Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems

Big Data Transforms Discovery-Utilization Therapeutics Continuum

Enabling omic technologies adopt a holistic view to produce unprecedented insights into the molecular underpinnings of health and disease, in part, by generating massive high-dimensional biological data. Leveraging these systems-level insights as an engine driving the healthcare evolution is maximized through integration with medical, demographic, and environmental datasets from individuals to populations. Big data analytics has accordingly emerged to add value to the technical aspects of storage, transfer, and analysis required for merging vast arrays of omic-, clinical-, and eco-datasets. In turn, this new field at the interface of biology, medicine, and information science is systematically transforming modern therapeutics across discovery, development, regulation, and utilization.

Pharmacogenetics for Safe Codeine Use in Sickle Cell Disease

After postoperative deaths in children who were prescribed codeine, several pediatric hospitals have removed it from their formularies. These deaths were attributed to atypical cytochrome P450 2D6 (CYP2D6) pharmacogenetics, which is also implicated in poor analgesic response. Because codeine is often prescribed to patients with sickle cell disease and is now the only Schedule III opioid analgesic in the United States, we implemented a precision medicine approach to safely maintain codeine as an option for pain control. Here we describe the implementation of pharmacogenetics-based codeine prescribing that accounts for CYP2D6 metabolizer status. Clinical decision support was implemented within the electronic health record to guide prescribing of codeine with the goal of preventing its use after tonsillectomy or adenoidectomy and in CYP2D6 ultra-rapid and poor metabolizer (high-risk) genotypes. As of June 2015, CYP2D6 genotype results had been reported for 2468 unique patients. Of the 830 patients with sickle cell disease, 621 (75%) had a CYP2D6 genotype result; 7.1% were ultra-rapid or possible ultra-rapid metabolizers, and 1.4% were poor metabolizers. Interruptive alerts recommended against codeine for patients with high-risk CYP2D6 status. None of the patients with an ultra-rapid or poor metabolizer genotype were prescribed codeine. Using genetics to tailor analgesic prescribing retained an important therapeutic option by limiting codeine use to patients who could safely receive and benefit from it. Our efforts represent an evidence-based, innovative medication safety strategy to prevent adverse drug events, which is a model for the use of pharmacogenetics to optimize drug therapy in specialized pediatric populations.

Disease-drug database for pharmacogenomic-based prescribing

Providers have expressed a strong desire to have additional clinical decision-support tools to help with interpretation of pharmacogenomic results. We developed and tested a novel disease-drug association tool that enables pharmacogenomic-based prescribing to treat common diseases. First, 324 drugs were mapped to 484 distinct diseases (mean number of drugs treating each disease was 4.9; range 1-37). Then the disease-drug association tool was pharmacogenomically annotated, with an average of 1.8 pharmacogenomically annotated drugs associated/disease. Applying this tool to a prospectively enrolled >1,000 patient cohort from a tertiary medical center showed that 90% of the top ∼20 diseases in this population and ≥93% of patients could appropriately be treated with ≥1 medication with actionable pharmacogenomic information. When combined with clinical patient genotypes, this tool permits delivery of patient-specific pharmacogenomically informed disease treatment recommendations to inform the treatment of many medical conditions of the US population, a key initial step towards implementation of precision medicine.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

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.

Pharmacogenomics in the clinic

After decades of discovery, inherited variations have been identified in approximately 20 genes that affect about 80 medications and are actionable in the clinic. And some somatically acquired genetic variants direct the choice of 'targeted' anticancer drugs for individual patients. Current efforts that focus on the processes required to appropriately act on pharmacogenomic variability in the clinic are moving away from discovery and towards implementation of an evidenced-based strategy for improving the use of medications, thereby providing a cornerstone for precision medicine.

The Outlier in All of Us: Why Implementing Pharmacogenomics Could Matter for Everyone

The field of pharmacogenomics originally emerged in the 1950s from observations that a few rare individuals had unexpected, severe reactions to drugs. As recently as just 6 years ago, prominent views on the subject had largely remained unchanged, with authors from the US Food and Drug Administration (FDA) citing the purpose of pharmacogenetics as "tailoring treatment for the outliers." It should not be surprising if this is the prevailing view--the best-studied pharmacogenomic drug examples are indeed just that, genetic explanations of extreme responses or susceptibilities among usually a very small fraction of the human population. Thiopurine methyltransferase (TPMT) deficiency as a cause of severe myelosuppression upon treatment with azathioprine or mercaptopurine is found as a heterozygous trait in only ∼ 10% of patients, and homozygous (deficiency) carriers are even more rare--occurring in fewer than 1 in 300 patients. Malignant hyperthermia resulting from inhaled anesthetics and succinylcholine is believed to have a genetic incidence of only about 1 in 2000 people.

PGRNseq: a targeted capture sequencing panel for pharmacogenetic research and implementation

OBJECTIVES

Although the costs associated with whole-genome and whole-exome next-generation sequencing continue to decline, they remain prohibitively expensive for large-scale studies of genetic variation. As an alternative, custom-target sequencing has become a common methodology on the basis of its favorable balance between cost, throughput, and deep coverage.

METHODS

We have developed PGRNseq, a custom-capture panel of 84 genes with associations to pharmacogenetic phenotypes, as a tool to explore the relationship between drug response and genetic variation, both common and rare. We utilized a set of 32 diverse HapMap trios and two clinical cohorts to assess platform performance, accuracy, and ability to discover novel variation.

RESULTS

We found that PGRNseq generates ultra-deep coverage data (mean=496x) that are over 99.8% concordant with orthogonal datasets. In addition, in our testing sets, PGRNseq identified many novel, rare variants of interest, underscoring its value in both research and clinical settings.

CONCLUSION

PGRNseq is an ideal platform for carrying out sequencing-based analyses of pharmacogenetic variation in large cohorts. In addition, the high accuracy associated with genotypes from PGRNseq highlight its utility as a clinical test.

Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC)

To move beyond a select few genes/drugs, the successful adoption of pharmacogenomics into routine clinical care requires a curated and machine-readable database of pharmacogenomic knowledge suitable for use in an electronic health record (EHR) with clinical decision support (CDS). Recognizing that EHR vendors do not yet provide a standard set of CDS functions for pharmacogenetics, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Working Group is developing and systematically incorporating a set of EHR-agnostic implementation resources into all CPIC guidelines. These resources illustrate how to integrate pharmacogenomic test results in clinical information systems with CDS to facilitate the use of patient genomic data at the point of care. Based on our collective experience creating existing CPIC resources and implementing pharmacogenomics at our practice sites, we outline principles to define the key features of future knowledge bases and discuss the importance of these knowledge resources for pharmacogenomics and ultimately precision medicine.

Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study

Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC) system–among potential users (i.e., physicians and pharmacists). Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient’s pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1) qualitative interviews with pharmacists and pharmacy students, (2) a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3) a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians’ and pharmacists’ attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient scenarios based on the recommendations displayed on the MSC interface. A frequent request among participants was to provide specific listings of alternative drugs and concrete dosage instructions. Negligence of other patient-specific factors for choosing the right treatment such as renal function and co-medication was a common concern related to the MSC system, while data privacy and cost-benefit considerations emerged as the participants’ major concerns regarding pharmacogenetic testing in general. The results of the card layout evaluation indicate that a gene-centered and tabulated presentation of the patient’s pharmacogenomic profile is helpful and well-accepted. Conclusions. We found that the MSC system was well-received among the physicians and pharmacists included in this study. A personalized pocket card that lists a patient’s metabolizer status along with critically affected drugs can alert physicians and pharmacists to the availability of essential therapy modifications.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records

IMPORTANCE

Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants.

OBJECTIVE

To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014.

EXPOSURES

One or more variants designated as pathogenic in SCN5A or KCNH2.

MAIN OUTCOMES AND MEASURES

Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review.

RESULTS

Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds.

CONCLUSIONS AND RELEVANCE

Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

KNOWLEDGE DRIVEN BINNING AND PHEWAS ANALYSIS IN MARSHFIELD PERSONALIZED MEDICINE RESEARCH PROJECT USING BIOBIN

Next-generation sequencing technology has presented an opportunity for rare variant discovery and association of these variants with disease. To address the challenges of rare variant analysis, multiple statistical methods have been developed for combining rare variants to increase statistical power for detecting associations. BioBin is an automated tool that expands on collapsing/binning methods by performing multi-level variant aggregation with a flexible, biologically informed binning strategy using an internal biorepository, the Library of Knowledge (LOKI). The databases within LOKI provide variant details, regional annotations and pathway interactions which can be used to generate bins of biologically-related variants, thereby increasing the power of any subsequent statistical test. In this study, we expand the framework of BioBin to incorporate statistical tests, including a dispersion-based test, SKAT, thereby providing the option of performing a unified collapsing and statistical rare variant analysis in one tool. Extensive simulation studies performed on gene-coding regions showed a Bin-KAT analysis to have greater power than BioBin-regression in all simulated conditions, including variants influencing the phenotype in the same direction, a scenario where burden tests often retain greater power. The use of Madsen- Browning variant weighting increased power in the burden analysis to that equitable with Bin-KAT; but overall Bin-KAT retained equivalent or higher power under all conditions. Bin-KAT was applied to a study of 82 pharmacogenes sequenced in the Marshfield Personalized Medicine Research Project (PMRP). We looked for association of these genes with 9 different phenotypes extracted from the electronic health record. This study demonstrates that Bin-KAT is a powerful tool for the identification of genes harboring low frequency variants for complex phenotypes.

Personalizing chemotherapy dosing using pharmacological methods

PURPOSE

Given the toxic nature and narrow therapeutic index of traditional chemotherapeutics, better methods of dose and therapy selection are critical. Pharmacological methods, including pharmacogenomics and pharmacokinetics, offer a practical method to enrich drug exposure, reduce toxicity, and improve quality of life for patients.

METHODS

PubMed and key abstracts from the American Society of Clinical Oncology (ASCO) and American Association for Cancer Research (AACR) were searched until July 2015 for clinical data relating to pharmacogenomic- and/or pharmacokinetic-guided dosing of anticancer drugs.

RESULTS

Based on the results returned from a thorough search of the literature and the plausibility of utilizing pharmacogenomic and/or pharmacokinetic methods to personalize chemotherapy dosing, we identified several chemotherapeutic agents with the potential for therapy individualization. We highlight the available data, clinical validity, and utility of using pharmacogenomics to personalize therapy for tamoxifen, 5-fluorouracil, mercaptopurine, and irinotecan, in addition to using pharmacokinetics to personalize dosing for 5-fluorouracil, busulfan, methotrexate, taxanes, and topotecan.

CONCLUSION

A concerted effort should be made by researchers to further elucidate the role of pharmacological methods in personalizing chemotherapy dosing to optimize the risk-benefit profile. Clinicians should be aware of the clinical validity, utility, and availability of pharmacogenomic- and pharmacokinetic-guided therapies in clinical practice, to ultimately allow optimal dosing for each and every cancer patient.

A GWAS Study on Liver Function Test Using eMERGE Network Participants

Introduction

Liver enzyme levels and total serum bilirubin are under genetic control and in recent years genome-wide population-based association studies have identified different susceptibility loci for these traits. We conducted a genome-wide association study in European ancestry participants from the Electronic Medical Records and Genomics (eMERGE) Network dataset of patient medical records with available genotyping data in order to identify genetic contributors to variability in serum bilirubin levels and other liver function tests and to compare the effects between adult and pediatric populations.

Methods

The process of whole genome imputation of eMERGE samples with standard quality control measures have been described previously. After removing missing data and outliers based on principal components (PC) analyses, 3294 samples from European ancestry were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and total serum bilirubin and other liver function tests was tested using linear regression, adjusting for age, gender, site, platform and ancestry principal components (PC).

Results

Consistent with previous results, a strong association signal has been detected for UGT1A gene cluster (best SNP rs887829, beta = 0.15, p = 1.30x10^-118) for total serum bilirubin level. Indeed, in this region more than 176 SNPs (or indels) had p<10⁻⁸ spanning 150Kb on the long arm of chromosome 2q37.1. In addition, we found a similar level of magnitude in a pediatric group (p = 8.26x10^-47, beta = 0.17). Further imputation using sequencing data as a reference panel revealed association of other markers including known TA7 repeat indels (rs8175347) (p = 9.78x10^-117) and rs111741722 (p = 5.41x10^-119) which were in proxy (r2 = 0.99) with rs887829. Among rare variants, two Asian subjects homozygous for coding SNP rs4148323 (G71R) were identified. Additional known effects for total serum bilirubin were also confirmed including organic anion transporters SLCO1B1-SLCO1B3, TDRP and ZMYND8 at FDR<0.05 with no gene-gene interaction effects. Phenome-wide association studies (PheWAS) suggest a protective effect of TA7 repeat against cerebrovascular disease in an adult cohort (OR = 0.75, p = 0.0008). Among other liver function tests, we also confirmed the previous effect of the ABO blood group locus for variation in serum alkaline phosphatase (rs579459, p = 9.44x10^-15).

Conclusions

Taken together, our data present interesting findings with strong confirmation of previous effects by simply using the eMERGE electronic health record phenotyping. In addition, our findings indicate that similar to the adult population, the UGT1A1 is the main locus responsible for normal variation of serum bilirubin in pediatric populations.

Practical considerations in genomic decision support: The eMERGE experience

BACKGROUND

Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more.

METHODS

In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered.

RESULTS

Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months.

CONCLUSIONS

These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.

A conceptual model for translating omic data into clinical action

Genomic, proteomic, epigenomic, and other “omic” data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requiring innovative approaches to translate such data into patient care. Here, we outline a conceptual model for the application of omic data in the clinical context, called “the omic funnel.” This model parallels the classic “Data, Information, Knowledge, Wisdom pyramid” and adds context for how to move between each successive layer. Its goal is to allow informaticians, researchers, and clinicians to approach the problem of translating omic data from bench to bedside, by using discrete steps with clearly defined needs. Such an approach can facilitate the development of modular and interoperable software that can bring precision medicine into widespread practice.

Genotype-based clinical trials in cardiovascular disease

Consensus practice guidelines and the implementation of clinical therapeutic advances are usually based on the results of large, randomized clinical trials (RCTs). However, RCTs generally inform us on an average treatment effect for a presumably homogeneous population, but therapeutic interventions rarely benefit the entire population targeted. Indeed, multiple RCTs have demonstrated that interindividual variability exists both in drug response and in the development of adverse effects. The field of pharmacogenomics promises to deliver the right drug to the right patient. Substantial progress has been made in this field, with advances in technology, statistical and computational methods, and the use of cell and animal model systems. However, clinical implementation of pharmacogenetic principles has been difficult because RCTs demonstrating benefit are lacking. For patients, the potential benefits of performing such trials include the individualization of therapy to maximize efficacy and minimize adverse effects. These trials would also enable investigators to reduce sample size and hence contain costs for trial sponsors. Multiple ethical, legal, and practical issues need to be considered for the conduct of genotype-based RCTs. Whether pre-emptive genotyping embedded in electronic health records will preclude the need for performing genotype-based RCTs remains to be seen.

Universal versus genotype-guided use of direct oral anticoagulants in atrial fibrillation patients: a decision analysis

AIM

This study aims to compare clinical and economic outcomes of CYP2C9 and VKORC1 genotype-guided (PG-DOAC) versus universal use of direct oral anticoagulant (DOAC) for stroke prevention in patients with atrial fibrillation (AF).

METHODS

Outcomes of oral anticoagulation therapy were simulated using life-long Markov modeling. In PG-DOAC, patients with genotype of high or low warfarin sensitivity were treated with DOAC, and patients with normal warfarin sensitivity genotype received warfarin.

RESULTS

Expected quality-adjusted life-years (QALYs) and cost of DOAC were higher than PG-DOAC. Incremental cost per QALY (ICER) of DOAC versus PG-DOAC was 314,129 USD/QALY, exceeding willingness-to-pay threshold (50,000 USD/QALY).

CONCLUSION

Using individual genotype to guide the use of DOAC versus warfarin appears to be the preferred strategy.

Cardiovascular pharmacogenomics: current status and future directions

Drugs are widely used and highly effective in the treatment of heart disease. Nevertheless, in some instances, even drugs effective in a population display lack of efficacy or adverse drug reactions in individual patients, often in an apparently unpredictable fashion. This review summarizes the genomic factors now known to influence variability in responses to widely used cardiovascular drugs such as clopidogrel, warfarin, heparin and statins. Genomic approaches being used to discover new pathways in common cardiovascular diseases and thus potential new targets for drug development are described. Finally, the way in which this new information is likely to be used in an electronic medical record environment is discussed.

The pharmacogenetic control of antiplatelet response: candidate genes and CYP2C19

INTRODUCTION

Aspirin, clopidogrel, prasugrel and ticagrelor are antiplatelet agents for the prevention of ischemic events in patients with acute coronary syndromes (ACS), percutaneous coronary intervention (PCI) and other indications. Variability in response is observed to different degrees with these agents, which can translate to increased risks for adverse cardiovascular events. As such, potential pharmacogenetic determinants of antiplatelet pharmacokinetics, pharmacodynamics and clinical outcomes have been actively studied.

AREAS COVERED

This article provides an overview of the available antiplatelet pharmacogenetics literature. Evidence supporting the significance of candidate genes and their potential influence on antiplatelet response and clinical outcomes are summarized and evaluated. Additional focus is directed at CYP2C19 and clopidogrel response, including the availability of clinical testing and genotype-directed antiplatelet therapy.

EXPERT OPINION

The reported aspirin response candidate genes have not been adequately replicated and few candidate genes have thus far been implicated in prasugrel or ticagrelor response. However, abundant data support the clinical validity of CYP2C19 and clopidogrel response variability among ACS/PCI patients. Although limited prospective trial data are available to support the utility of routine CYP2C19 testing, the increased risks for reduced clopidogrel efficacy among ACS/PCI patients that carry CYP2C19 loss-of-function alleles should be considered when genotype results are available.

Prospective participant selection and ranking to maximize actionable pharmacogenetic variants and discovery in the eMERGE Network

Background

In an effort to return actionable results from variant data to electronic health records (EHRs), participants in the Electronic Medical Records and Genomics (eMERGE) Network are being sequenced with the targeted Pharmacogenomics Research Network sequence platform (PGRNseq). This cost-effective, highly-scalable, and highly-accurate platform was created to explore rare variation in 84 key pharmacogenetic genes with strong drug phenotype associations.

Methods

To return Clinical Laboratory Improvement Amendments (CLIA) results to our participants at the Group Health Cooperative, we sequenced the DNA of 900 participants (61 % female) with non-CLIA biobanked samples. We then selected 450 of those to be re-consented, to redraw blood, and ultimately to validate CLIA variants in anticipation of returning the results to the participant and EHR. These 450 were selected using an algorithm we designed to harness data from self-reported race, diagnosis and procedure codes, medical notes, laboratory results, and variant-level bioinformatics to ensure selection of an informative sample. We annotated the multi-sample variant call format by a combination of SeattleSeq and SnpEff tools, with additional custom variables including evidence from ClinVar, OMIM, HGMD, and prior clinical associations.

Results

We focused our analyses on 27 actionable genes, largely driven by the Clinical Pharmacogenetics Implementation Consortium. We derived a ranking system based on the total number of coding variants per participant (75.2±14.7), and the number of coding variants with high or moderate impact (11.5±3.9). Notably, we identified 11 stop-gained (1 %) and 519 missense (20 %) variants out of a total of 1785 in these 27 genes. Finally, we prioritized variants to be returned to the EHR with prior clinical evidence of pathogenicity or annotated as stop-gain for the following genes: CACNA1S and RYR1 (malignant hyperthermia); SCN5A, KCNH2, and RYR2 (arrhythmia); and LDLR (high cholesterol).

Conclusions

The incorporation of genetics into the EHR for clinical decision support is a complex undertaking for many reasons including lack of prior consent for return of results, lack of biospecimens collected in a CLIA environment, and EHR integration. Our study design accounts for these hurdles and is an example of a pilot system that can be utilized before expanding to an entire health system.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0181-z) contains supplementary material, which is available to authorized users.

Extracting research-quality phenotypes from electronic health records to support precision medicine

The convergence of two rapidly developing technologies - high-throughput genotyping and electronic health records (EHRs) - gives scientists an unprecedented opportunity to utilize routine healthcare data to accelerate genomic discovery. Institutions and healthcare systems have been building EHR-linked DNA biobanks to enable such a vision. However, the precise extraction of detailed disease and drug-response phenotype information hidden in EHRs is not an easy task. EHR-based studies have successfully replicated known associations, made new discoveries for diseases and drug response traits, rapidly contributed cases and controls to large meta-analyses, and demonstrated the potential of EHRs for broad-based phenome-wide association studies. In this review, we summarize the advantages and challenges of repurposing EHR data for genetic research. We also highlight recent notable studies and novel approaches to provide an overview of advanced EHR-based phenotyping.

Perspectives on genetic and genomic technologies in an academic medical center: the duke experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice.

METHODS

We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers' use of genetic and genomic testing options and indications in clinical practice, providers' awareness of pharmacogenetic applications, and providers' opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships.

Whole genome sequencing in pharmacogenomics

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

Review of pharmacoeconomic evaluation of genotype-guided antiplatelet therapy

INTRODUCTION

Clopidogrel is an antiplatelet agent widely prescribed for acute coronary syndrome (ACS), and it is activated by the CYP enzyme system to active metabolite. CYP2C19 loss-of-function (LOF) allele(s) affect the responsiveness of clopidogrel, but not the new antiplatelet agents (prasugrel and ticagrelor). We reviewed the pharmacoeconomic studies on genotype-guided use of new antiplatelet agents.

AREAS COVERED

A literature search was conducted between the period of 2000 and 2014. Seven studies including cost-effectiveness and risk-benefit analyses of CYP2C19 genotype-guided antiplatelet therapy in ACS patients were reviewed. Genotype-guided prasugrel was found to be cost-effective when compared with universal antiplatelet therapy in four studies. Three studies showed genotype-guided ticagrelor to be cost-effective in ACS patients with percutaneous coronary intervention (PCI), and universal ticagrelor to be cost-effective in ACS patients. Drug cost of antiplatelet agents and relative risk of the new antiplatelet versus clopidogrel for clinical events were common influential factors of cost-effectiveness analyses.

EXPERT OPINION

All studies in the present review focused on selecting antiplatelet agents for carriers of CYP2C19 LOF allele(s). Cost-effectiveness of genotype-guided use of antiplatelets was demonstrated in high-risk ACS patients.

Clinician Perspectives on Using Pharmacogenomics in Clinical Practice

AIM

To describe the knowledge and attitudes of clinicians participating in a large pharmacogenomics implementation program.

MATERIALS & METHODS

Semi-structured interviews with 15 physicians and nurse practitioners were conducted.

RESULTS

Three categories of themes were identified: preparation and knowledge, pharmacogenomics usage in practice, and future management of genomic variants. Providers expressed an inability to keep up with the rapid pace of evidence generation and indicated strong support for clinical decision support to assist with genotype-tailored therapies. Concerns raised by clinicians included effectively communicating results, long-term responsibility for actionable results and hand-offs with providers outside the implementation program.

CONCLUSIONS

Clinicians identified their own knowledge deficits, workflow integration, and longitudinal responsibility as challenges to successful usage of pharmacogenomics in clinical practice.

eMERGEing progress in genomics-the first seven years

The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.

Performance of exome sequencing for pharmacogenomics

AIM

We present the potential false-negative rate of exome sequencing for the detection of pharmacogenomic variants.

MATERIALS & METHODS

Depth of coverage of 1928 pharmacogenomically relevant variant positions was ascertained from 62 exome-sequenced samples.

RESULTS

Approximately 14% of the 1928 variant locations examined had inadequate depth of coverage (<20x). The variants with inadequate coverage were predominantly located outside of protein-coding portions and included some clinically relevant variant positions, such as the warfarin VKORC1 variant.

CONCLUSION

While the use of exome sequencing is becoming more prevalent in fundamental research, clinical trials and clinical use; there is a possibility of false-negative results. The possible quality issues such as false-negative rate should be considered with the use of exome sequencing.