High Probability of Gene-Drug Interactions Associated with Medication Side Effects in Adolescent Depression: Results from a Randomized Controlled Trial of Pharmacogenetic Testing

Introduction: Combinatorial pharmacogenetic testing panels are widely available in clinical practice and often separate medications into columns/bins associated with low, medium, or high probability of gene-drug interactions. The objective of the Adolescent Management of Depression (AMOD) study was to determine the clinical utility of combinatorial pharmacogenetic testing in a double-blind, randomized, controlled effectiveness study by comparing patients who had genetic testing results at time of medication initiation to those that did not have results until week 8. The objective of this post hoc analysis was to assess and report additional outcomes with respect to significant gene-drug interactions (i.e., a medication in the high probability gene-drug interaction bin as defined by a proprietary algorithm) compared with patients taking a medication with minimal to moderate gene-drug interactions (i.e., a medication from the low or medium probability gene-drug interaction bin, respectively). Methods: Adolescents 13-18 years (N = 170) with moderate to severe major depressive disorder received pharmacogenetic testing. Symptom improvement and side effects were assessed at baseline, week 4, week 8, and 6 months. Patients were grouped into three categories based on whether the medication they were prescribed was associated with low, medium, or high risk for gene-drug interactions. Patients taking a medication from the low/medium gene-drug interaction bin were compared with patients taking a medication from the high gene-drug interaction bin. Results: Patients taking a medication from the high gene-drug interaction bin were more likely to endorse side effects compared with patients taking a medication in the low/medium gene-drug interaction bin at week 8 (p = 0.001) and 6 months (p < 0.0001). Depressive symptom severity scores did not differ significantly across the medication bins. Conclusions: This study demonstrates the utility of gene-drug interaction testing to guide medication decisions to minimize side effect burden rather than solely prioritizing the search for the most efficacious medication. (Clinical Trials Registration Identifier: NCT02286440).

Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity

Variability in genes involved in drug pharmacokinetics or drug response can be responsible for suboptimal treatment efficacy or predispose to adverse drug reactions. In addition to common genetic variations, large-scale sequencing studies have uncovered multiple rare genetic variants predicted to cause functional alterations in genes encoding proteins implicated in drug metabolism, transport and response. To understand the functional importance of rare genetic variants in DPYD, a pharmacogene whose alterations can cause severe toxicity in patients exposed to fluoropyrimidine-based regimens, massively parallel sequencing of the exonic regions and flanking splice junctions of the DPYD gene was performed in a series of nearly 3000 patients categorized according to pre-emptive DPD enzyme activity using the dihydrouracil/uracil ([UH2]/[U]) plasma ratio as a surrogate marker of DPD activity. Our results underscore the importance of integrating next-generation sequencing-based pharmacogenomic interpretation into clinical decision making to minimize fluoropyrimidine-based chemotherapy toxicity without altering treatment efficacy.

Pre-emptive pharmacogenomics implementation among polypharmacy patients 65 years old and older: a clinical pilot

Aim: Pre-emptive testing of pharmacogenomic (PGx) variations has potential to improve medication safety and effectiveness; however, testing is not routine. Given the newfound payor coverage of multigene testing and the potential value of testing within aging patients, it is imperative to test local PGx testing capabilities, report results to patients and providers, and determine the value of testing. Materials & methods: We designed a randomized clinical pilot of a pre-emptive PGx testing process using the electronic health record compared with usual care among an aging primary care population. Results & conclusion: The impact of the program on prescribing patterns, healthcare utilization and costs of care will be evaluated. We hypothesize that implementation of a pre-emptive multigene PGx panel is feasible among elderly, polypharmacy, primary care patients, measured by the number of enrolled patients with PGx results entered in the medical record. Health system wide PGx implementation, including capacity needed to integrate these valuable results, is also described.

Attitudes on pharmacogenomic results as secondary findings among medical geneticists

OBJECTIVES

As evidence mounts supporting the utility of pharmacogenomic-guided medication management, incorporating pharmacogenomic genes into secondary finding results from sequencing panels is increasingly under consideration. We studied medical geneticists' attitudes on receiving pharmacogenomic results as secondary finding.

METHODS

Four focus groups with 16 medical geneticists total were conducted followed by thematic analysis.

RESULTS

All participants ordered genetic sequencing tests; however, the majority had rarely or never ordered pharmacogenomic tests (10/16) or prescribed medications with established response variability (11/16). In total 81.3% expressed low comfort interpreting pharmacogenomic results without appropriate clinical resources (13/16). The positives of receiving pharmacogenomic results as secondary finding included prevention of adverse drug reactions in adults, grateful information-seeking patients, the ability to rapidly prescribe more effective treatments and appreciation of the recent advances in both pharmacogenomic knowledge and available guidelines. Negatives included laboratory reporting issues, exclusivity of pharmacogenomic results to certain populations, lengthy reports concealing pharmacogenomic results in patient charts and laboratories marketing to individuals without prior pharmacogenomic knowledge or targeting inappropriate populations. The most desirable pharmacogenomic resources included a universal electronic health record clinical decision support tool to assist identifying and implementing pharmacogenomic results, a specialized pharmacist as part of the care team, additional pharmacogenomic training during medical/graduate school, and a succinct interpretation of pharmacogenomic results included on laboratory reports.

CONCLUSIONS

The majority of participants agreed that adding certain actionable pharmacogenomic genes to the American College of Medical Genetics and Genomics SF list is reasonable; however, this was qualified with a need for additional resources to support implementation.

The Impact of the CYP2D6 "Enhancer" Single Nucleotide Polymorphism on CYP2D6 Activity

rs5758550 has been associated with enhanced transcription and suggested to be a useful marker of CYP2D6 activity. As there are limited and inconsistent data regarding the utility of this distant "enhancer" single nucleotide polymorphism (SNP), our goal was to further assess the impact of rs5758550 on CYP2D6 activity toward two probe substrates, atomoxetine (ATX) and dextromethorphan (DM), using in vivo urinary metabolite (DM; n = 188) and pharmacokinetic (ATX; n = 70) and in vitro metabolite formation (ATX and DM; n = 166) data. All subjects and tissues were extensively genotyped, the "enhancer" SNP phased with established CYP2D6 haplotypes either computationally or experimentally, and the impact on CYP2D6 activity investigated using several linear models of varying complexity to determine the proportion of variability in CYP2D6 activity captured by each model. For all datasets and models, the "enhancer" SNP had no or only a modest impact on CYP2D6 activity prediction. An increased effect, when present, was more pronounced for ATX than DM suggesting potential substate-dependency. In addition, CYP2D6*2 alleles with the "enhancer" SNP were associated with modestly higher metabolite formation rates in vitro, but not in vivo; no effect was detected for CYP2D6*1 alleles with "enhancer" SNP. In summary, it remains inconclusive whether the small effects detected in this investigation are indeed caused by the "enhancer" SNP or are rather due to its incomplete linkage with other variants within the gene. Taken together, there does not appear to be sufficient evidence to warrant the "enhancer" SNP be included in clinical CYP2D6 pharmacogenetic testing.

PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.

Analysis Approaches to Identify Pharmacogenetic Associations With Pharmacodynamics

Pharmacogenetics (PGx) seeks to enable selection of the right dose of the right drug for each patient to optimize therapeutic outcomes. Most PGx focuses on pharmacokinetics (PKs), due to our relatively advanced understanding of the genes involved in PKs and the causative effects of variants in those genes. Genetic variants can also affect pharmacodynamics (PDs), but relatively few PGx-PD associations have been identified. This is partially due to a more limited understanding of the relevant genes and the consequences of genetic variation, but is also due in part to the potential confounding of PK variability in assessments of clinical outcomes that have a contribution from both PKs and PDs. For example, it is challenging to confirm the effect of mu opioid receptor (OPRM1) genetic variation on opioid response due to the contribution of CYP2D6 genotype to bioactivation of some opioid drugs (i.e., codeine and tramadol). The objectives of this mini-review are to describe several recent efforts to discover and validate PGx-PD that disentangle the influence of PK variability and propose potential approaches that could be used in future PGx-PD analyses. We use the effect of OPRM1 genetics on opioid response to illustrate how these analyses could be conducted and conclude by discussing how PGx-PD could be translated into clinical practice to improve therapeutic outcomes.

Polymorphisms in GNMT and DNMT3b are associated with methotrexate treatment outcome in plaque psoriasis

Methotrexate is used as first-line treatment of moderate to severe psoriasis. Despite the marked variability in treatment outcomes, no pharmacogenetic markers are currently used for personalised management of therapy. In this retrospective study, we investigated the effects of genetic predisposition on efficacy and toxicity of low-dose methotrexate in a cohort of 137 patients with moderate to severe plaque psoriasis. We genotyped 16 polymorphisms in genes for enzymes involved in the folate-methionine pathway and in methotrexate transport, and analysed their association with treatment efficacy and toxicity using classification and regression tree analysis and logistic regression. The most pronounced effect observed in this study was for GNMT rs10948059, which was identified as a risk factor for inadequate efficacy leading to treatment discontinuation. Patients carrying at least one variant allele had ~7-fold increased risk of treatment failure compared to patients with the wild-type genotype, as shown by the classification and regression tree analysis and logistic regression (odds ratio [OR], 6.94; p = 0.0004). Another risk factor associated with insufficient treatment responses was DNMT3b rs2424913, where patients carrying at least one variant allele had a 4-fold increased risk of treatment failure compared to patients with the wild-type genotype (OR, 4.10; p = 0.005). Using classification and regression tree analysis, we show that DNMT3b rs2424913 has a more pronounced role in patients with the variant GNMT genotype, and hence we suggest an interaction between these two genes. Further, we show that patients with the BHMT rs3733890 variant allele had increased risk of hepatotoxicity (OR, 3.17; p = 0.022), which is the most prominent reason for methotrexate discontinuation. We also show that variants in the genes for methotrexate transporters OATP1B1 (rs2306283/rs4149056 SLCO1B1 haplotypes) and ABCC2 (rs717620) are associated with increased risk of treatment failure. The associations identified have not been reported previously. These data suggest that polymorphisms in genes for enzymes of the methionine cycle (which affect cell methylation potential) might have significant roles in treatment responses to methotrexate of patients with psoriasis. Further studies are warranted to validate the potential of the pharmacogenetic markers identified.

Clinical Trial in a Dish: Using Patient-Derived Induced Pluripotent Stem Cells to Identify Risks of Drug-Induced Cardiotoxicity

Drug-induced cardiotoxicity is a significant clinical issue, with many drugs in the market being labeled with warnings on cardiovascular adverse effects. Treatments are often prematurely halted when cardiotoxicity is observed, which limits their therapeutic potential. Moreover, cardiotoxicity is a major reason for abandonment during drug development, reducing available treatment options for diseases and creating a significant financial burden and disincentive for drug developers. Thus, it is important to minimize the cardiotoxic effects of medications that are in use or in development. To this end, identifying patients at a higher risk of developing cardiovascular adverse effects for the drug of interest may be an effective strategy. The discovery of human induced pluripotent stem cells has enabled researchers to generate relevant cell types that retain a patient's own genome and examine patient-specific disease mechanisms, paving the way for precision medicine. Combined with the rapid development of pharmacogenomic analysis, the ability of induced pluripotent stem cell-derivatives to recapitulate patient-specific drug responses provides a powerful platform to identify subsets of patients who are particularly vulnerable to drug-induced cardiotoxicity. In this review, we will discuss the current use of patient-specific induced pluripotent stem cells in identifying populations who are at risk to drug-induced cardiotoxicity and their potential applications in future precision medicine practice. Graphic Abstract: A graphic abstract is available for this article.

Actionable pharmacogenetic variants in Hong Kong Chinese exome sequencing data and projected prescription impact in the Hong Kong population

Preemptive pharmacogenetic testing has the potential to improve drug dosing by providing point-of-care patient genotype information. Nonetheless, its implementation in the Chinese population is limited by the lack of population-wide data. In this study, secondary analysis of exome sequencing data was conducted to study pharmacogenomics in 1116 Hong Kong Chinese. We aimed to identify the spectrum of actionable pharmacogenetic variants and rare, predicted deleterious variants that are potentially actionable in Hong Kong Chinese, and to estimate the proportion of dispensed drugs that may potentially benefit from genotype-guided prescription. The projected preemptive pharmacogenetic testing prescription impact was evaluated based on the patient prescription data of the public healthcare system in 2019, serving 7.5 million people. Twenty-nine actionable pharmacogenetic variants/ alleles were identified in our cohort. Nearly all (99.6%) subjects carried at least one actionable pharmacogenetic variant, whereas 93.5% of subjects harbored at least one rare deleterious pharmacogenetic variant. Based on the prescription data in 2019, 13.4% of the Hong Kong population was prescribed with drugs with pharmacogenetic clinical practice guideline recommendations. The total expenditure on actionable drugs was 33,520,000 USD, and it was estimated that 8,219,000 USD (24.5%) worth of drugs were prescribed to patients with an implicated actionable phenotype. Secondary use of exome sequencing data for pharmacogenetic analysis is feasible, and preemptive pharmacogenetic testing has the potential to support prescription decisions in the Hong Kong Chinese population.

Pharmacogenetic testing provides relevant drug phenotype information to guide personalized drug prescription, which potentially improves drug efficacy and prevent adverse drug reactions. However, its implementation in the Chinese population is limited by the lack of Chinese-specific pharmacogenetics data. In this study, we studied the spectrum of 133 actionable pharmacogenetic variants and rare deleterious variants in 108 pharmacogenes using an exome sequencing consisting of 1116 Hong Kong Chinese subjects. It was found that nearly all individuals carried at least one actionable pharmacogenetic variant and one rare, predicted deleterious pharmacogenetic variant. In addition, we projected the potential prescription impact of actionable pharmacogenetic variants using prescription data of the Hong Kong's public healthcare system. We estimated that one-seventh of the Hong Kong population received at least one of the 36 drugs with clinical pharmacogenetics guideline recommendations. The findings demonstrated the potential of pharmacogenetic testing in improving patient care and resource allocation in Chinese. The cohort dataset also supports clinical implementation of pharmacogenetics in the Chinese population.

Synthesis of major pharmacogenomics pretest counseling themes: a multisite comparison

The accessibility of pharmacogenomic (PGx) testing has grown substantially over the last decade and with it has arisen a demand for patients to be counseled on the use of these tests. While guidelines exist for the use of PGx results; objective determinants for who should receive PGx testing remain incomplete. PGx clinical services have been created to meet these screening and education needs and significant variability exists between these programs. This article describes the practices of four PGx clinics during pretest counseling sessions. A description of the major tenets of the benefits, limitations and risks of testing are compiled. Additional tools are provided to serve as a foundation for those wishing to begin or expand their own counseling service.

A case of personalized and precision medicine: Pharmacometabolomic applications to rare cancer, microbiological investigation, and therapy

RATIONALE

Advances in metabolomics, together with consolidated genetic approaches, have opened the way for investigating the health of patients using a large number of molecules simultaneously, thus providing firm scientific evidence for personalized medicine and consequent interventions. Metabolomics is an ideal approach for investigating specific biochemical alterations occurring in rare clinical situations, such as those caused by rare associations between comorbidities and immunosuppression.

METHODS

Metabolomic database matching enables clear identification of molecular factors associated with a metabolic disorder and can provide a rationale for elaborating personalized therapeutic protocols. Mass spectrometry (MS) forms the basis of metabolomics and uses mass-to-charge ratios for metabolite identification. Here, we used an MS-based approach to diagnose and develop treatment options in the clinical case of a patient afflicted with a rare disease further complicated by immunosuppression. The patient's data were analyzed using proprietary databases, and a personalized and efficient therapeutic protocol was consequently elaborated.

RESULTS

The patient exhibited significant alterations in homocysteine:methionine and homocysteine:thiodiglycol acid plasma concentration ratios, and these were associated with low immune system function. This led to cysteine concentration deficiency causing extreme oxidative stress. Plasmatic thioglycolic acid concentrations were initially altered and were used for therapeutic follow-up and to evaluate cysteine levels.

CONCLUSIONS

An MS-based pharmacometabolomics approach was used to define a personalized protocol in a clinical case of rare peritoneal carcinosis with confounding immunosuppression. This personalized protocol reduced both oxidative stress and resistance to antibiotics and antiviral drugs.

Pharmacogenomics Biomarker Discovery and Validation for Translation in Clinical Practice

Interindividual variability in drug efficacy and toxicity is a major challenge in clinical practice. Variations in drug pharmacokinetics (PKs) and pharmacodynamics (PDs) can be, in part, explained by polymorphic variants in genes encoding drug metabolizing enzymes and transporters (absorption, distribution, metabolism, and excretion) or in genes encoding drug receptors. Pharmacogenomics (PGx) has allowed the identification of predictive biomarkers of drug PKs and PDs and the current knowledge of genome-disease and genome-drug interactions offers the opportunity to optimize tailored drug therapy. High-throughput PGx genotyping, from targeted to more comprehensive strategies, allows the identification of PK/PD genotypes to be developed as clinical predictive biomarkers. However, a biomarker needs a robust process of validation followed by clinical-grade assay development and must comply to stringent regulatory guidelines. We here discuss the methodological challenges and the emerging technological tools in PGx biomarker discovery and validation, at the crossroad among molecular genetics, bioinformatics, and clinical medicine.

Sex-, Age-, and Race/Ethnicity-Dependent Variations in Drug-Processing and NRF2-Regulated Genes in Human Livers

Individual variations in xenobiotic metabolism affect the sensitivity to diseases. In this study, the impacts of sex, age, and race/ethnicity on drug-processing genes and nuclear factor erythroid 2-related factor 2 (NRF2) genes in human livers were examined via QuantiGene multiplex suspension array (226 samples) and quantitative polymerase chain reaction (qPCR) (247 samples) to profile the expression of nuclear receptors, cytochrome P450s, conjugation enzymes, transporters, bile acid metabolism, and NRF2-regulated genes. Sex differences were found in expression of about half of the genes, but in general the differences were not large. For example, females had higher transcript levels of catalase, glutamate-cysteine ligase catalytic subunit (GCLC), heme oxygenase 1 (HO-1), Kelch-like ECH-associated protein 1 (KEAP1), superoxide dismutase 1, and thioredoxin reductase-1 compared with males via qPCR. There were no apparent differences due to age, except children had higher glutamate-cysteine ligase modifier subunit (GCLM) and elderly had higher multidrug resistance protein 3. African Americans had lower expression of farnesoid X receptor (FXR) but higher expression of HO-1, Caucasians had higher expression of organic anion transporter 2, and Hispanics had higher expression of FXR, SULT2A1, small heterodimer partner, and bile salt export pump. An examination of 34 diseased and control human liver samples showed that compared with disease-free livers, fibrotic livers had higher NAD(P)H-quinone oxidoreductase 1 (NQO1), GCLC, GCLM, and NRF2; hepatocellular carcinoma had higher transcript levels of NQO1 and KEAP1; and steatotic livers had lower GCLC, GCLM, and HO-1 expression. In summary, in drug-processing gene and NRF2 genes, sex differences were the major findings, and there were no apparent age differences, and race/ethnicity differences occurred for a few genes. These descriptive findings could add to our understanding of the sex-, age-, and race/ethnicity-dependent differences in drug-processing genes as well as NRF2 genes in normal and diseased human livers. SIGNIFICANCE STATEMENT: In human liver drug-processing and nuclear factor erythroid 2-related factor 2 genes, sex differences were the main finding. There were no apparent differences due to age, except children had higher glutamate-cysteine ligase modifier subunit, and elderly had higher multidrug resistance protein 3. African Americans had lower expression of farnesoid X receptor (FXR) but higher expression of heme oxygenase 1, Caucasians had higher expression of organic anion transporter 2, and Hispanics had higher expression of FXR, small heterodimer partner, SULT2A1, and bile salt export pump.

Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients

IMPORTANCE

Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation.

OBJECTIVE

To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions.

DESIGN, SETTING, AND PARTICIPANTS

This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020.

EXPOSURES

Prescription of 38 level A medications based on electronic health records.

MAIN OUTCOMES AND MEASURES

Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally.

RESULTS

Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes.

CONCLUSIONS AND RELEVANCE

These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Effect of Routine Cytochrome P450 2D6 and 2C19 Genotyping on Antipsychotic Drug Persistence in Patients With Schizophrenia: A Randomized Clinical Trial

IMPORTANCE

Genetic polymorphism of genes encoding the drug metabolizing enzymes, cytochrome P450 2D6 and 2C19 (CYP2D6 and CYP2C19), is associated with treatment failure of and adverse reactions to psychotropic drugs. The clinical utility of routine CYP2D6 and CYP2C19 genotyping (CYP testing) is unclear.

OBJECTIVE

To estimate whether routine CYP testing effects the persistence of antipsychotic drug treatment.

DESIGN, SETTING, AND PARTICIPANTS

This single-masked, 3-group randomized clinical trial included patients aged 18 years or older who had been diagnosed within the schizophrenic spectrum (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes, F20-F29) and not previously genotyped. A total of 669 of 1406 potentially eligible patients from 12 psychiatric outpatient clinics in Denmark were approached between July 2008 and December 2009. Overall, 528 patients were genotyped and randomly allocated to 1 of 3 study groups or exclusion in a sequence of 1:1:1:3 using a predictive enrichment design, aiming to double the proportion of poor or ultrarapid metabolizers for CYP2D6 or CYP2C19. Outcome measurements were recorded at baseline and 1-year follow-up. Data analysis was performed in December 2012 and updated March 2019.

INTERVENTIONS

The trial included 2 intervention groups, where antipsychotic drug treatment was guided by either CYP test (CYP test-guided [CTG]) or structured clinical monitoring (SCM), in which adverse effects and factors influencing compliance were systematically recorded at least once quarterly, and 1 control group.

MAIN OUTCOMES AND MEASURES

Primary outcome was antipsychotic drug persistence, ie, days to first modification of the initial treatment. Secondary outcomes were number of drug and dose changes, adverse effects, and psychotic symptoms, ie, hallucinations and delusions.

RESULTS

A total of 528 participants were genotyped, and 311 (median [interquartile range {IQR} age, 41 [30-50] years; 139 [45%] women; median [IQR] duration of illness, 6 [3-13] years) were randomly allocated to 1 of 3 study groups. Overall, 61 participants (20%) were extreme metabolizers. There was no difference in antipsychotic drug persistence between the CTG group and the control group (hazard ratio [HR], 1.02; 95% CI, 0.71-1.45) or SCM and the control group (HR, 0.88; 95% CI, 0.61-1.26). Subanalyses among extreme metabolizers showed similar results (CTG: HR, 0.99; 95% CI, 0.48-2.03; SCM: HR, 0.93; 95% CI, 0.44-1.96).

CONCLUSIONS AND RELEVANCE

The results of this randomized clinical trial do not support routine CYP testing in patients with schizophrenia.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00707382.

Pharmacokinetic, pharmacodynamic, and pharmacogenetic assays to monitor clopidogrel therapy

Clopidogrel is the most common and widely used antiplatelet agent for patients with coronary artery disease following confirmation by electrocardiographic studies. The nonresponsiveness of patients to clopidogrel and the possibility of testing for clopidogrel resistance by platelet function assays (PFA) are contentious issues. Light transmission aggregometry (LTA) is considered as the gold standard test among all PFA. In this review, the most commonly used PFA used for monitoring the effect of clopidogrel, LTA, vasodilator-stimulated phosphoprotein assay phosphorylation, rotational thromboelastometry (ROTEM) delta and ROTEM platelet, thromboelastography, PFA-100, VerifyNow P2Y12 assay, Multiplate analyzer, Plateletworks assay and pharmacogenetic studies, are comparatively discussed including their principles of action, advantages, and disadvantages. VerifyNow P2Y12 assay can be accepted as the ideal point of care test out of the discussed assays. However, modified assays are required which could overcome the limitations associated with currently available assays.

Biomarkers for Immunotherapy

Immune checkpoint inhibitor (ICI) therapy has been approved for several solid tumors, including non-small cell lung cancer. ICIs have shown unprecedented durable responses and higher response rates than chemotherapy in selected patients. The development of biomarkers that serve as predictors of response is crucial for treatment selection. Evidence suggests that the response to immunotherapy depends on tumor genomics and the interactions with the immune system and the tumor microenvironment. This article reviews the data supporting the use of these biomarkers to optimize patient selection for these therapies and explores biomarkers that are the focus of ongoing research.

Pharmacogenetics in psychiatric care, a call for uptake of available applications

In this narrative, we evaluate the role of pharmacogenetics in psychiatry from a pragmatic clinical perspective and address current barriers of clinical implementation of pharmacogenetics. Pharmacogenetics has been successfully implemented to improve drug therapy in several clinical areas, but not psychiatry. Yet, psychotropics account for more than one-third of the drugs for which pharmacogenetic guidelines are available and drug therapy in mental disorders is suboptimal with insufficient effectiveness and frequent adverse events. The limited application of pharmacogenetics in psychiatry is influenced by several factors; e.g. the complexity of psychotropic drug metabolism, possibly impeding the clinical understanding of the benefits of pharmacogenetics. Also, recommendations for most psychotropics classify pharmacogenetic testing only as (potentially) beneficial, not as essential, possibly because life-threatening adverse events are often not involved in these drug-gene interactions. Implementing pharmacogenetics in psychiatry could improve the current practice of time-consuming switching of therapies causing undue delays associated with worse outcomes. We expect pharmacogenetics in psychiatry to expedite with panel-based genotyping, including clinically relevant variants, which will address the complex enzymatic metabolism of psychotropic drugs. Until then, we stress that available pharmacogenetic testing should be seen as an integrated companion, not a competitor, in current clinical psychiatric care.

[Pharmacogenetic testing in acute and chronic pain: a preliminary study]

Background. Pain is one of the most common symptoms that weighs on life's quality and health expenditure. In a reality in which increasingly personalized therapies are needed, the early use of genetic tests that highlight the individual response to analgesic drugs could be a valuable help in clinical practice helping to reduce response times, to achieve a good level of analgesia and to reduce the risk of side effects and adverse events. The study aims to confront the clinical response to analgesic drugs with the result of pharmacogenetic testing in patients with persistent pain. Methods. This preliminary study compares the genetic results of pharmacological effectiveness and tolerability analyzed with a Pharmacogenetic Test with the results obtained in clinical practice in 5 patients suffering from acute and chronic pain. Results. Regarding the genetic results of the 5 samples analyzed, 2 reports were found to be completely comparable to what found in clinical practice, while 3 reports showed that the profile of tolerability and effectiveness were partially discordant. Conclusions. In light of the data, not completely overlapping with results observed in clinical practice, further studies would be appropriate in order to acquire more information on the use of the PGT in clinical practice.

MASS SPECTROMETRY-BASED PERSONALIZED DRUG THERAPY

Personalized drug therapy aims to provide tailored treatment for individual patient. Mass spectrometry (MS) is revolutionarily involved in this area because MS is a rapid, customizable, cost-effective, and easy to be used high-throughput method with high sensitivity, specificity, and accuracy. It is driving the formation of a new field, MS-based personalized drug therapy, which currently mainly includes five subfields: therapeutic drug monitoring (TDM), pharmacogenomics (PGx), pharmacomicrobiomics, pharmacoepigenomics, and immunopeptidomics. Gas chromatography-MS (GC-MS) and liquid chromatography-MS (LC-MS) are considered as the gold standard for TDM, which can be used to optimize drug dosage. Matrix-assisted laser desorption ionization-time of flight-MS (MALDI-TOF-MS) significantly improves the capability of detecting biomacromolecule, and largely promotes the application of MS in PGx. It is becoming an indispensable tool for genotyping, which is used to discover and validate genetic biomarkers. In addition, MALDI-TOF-MS also plays important roles in identity of human microbiome whose diversity can explain interindividual differences of drug response. Pharmacoepigenetics is to study the role of epigenetic factors in individualized drug treatment. MS can be used to discover and validate pharmacoepigenetic markers (DNA methylation, histone modification, and noncoding RNA). For the emerging cancer immunotherapy, personalized cancer vaccine has effective immunotherapeutic activity in the clinic. MS-based immunopeptidomics can effectively discover and screen neoantigens. This article systematically reviewed MS-based personalized drug therapy in the above mentioned five subfields. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Advances in Genomics for Drug Development

Drug development (target identification, advancing drug leads to candidates for preclinical and clinical studies) can be facilitated by genetic and genomic knowledge. Here, we review the contribution of population genomics to target identification, the value of bulk and single cell gene expression analysis for understanding the biological relevance of a drug target, and genome-wide CRISPR editing for the prioritization of drug targets. In genomics, we discuss the different scope of genome-wide association studies using genotyping arrays, versus exome and whole genome sequencing. In transcriptomics, we discuss the information from drug perturbation and the selection of biomarkers. For CRISPR screens, we discuss target discovery, mechanism of action and the concept of gene to drug mapping. Harnessing genetic support increases the probability of drug developability and approval.

Identifying key transcription factors for pharmacogenetic studies of antipsychotics induced extrapyramidal symptoms

INTRODUCTION

We explore the transcription factors involved in the molecular mechanism of antipsychotic (AP)-induced acute extrapyramidalsymptoms (EPS) in order to identify new candidate genes for pharmacogenetic studies.

METHODS

Protein-protein interaction (PPI) networks previously created from three pharmacogenomic models (in vitro, animal, and peripheral blood inhumans) were used to, by means of several bioinformatic tools; identify key transcription factors (TFs) that regulate each network. Once the TFs wereidentified, SNPs disrupting the binding sites (TFBS) of these TFs in the genes of each network were selected for genotyping. Finally, SNP-basedassociations with EPS were analyzed in a sample of 356 psychiatric patients receiving AP.

RESULTS

Our analysis identified 33 TFs expressed in the striatum, and 125 SNPs disrupting TFBS in 50 genes of our initial networks. Two SNPs (rs938112,rs2987902) in two genes (LSMAP and ABL1) were significantly associated with AP induced EPS (p < 0.001). These SNPs disrupt TFBS regulated byPOU2F1.

CONCLUSION

Our results highlight the possible role of the disruption of TFBS by SNPs in the pharmacological response to AP.

[Pharmacogenetics in daily practice]

With the exception of a few medical specialties, the implementation of pharmacogenetic tests in daily practice has thus far been limited. The Royal Dutch Pharmacists Association (KNMP) has developed pharmacogenetics-based therapeutic doserecommendations for 80 medicinal product combinations on the basis of a systematic literature review. Genotyping of patients can take place on a reactive or pre-emptive basis; the advantage of pre-emptive genotyping is that it provides genetic information the moment a medicinal product is prescribed. Clinical decision support software is crucial to implement pharmacogenetics into daily practice.

Open-source chemogenomic data-driven algorithms for predicting drug-target interactions

While novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery. Doubtlessly, the availability of open-accessible data from basic chemical biology research and the success of human genome sequencing are crucial to develop effective in silico drug repositioning methods allowing the identification of potential targets for existing drugs. In this work, we review several chemogenomic data-driven computational algorithms with source codes publicly accessible for predicting drug-target interactions (DTIs). We organize these algorithms by model properties and model evolutionary relationships. We re-implemented five representative algorithms in R programming language, and compared these algorithms by means of mean percentile ranking, a new recall-based evaluation metric in the DTI prediction research field. We anticipate that this review will be objective and helpful to researchers who would like to further improve existing algorithms or need to choose appropriate algorithms to infer potential DTIs in the projects. The source codes for DTI predictions are available at: https://github.com/minghao2016/chemogenomicAlg4DTIpred.

Pharmacogenetic-Whole blood and intracellular pharmacokinetic-Pharmacodynamic (PG-PK2-PD) relationship of tacrolimus in liver transplant recipients

Tacrolimus (TAC) is the cornerstone of immunosuppressive therapy in liver transplantation. This study aimed at elucidating the interplay between pharmacogenetic determinants of TAC whole blood and intracellular exposures as well as the pharmacokinetic-pharmacodynamic relationship of TAC in both compartments. Complete pharmacokinetic profiles (Predose, and 20 min, 40 min, 1h, 2h, 3h, 4h, 6h, 8h, 12h post drug intake) of twice daily TAC in whole blood and peripheral blood mononuclear cells (PBMC) were collected in 32 liver transplanted patients in the first ten days post transplantation. A non-parametric population pharmacokinetic model was applied to explore TAC pharmacokinetics in blood and PBMC. Concurrently, calcineurin activity was measured in PBMC. Influence of donor and recipient genetic polymorphisms of ABCB1, CYP3A4 and CYP3A5 on TAC exposure was assessed. Recipient ABCB1 polymorphisms 1199G>A could influence TAC whole blood and intracellular exposure (p<0.05). No association was found between CYP3A4 or CYP3A5 genotypes and TAC whole blood or intracellular concentrations. Finally, intra-PBMC calcineurin activity appeared incompletely inhibited by TAC and less than 50% of patients were expected to achieve intracellular IC₅₀ concentration (100 pg/millions of cells) at therapeutic whole blood concentration (i.e.: 4–10 ng/mL). Together, these data suggest that personalized medicine regarding TAC therapy might be optimized by ABCB1 pharmacogenetic biomarkers and by monitoring intracellular concentration whereas the relationship between intracellular TAC exposure and pharmacodynamics biomarkers more specific than calcineurin activity should be further investigated.

Pharmacogenetic Markers: A Path toward Individualized HIV Therapy

INTRODUCTION Approximately 73% of persons with HIV who receive antiretroviral therapy in Cuba are in viral suppression. The non-response of the remaining 27% could be due to several factors including adverse drug reactions and HIV resistance to antiretroviral drugs, as well as social factors and idiosyncratic characteristics of each patient. Genetic information explains from 20% to 95% of a drug's effects and variations in response. Considering optimization of therapeutic efficacy in our country, genetic factors of the host should be identified. OBJECTIVE Identify polymorphisms affecting genetic variability of responses to antiretroviral drugs. EVIDENCE ACQUISITION A literature review was conducted (of original articles, published theses, clinical reports and bibliographic review studies, from 2000 to 2018, in Spanish and English listed in MEDLINE/PubMed, SciELO, LILACS, PharmGKB and Google Scholar) with the following key words: pharmacogenetics, human immunodeficiency virus, anti-retroviral agents, genetic polymorphism, genetic techniques, pharmacogenomic variants. DEVELOPMENT The review identified 77 relevant publications meeting specific quality criteria. A summary table was built with data collected on antiretroviral drugs, genes and proteins involved in polymorphic variations, their associated effects and relevant scientific references. Information was included on polymorphisms related to 12 antiretroviral drugs used in HIV therapy. Polymorphisms determine variations in proteins involved in drug transport and metabolism and in elements of immunity. Relevant pharmacogenetic biomarkers recognized by drug regulatory agencies were identified. CONCLUSIONS The study identified genetic variations (single-nucleotide polymorphisms) associated with 12 antiretroviral drugs. In most cases, no statistically significant causal association was found. Identifying polymorphic variations is a medium- and long-term objective that requires statistical support and adoption of strategies to optimize antiretroviral therapy. An approach combining plasma-level monitoring and pharmacogenetic analysis is recommended to optimize therapy for HIV patients. KEYWORDS Pharmacogenetics, HIV, anti-retroviral agents, antiretroviral therapy, genetic polymorphism, genetic techniques, pharmacogenomic variants.

Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation

The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.

A stepwise approach to implementing pharmacogenetic testing in the primary care setting

Pharmacogenetic testing can help identify primary care patients at increased risk for medication toxicity, poor response or treatment failure and inform drug therapy. While testing availability is increasing, providers are unprepared to routinely use pharmacogenetic testing for clinical decision-making. Practice-based resources are needed to overcome implementation barriers for pharmacogenetic testing in primary care.The NHGRI's IGNITE I Network (Implementing GeNomics In pracTicE; www.ignite-genomics.org) explored practice models, challenges and implementation barriers for clinical pharmacogenomics. Based on these experiences, we present a stepwise approach pharmacogenetic testing in primary care: patient identification; pharmacogenetic test ordering; interpretation and application of test results, and patient education. We present clinical factors to consider, test-ordering processes and resources, and provide guidance to apply test results and counsel patients. Practice-based resources such as this stepwise approach to clinical decision-making are important resources to equip primary care providers to use pharmacogenetic testing.

Recommendations for Clinical CYP2C9 Genotyping Allele Selection: A Joint Recommendation of the Association for Molecular Pathology and College of American Pathologists

The goals of the Association for Molecular Pathology Pharmacogenomics (PGx) Working Group of the Association for Molecular Pathology Clinical Practice Committee are to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document provides recommendations for a minimum panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories when designing assays for CYP2C9 testing. The Working Group considered the functional impact of the variants, allele frequencies in different populations and ethnicities, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. Our goal is to promote standardization of testing PGx genes and alleles across clinical laboratories. These recommendations are not to be interpreted as restrictive but to provide a reference guide. The current document will focus on CYP2C9 testing that can be applied to all CYP2C9-related medications. A separate recommendation on warfarin PGx testing is being developed to include recommendations on CYP2C9 alleles and additional warfarin sensitivity-associated genes and alleles.

Are There Different Evidence Thresholds for Genomic Versus Clinical Precision Medicine? A Value of Information-Based Framework Applied to Antiplatelet Drug Therapy

BACKGROUND

The threshold of sufficient evidence for adoption of clinically- and genomically-guided precision medicine (PM) has been unclear.

OBJECTIVE

To evaluate evidence thresholds for clinically guided PM versus genomically guided PM.

METHODS

We develop an "evidence threshold criterion" (ETC), which is the time-weighted difference between expected value of perfect information and incremental net health benefit minus the cost of research, and use it as a measure of evidence threshold that is proportional to the upper bound of disutility to a risk-averse decision maker for adopting a new intervention under decision uncertainty. A larger (more negative) ETC value indicates that only decision makers with low risk aversion would adopt new intervention. We evaluated the ETC plus cost of research (ETCc), assuming the same cost of research for both interventions, over time for a pharmacogenomic (PGx) testing intervention and avoidance of a drug-drug interaction (aDDI) intervention for acute coronary syndrome patients indicated for antiplatelet therapy. We then examined how the ETC may explain incongruous decision making across different national decision-making bodies.

RESULTS

The ETCc for PGx increased over time, whereas the ETCc for aDDI decreased to a negative value over time, indicating that decision makers with even low risk aversion will have doubts in adopting PGx, whereas decision makers who are highly risk-averse will continue to have doubts about adopting aDDI. National recommendation bodies appear to be consistent over time within their own decision making, but had different levels of risk aversion.

CONCLUSION

The ETC may be a useful metric for assessing policy makers' risk preferences and, in particular, understanding differences in policy recommendations for genomic versus clinical PM.

Mapping the knowledge structure and trends of epilepsy genetics over the past decade: A co-word analysis based on medical subject headings terms

INTRODUCTION

Over the past 10 years, epilepsy genetics has made dramatic progress. This study aimed to analyze the knowledge structure and the advancement of epilepsy genetics over the past decade based on co-word analysis of medical subject headings (MeSH) terms.

METHODS

Scientific publications focusing on epilepsy genetics from the PubMed database (January 2009-December 2018) were retrieved. Bibliometric information was analyzed quantitatively using Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) software. A knowledge social network analysis and publication trend based on the high-frequency MeSH terms was built using VOSviewer.

RESULTS

According to the search strategy, a total of 5185 papers were included. Among all the extracted MeSH terms, 86 high-frequency MeSH terms were identified. Hot spots were clustered into 5 categories including: "ion channel diseases," "beyond ion channel diseases," "experimental research & epigenetics," "single nucleotide polymorphism & pharmacogenetics," and "genetic techniques". "Epilepsy," "mutation," and "seizures," were located at the center of the knowledge network. "Ion channel diseases" are typically in the most prominent position of epilepsy genetics research. "Beyond ion channel diseases" and "genetic techniques," however, have gradually grown into research cores and trends, such as "intellectual disability," "infantile spasms," "phenotype," "exome," " deoxyribonucleic acid (DNA) copy number variations," and "application of next-generation sequencing." While ion channel genes such as "SCN1A," "KCNQ2," "SCN2A," "SCN8A" accounted for nearly half of epilepsy genes in MeSH terms, a number of additional beyond ion channel genes like "CDKL5," "STXBP1," "PCDH19," "PRRT2," "LGI1," "ALDH7A1," "MECP2," "EPM2A," "ARX," "SLC2A1," and more were becoming increasingly popular. In contrast, gene therapies, treatment outcome, and genotype-phenotype correlations were still in their early stages of research.

CONCLUSION

This co-word analysis provides an overview of epilepsy genetics research over the past decade. The 5 research categories display publication hot spots and trends in epilepsy genetics research which could consequently supply some direction for geneticists and epileptologists when launching new projects.

Protocol for the development of the STrengthening the Reporting Of Pharmacogenetic Studies (STROPS) guideline: checklist of items for reporting pharmacogenetic studies

INTRODUCTION

Large sample sizes are often required to detect statistically significant associations between pharmacogenetic markers and treatment response. Meta-analysis may be performed to synthesise data from several studies, increasing sample size and consequently power to detect significant genetic effects. However, performing robust synthesis of data from pharmacogenetic studies is often challenging due to poor reporting of key data in study reports. There is currently no guideline for the reporting of pharmacogenetic studies. The aim of this project is to develop the STrengthening the Reporting Of Pharmacogenetic Studies (STROPS) guideline. The STROPS guideline will facilitate the conduct of high-quality meta-analyses and thus improve the power to detect genetic associations.

METHODS AND ANALYSIS

We will establish a preliminary checklist of reporting items to be considered for inclusion in the guideline. We will then conduct a Delphi survey of key stakeholder groups to gain consensus opinion on which reporting items to include in the final guideline. The Delphi survey will consist of two rounds: the first round will invite participants to score items from the preliminary checklist and to suggest additional relevant items; the second round will provide feedback from the previous round and invite participants to re-score the items. Following the second round, we will summarise the distribution of scores for each item, stratified by stakeholder group. The Steering Committee for the project and representatives from the key stakeholder groups will meet to consider the results of the Delphi survey and to finalise the list of reporting items. We will then draft, pilot-test and publish the STROPS reporting guideline and accompanying explanatory document.

ETHICS AND DISSEMINATION

The University of Liverpool Ethics Committee has confirmed ethical approval for this study (reference: 3586). Dissemination activities will include presenting the reporting guideline at conferences relevant to pharmacogenetic research.

Opioids: The Painful Public Health Reality

The analgesic, sedative, antidepressant, euphoriant, intoxicating, and addictive properties of opium and its synthetic derivatives are well known and have been known for centuries. Hence, the current major public health problems due to excessive availability should be no surprise. What is unprecedented in the United States, and emerging elsewhere, is the extent of the profound consequences and complexity of addressing this public health crisis.

Estimated nationwide impact of implementing a preemptive pharmacogenetic panel approach to guide drug prescribing in primary care in The Netherlands

BACKGROUND

Pharmacogenetics (PGx) is currently implemented in hospitals to optimize therapy with high-risk drugs. However, many drugs with dosing recommendations from the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium are used in primary care. Actionable phenotypes for the genes covered in these guidelines are common with estimates ranging from 85 to 95% of the population carrying at least one actionable phenotype. The goal of this study was to estimate the clinical impact of implementation of an upfront panel-based pharmacogenetic screening for eight genes related to drugs used in primary care for 2016.

METHODS

For this study, dispensing data concerning first prescription for the period January 1-December 31, 2016, were combined with frequency data obtained in the "Implementation of Pharmacogenetics into Primary Care Project" (IP3) study to estimate the occurrence of actionable gene-drug pairs in daily practice in community pharmacies.

RESULTS

In 23.6% of all new prescriptions of 45 drugs (n = 856,002 new prescriptions/year), an actionable gene-drug interaction (GDI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group. More importantly, these GDIs would result in a dose adjustment or switch to another drug in 5.4% of all new prescriptions.

CONCLUSIONS

Consequently, with an anticipated near future where healthcare professionals will be regularly confronted with PGx test results, adjusting pharmacotherapy based on this information will become a routine task in healthcare.

On the utilization of polygenic risk scores for therapeutic targeting

The promise of personalized genomic medicine is that knowledge of a person's gene sequences and activity will facilitate more appropriate medical interventions, particularly drug prescriptions, to reduce the burden of disease. Early successes in oncology and pediatrics have affirmed the power of positive diagnosis and are mostly based on detection of one or a few mutations that drive the specific pathology. However, genetically more complex diseases require the development of polygenic risk scores (PRSs) that have variable accuracy. The rarity of events often means that they have necessarily low precision: many called positives are actually not at risk, and only a fraction of cases are prevented by targeted therapy. In some situations, negative prediction may better define the population at low risk. Here, I review five conditions across a broad spectrum of chronic disease (opioid pain medication, hypertension, type 2 diabetes, major depression, and osteoporotic bone fracture), considering in each case how genetic prediction might be used to target drug prescription. This leads to a call for more research designed to evaluate genetic likelihood of response to therapy and a call for evaluation of PRS, not just in terms of sensitivity and specificity but also with respect to potential clinical efficacy.

Community pharmacists' educational needs for implementing clinical pharmacogenomic services

OBJECTIVES

Pharmacist leadership and knowledge of pharmacogenomics is critical to the acceleration and enhancement of clinical pharmacogenomic services. This study aims for a qualitative description of community pharmacists' pharmacogenomic educational needs when implementing clinical pharmacogenomic services at community pharmacies.

METHODS

Pharmacists practicing at Rite Aid Pharmacy locations in the Greater Pittsburgh Area were recruited to participate in this qualitative analysis. Pharmacists from pharmacy locations offering pharmacogenomic testing and robust patient care services were eligible to participate in a semistructured, audio-recorded interview. The semistructured interview covered 4 domains crafted by the investigative team: (1) previous knowledge of pharmacogenomics; (2) implementation resources; (3) workflow adaptation; and (4) learning preferences. Interviews were transcribed verbatim and independently coded by 2 researchers. A thematic analysis by the investigative team followed. Supporting quotes were selected to illustrate each theme.

RESULTS

Eleven pharmacists from 9 unique pharmacy locations participated in this study. The average length of practice as a community pharmacist was 12 years (range, 1.5-31 years). Pharmacist's pharmacogenomic educational needs were categorized into 5 key themes: (1) enriched pharmacogenomic education and training; (2) active learning to build confidence in using pharmacogenomic data in practice; (3) robust and reputable clinical resources to effectively implement pharmacogenomic services; (4) team-based approach throughout implementation; (5) readily accessible network of pharmacogenomic experts.

CONCLUSION

This study describes the educational needs and preferences of community pharmacists for the successful provision of clinical pharmacogenomic services in community pharmacies. Pharmacists recognized their needs for enriched knowledge and instruction, practice applying pharmacogenomic principles with team-based approaches, robust clinical resources, and access to pharmacogenomic experts. This deeper understanding of pharmacist needs for pharmacogenomic education could help to accelerate and enhance the clinical implementation of pharmacogenomic services led by community pharmacists.

Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment

Personalized medicine is focused on research disciplines which contribute to the individualization of therapy, like pharmacogenomics and pharmacotranscriptomics. Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood. It is one of the pediatric malignancies with the highest cure rate, but still a lethal outcome due to therapy accounts for 1%⁻3% of deaths. Further improvement of treatment protocols is needed through the implementation of pharmacogenomics and pharmacotranscriptomics. Emerging high-throughput technologies, including microarrays and next-generation sequencing, have provided an enormous amount of molecular data with the potential to be implemented in childhood ALL treatment protocols. In the current review, we summarized the contribution of these novel technologies to the pharmacogenomics and pharmacotranscriptomics of childhood ALL. We have presented data on molecular markers responsible for the efficacy, side effects, and toxicity of the drugs commonly used for childhood ALL treatment, i.e., glucocorticoids, vincristine, asparaginase, anthracyclines, thiopurines, and methotrexate. Big data was generated using high-throughput technologies, but their implementation in clinical practice is poor. Research efforts should be focused on data analysis and designing prediction models using machine learning algorithms. Bioinformatics tools and the implementation of artificial i Lack of association of the CEP72 rs924607 TT genotype with intelligence are expected to open the door wide for personalized medicine in the clinical practice of childhood ALL.

Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment

Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework—Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment.

The antibiotic resistance epidemic has created a pressing need to understand factors that influence antibiotic efficacy. An often-overlooked factor in the search for new treatments is the pathogen environment. Understanding the differences in pathogen sensitivity to antibiotics in lab conditions versus inside the host is necessary for translating new discoveries into the clinic. Hence, we experimentally measured the sensitivity of E. coli to drugs and drug combinations in different metabolic conditions. Our data revealed that the environment dramatically changes treatment potency. Each antibiotic class was affected uniquely by each metabolic condition. The large number of metabolic conditions inside the host greatly complicates the identification of effective therapies. To address this challenge, we present a computational approach called MAGENTA that accurately predicted efficacy of antibiotic regimens in different conditions, which we confirmed experimentally. Furthermore, we show that MAGENTA can be applied to other bacterial pathogens such as A. baumannii and M. tuberculosis without the need for generating expensive data in each organism. MAGENTA accurately predicted efficacy in the pathogen A. baumannii using data from E. coli by identifying genes that are common between the two bacteria. Our study revealed the significant yet predictable impact of environment on drug combination potency.

Towards precision medicine; a new biomedical cosmology

Precision Medicine has become a common label for data-intensive and patient-driven biomedical research. Its intended future is reflected in endeavours such as the Precision Medicine Initiative in the USA. This article addresses the question whether it is possible to discern a new 'medical cosmology' in Precision Medicine, a concept that was developed by Nicholas Jewson to describe comprehensive transformations involving various dimensions of biomedical knowledge and practice, such as vocabularies, the roles of patients and physicians and the conceptualisation of disease. Subsequently, I will elaborate my assessment of the features of Precision Medicine with the help of Michel Foucault, by exploring how precision medicine involves a transformation along three axes: the axis of biomedical knowledge, of biomedical power and of the patient as a self. Patients are encouraged to become the managers of their own health status, while the medical domain is reframed as a data-sharing community, characterised by changing power relationships between providers and patients, producers and consumers. While the emerging Precision Medicine cosmology may surpass existing knowledge frameworks; it obscures previous traditions and reduces research-subjects to mere data. This in turn, means that the individual is both subjected to the neoliberal demand to share personal information, and at the same time has acquired the positive 'right' to become a member of the data-sharing community. The subject has to constantly negotiate the meaning of his or her data, which can either enable self-expression, or function as a commanding Superego.

Pharmacogenetic testing in oncology: a Brazilian perspective

Pharmacogenetics, a major component of individualized or precision medicine, relies on human genetic diversity. The remarkable developments in sequencing technologies have revealed that the number of genetic variants modulating drug action is much higher than previously thought and that a true personalized prediction of drug response requires attention to rare mutations (minor allele frequency, MAF<1%) in addition to polymorphisms (MAF>1%) in pharmacogenes. This has major implications for the conceptual development and clinical implementation of pharmacogenetics. Drugs used in cancer treatment have been major targets of pharmacogenetics studies, encompassing both germline polymorphisms and somatic variants in the tumor genome. The present overview, however, has a narrower scope and is focused on germline cancer pharmacogenetics, more specifically, on drug/gene pairs for which pharmacogenetics-informed prescription guidelines have been published by the Clinical Pharmacogenetics Implementation Consortium and/or the Dutch Pharmacogenetic Working Group, namely, thiopurines/TPMT, fluoropyrimidines/UGT1A1, irinotecan/UGT1A1 and tamoxifen/CYP2D6. I begin by reviewing the general principles of pharmacogenetics-informed prescription, pharmacogenetics testing and the perceived barriers to the adoption of routine pharmacogenetics testing in clinical practice. Then, I highlight aspects of the pharmacogenetics testing of the selected drug-gene pairs and finally present pharmacogenetics data from Brazilian studies pertinent to these drug-gene pairs. I conclude with the notion that pharmacogenetics testing has the potential to greatly benefit patients by enabling precision medicine applied to drug therapy, ensuring better efficacy and reducing the risk of adverse effects.

Mapping genetic vulnerabilities reveals BTK as a novel therapeutic target in oesophageal cancer

OBJECTIVE

Oesophageal cancer is the seventh most common cause of cancer-related death worldwide. Disease relapse is frequent and treatment options are limited.

DESIGN

To identify new biomarker-defined therapeutic approaches for patients with oesophageal cancer, we integrated the genomic profiles of 17 oesophageal tumour-derived cell lines with drug sensitivity data from small molecule inhibitor profiling, identifying drug sensitivity effects associated with cancer driver gene alterations. We also interrogated recently described RNA interference screen data for these tumour cell lines to identify candidate genetic dependencies or vulnerabilities that could be exploited as therapeutic targets.

RESULTS

By integrating the genomic features of oesophageal tumour cell lines with siRNA and drug screening data, we identified a series of candidate targets in oesophageal cancer, including a sensitivity to inhibition of the kinase BTK in MYC amplified oesophageal tumour cell lines. We found that this genetic dependency could be elicited with the clinical BTK/ERBB2 kinase inhibitor, ibrutinib. In both MYC and ERBB2 amplified tumour cells, ibrutinib downregulated ERK-mediated signal transduction, cMYC Ser-62 phosphorylation and levels of MYC protein, and elicited G1 cell cycle arrest and apoptosis, suggesting that this drug could be used to treat biomarker-selected groups of patients with oesophageal cancer.

CONCLUSIONS

BTK represents a novel candidate therapeutic target in oesophageal cancer that can be targeted with ibrutinib. On the basis of this work, a proof-of-concept phase II clinical trial evaluating the efficacy of ibrutinib in patients with MYC and/or ERBB2 amplified advanced oesophageal cancer is currently underway (NCT02884453).

TRIAL REGISTRATION NUMBER

NCT02884453; Pre-results.

Expression levels of selected genes can predict individual rheumatoid arthritis patient response to tumor necrosis factor alpha blocker treatment

OBJECTIVES

Rheumatoid arthritis (RA) patients have many therapeutic options; however, tools to predict individual patient response are limited. The Genefron personal diagnostic kit, developed by analyzing large datasets, utilizes selected interferon stimulated gene expressions to predict treatment response. This study evaluates the kit's prediction accuracy of individual RA patients' response to tumor necrosis alpha (TNFα) blockers.

METHODS

A retrospective analysis was performed on RA patients reported in published datasets. A prospective analysis assessed RA patients, before and 3 months after starting a TNFα blocker. Clinical response was evaluated according to EULAR response criteria. Blood samples were obtained before starting treatment and were analyzed utilizing the kit which measures expression levels of selected genes by quantitative real time polymerase chain reaction (PCR). ROC analysis was applied to the published datasets and the prospective data.

RESULTS

The Genefron kit analysis of retrospective data predicted the response to a TNFα blocker in 53 of 61 RA patients (86.8% accuracy). In the prospective analysis, the kit predicted the response in 16 of 18 patients (89% accuracy) achieving a EULAR moderate response, and in 15 of 18 patients achieving a EULAR good response (83.3% accuracy). ROC analysis applied to the two published datasets yielded an AUC of 0.89. ROC analysis applied to the prospective data yielded an AUC of 0.83 (sensitivity - 100%, specificity - 75%) The statistical power obtained in the prospective study was .9.

CONCLUSION

The diagnostic kit predicted the response to TNFα blockers in a high percentage of patients assessed retrospectively or prospectively. This personal kit may guide selection of a suitable biological drug for the individual RA patient.

Genotype-Based Recall Studies in Complex Cardiometabolic Traits

In genotype-based recall (GBR) studies, people (or their biological samples) who carry genotypes of special interest for a given hypothesis test are recalled from a larger cohort (or biobank) for more detailed investigations. There are several GBR study designs that offer a range of powerful options to elucidate (1) genotype-phenotype associations (by increasing the efficiency of genetic association studies, thereby allowing bespoke phenotyping in relatively small cohorts), (2) the effects of environmental exposures (within the Mendelian randomization framework), and (3) gene-treatment interactions (within the setting of GBR interventional trials). In this review, we overview the literature on GBR studies as applied to cardiometabolic health outcomes. We also review the GBR approaches used to date and outline new methods and study designs that might enhance the utility of GBR-focused studies. Specifically, we highlight how GBR methods have the potential to augment randomized controlled trials, providing an alternative application for the now increasingly accepted Mendelian randomization methods usually applied to large-scale population-based data sets. Further to this, we consider how functional and basic science approaches alongside GBR designs offer intellectually intriguing and potentially powerful ways to explore the implications of alterations to specific (and potentially druggable) biological pathways.

Benefit of Preemptive Pharmacogenetic Information on Clinical Outcome

The development of new knowledge around the genetic determinants of variable drug action has naturally raised the question of how this new knowledge can be used to improve the outcome of drug therapy. Two broad approaches have been taken: a point-of-care approach in which genotyping for specific variant(s) is undertaken at the time of drug prescription, and a preemptive approach in which multiple genetic variants are typed in an individual patient and the information archived for later use when a drug with a "pharmacogenetic story" is prescribed. This review addresses the current state of implementation, the rationale for these approaches, and barriers that must be overcome. Benefits to pharmacogenetic testing are only now being defined and will be discussed.

Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 × 10-6 ). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-β) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D.

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10-8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis.