in poorly conserved pharmacogenes. Here, we evaluated the performance of 18 current functionality prediction methods leveraging experimental high-quality activity data from 337 variants in genes involved in drug metabolism and transport and found that these models only achieved probabilities of 0.1–50.6% to make informed conclusions. We therefore developed a functionality prediction framework optimized for pharmacogenetic assessments that significantly outperformed current algorithms. Our model achieved 93% for both sensitivity and specificity for both loss-of-function and functionally neutral variants, and we confirmed its superior performance using cross validation analyses. This novel model holds promise to improve the translation of personal genetic information into biological conclusions and pharmacogenetic recommendations, thereby facilitating the implementation of Next-Generation Sequencing data into clinical diagnostics.

Current Strategies and Applications for Precision Drug Design

Since Human Genome Project (HGP) revealed the heterogeneity of individuals, precision medicine that proposes the customized healthcare has become an intractable and hot research. Meanwhile, as the Precision Medicine Initiative launched, precision drug design which aims at maximizing therapeutic effects while minimizing undesired side effects for an individual patient has entered a new stage. One of the key strategies of precision drug design is target based drug design. Once a key pathogenic target is identified, rational drug design which constitutes the major part of precision drug design can be performed. Examples of rational drug design on novel druggable targets and protein-protein interaction surfaces are summarized in this review. Besides, various kinds of computational modeling and simulation approaches increasingly benefit for the drug discovery progress. Molecular dynamic simulation, drug target prediction and in silico clinical trials are discussed. Moreover, due to the powerful ability in handling high-dimensional data and complex system, deep learning has efficiently promoted the applications of artificial intelligence in drug discovery and design. In this review, deep learning methods that tailor to precision drug design are carefully discussed. When a drug molecule is discovered, the development of specific targeted drug delivery system becomes another key aspect of precision drug design. Therefore, state-of-the-art techniques of drug delivery system including antibody-drug conjugates (ADCs), and ligand-targeted conjugates are also included in this review.

Integrating rare genetic variants into pharmacogenetic drug response predictions

BACKGROUND

Variability in genes implicated in drug pharmacokinetics or drug response can modulate treatment efficacy or predispose to adverse drug reactions. Besides common genetic polymorphisms, recent sequencing projects revealed a plethora of rare genetic variants in genes encoding proteins involved in drug metabolism, transport, and response.

RESULTS

To understand the global importance of rare pharmacogenetic gene variants, we mapped the variability in 208 pharmacogenes by analyzing exome sequencing data from 60,706 unrelated individuals and estimated the importance of rare and common genetic variants using a computational prediction framework optimized for pharmacogenetic assessments. Our analyses reveal that rare pharmacogenetic variants were strongly enriched in mutations predicted to cause functional alterations. For more than half of the pharmacogenes, rare variants account for the entire genetic variability. Each individual harbored on average a total of 40.6 putatively functional variants, rare variants accounting for 10.8% of these. Overall, the contribution of rare variants was found to be highly gene- and drug-specific. Using warfarin, simvastatin, voriconazole, olanzapine, and irinotecan as examples, we conclude that rare genetic variants likely account for a substantial part of the unexplained inter-individual differences in drug metabolism phenotypes.

CONCLUSIONS

Combined, our data reveal high gene and drug specificity in the contributions of rare variants. We provide a proof-of-concept on how this information can be utilized to pinpoint genes for which sequencing-based genotyping can add important information to predict drug response, which provides useful information for the design of clinical trials in drug development and the personalization of pharmacological treatment.

Epigenetics and MicroRNAs in Pharmacogenetics

Germline pharmacogenetics has so far mainly studied common variants in "pharmacogenes," i.e., genes encoding drug metabolizing enzymes and transporters (DMET genes), certain auxiliary and regulatory genes, and drug target genes. Despite remarkable progress in understanding genetically determined differences in pharmacokinetics and pharmacodynamics of drugs, currently known common variants even in important pharmacogenes explain genetic variability only partially. This suggests "missing heritability" that may in part be due to rare variants in the classical pharmacogenes, but current evidence suggests that largely unexplored resources with potential for pharmacogenetics exist, both within already known pharmacogenes and in entirely new areas. In particular, recent studies suggest that epigenetic processes and noncoding RNAs, including mostly microRNAs (miRNAs), represent important and largely unexplored layers of DMET gene regulation that may fill some of the gaps in understanding interindividual variability and lead to new biomarkers. In this chapter we summarize recent advances in the understanding of genetic variability in epigenetic and miRNA-mediated processes with focus on their significance for DMET regulation and pharmacokinetic or pharmacological endpoints.

Association of STAT-3 rs1053004 and VDR rs11574077 With FOLFIRI-Related Gastrointestinal Toxicity in Metastatic Colorectal Cancer Patients

Pharmacogenomics has largely been applied to the personalization of irinotecan-based treatment, focusing mainly on the study of genetic variants in adsorption, distribution, metabolism, and excretion (ADME) genes. The transcriptional control of ADME gene expression is mediated by a set of nuclear factors responding to cancer-related inflammation, which could have pharmacological implications. The aim of the present study was to uncover novel genetic predictors of neutropenia and gastrointestinal toxicity risk among 246 haplotype-tagging polymorphisms in 22 genes encoding inflammation-related cytokines and transcriptional regulators of ADME genes. The study comprised overall more than 400 metastatic colorectal cancer (mCRC) patients treated with first-line FOLFIRI, grouped in a discovery and a replication cohorts. A concordant protective effect of STAT-3 rs1053004 polymorphism against the risk of grade 3–4 gastrointestinal toxicity was observed in both the cohorts of patients (OR = 0.51, p = 0.045, q = 0.521 and OR = 0.39, p = 0.043, respectively). VDR rs11574077 polymorphism was demonstrated to affect both irinotecan biliary index (BI) and glucuronidation ratio (GR) by a pharmacokinetic analysis. This effect was consistent with an increased risk of grade 3–4 gastrointestinal toxicity in the discovery cohort (OR = 4.46, p = 0.010, q = 0.305). The association was not significant in the replication cohort (OR = 1.44, p = 0.601). These findings suggest an effect of STAT-3 and VDR polymorphisms on FOLFIRI-related gastrointestinal toxicity. If prospectively validated as predictive markers, they could be used to improve the clinical management of mCRC.

The Pharmacogenetics of Immune-Modulating Therapy

Immunosuppressive drugs are a prerequisite in organ transplantation to prevent rejection and are also widely used in inflammatory diseases such as inflammatory bowel disease (IBD) or also in some hematologic malignancies-depending on the mode of action. For thiopurine analogs the polymorphic thiopurine S-methyltransferase (TPMT) was early detected to be associated with thiopurine-induced leukopenia; recent studies identified also NUDT15 to be related to this severe side effect. For drugs like methotrexate and mycophenolate mofetil a number of ADME genes like UDP-glucuronosyltransferases (UGTs) and ABC efflux transporters were investigated, however, with partly contradicting results. For calcineurin inhibitors like cyclosporine and in particular tacrolimus however, cytochrome P450 3A4 and 3A5 variants were found to significantly affect the pharmacokinetics. Genetic variants in genes encoding relevant pharmacodynamic proteins, however, lacked compelling evidence to affect the clinical outcome. This chapter reviews the current evidence on the association of pharmacogenetic traits to dose finding and clinical outcome of small-molecule immunosuppressants. Moreover this chapter critically summarizes suitability to apply pharmacogenetics in clinical practice in order to optimize immunosuppressant therapy.

Genetic variation of cytochrome P450 in Uyghur Chinese population

Interindividual and interethnic variability of drug responses could be attributed to the differences of genetic polymorphisms in the drug metabolizing enzymes and transporters genes among the populations. Here we reviewed the studies of genetic variations in Uyghur Chinese of fifteen CYP450 genes including CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP2J2, CYP2W1, CYP3A4, CYP3A5, CYP4A11, and CYP17A1, which totally covered 277 variants. We also collected the data of 277 variants covered in our study in two extensive population sequencing projects, the International HapMap Project (Hap-Map) and the 1000 Genomes Project and compared them with the data of Uyghur Chinese. The results suggested that remarkable differences of variants allele frequencies of CYP450 genes were existed among Uyghur Chinese and other world populations and drug doses should be adjusted clinically in Uyghur in contrast to Han Chinese and Caucasians.

Novel copy-number variations in pharmacogenes contribute to interindividual differences in drug pharmacokinetics

PurposeVariability in pharmacokinetics and drug response is shaped by single-nucleotide variants (SNVs) as well as copy-number variants (CNVs) in genes with importance for drug absorption, distribution, metabolism, and excretion (ADME). While SNVs have been extensively studied, a systematic assessment of the CNV landscape in ADME genes is lacking.MethodsWe integrated data from 2,504 whole genomes from the 1000 Genomes Project and 59,898 exomes from the Exome Aggregation Consortium to identify CNVs in 208 relevant pharmacogenes.ResultsWe describe novel exonic deletions and duplications in 201 (97%) of the pharmacogenes analyzed. The deletions are population-specific and frequencies range from singletons up to 1%, accounting for >5% of all loss-of-function alleles in up to 42% of the genes studied. We experimentally confirmed novel deletions in CYP2C19, CYP4F2, and SLCO1B3 by Sanger sequencing and validated their allelic frequencies in selected populations.ConclusionCNVs are an additional source of pharmacogenetic variability with important implications for drug response and personalized therapy. This, together with the important contribution of rare alleles to the variability of pharmacogenes, emphasizes the necessity of comprehensive next-generation sequencing-based genotype identification for an accurate prediction of the genetic variability of drug pharmacokinetics.

Pharmakogenetik

Interindividuelle Unterschiede zur Wirksamkeit und Verträglichkeit von Arzneimitteln sind ein erhebliches Problem der Gesundheitsversorgung. Genetische Varianten tragen hierzu bei. Ziel der Arbeit ist eine Übersicht über den gegenwärtigen Erkenntnisstand und regulatorische Aspekte der Pharmakogenetik zu geben sowie Fragen zur Problematik der Implementierung in die Klinik unter Hinzuziehung der aktuellen Literatur zu diskutieren. Die Empfehlungen des Clinical Pharmacogenetics Implementation Consortiums (CPIC) stellen gegenwärtig den wissenschaftlich solidesten Ausgangspunkt für auf Pharmakogenetik beruhende Auswahl und Dosierung ausgewählter Arzneistoffe dar. Auf nationaler Ebene geben die Richtlinien der Gendiagnostikkommission einen Rahmen, welche Klassen bei der Einordnung der Bedeutung hereditärer Varianten für Wirksamkeit und Verträglichkeit berücksichtigt werden sollten. Während für bestimmte Gen-Arzneistoff-Paare neben dem klinischen auch der ökonomische Nutzen bereits gezeigt werden konnte, sind für eine Vielzahl weiterer prospektive bzw. auf präemptiver Testung beruhende Studien notwendig, um den Erfolg der Anwendung in der Klinik zu belegen. Hierzu werden gegenwärtig Studien durch große Konsortien in Europa und besonders in Nordamerika durchgeführt.

The AAV-mediated and RNA-guided CRISPR/Cas9 system for gene therapy of DMD and BMD

Mutations in the dystrophin gene (Dmd) result in Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD), which afflict many newborn boys. In 2016, Brain and Development published several interesting articles on DMD treatment with antisense oligonucleotide, kinase inhibitor, and prednisolone. Even more strikingly, three articles in the issue 6271 of Science in 2016 provide new insights into gene therapy of DMD and BMD via the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9). In brief, adeno-associated virus (AAV) vectors transport guided RNAs (gRNAs) and Cas9 into mdx mouse model, gRNAs recognize the mutated Dmd exon 23 (having a stop codon), and Cas9 cut the mutated exon 23 off the Dmd gene. These manipulations restored expression of truncated but partially functional dystrophin, improved skeletal and cardiac muscle function, and increased survival of mdx mice significantly. This review concisely summarized the related advancements and discussed their primary implications in the future gene therapy of DMD, including AAV-vector selection, gRNA designing, Cas9 optimization, dystrophin-restoration efficiency, administration routes, and systemic and long-term therapeutic efficacy. Future orientations, including off-target effects, safety concerns, immune responses, precision medicine, and Dmd-editing in the brain (potentially blocked by the blood-brain barrier) were also elucidated briefly. Collectively, the AAV-mediated and RNA-guided CRISPR/Cas9 system has major superiorities compared with traditional gene therapy, and might contribute to the treatment of DMD and BMD substantially in the near future.

Worldwide Distribution of Cytochrome P450 Alleles: A Meta-analysis of Population-scale Sequencing Projects

Genetic polymorphisms in cytochrome P450 (CYP) genes can result in altered metabolic activity toward a plethora of clinically important medications. Thus, single nucleotide variants and copy number variations in CYP genes are major determinants of drug pharmacokinetics and toxicity and constitute pharmacogenetic biomarkers for drug dosing, efficacy, and safety. Strikingly, the distribution of CYP alleles differs considerably between populations with important implications for personalized drug therapy and healthcare programs. To provide a global distribution map of CYP alleles with clinical importance, we integrated whole‐genome and exome sequencing data from 56,945 unrelated individuals of five major human populations. By combining this dataset with population‐specific linkage information, we derive the frequencies of 176 CYP haplotypes, providing an extensive resource for major genetic determinants of drug metabolism. Furthermore, we aggregated this dataset into spectra of predicted functional variability in the respective populations and discuss the implications for population‐adjusted pharmacological treatment strategies.

Membrane Associated Progesterone Receptors: Promiscuous Proteins with Pleiotropic Functions - Focus on Interactions with Cytochromes P450

Membrane-associated progesterone receptors (MAPR) are a group of four rather small, partially homologous proteins, which share a similar non-covalent heme-binding domain that is related to cytochrome b5, a well-known functional interaction partner of microsomal cytochrome P450 (CYP) monooxygenase systems. Apart from their structural similarities the four proteins progesterone membrane component 1 (PGRMC1, also referred to as IZA, sigma-2 receptor, Dap1), PGRMC2, neudesin (NENF) and neuferricin (CYB5D2) display surprisingly divergent and multifunctional physiological properties related to cholesterol/steroid biosynthesis, drug metabolism and response, iron homeostasis, heme trafficking, energy metabolism, autophagy, apoptosis, cell cycle regulation, cell migration, neural functions, and tumorigenesis and cancer progression. The purpose of this mini-review is to briefly summarize the structural and functional properties of MAPRs with particular focus on their interactions with the CYP system. For PGRMC1, originally identified as a non-canonical progesterone-binding protein that mediates some immediate non-genomic actions of progesterone, available evidence indicates mainly activating interactions with steroidogenic CYPs including CYP11A1, CYP21A2, CYP17, CYP19, CYP51A1, and CYP61A1, while interactions with drug metabolizing CYPs including CYP2C2, CYP2C8, CYP2C9, CYP2E1, and CYP3A4 were either ineffective or slightly inhibitory. For the other MAPRs the evidence is so far less conclusive. We also point out that experimental limitations question some of the previous conclusions. Use of appropriate model systems should help to further clarify the true impact of these proteins on CYP-mediated metabolic pathways.

The Importance of Patient-Specific Factors for Hepatic Drug Response and Toxicity

Responses to drugs and pharmacological treatments differ considerably between individuals. Importantly, only 50%-75% of patients have been shown to react adequately to pharmacological interventions, whereas the others experience either a lack of efficacy or suffer from adverse events. The liver is of central importance in the metabolism of most drugs. Because of this exposed status, hepatotoxicity is amongst the most common adverse drug reactions and hepatic liabilities are the most prevalent reason for the termination of development programs of novel drug candidates. In recent years, more and more factors were unveiled that shape hepatic drug responses and thus underlie the observed inter-individual variability. In this review, we provide a comprehensive overview of different principle mechanisms of drug hepatotoxicity and illustrate how patient-specific factors, such as genetic, physiological and environmental factors, can shape drug responses. Furthermore, we highlight other parameters, such as concomitantly prescribed medications or liver diseases and how they modulate drug toxicity, pharmacokinetics and dynamics. Finally, we discuss recent progress in the field of in vitro toxicity models and evaluate their utility in reflecting patient-specific factors to study inter-individual differences in drug response and toxicity, as this understanding is necessary to pave the way for a patient-adjusted medicine.

Pharmacogenomics of the cytochrome P450 2C family: impacts of amino acid variations on drug metabolism

Pharmacogenomics investigates DNA and RNA variations in the human genome related to drug responses. Cytochrome P450 (CYP) is a supergene family of drug-metabolizing enzymes responsible for the metabolism of approximately 90% of human drugs. Among the major CYP isoforms, the CYP2C subfamily is of clinical significance because it metabolizes approximately 20% of clinically administrated drugs and represents several variant alleles leading to adverse drug reactions or altering drug efficacy. Here, we review recent progress on understanding the interindividual variability of the CYP2C members and the functional and clinical impact on drug metabolism. We summarize current advances in the molecular modeling of CYP2C polymorphisms and discuss the structural bases and molecular mechanisms of amino acid variants of CYP2C members that affect drug metabolism.

Pregnane X receptor, constitutive androstane receptor and hepatocyte nuclear factors as emerging players in cancer precision medicine

Great research effort has been focused on elucidating the contribution of host genetic variability on pharmacological outcomes in cancer. Nuclear receptors have emerged as mediators between environmental stimuli and drug pharmacokinetics and pharmacodynamics. The pregnane X receptor, constitutive androstane receptor and hepatocyte nuclear factors have been reported to regulate transcription of genes that encode drug metabolizing enzymes and transporters. Altered nuclear receptor expression has been shown to affect the metabolism and pharmacological profile of traditional chemotherapeutics and targeted agents. Accordingly, polymorphic variants in these genes have been studied as pharmacogenetic markers of outcome variability. This review summarizes the state of knowledge about the roles played by pregnane X receptor, constitutive androstane receptor and hepatocyte nuclear factor expression and genetics as predictive markers of anticancer drug toxicity and efficacy, which can improve cancer precision medicine.

Screening for genotypic and phenotypic variations in CYP450 activity in patients with therapeutic problems in a psychiatric setting, a retrospective study

OBJECTIVES

This retrospective study aimed to assess to what extent an adverse drug reaction (ADR), an abnormal therapeutic drug monitoring (TDM) or a non-response, was attributable to an abnormal cytochrome P450 activity in a psychiatric setting.

METHOD

We collected the results of investigations performed in these situations related to psychotropic drugs between January 2005 and November 2014. Activities of different cytochrome P450 were assessed by genotyping and/or phenotyping. Two experienced clinical pharmacologists assessed independently the possible association between the event and the results of the investigations.

RESULTS

One hundred and thirty eight clinical or biological situations had a complete assessment of all major metabolic pathways of the target drug. A majority of clinical or biological situations were observed with antidepressants (n=93, 67.4%), followed by antipsychotics (n=28, 20.3%), benzodiazepines and hypnotics (n=13, 9.4%), and psychostimulants (n=4, 2.9%). Genotype and/or phenotype determination was mainly performed because of ADRs (n=68, 49.3%) or non-response (n=46, 33.3%). Inter-rate reliability of the scoring system between the pharmacologists was excellent (kappa=0.94). The probability of an association between ADR, TDM or non-response and metabolic status was rated as intermediate to high in 34.7% of all cases, with proportions of 30.4% and 36.7%, for non-response and ADR respectively.

CONCLUSION

When indicated by clinical pharmacologists, ADR, TDM or non-response may be attributable to a variation of the metabolic status with an intermediate to high probability in 34.7% of patients, based on the congruent assessment made by two clinical pharmacologists. Further studies assessing the clinical relevance of prospective explorations and clarifying the appropriate method according to the clinical context are needed.

Requirements for comprehensive pharmacogenetic genotyping platforms

Recent research highlighted the large extent of rare variants in pharmacogenes and, on this basis, it was estimated that rare variants account for 30-40% of the functional variability in pharmacogenes. It has been proposed that comprehensive next-generation sequencing (NGS)-based sequencing of pharmacogenes could soon be a cost-effective methodology for clinical routine genotyping. Yet, multiple challenges on technical, interpretative and ethical levels need to be overcome to enable the reasonable dissemination of comprehensive pharmacogenetic genotyping, that includes rare genetic variation, into clinical practice. We argue that current pre-emptive pharmacogenetic testing cannot be based on comprehensive approaches but needs to be restricted to validated variants. Rather, comprehensive strategies should only be used for retrospective analyses of patients exhibiting unanticipated drug responses. Thereby, subsequent to computational analyses and functional validations, emerging variants with confirmed functional relevance can be incorporated into candidate genotyping strategies, thus refining and enhancing future pre-emptive genetic testing.

Targeting mitochondrial phenotypes for non-communicable diseases

The concept that "Exercise is Medicine" has been challenged by the rising prevalence of non-communicable chronic diseases (NCDs). This is partly due to the fact that the underlying mechanisms of how exercise influences energy homeostasis and counteracts high-fat diets and physical inactivity is complex and remains relatively poorly understood on a molecular level. In addition to genetic polymorphisms in humans that lead to gross variations in responsiveness to exercise, adaptation in mitochondrial networks is central to physical activity, inactivity, and diet. To harness the benefits of exercise for NCDs, much work still needs to be done to improve health effectively on a societal level such as developing personalized exercise interventions aided by advances in high-throughput genomics, proteomics, and metabolomics. We propose that understanding the mitochondrial phenotype according to the molecular information of genotypes, lifestyles, and exercise responsiveness in individuals will optimize exercise effects for prevention of NCDs.