Understanding the use of observational and randomized data in cardiovascular medicine

The availability of large datasets from multiple sources [e.g. registries, biobanks, electronic health records (EHRs), claims or billing databases, implantable devices, wearable sensors, and mobile apps], coupled with advances in computing and analytic technologies, have provided new opportunities for conducting innovative health research. Equally, improved digital access to health information has facilitated the conduct of efficient randomized controlled trials (RCTs) upon which clinical management decisions can be based, for instance, by permitting the identification of eligible patients for recruitment and/or linkage for follow-up via their EHRs. Given these advances in cardiovascular data science and the complexities they behold, it is important that health professionals have clarity on the appropriate use and interpretation of observational, so-called 'real-world', and randomized data in cardiovascular medicine. The Cardiovascular Roundtable of the European Society of Cardiology (ESC) held a workshop to explore the future of RCTs and the current and emerging opportunities for gathering and exploiting complex observational datasets in cardiovascular research. The aim of this article is to provide a perspective on the appropriate use of randomized and observational data and to outline the ESC plans for supporting the collection and availability of clinical data to monitor and improve the quality of care of patients with cardiovascular disease in Europe and provide an infrastructure for undertaking pragmatic RCTs. Moreover, the ESC continues to campaign for greater engagement amongst regulators, industry, patients, and health professionals in the development and application of a more efficient regulatory framework that is able to take maximal advantage of new opportunities for improving the design and efficiency of observational studies and RCT in patients with cardiovascular disease.

Genomewide Association Study of Platelet Reactivity and Cardiovascular Response in Patients Treated With Clopidogrel: A Study by the International Clopidogrel Pharmacogenomics Consortium

Antiplatelet response to clopidogrel shows wide variation, and poor response is correlated with adverse clinical outcomes. CYP2C19 loss‐of‐function alleles play an important role in this response, but account for only a small proportion of variability in response to clopidogrel. An aim of the International Clopidogrel Pharmacogenomics Consortium (ICPC) is to identify other genetic determinants of clopidogrel pharmacodynamics and clinical response. A genomewide association study (GWAS) was performed using DNA from 2,750 European ancestry individuals, using adenosine diphosphate‐induced platelet reactivity and major cardiovascular and cerebrovascular events as outcome parameters. GWAS for platelet reactivity revealed a strong signal for CYP2C19*2 (P value = 1.67e−33). After correction for CYP2C19*2 no other single‐nucleotide polymorphism reached genomewide significance. GWAS for a combined clinical end point of cardiovascular death, myocardial infarction, or stroke (5.0% event rate), or a combined end point of cardiovascular death or myocardial infarction (4.7% event rate) showed no significant results, although in coronary artery disease, percutaneous coronary intervention, and acute coronary syndrome subgroups, mutations in SCOS5P1, CDC42BPA, and CTRAC1 showed genomewide significance (lowest P values: 1.07e−09, 4.53e−08, and 2.60e−10, respectively). CYP2C19*2 is the strongest genetic determinant of on‐clopidogrel platelet reactivity. We identified three novel associations in clinical outcome subgroups, suggestive for each of these outcomes.

High-Throughput Reclassification of SCN5A Variants

Partial or complete loss-of-function variants in SCN5A are the most common genetic cause of the arrhythmia disorder Brugada syndrome (BrS1). However, the pathogenicity of SCN5A variants is often unknown or disputed; 80% of the 1,390 SCN5A missense variants observed in at least one individual to date are variants of uncertain significance (VUSs). The designation of VUS is a barrier to the use of sequence data in clinical care. We selected 83 variants: 10 previously studied control variants, 10 suspected benign variants, and 63 suspected Brugada syndrome-associated variants, selected on the basis of their frequency in the general population and in individuals with Brugada syndrome. We used high-throughput automated patch clamping to study the function of the 83 variants, with the goal of reclassifying variants with functional data. The ten previously studied controls had functional properties concordant with published manual patch clamp data. All 10 suspected benign variants had wild-type-like function. 22 suspected BrS variants had loss of channel function (<10% normalized peak current) and 22 variants had partial loss of function (10%-50% normalized peak current). The previously unstudied variants were initially classified as likely benign (n = 2), likely pathogenic (n = 10), or VUSs (n = 61). After the patch clamp studies, 16 variants were benign/likely benign, 45 were pathogenic/likely pathogenic, and only 12 were still VUSs. Structural modeling identified likely mechanisms for loss of function including altered thermostability and disruptions to alpha helices, disulfide bonds, or the permeation pore. High-throughput patch clamping enabled reclassification of the majority of tested VUSs in SCN5A.

Variants in ADRB1 and CYP2C9: Association with Response to Atenolol and Losartan in Marfan Syndrome

OBJECTIVE

To test whether variants in ADRB1 and CYP2C9 genes identify subgroups of individuals with differential response to treatment for Marfan syndrome through analysis of data from a large, randomized trial.

STUDY DESIGN

In a subset of 250 white, non-Hispanic participants with Marfan syndrome in a prior randomized trial of atenolol vs losartan, the common variants rs1801252 and rs1801253 in ADRB1 and rs1799853 and rs1057910 in CYP2C9 were analyzed. The primary outcome was baseline-adjusted annual rate of change in the maximum aortic root diameter z-score over 3 years, assessed using mixed effects models.

RESULTS

Among 122 atenolol-assigned participants, the 70 with rs1801253 CC genotype had greater rate of improvement in aortic root z-score compared with 52 participants with CG or GG genotypes (Time × Genotype interaction P = .005, mean annual z-score change ± SE -0.20 ± 0.03 vs -0.09 ± 0.03). Among participants with the CC genotype in both treatment arms, those assigned to atenolol had greater rate of improvement compared with the 71 of the 121 assigned to losartan (interaction P = .002; -0.20 ± 0.02 vs -0.07 ± 0.02; P < .001). There were no differences in atenolol response by rs1801252 genotype or in losartan response by CYP2C9 metabolizer status.

CONCLUSIONS

In this exploratory study, ADRB1-rs1801253 was associated with atenolol response in children and young adults with Marfan syndrome. If these findings are confirmed in future studies, ADRB1 genotyping has the potential to guide therapy by identifying those who are likely to have greater therapeutic response to atenolol than losartan.

How Will Genetics Inform the Clinical Care of Atrial Fibrillation?

Susceptibility to atrial fibrillation (AF) is determined by well-recognized risk factors such as diabetes mellitus or hypertension, emerging risk factors such as sleep apnea or inflammation, and increasingly well-defined genetic variants. As discussed in detail in a companion article in this series, studies in families and in large populations have identified multiple genetic loci, specific genes, and specific variants increasing susceptibility to AF. Since it is becoming increasingly inexpensive to obtain genotype data and indeed whole genome sequence data, the question then becomes to define whether using emerging new genetics knowledge can improve care for patients both before and after development of AF. Examples of improvements in care could include identifying patients at increased risk for AF (and thus deploying increased surveillance or even low-risk preventive therapies should these be available), identifying patient subsets in whom specific therapies are likely to be effective or ineffective or in whom the driving biology could motivate the development of new mechanism-based therapies or identifying an underlying susceptibility to comorbid cardiovascular disease. While current guidelines for the care of patients with AF do not recommend routine genetic testing, this rapidly increasing knowledge base suggests that testing may now or soon have a place in the management of select patients. The opportunity is to generate, validate, and deploy clinical predictors (including family history) of AF risk, to assess the utility of incorporating genomic variants into those predictors, and to identify and validate interventions such as wearable or implantable device-based monitoring ultimately to intervene in patients with AF before they present with catastrophic complications like heart failure or stroke.

High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1

BACKGROUND

KCHN2 encodes the K_V11.1 potassium channel responsible for I_Kr, a major repolarization current during the cardiomyocyte action potential. Variants in KCNH2 that lead to decreased I_Kr have been associated with long QT syndrome type 2 (LQT2). The mechanism of LQT2 is most often induced loss of K_V11.1 trafficking to the cell surface. Accurately discriminating between variants with normal and abnormal trafficking would aid in understanding the deleterious nature of these variants; however, the volume of reported nonsynonymous KCNH2 variants precludes the use of conventional methods for functional study.

OBJECTIVE

The purpose of this study was to report a high-throughput, multiplexed screening method for KCNH2 genetic variants capable of measuring the cell surface abundance of hundreds of missense variants in the resulting K_V11.1 channel.

METHODS

We developed a method to quantitate K_V11.1 variant trafficking on a pilot region of 11 residues in the S5 helix.

RESULTS

We generated trafficking scores for 220 of 231 missense variants in the pilot region. For 5 of 5 variants, high-throughput trafficking scores validated when tested in single variant flow cytometry and confocal microscopy experiments. We further explored these results with planar patch electrophysiology and found that loss-of-trafficking variants do not produce I_Kr. Conversely, but expectedly, some variants that traffic normally were still functionally compromised.

CONCLUSION

We describe a new method for detecting K_V11.1 trafficking-deficient variants in a multiplexed assay. This new method accurately generated trafficking data for variants in K_V11.1 and is extendable both to all residues in K_V11.1 and to other cell surface proteins.

Leveraging Human Genetics to Identify Safety Signals Prior to Drug Marketing Approval and Clinical Use

INTRODUCTION

When a new drug or biologic product enters the market, its full spectrum of side effects is not yet fully understood, as use in the real world often uncovers nuances not suggested within the relatively narrow confines of preapproval preclinical and trial work.

OBJECTIVE

We describe a new, phenome-wide association study (PheWAS)- and evidence-based approach for detection of potential adverse drug effects.

METHODS

We leveraged our established platform, which integrates human genetic data with associated phenotypes in electronic health records from 29,722 patients of European ancestry, to identify gene-phenotype associations that may represent known safety issues. We examined PheWAS data and the published literature for 16 genes, each of which encodes a protein targeted by at least one drug or biologic product.

RESULTS

Initial data demonstrated that our novel approach (safety ascertainment using PheWAS [SA-PheWAS]) can replicate published safety information across multiple drug classes, with validated findings for 13 of 16 gene-drug class pairs.

CONCLUSIONS

By connecting and integrating in vivo and in silico data, SA-PheWAS offers an opportunity to supplement current methods for predicting or confirming safety signals associated with therapeutic agents.

A Bayesian method to estimate variant-induced disease penetrance

A major challenge emerging in genomic medicine is how to assess best disease risk from rare or novel variants found in disease-related genes. The expanding volume of data generated by very large phenotyping efforts coupled to DNA sequence data presents an opportunity to reinterpret genetic liability of disease risk. Here we propose a framework to estimate the probability of disease given the presence of a genetic variant conditioned on features of that variant. We refer to this as the penetrance, the fraction of all variant heterozygotes that will present with disease. We demonstrate this methodology using a well-established disease-gene pair, the cardiac sodium channel gene SCN5A and the heart arrhythmia Brugada syndrome. From a review of 756 publications, we developed a pattern mixture algorithm, based on a Bayesian Beta-Binomial model, to generate SCN5A penetrance probabilities for the Brugada syndrome conditioned on variant-specific attributes. These probabilities are determined from variant-specific features (e.g. function, structural context, and sequence conservation) and from observations of affected and unaffected heterozygotes. Variant functional perturbation and structural context prove most predictive of Brugada syndrome penetrance.

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome

Supplemental Digital Content is available in the text.

Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility.

Cardiovascular Toxicities Associated With Ibrutinib

BACKGROUND

Ibrutinib has revolutionized treatment for several B-cell malignancies. However, a recent clinical trial where ibrutinib was used in a front-line setting showed increased mortality during treatment compared with conventional chemotherapy. Cardiovascular toxicities were suspected as the culprit but not directly assessed in the study.

OBJECTIVES

The purpose of this study was to identify and characterize cardiovascular adverse drug reactions (CV-ADR) associated with ibrutinib.

METHODS

This study utilized VigiBase (International pharmacovigilance database) and performed a disproportionality analysis using reporting odds ratios (ROR) and information component (IC) to determine whether CV-ADR and CV-ADR deaths were associated with ibrutinib. IC compares observed and expected values to find associations between drugs and adverse drug reactions using disproportionate Bayesian-reporting; IC₀₂₅ (lower end of the IC 95% credibility interval) >0 is significant.

RESULTS

This study identified 303 ibrutinib-associated cardiovascular deaths. Ibrutinib was associated with higher reporting of supraventricular arrhythmias (SVAs) (ROR: 23.1; 95% confidence interval: 21.6 to 24.7; p < 0.0001; IC₀₂₅: 3.97), central nervous system (CNS) hemorrhagic events (ROR: 3.7; 95% confidence interval: 3.4 to 4.1; p < 0.0001; IC₀₂₅: 1.63), heart failure (ROR: 3.5; 95% confidence interval: 3.1 to 3.8; p < 0.0001; IC₀₂₅: 1.46), ventricular arrhythmias (ROR: 4.7; 95% confidence interval: 3.7 to 5.9; p < 0.0001; IC₀₂₅: 0.96), conduction disorders (ROR: 3.5; 95% confidence interval: 2.7 to 4.6; p < 0.0001; IC₀₂₅: 0.76), CNS ischemic events (ROR: 2.2; 95% confidence interval: 2.0 to 2.5; p < 0.0001; IC₀₂₅: 0.73), and hypertension (ROR: 1.7; 95% confidence interval: 1.5 to 1.9; p < 0.0001; IC₀₂₅: 0.4). CV-ADR often occurred early after ibrutinib administration. Importantly, CV-ADR were associated with fatalities that ranged from ∼10% (SVAs and ventricular arrhythmias) to ∼20% (CNS events, heart failure, and conduction disorders). Ibrutinib-associated SVA portends poor prognosis when CNS events occur concomitantly, with 28.8% deaths (15 of 52 cases).

CONCLUSIONS

Severe and occasionally fatal cardiac events occur in patients exposed to ibrutinib. These events should be considered in patient care and in clinical trial designs. (Evaluation of Reporting of Cardio-vascular Adverse Events With Antineoplastic and Immunomodulating Agents [EROCA]; NCT03530215).

A current understanding of drug-induced QT prolongation and its implications for anticancer therapy

The QT interval, a global index of ventricular repolarization, varies among individuals and is influenced by diverse physiologic and pathophysiologic stimuli such as gender, age, heart rate, electrolyte concentrations, concomitant cardiac disease, and other diseases such as diabetes. Many drugs produce a small but reproducible effect on QT interval but in rare instances this is exaggerated and marked QT prolongation can provoke the polymorphic ventricular tachycardia 'torsades de pointes', which can cause syncope or sudden cardiac death. The generally accepted common mechanism whereby drugs prolong QT is block of a key repolarizing potassium current in heart, IKr, generated by expression of KCNH2, also known as HERG. Thus, evaluation of the potential that a new drug entity may cause torsades de pointes has relied on exposure of normal volunteers or patients to drug at usual and high concentrations, and on assessment of IKr block in vitro. More recent work, focusing on anticancer drugs with QT prolonging liability, is defining new pathways whereby drugs can prolong QT. Notably, the in vitro effects of some tyrosine kinase inhibitors to prolong cardiac action potentials (the cellular correlate of QT) can be rescued by intracellular phosphatidylinositol 3,4,5-trisphosphate, the downstream effector of phosphoinositide 3-kinase. This finding supports a role for inhibition of this enzyme, either directly or by inhibition of upstream kinases, to prolong QT through mechanisms that are being worked out, but include enhanced inward 'late' sodium current during the plateau of the action potential. The definition of non-IKr-dependent pathways to QT prolongation will be important for assessing risk, not only with anticancer therapies but also with other QT prolonging drugs and for generating a refined understanding how variable activity of intracellular signalling systems can modulate QT and associated arrhythmia risk.

The polygenic architecture of left ventricular mass mirrors the clinical epidemiology

Left ventricular (LV) mass is a prognostic biomarker for incident heart disease and all-cause mortality. Large-scale genome-wide association studies have identified few SNPs associated with LV mass. We hypothesized that a polygenic discovery approach using LV mass measurements made in a clinical population would identify risk factors and diseases associated with adverse LV remodeling. We developed a polygenic single nucleotide polymorphism-based predictor of LV mass in 7,601 individuals with LV mass measurements made during routine clinical care. We tested for associations between this predictor and 894 clinical diagnoses measured in 58,838 unrelated genotyped individuals. There were 29 clinical phenotypes associated with the LV mass genetic predictor at FDR q < 0.05. Genetically predicted higher LV mass was associated with modifiable cardiac risk factors, diagnoses related to organ dysfunction and conditions associated with abnormal cardiac structure including heart failure and atrial fibrillation. Secondary analyses using polygenic predictors confirmed a significant association between higher LV mass and body mass index and, in men, associations with coronary atherosclerosis and systolic blood pressure. In summary, these analyses show that LV mass-associated genetic variability associates with diagnoses of cardiac diseases and with modifiable risk factors which contribute to these diseases.

Atropine-induced sinus tachycardia protects against exercise-induced ventricular arrhythmias in patients with catecholaminergic polymorphic ventricular tachycardia

AIMS

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited arrhythmia syndrome characterized by exercise-induced ventricular arrhythmias, sudden death, and sinus bradycardia. Elevating supraventricular rates with pacing or atropine protects against catecholaminergic ventricular arrhythmias in a CPVT mouse model. We tested the hypothesis that increasing sinus heart rate (HR) with atropine prevents exercise-induced ventricular arrhythmias in CPVT patients.

METHODS AND RESULTS

We performed a prospective open-label trial of atropine prior to exercise in CPVT patients (clinicaltrials.gov NCT02927223). Subjects performed a baseline standard Bruce treadmill test on their usual medical regimen. After a 2-h recovery period, subjects performed a second exercise test after parasympathetic block with atropine (0.04 mg/kg intravenous). The primary outcome measure was the total number of ventricular ectopic beats during exercise. All six subjects (5 men, 22-57 years old) completed the study with no adverse events. Atropine increased resting sinus rate from median 52 b.p.m. (range 52-64) to 98 b.p.m. (84-119), P = 0.02. Peak HRs (149 b.p.m., range 136-181 vs. 149 b.p.m., range 127-182, P = 0.46) and exercise duration (612 s, range 544-733 vs. 584 s, range 543-742, P = 0.22) were not statistically different. All subjects had ventricular ectopy during the baseline exercise test. Atropine pre-treatment significantly decreased the median number of ventricular ectopic beats from 46 (6-192) to 0 (0-29), P = 0.026; ventricular ectopy was completely eliminated in 4/6 subjects.

CONCLUSION

Elevating sinus rates with atropine reduces or eliminates exercise-induced ventricular ectopy in patients with CPVT. Increasing supraventricular rates may represent a novel therapeutic strategy in CPVT.

Accelerating Biomarker Discovery Through Electronic Health Records, Automated Biobanking, and Proteomics

BACKGROUND

Circulating biomarkers can facilitate diagnosis and risk stratification for complex conditions such as heart failure (HF). Newer molecular platforms can accelerate biomarker discovery, but they require significant resources for data and sample acquisition.

OBJECTIVES

The purpose of this study was to test a pragmatic biomarker discovery strategy integrating automated clinical biobanking with proteomics.

METHODS

Using the electronic health record, the authors identified patients with and without HF, retrieved their discarded plasma samples, and screened these specimens using a DNA aptamer-based proteomic platform (1,129 proteins). Candidate biomarkers were validated in 3 different prospective cohorts.

RESULTS

In an automated manner, plasma samples from 1,315 patients (31% with HF) were collected. Proteomic analysis of a 96-patient subset identified 9 candidate biomarkers (p < 4.42 × 10^-5). Two proteins, angiopoietin-2 and thrombospondin-2, were associated with HF in 3 separate validation cohorts. In an emergency department-based registry of 852 dyspneic patients, the 2 biomarkers improved discrimination of acute HF compared with a clinical score (p < 0.0001) or clinical score plus B-type natriuretic peptide (p = 0.02). In a community-based cohort (n = 768), both biomarkers predicted incident HF independent of traditional risk factors and N-terminal pro-B-type natriuretic peptide (hazard ratio per SD increment: 1.35 [95% confidence interval: 1.14 to 1.61; p = 0.0007] for angiopoietin-2, and 1.37 [95% confidence interval: 1.06 to 1.79; p = 0.02] for thrombospondin-2). Among 30 advanced HF patients, concentrations of both biomarkers declined (80% to 84%) following cardiac transplant (p < 0.001 for both).

CONCLUSIONS

A novel strategy integrating electronic health records, discarded clinical specimens, and proteomics identified 2 biomarkers that robustly predict HF across diverse clinical settings. This approach could accelerate biomarker discovery for many diseases.

Androgenic effects on ventricular repolarization: A translational study from the international pharmacovigilance database to iPSC-cardiomyocytes

BACKGROUND

Male hypogonadism, arising from a range of etiologies including androgen-deprivation therapies (ADTs), has been reported as a risk factor for acquired long-QT syndrome (aLQTS) and torsades de pointes (TdP). A full description of the clinical features of aLQTS associated with ADT and of underlying mechanisms is lacking.

METHODS

We searched the international pharmacovigilance database VigiBase for men (n=6 560 565 individual case safety reports) presenting with aLQTS, TdP, or sudden death associated with ADT. In cardiomyocytes derived from induced pluripotent stem cells from men, we studied electrophysiological effects of ADT and dihydrotestosterone.

RESULTS

Among subjects receiving ADT in VigiBase, we identified 184 cases of aLQTS (n=168) and/or TdP (n=68; 11% fatal), and 99 with sudden death. Of the 10 ADT drugs examined, 7 had a disproportional association (reporting odds ratio=1.4-4.7; P<0.05) with aLQTS, TdP, or sudden death. The minimum and median times to sudden death were 0.25 and 92 days, respectively. The androgen receptor antagonist enzalutamide was associated with more deaths (5430/31 896 [17%]; P<0.0001) than other ADT used for prostate cancer (4208/52 089 [8.1%]). In induced pluripotent stem cells, acute and chronic enzalutamide (25μM) significantly prolonged action potential durations (action potential duration at 90% when paced at 0.5Hz; 429.7±27.1 (control) versus 982.4±33.2 (acute, P<0.001) and 1062.3±28.9ms (chronic; P<0.001), and generated afterdepolarizations and/or triggered activity in drug-treated cells (11/20 acutely and 8/15 chronically). Enzalutamide acutely and chronically inhibited delayed rectifier potassium current, and chronically enhanced late sodium current. Dihydrotestosterone (30nM) reversed enzalutamide electrophysiological effects on induced pluripotent stem cells.

CONCLUSION

QT prolongation and TdP are a risk in men receiving enzalutamide and other ADTs.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT03193138.

Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease

IMPORTANCE

Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.

OBJECTIVE

To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.

EXPOSURES

Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.

MAIN OUTCOMES AND MEASURES

Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI).

RESULTS

The study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort.

CONCLUSIONS AND RELEVANCE

In this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.

Genetic Susceptibility for Atrial Fibrillation in Patients Undergoing Atrial Fibrillation Ablation

BACKGROUND

Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF.

METHODS

Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation.

RESULTS

Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger (P<0.001) and had fewer clinical risk factors for AF (P=0.001). Persistent AF (hazard ratio [HR], 1.39 [95% CI, 1.22-1.58]; P<0.001), left atrial size (per cm: HR, 1.32 [95% CI, 1.19-1.46]; P<0.001), and left ventricular ejection fraction (per 10%: HR, 0.88 [95% CI, 0.80-0.97]; P=0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 [95% CI, 0.99-1.18]; P=0.07), which became less significant in multivariable analysis (HR, 1.06 [95% CI, 0.98-1.15]; P=0.13).

CONCLUSIONS

Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.

Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real-World Data From Electronic Health Records

Postmarketing population pharmacokinetic (PK) and pharmacodynamic (PD) studies can be useful to capture patient characteristics affecting PK or PD in real-world settings. These studies require longitudinally measured dose, outcomes, and covariates in large numbers of patients; however, prospective data collection is cost-prohibitive. Electronic health records (EHRs) can be an excellent source for such data, but there are challenges, including accurate ascertainment of drug dose. We developed a standardized system to prepare datasets from EHRs for population PK/PD studies. Our system handles a variety of tasks involving data extraction from clinical text using a natural language processing algorithm, data processing, and data building. Applying this system, we performed a fentanyl population PK analysis, resulting in comparable parameter estimates to a prior study. This new system makes the EHR data extraction and preparation process more efficient and accurate and provides a powerful tool to facilitate postmarketing population PK/PD studies using information available in EHRs.