Search

Heart failure (HF) is a rising global cardiovascular epidemic driven by aging and chronic inflammation. As elderly populations continue to increase, precision treatments for age-related cardiac decline are urgently needed. Here we report that cardiac and blood expression of IGFBP7 is robustly increased in patients with chronic HF and in an HF mouse model. In a pressure overload mouse HF model, Igfbp7 deficiency attenuated cardiac dysfunction by reducing cardiac inflammatory injury, tissue fibrosis and cellular senescence. IGFBP7 promoted cardiac senescence by stimulating IGF-1R/IRS/AKT-dependent suppression of FOXO3a, preventing DNA repair and reactive oxygen species (ROS) detoxification, thereby accelerating the progression of HF. In vivo, AAV9-shRNA-mediated cardiac myocyte Igfbp7 knockdown indicated that myocardial IGFBP7 directly regulates pathological cardiac remodeling. Moreover, antibody-mediated IGFBP7 neutralization in vivo reversed IGFBP7-induced suppression of FOXO3a, restored DNA repair and ROS detoxification signals and attenuated pressure-overload-induced HF in mice. Consequently, selectively targeting IGFBP7-regulated senescence pathways may have broad therapeutic potential for HF.

Aims: In order to understand how sex differences impact the generalizability of randomized clinical trials (RCTs) in patients with heart failure (HF) and reduced ejection fraction (HFrEF), we sought to compare clinical characteristics and clinical outcomes between RCTs and HF observational registries stratified by sex. Methods and results: Data from two HF registries and five HFrEF RCTs were used to create three subpopulations: one RCT population (n = 16 917; 21.7% females), registry patients eligible for RCT inclusion (n = 26 104; 31.8% females), and registry patients ineligible for RCT inclusion (n = 20 810; 30.2% females). Clinical endpoints included all-cause mortality, cardiovascular mortality, and first HF hospitalization at 1 year. Males and females were equally eligible for trial enrolment (56.9% of females and 55.1% of males in the registries). One-year mortality rates were 5.6%, 14.0%, and 28.6% for females and 6.9%, 10.7%, and 24.6% for males in the RCT, RCT-eligible, and RCT-ineligible groups, respectively. After adjusting for 11 HF prognostic variables, RCT females showed higher survival compared to RCT-eligible females (standardized mortality ratio [SMR] 0.72; 95% confidence interval [CI] 0.62–0.83), while RCT males showed higher adjusted mortality rates compared to RCT-eligible males (SMR 1.16; 95% CI 1.09–1.24). Similar results were also found for cardiovascular mortality (SMR 0.89; 95% CI 0.76–1.03 for females, SMR 1.43; 95% CI 1.33–1.53 for males). Conclusion: Generalizability of HFrEF RCTs differed substantially between the sexes, with females having lower trial participation and female trial participants having lower mortality rates compared to similar females in the registries, while males had higher than expected cardiovascular mortality rates in RCTs compared to similar males in registries.

Little is known about the mechanisms of aging on vascular beds and its relationship with tetra and di-hydrobiopterin (BH4 and BH2) levels. This observational clinical study analyzed the impact of aging on plasma and platelet biopterins, cutaneous blood flow (CBF), and coronary flow reserve (CFR) in healthy adults. The study enrolled healthy adults in 3 age groups: 18–30, 50–59, and 60–70 years (n = 25/group). Biopterins were assessed by LC-MS/MS using newly defined pre-analytical conditions limiting BH4 oxidation and improving long-term stability. CBF was measured by Laser Speckle Contrast Imaging coupled with acetylcholine-iontophoresis and CFR by adenosine stress cardiac magnetic resonance. In healthy adults, aging (60–70 years vs 18–30 years) significantly increased platelet BH2 (+75%, P = 0.033) and BH2 + BH4 (+31%, P = 0.033), and to a lesser extent plasma BH2 (+29%, P = 0.009) without affecting BH4 and BH4/BH2. Simultaneously, CBF was decreased (-23%, P = 0.004) but not CFR, CBF being inversely correlated with platelet BH2 (r = -0.42, P = 0.001) and BH2 + BH4 (r = -0.41, P = 0.002). The proportion of adults with abnormal platelet BH2 increased with age (+28% in 60-70y). These abnormal BH2 levels were significantly associated with reduced CBF and CFR (-16%, P = 0.03 and -26%, P = 0.02). In conclusion, our study showed that age-related peripheral endothelial dysfunction was associated with an increase in circulating BH2 without decreasing BH4, the effect being more marked in platelets, the most relevant blood compartment to assess biopterin bioavailability. Peripheral but not coronary vascular function is progressively impaired with aging in healthy adults. All these findings support biopterins as therapeutic targets to improve vascular function.

Background Heart failure (HF) trials have stringent inclusion and exclusion criteria, but limited data exist regarding generalizability of trials. We compared patient characteristics and outcomes between patients with HF and reduced ejection fraction (HFrEF) in trials and observational registries. Methods and Results Individual patient data for 16 922 patients from five randomized clinical trials and 46 914 patients from two HF registries were included. The registry patients were categorized into trial-eligible and non-eligible groups using the most commonly used inclusion and exclusion criteria. A total of 26 104 (56%) registry patients fulfilled the eligibility criteria. Unadjusted all-cause mortality rates at 1 year were lowest in the trial population (7%), followed by trial-eligible patients (12%) and trial-non-eligible registry patients (26%). After adjustment for age and sex, all-cause mortality rates were similar between trial participants and trial-eligible registry patients [standardized mortality ratio (SMR) 0.97; 95% confidence interval (CI) 0.92–1.03] but cardiovascular mortality was higher in trial participants (SMR 1.19; 1.12–1.27). After full case-mix adjustment, the SMR for cardiovascular mortality remained higher in the trials at 1.28 (1.20–1.37) compared to RCT-eligible registry patients. Conclusion In contemporary HF registries, over half of HFrEF patients would have been eligible for trial enrolment. Crude clinical event rates were lower in the trials, but, after adjustment for case-mix, trial participants had similar rates of survival as registries. Despite this, they had about 30% higher cardiovascular mortality rates. Age and sex were the main drivers of differences in clinical outcomes between HF trials and observational HF registries.

This study aims to investigate normal changes throughout aging of the heart in cardiac magnetic resonance (CMR) imaging in healthy volunteers. While type 2 diabetes mellitus is a frequent finding in the elderly population, also the influence of this circumstance in otherwise healthy persons is part of our study.In this prospective single-center trial, 75 healthy subjects in distinct age groups and 10 otherwise healthy diabetics were enrolled. All subjects underwent functional, flow sensitive, native T2- and T1-mapping in a 1.5T CMR scanner.No differences in right and left ventricular ejection fractions were observed between aging healthy groups. Bi-ventricular volumes lowered significantly (p0.001) between the age groups. There was also a significant decrease in myocardial T1 values, aortic distensibility, and left ventricular peak diastolic strain rates. There were no differences in T2 mapping and the other deformation parameters. Patients with type 2 diabetes mellitus had lower end-diastolic volume indexes; all the other measurements were comparable.Aging processes in the healthy heart involve a decrease in ventricular volumes, with ejection fractions remaining normal. Stiffening of the myocardium and aorta and a decrease in T1 values are potential indications of age-related remodeling. Type 2 diabetes mellitus seems to have no major influence on aging processes of the heart.EudraCT Identifier: EudraCT 2017-000045-42.

BackgroundReliable identification of heart failure (HF) subtypes might allow targeted management. Machine learning (ML) has been used to explore HF subtypes, but neither across large, independent, population-based datasets, nor across the full spectrum of causes and presentations, nor with clinical and non-clinical validation by different ML methods. Using our published framework, we identified and validated HF subtypes to address these gaps.MethodsWe analysed individuals ≥30 years with incident HF from two population-based electronic health records resources (1998-2018; Clinical Practice Research Datalink, CPRD: n=188,799 HF cases; The Health Improvement Network, THIN: n=124,263 HF cases). Pre-and post-HF factors (n=645) included demography, history, examination, blood laboratory values and medications. We identified subtypes using four unsupervised ML methods (K-means, hierarchical, K-Medoids and mixture model clustering) with 87 (from 645) factors in each dataset. We evaluated subtypes for: (i) external validity (across independent datasets); (ii) prognostic validity (predictive accuracy for 1-year mortality); and (iii) uniquely, genetic validity (in UK Biobank; n=9573 cases): association with polygenic risk score (PRS) for 11 HF related traits, and direct association with 12 reported HF single nucleotide polymorphisms (SNPs).FindingsAfter identifying five clusters, we labelled HF subtypes: 1.Early-onset, 2.Late-onset, 3.AF-related, 4.Metabolic, and 5.Cardiometabolic. External validity: Subtypes were similar across datasets (c-statistic: 0.94, 0.80, 0.79, 0.83, 0.92 for the THIN model in CPRD and 0.79, 0.92, 0.90, 0.89, 0.92 for the CPRD model in THIN for subtypes 1-5, respectively). Prognostic validity: One-year all-cause mortality, risk of non-fatal cardiovascular diseases and all-cause hospitalisation (before and after HF diagnosis) differed across subtypes in CPRD and THIN data. Genetic validity: The AF-related subtype showed associations with PRS for related traits. Late-onset and Cardiometabolic subtypes were most comparable and strongly associated with PRS for Hypertension, Myocardial Infarction and Obesity (p-value < 9.09 × 10−4). We developed a prototype for clinical use, which could enable evaluation of effectiveness and cost-effectiveness.InterpretationAcross four methods and three datasets, and including genetic data, in the largest HF study to-date, ML algorithms identified five subtypes in individuals with incident HF. These subtypes may inform aetiologic research, clinical risk prediction and the design of HF trials.FundingEuropean Union Innovative Medicines Initiative.Research in contextEvidence before this studyIn a systematic review until December 2019, we showed that studies of machine learning in subtyping and risk prediction in cardiovascular diseases are limited by small population size, relatively few factors and poor generalisability of findings due to lack of external validation. We further searched PubMed, medRxiv, bioRxiv, arXiv, for relevant peer-reviewed articles and preprints, focusing on machine learning studies in heart failure. Studies remain focused on single diseases, limited risk factors, often single method of machine learning, rarely use subtyping and risk prediction together, and have not been externally validated across datasets. For heart failure, all subtype discovery studies have identified subtypes based on clustering, but so far with no application to clinical practice.Added value of this studyAcross two independent, population-based datasets, we used four machine learning methods for subtyping and risk prediction with 89 aetiologic factors as well as 556 further factors for heart failure. We identified and validated five subtypes in incident heart failure, which differentially predicted outcomes. In addition, we externally validated clinical cluster differences by exploring corresponding genetic differences in a large-scale genetic cohort. Our methods and results highlight potential value of electronic health records and machine learning in understanding disease subtypes. Moreover, our approach to external, prognostic, and genetic validity provides a framework for validation of machine learning approaches for disease subtype discovery.Implications of all the available evidenceOur analyses support coordinated use of large-scale, linked electronic health records to identify and validate disease subtypes with relevance for clinical risk prediction, patient selection for trials, and future genetic research.

Aims The HERMES (HEart failure Molecular Epidemiology for Therapeutic targets) consortium aims to identify the genomic and molecular basis of heart failure.Methods and results The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of >1.10 for common variants (allele frequency > 0.05) and >1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 x 10(-8) under an additive genetic model.Conclusions HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Background Actigraphy-based measurements of physiologic parameters may enable design of patient-centric heart failure (HF) clinical trials. Recently, the Heart Failure Collaboratory (HFC) focused on recommendations for meaningful change and use of actigraphy as an endpoint in HF clinical trials. We aimed to evaluate randomized controlled trials (RCTs) that have quantified the impact of HF interventions using actigraphy. Methods Using a scoping review strategy, we evaluated the use of actigraphy in HF RCTs. Studies were identified through electronic searches of Embase, OVID MEDLINE, PubMed, and Cochrane review. Data on trial characteristics and results were collected. Results We identified 11 RCTs with a total of 1,455 participants. The risk of bias across the included trials was overall high. All trials had the primary outcomes reflecting measures of either physical activity (n=8), sleep (n=2), or both (n=1). Five trials evaluated response to pharmacologic therapies compared to placebo, three evaluated physical activity interventions, two evaluated group or cognitive therapy, and one evaluated sleep-ventilation strategy. Sample sizes ranged from 30 to 619 participants. There was significant heterogeneity relating to device type, body placement site, and handling of missing actigraphy data. Duration of monitoring ranged from 48 hours to 12 weeks. None of the studies evaluating pharmacologic therapies (n=5) demonstrated a significant improvement of actigraphy-based primary endpoints measurements. Conclusions There is significant heterogeneity in the use, methodology, and results of actigraphy-based HF RCTs. Our results highlight the need to develop, standardize, and validate actigraphy-specific outcomes for use in HF clinical trials

The antifibrinolytic enzyme carboxypeptidase U (CPU, TAFIa, CPB2) is an appealing target for the treatment of acute ischemic stroke (AIS). Increased insights in CPU activation and inactivation during thrombolysis (rtPA) with or without endovascular thrombectomy (EVT) are required to develop CPU inhibitors as profibrinolytic agents with optimal benefits/risks. Therefore, CPU kinetics during ischemic stroke treatment were evaluated. AIS patients with documented cerebral artery occlusion receiving rtPA (N = 20) or rtPA + EVT (N = 16) were included. CPU activation during thrombolysis was measured by an ultrasensitive HPLC-based CPU activity method and by an ELISA measuring both CPU and inactivated CPU (CPU + CPUi). Intravenous blood samples were collected at admission and throughout the first 24 h. Additional in situ blood samples were collected in the rtPA + EVT cohort proximal from the thrombus. The NIHSS score was determined at baseline and 24 h. CPU activity and CPU + CPUi levels increased upon rtPA administration and reached peak values at the end of thrombolysis (1 h). High inter-individual variability was observed in both groups. CPU activity decreased rapidly within 3 h, while CPU + CPUi levels were still elevated at 7 h. CPU activity or CPU + CPUi levels were similar in in situ and peripheral samples. No correlation between CPU or CPU + CPUi and NIHSS or thrombus localization was found. The CPU system was rapidly activated and deactivated following thrombolysis and thrombectomy in stroke patients, suggesting that a CPU inhibitor would have to be administered during rtPA infusion and over the next few hours. The high CPU generation variability suggests that some patients may not respond to the treatment. EudraCT number 2017-002760-41.

Introduction: The impact of the sympathetic nervous system (SNS) modulation on the risk of heart failure (HF) outside of ß1 receptor blockade remains controversial. Methods: We performed a two-sample Mendelian randomization (MR) study using common independent genetic variants located in the cis region of genes encoding the 9 SNS receptors (α1 A, B, D, α2 A, B, C and ß 1, 2 and 3) that were associated at genome-wide significance (P-value ≤ 5х10 –8 ) with blood pressure (BP) and/or heart rate (HR) in published genome-wide association studies (GWAS) available for BP and HR. Variants were filtered out by Linkage Disequilibrium clumping (LD R 2 > 0.1) and based on their minor allele frequency (MAF < 0.01). The effects of selected variants on the genetic risk of HF were extracted from a GWAS of HF from the HERMES consortium, based on a non-overlapping sample population. MR estimates were obtained using the Wald estimator for a single variant or the inverse variance weighted method for multiple variants. Results: 542,362 controls and 40,805 HF cases were evaluated. Independent variants in genes encoding 4 SNS receptors associated with BP or HR were identified as follows: α1A (diastolic BP), α2B (diastolic BP and HR), ß1 and ß2 (diastolic and systolic BP). MR analysis of α1A and ß1, weighted by their effects on diastolic BP, estimated an association with a higher risk of HF, while α2B variants were associated with a lower risk. We found no evidence for an effect of ß2. A similar relationship with systolic BP was found for ß1 and ß2. HR increasing effect of α2B variants was associated with a decreased odd of HF. Conclusions: Mindful of pleiotropic effects, these findings are consistent with the known benefits of ß1 blockade in HF and support a similar role for α1A blockade; conversely, they suggest a detrimental lowering effect of BP and HR through α2B modulation that deserves further studies. No evidence for a role of ß2 in HF was found.

Background: The usefulness of adjudication by central end point committees (CECs) is poorly assessed in heart failure (HF) trials. We aimed to assess its impact on the outcome of the SHIFT trial (Systolic HF Treatment With the If Inhibitor Ivabradine Trial). Methods: SHIFT was a randomized placebo-controlled trial investigating the effect of ivabradine in 6505 HF patients with reduced ejection fraction. Prespecified end points, reported by investigators (all cardiologists) using specific case report form pages, included all-cause and specific causes of deaths and hospitalizations. The primary end point was a composite of cardiovascular deaths or hospitalizations for worsening HF. We compared the adjudication of prespecified end points made by investigators and by the CEC. Results: Investigators identified 7529 prespecified end points, 6793 of which were confirmed by the CEC: 98.1% of cardiovascular deaths, 88.6% of all hospitalizations, and 84.4% of hospitalizations for worsening HF. These differences had no meaningful impact on the study results; hazard ratio for the primary composite end point: investigators, 0.83 (95% CI, 0.76–0.91) versus CEC, 0.82 (95% CI, 0.75–0.90), with similar results for each component of the primary end point (hazard ratio of 0.92 versus 0.91 for cardiovascular death and 0.78 versus 0.74 for hospitalization for worsening HF). Conclusions: Central adjudication by a CEC in the SHIFT study confirmed most of cardiovascular deaths and worsening HF hospitalizations assessed by cardiologists and did not result in a significant change of the final result as compared to investigator judgment. In this context, the benefits of CEC in blinded HF trials should be reconsidered. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02441218. URL: http://www.isrctn.com/ISRCTN70429960 ; Unique identifier: ISRCTN70429960.

Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the ‘no horizontal pleiotropy assumption’ is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses., Mendelian randomisation (MR) analysis of drug targets has potential to aid drug development. Here, the authors introduce a mathematical framework to elucidate this specific application of MR.

BackgroundNaturally occurring human genetic variants provide a valuable tool to identify drug targets and guide drug prioritization and clinical trial design. Ivabradine is a heart rate lowering drug with protective effects on heart failure despite increasing the risk of atrial fibrillation. In patients with coronary artery disease without heart failure, the drug does not protect against major cardiovascular adverse events prompting questions about the ability of genetics to have predicted those effects. This study evaluates the effect of a mutation in HCN4, ivabradine’s drug target, on safety and efficacy endpoints.MethodsWe used genetic association testing and Mendelian randomization to predict the effect of ivabradine and heart rate lowering on cardiovascular outcomes.ResultsUsing data from the UK Biobank and large GWAS consortia, we evaluated the effect of a heart rate-reducing genetic variant at the HCN4 locus encoding ivabradine’s drug target. These genetic association analyses showed increases in risk for atrial fibrillation (OR 1.09, 95% CI: 1.06-1.13, P=9.3 ×10−9) in the UK Biobank. In a cause-specific competing risk model to account for the increased risk of atrial fibrillation, the HCN4 variant reduced incident heart failure in participants that did not develop atrial fibrillation (HR 0.90, 95% CI: 0.83-0.98, P=0.013). In contrast, the same heart rate reducing HCN4 variant did not prevent a composite endpoint of myocardial infarction or cardiovascular death (OR 0.99, 95% CI: 0.93-1.04, P=0.61).ConclusionGenetic modelling of ivabradine recapitulates its benefits in heart failure, promotion of atrial fibrillation, and neutral effect on myocardial infarction.CONDENSED ABSTRACTThe effects of drugs can sometimes be predicted from the effects of mutations in genes encoding drug targets. We tested the effect of a heart rate reducing allele at the HCN4 locus encoding ivabradine’s drug target and found results coherent with the SHIFT and SIGNIFY clinical trials of ivabradine. The genetic variant increased the risk of atrial fibrillation and cardioembolic stroke and protected against heart failure in a competing risk model accounting for the increased risk of atrial fibrillation. The variant had a neutral effect on a composite of myocardial infarction and cardiovascular death.

Aims Antiarrhythmic drugs (AADs) for the treatment of atrial fibrillation (AF) are associated with limited efficacy and adverse effects. Inhibition of the atrial current IKur, absent from the ventricle, is expected to be antiarrhythmic, without adverse cardiac effects, particularly ventricular pro-arrhythmic effects. Methods and results A randomized clinical trial in symptomatic paroxysmal AF patients being considered for ablation. The primary endpoint was AF burden (AFB) as measured by insertable continuous monitoring (ICM) devices. Screened patients had an ICM implanted and were included if AFB was between 1% and 70% after 4 weeks of recording. They were randomly allocated to 4-week treatment of a selective IKur inhibitor S66913 (5 mg, 25 mg, or 100 mg orally per day) or placebo. The study was to enroll 160 patients. The study was terminated prematurely, due to non-study related preclinical safety concerns, after 58 patients had been enrolled. The median AFB ranged from 4.3% to 10.3% at baseline in the four treatment groups. S66913 had no significant effect on AFB or on AFB plus atrial tachycardia (AT) burden, at any dosage; nor on any secondary endpoints including the number and duration of AT or AF episodes, and symptoms. The drug was well tolerated with no safety concern during the treatment or the extended clinical follow-up. Conclusions DIAGRAF-IKUR was the first study to show that using ICM to assess the effect of an AAD is feasible. The selective IKur inhibitor S66913 was safe but had no clinically meaningful effect at the time of early termination of the study.

Despite the availability of a number of different classes of therapeutic agents with proven efficacy in heart failure, the clinical course of heart failure patients is characterized by a reduction in life expectancy, a progressive decline in health-related quality of life and functional status, as well as a high risk of hospitalization. New approaches are needed to address the unmet medical needs of this patient population. The European Medicines Agency (EMA) is undertaking a revision of its Guideline on Clinical Investigation of Medicinal Products for the Treatment of Chronic Heart Failure. The draft version of the Guideline was released for public consultation in January 2016. The Cardiovascular Round Table of the European Society of Cardiology (ESC), in partnership with the Heart Failure Association of the ESC, convened a dedicated two-day workshop to discuss three main topic areas of major interest in the field and addressed in this draft EMA guideline: (i) assessment of efficacy (i.e. endpoint selection and statistical analysis); (ii) clinical trial design (i.e. issues pertaining to patient population, optimal medical therapy, run-in period); and (iii) research approaches for testing novel therapeutic principles (i.e. cell therapy). This paper summarizes the key outputs from the workshop, reviews areas of expert consensus, and identifies gaps that require further research or discussion. Collaboration between regulators, industry, clinical trialists, cardiologists, health technology assessment bodies, payers, and patient organizations is critical to address the ongoing challenge of heart failure and to ensure the development and market access of new therapeutics in a scientifically robust, practical and safe way.

Mendelian randomisation analysis has emerged as an important tool to elucidate the causal relevance of a range of environmental and biological risk factors for human disease. However, inference on cause is undermined if the genetic variants used to instrument a risk factor of interest also associate with other traits that open alternative pathways to the disease (horizontal pleiotropy). We show how the ‘no horizontal pleiotropy assumption’ in MR analysis is strengthened when proteins are the risk factors of interest. Proteins are the proximal effectors of biological processes encoded in the genome, and are becoming assayable on an-omics scale. Moreover, proteins are the targets of most medicines, so Mendelian randomization (MR) studies of drug targets are becoming a fundamental tool in drug development. To enable such studies we introduce a formal mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. Finally, we illustrate key model decisions and introduce an analytical framework for maximizing power and elucidating the robustness of drug target MR analyses.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2–4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.

IntroductionInternational sharing of health data opens the door to the study of the so-called ‘Big Data’, which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a ‘social license’ is identifying the views patients and the public may hold with regard to data sharing for health research.MethodsWe performed a narrative review of the empirical evidence addressing patients’ and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients’ and public attitudes were extracted from selected references and thematically categorised.ResultsTwenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread—though conditional—support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability.ConclusionsOur results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests.

Background Selective inhibitors of Kv1.5 channels are being developed for the treatment of atrial fibrillation (AF). Objectives The purpose of this study was to investigate the effects of the highly selective Kv1.5 inhibitor XEN-D0103 on human atrial action potentials (APs) at high excitation rates and to assess safety. Methods Intracellular APs (stimulation rates 1–5 Hz) were measured in right atrial trabeculae from patients in sinus rhythm (SR), chronic AF (cAF; AF of >6 months duration), and paroxysmal AF (pAF). The safety and tolerability of XEN-D0103 were tested in a double-blind, randomized, placebo-controlled phase 1 study. Results Depending on its concentration, XEN-D0103 elevated the plateau potential. At 1 Hz, XEN-D0103 (3 µM) shortened action potential duration at 90% repolarization (APD90) and effective refractory period (ERP) in SR preparations, but prolonged these parameters in cAF preparations. In SR and pAF preparations, the shortening effects on APD90 and ERP turned into prolongation at high rates. In cAF trabeculae, XEN-D0103 prolonged APD90 and ERP at 2 and 3 Hz. At high rates, more SR and pAF preparations failed to capture excitation in the presence of the drug than in its absence. XEN-D0103 (10 µM) did not significantly affect human ventricular APs. Even with plasma concentrations reaching 7000 ng/mL, XEN-D0103 did not increase ∆∆QTcF (QT interval corrected by the Fridericia formula) in the analysis of electrocardiograms of healthy volunteers, and no subjects receiving an active treatment had a QT or QTcF interval >450 ms, or increase in QTcF from baseline >30 ms. Conclusion APD prolongation and suppression of APs by XEN-D0103 at high stimulation rates in SR and pAF tissue, but not cAF, could be of therapeutic benefit for reducing AF burden. This concept needs to be confirmed in clinical trials.

The effect of bilastine on cardiac repolarization was studied in 30 healthy participants during a multiple-dose, triple-dummy, crossover, thorough QT study that included 5 arms: placebo, active control (400 mg moxifloxacin), bilastine at therapeutic and supratherapeutic doses (20 mg and 100 mg once daily, respectively), and bilastine 20 mg administered with ketoconazole 400 mg. Time-matched, triplicate electrocardiograms (ECGs) were recorded with 13 time points extracted predose and 16 extracted over 72 hours post day 4 dosing. Four QT/RR corrections were implemented: QTcB; QTcF; a linear individual correction (QTcNi), the primary correction; and a nonlinear one (QTcNnl). Moxifloxacin was associated with a significant increase in QTcNi at all time points between 1 and 12 hours, inclusively. Bilastine administration at 20 mg and 100 mg had no clinically significant impact on QTc (maximum increase in QTcNi, 5.02 ms; upper confidence limit [UCL] of the 1-sided, 95% confidence interval, 7.87 ms). Concomitant administration of ketoconazole and bilastine 20 mg induced a clinically relevant increase in QTc (maximum increase in QTcNi, 9.3 ms; UCL, 12.16 ms). This result was most likely related to the cardiac effect of ketoconazole because for all time points, bilastine plasma concentrations were lower than those observed following the supratherapeutic dose.

Newer algorithms for automated QT interval measurements may be more reliable than previous algorithms.This study compares Bazett-corrected QTc obtained by an older algorithm (Old12SL) and by 2 newer ones (New12SL and v3.19) to semiautomated measurement performed by experienced cardiologists.A total of 6105 randomly selected electrocardiograms were classified by the cardiologists as normal (4227), borderline (1254), abnormal (575), or not analyzable (49). Errors of automated measurement were defined by more than 30 milliseconds of absolute difference between Bazett-corrected QTc obtained by automated algorithms and semiautomated measurement.The Old12SL had approximately twice as many errors (5.25%) as the New12SL (2.33%) and v3.19 (2.30%), P.0001. Abnormal tracings resulted in more errors than did normal ones (Old12SL: 16.52% vs 3.45%, New12SL: 7.30% vs 1.51%, and v3.19: 10.61% vs 1.21%).Newer automated algorithms for QT measurements are highly reliable in normal tracings. However, electrocardiogram abnormalities increase the risk of QT measurement errors.

This study compares the ability of 2 semiautomated methods with a fully automated method for QT measurement to minimize the sample size required to detect a moxifloxacin effect and exclude a placebo effect in a thorough QT/QTc study. The fully automated and 1 of 2 semiautomated methods used a global QT measurement in 12 leads, whereas the other semiautomated method used a tangent method on single lead raw complexes. Mean QTcF intervals were greater when measured on a global QT electrocardiogram than on raw complexes, but the mean magnitudes of DeltaQTcF were similar for all methods. The 3 methods detected a statistically significant increase in QTcF for moxifloxacin compared to placebo and were able to exclude a placebo effect on QTcF in all 62 participants. However, due to a smaller variability, the semiautomated methods allowed these detections with fewer than 20 participants, whereas the fully automated required at least 27 participants.

Background: The global QT interval, emerging as a standard measurement provided by digital electrocardiographs, is defined by the earliest QRS onset and latest T-wave offset that occur in any of the standard leads. Differences between global ECG measurements and those from individual ECG leads have implications for the redefinition of normal values, for recognition of disease, and for drug safety. This study sought to quantify the differences between global QT intervals measured from 12 superimposed ECG leads with QT intervals and from single lead complexes, to examine the separate effects of QRS onset and T-wave offset on these differences, and to examine the reproducibility of these measurements. Methods: QTo intervals (Q onset to T offset) from 50 digitized ECGs sampled at 500 Hz were examined by computer assisted derivation of representative complexes from standard leads II, V2, and V3, by both baseline and tangent methods. Global QTo intervals were measured from superimposition of the representative complexes of all 12 leads. A time-coherent matrix of waveform onset and offset points allowed direct comparison of the components of the differences. Results: Global QTo and Bazett-adjusted global QTc were greater than each of the baseline and tangent measurements in representative leads II, V2, and V3, with mean differences ranging from 8 to 18 ms. QRS onset was earlier in the global complex than in each of the representative leads, with mean differences of 3–5 ms, whereas T-wave offset was significantly later in the global complex than in each of the representative leads, with mean differences of 5–11 ms. Remeasurement of all ECGs after an interval of 6 months confirmed the relative magnitudes of the global and individual lead QTo durations and small mean differences between pairs (−0.9 to 2.7 ms). Although global QTo had the largest mean difference (only 2.7 ms), it had the smallest standard deviation of the mean difference and lowest coefficient of variability (1.58%) of all measurements. Conclusion: Global QT measurements are systematically larger than measurements from representative complexes of individual leads. These differences result from the combined effects of earlier QRS onset and later T-wave offset in the global complex, with T-wave offset the more dominant component of the difference.

The International Conference of Harmonisation (ICH) E14 guideline for thorough QT studies requires assessing the propensity of new non-antiarrhythmic drugs to affect cardiac repolarization. The present study investigates whether a composite ECG measure of T-wave morphology (Morphology Combination Score [MCS]) can be used together with the heart rate corrected QT interval (QTc) in a fully ICH E14-compliant thorough QT study to exclude clinically relevant repolarization effects of bilastine, a novel antihistamine.Thirty participants in this crossover study were randomly assigned to receive placebo, moxifloxacin 400 mg, bilastine at therapeutic and supratherapeutic doses (20 and 100 mg) and bilastine 20 mg co-administered with ketoconazole 400 mg. Resting ECGs recorded at 12 nominal time points before and after treatments were used to determine Fridericia corrected QTc (QTcF) and MCS from the T-wave characteristics: asymmetry, flatness and notching.There were no effects of bilastine monotherapy (20 and 100 mg) on MCS or QTcF at those study times where the bilastine plasma concentrations were highest. MCS changes for bilastine monotherapy did not exceed the normal intrasubject variance of T-wave shapes for triplicate ECG recordings. Maximum QTcF prolongation for bilastine monotherapy was 5 ms or less: 3.8 ms (90% CI 0.3, 7.3 ms) for bilastine 20 mg and 5.0 ms (90% CI 2.0, 8.0 ms) for bilastine 100 mg. There were no indications of bilastine inducing larger repolarization effects on T-wave morphology as compared with the QTcF interval, as evidenced by the similarity of z-score equivalents for placebo-corrected changes in MCS and QTcF values.This study shows that bilastine, at therapeutic and supratherapeutic dosages, does not induce any effects on T-wave morphology or QTcF. These results confirm the absence of an effect for bilastine on cardiac repolarization.

B Tyl1,S Azzam2,E Reinbolt2,N Blanco1, J Olbertz3, W Wheeler11MDS Pharma Services, Centralized Cardiac Services, Baillet-en-France, France; 2MDS Pharma Services, Early Clinical Research, Lincoln (Nebraska), USA; 3MDS Pharma Services, Early Clinical Research, Phoenix (Arizona), USABackground: The primary endpoint of a thorough QT study (TQTS) is the change from baseline in QT corrected (QTc) measured on electrocardiograms (ECG) tracings. It has been suggested that during a crossover study, the time-matched or predose baseline could be recorded. The choice of method for baseline ECG collection may influence the results and the cost of the TQTS.Objective: The objective of our study was to compare the collection of a time-matched baseline before each period (TMEACH), an average of all the time-matched baseline (TMMEAN), a time-matched baseline before period 1 (TMP1) and a predose baseline (PDEACH) on QT interval prolongation induced by moxifloxacin, in a 30 subjects, 5 arm cross-over TQTS.Results: Moxifloxacin induced a similar significant increase in QT corrected using Fridericia’s formula (QTc) (lower limit of the confidence interval excluded 5 ms) at all time-points between 0.5 hours and 12 hours with all baseline methods. TMEACH was associated with a lower within subject variability (SD 5.59 ms) than TMMEAN and TMP1 (5.90 and 6.90 ms, respectively). PDEACH was associated with the highest variability (7.41 ms).Conclusion: The collection of ECG tracings during a full baseline day before each period was associated with the lowest variability. However, the two more cost effective designs (TMP1 and PDEACH) were sufficient, in this small TQTS, to significantly detect moxifloxacin.Keywords: thorough QT study, QT correction, baseline, design, superimposed representative complex, moxifloxacin