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BACKGROUND - Immune checkpoint inhibitors (ICIs) have substantially improved clinical outcomes in multiple cancer types and are increasingly being used in early disease settings and in combinations of different immunotherapies. However, ICIs can also cause severe or fatal immune-related adverse-events (irAEs). We aimed to identify and characterise cardiovascular irAEs that are significantly associated with ICIs.
METHODS - In this observational, retrospective, pharmacovigilance study, we used VigiBase, WHO's global database of individual case safety reports, to compare cardiovascular adverse event reporting in patients who received ICIs (ICI subgroup) with this reporting in the full database. This study included all cardiovascular irAEs classified by group queries according to the Medical Dictionary for Regulatory Activities, between inception on Nov 14, 1967, and Jan 2, 2018. We evaluated the association between ICIs and cardiovascular adverse events using the reporting odds ratio (ROR) and the information component (IC). IC is an indicator value for disproportionate Bayesian reporting that compares observed and expected values to find associations between drugs and adverse events. IC is the lower end of the IC 95% credibility interval, and an IC value of more than zero is deemed significant. This study is registered with ClinicalTrials.gov, number NCT03387540.
FINDINGS - We identified 31 321 adverse events reported in patients who received ICIs and 16 343 451 adverse events reported in patients treated with any drugs (full database) in VigiBase. Compared with the full database, ICI treatment was associated with higher reporting of myocarditis (5515 reports for the full database vs 122 for ICIs, ROR 11·21 [95% CI 9·36-13·43]; IC 3·20), pericardial diseases (12 800 vs 95, 3·80 [3·08-4·62]; IC 1·63), and vasculitis (33 289 vs 82, 1·56 [1·25-1·94]; IC 0·03), including temporal arteritis (696 vs 18, 12·99 [8·12-20·77]; IC 2·59) and polymyalgia rheumatica (1709 vs 16, 5·13 [3·13-8·40]; IC 1·33). Pericardial diseases were reported more often in patients with lung cancer (49 [56%] of 87 patients), whereas myocarditis (42 [41%] of 103 patients) and vasculitis (42 [60%] of 70 patients) were more commonly reported in patients with melanoma (χ test for overall subgroup comparison, p<0·0001). Vision was impaired in five (28%) of 18 patients with temporal arteritis. Cardiovascular irAEs were severe in the majority of cases (>80%), with death occurring in 61 (50%) of 122 myocarditis cases, 20 (21%) of 95 pericardial disease cases, and five (6%) of 82 vasculitis cases (χ test for overall comparison between pericardial diseases, myocarditis, and vasculitis, p<0·0001).
INTERPRETATION - Treatment with ICIs can lead to severe and disabling inflammatory cardiovascular irAEs soon after commencement of therapy. In addition to life-threatening myocarditis, these toxicities include pericardial diseases and temporal arteritis with a risk of blindness. These events should be considered in patient care and in combination clinical trial designs (ie, combinations of different immunotherapies as well as immunotherapies and chemotherapy).
FUNDING - The Cancer Institut Thématique Multi-Organisme of the French National Alliance for Life and Health Sciences (AVIESAN) Plan Cancer 2014-2019; US National Cancer Institute, National Institutes of Health; the James C. Bradford Jr. Melanoma Fund; and the Melanoma Research Foundation.
Copyright © 2018 Elsevier Ltd. All rights reserved.
Isolevuglandins are 4-ketoaldehydes formed by peroxidation of arachidonic acid. Isolevuglandins react rapidly with primary amines including the lysyl residues of proteins to form irreversible covalent modifications. This review highlights evidence for the potential role of isolevuglandin modification in the disease processes, especially atherosclerosis, and some of the tools including small molecule dicarbonyl scavengers utilized to assess their contributions to disease.
Copyright © 2018. Published by Elsevier Inc.
RATIONALE & OBJECTIVE - Inflammation, cardiac remodeling, and fibrosis may explain in part the excess risk for cardiovascular disease (CVD) in patients with chronic kidney disease (CKD). Growth differentiation factor 15 (GDF-15), galectin 3 (Gal-3), and soluble ST2 (sST2) are possible biomarkers of these pathways in patients with CKD.
STUDY DESIGN - Observational cohort study.
SETTING & PARTICIPANTS - Individuals with CKD enrolled in either of 2 multicenter CKD cohort studies: the Seattle Kidney Study or C-PROBE (Clinical Phenotyping and Resource Biobank Study).
EXPOSURES - Circulating GDF-15, Gal-3, and sST2 measured at baseline.
OUTCOMES - Primary outcome was all-cause mortality. Secondary outcomes included hospitalization for physician-adjudicated heart failure and the atherosclerotic CVD events of myocardial infarction and cerebrovascular accident.
ANALYTIC APPROACH - Cox proportional hazards models used to test the association of each biomarker with each outcome, adjusting for demographics, CVD risk factors, and kidney function.
RESULTS - Among 883 participants, mean estimated glomerular filtration rate was 49±19mL/min/1.73m. Higher GDF-15 (adjusted HR [aHR] per 1-SD higher, 1.87; 95% CI, 1.53-2.29), Gal-3 (aHR per 1-SD higher, 1.51; 95% CI, 1.36-1.78), and sST2 (aHR per 1-SD higher, 1.36; 95% CI, 1.17-1.58) concentrations were significantly associated with mortality. Only GDF-15 level was also associated with heart failure events (HR per 1-SD higher, 1.56; 95% CI, 1.12-2.16). There were no detectable associations between GDF-15, Gal-3, or sST2 concentrations and atherosclerotic CVD events.
LIMITATIONS - Event rates for heart failure and atherosclerotic CVD were low.
CONCLUSIONS - Adults with CKD and higher circulating GDF-15, Gal-3, and sST2 concentrations experienced greater mortality. Elevated GDF-15 concentration was also associated with an increased rate of heart failure. Further work is needed to elucidate the mechanisms linking these circulating biomarkers with CVD in patients with CKD.
Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
OBJECTIVE - Patients with rheumatoid arthritis (RA) have increased cardiovascular (CV) risk. In the general population, exercise improves several CV risk factors. In a cross-sectional study, we examined the hypothesis that more exercise is associated with protective traditional and non-traditional CV risk factor profile in patients with RA.
METHODS - Patient-reported exercise outside of daily activities was quantified by time and metabolic equivalents per week (METmin/week) and CV risk factors including blood pressure, standard lipid profiles, lipoprotein particle concentrations (NMR spectroscopy), and vascular indices were measured in 165 patients with RA. The relationship between exercise and CV risk factors was assessed according to whether patients exercised or not, and after adjustment for age, race and sex.
RESULTS - Over half (54%) of RA patients did not exercise. Among those who did exercise, median value for exercise duration was 113 min/week [IQR: 60, 210], and exercise metabolic equivalent expenditure was 484 METmin/week [IQR: 258, 990]. Disease activity (measured by DAS28 score), C-reactive protein, waist-hip ratio, and prevalence of hypertension were lower in patients who exercised compared to those who did not (all p-values < 0.05) but standard lipid profile and body mass index were not significantly different. Patients who exercised had significantly higher concentrations of HDL particles (p = 0.004) and lower vascular stiffness as measured by pulse wave velocity (p = 0.005).
CONCLUSIONS - More self-reported exercise in patients with RA was associated with a protective CV risk factor profile including lower waist-hip ratio, higher HDL particle concentration, lower vascular stiffness, and a lower prevalence of hypertension.
The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.
© 2018 American Heart Association, Inc.
Drug-induced cardiovascular complications are the most common adverse drug events and account for the withdrawal or severe restrictions on the use of multitudinous postmarketed drugs. In this study, we developed new in silico models for systematic identification of drug-induced cardiovascular complications in drug discovery and postmarketing surveillance. Specifically, we collected drug-induced cardiovascular complications covering the five most common types of cardiovascular outcomes (hypertension, heart block, arrhythmia, cardiac failure, and myocardial infarction) from four publicly available data resources: Comparative Toxicogenomics Database, SIDER, Offsides, and MetaADEDB. Using these databases, we developed a combined classifier framework through integration of five machine-learning algorithms: logistic regression, random forest, k-nearest neighbors, support vector machine, and neural network. The totality of models included 180 single classifiers with area under receiver operating characteristic curves (AUC) ranging from 0.647 to 0.809 on 5-fold cross-validations. To develop the combined classifiers, we then utilized a neural network algorithm to integrate the best four single classifiers for each cardiovascular outcome. The combined classifiers had higher performance with an AUC range from 0.784 to 0.842 compared to single classifiers. Furthermore, we validated our predicted cardiovascular complications for 63 anticancer agents using experimental data from clinical studies, human pluripotent stem cell-derived cardiomyocyte assays, and literature. The success rate of our combined classifiers reached 87%. In conclusion, this study presents powerful in silico tools for systematic risk assessment of drug-induced cardiovascular complications. This tool is relevant not only in early stages of drug discovery but also throughout the life of a drug including clinical trials and postmarketing surveillance.
PURPOSE OF REVIEW - The goal of this review is to highlight the potential of induced pluripotent stem cell (iPSC)-based modeling as a tool for studying human cardiovascular diseases. We present some of the current cardiovascular disease models utilizing genome editing and patient-derived iPSCs.
RECENT FINDINGS - The incorporation of genome-editing and iPSC technologies provides an innovative research platform, providing novel insight into human cardiovascular disease at molecular, cellular, and functional level. In addition, genome editing in diseased iPSC lines holds potential for personalized regenerative therapies. The study of human cardiovascular disease has been revolutionized by cellular reprogramming and genome editing discoveries. These exceptional technologies provide an opportunity to generate human cell cardiovascular disease models and enable therapeutic strategy development in a dish. We anticipate these technologies to improve our understanding of cardiovascular disease pathophysiology leading to optimal treatment for heart diseases in the future.
The frequency of prediabetes is increasing as the prevalence of obesity rises worldwide. In prediabetes, hyperglycemia, insulin resistance, and inflammation and metabolic derangements associated with concomitant obesity cause endothelial vasodilator and fibrinolytic dysfunction, leading to increased risk of cardiovascular and renal disease. Importantly, the microvasculature affects insulin sensitivity by affecting the delivery of insulin and glucose to skeletal muscle; thus, endothelial dysfunction and extracellular matrix remodeling promote the progression from prediabetes to diabetes mellitus. Weight loss is the mainstay of treatment in prediabetes, but therapies that improved endothelial function and vasodilation may not only prevent cardiovascular disease but also slow progression to diabetes mellitus.
© 2018 American Heart Association, Inc.
The objective of this study was to isolate the impact of hydrodynamics on selectin-mediated cell rolling in branched microvessels. Significant advancements have been made in furthering the understanding of complex interactions between biochemical and physical factors in the inflammatory cascade in simplified planar geometries. However, few studies have sought to quantify the effects of branched configurations and to isolate the effects of associated fluid forces. Experimental techniques were developed to perform in vitro adhesion experiments in Y-shaped micro-slides. The micro-slides were coated with P-selectin and microspheres coated with Sialyl-Lewis were observed as they rolled in the chambers at different wall shear stresses. Study results revealed that microsphere rolling velocities and rolling flux were lowest in regions closest to the apex of a junctional region and were dependent on both branch angle and wall shear stress. The regions closest to the junctional region were shown to have low bulk flow velocities and shear stresses using computational fluid dynamics (CFD) modeling. Collectively, the study demonstrates that despite the presence of a uniform coating of P-selectin, hydrodynamic factors associated with the chamber geometry yield non-uniform effects on particle behavior. These findings could explain why cells have been observed to preferentially adhere or transmigrate near junctional regions. Future characterization of inflammatory processes in microvascular network configurations is therefore crucial for furthering our fundamental understanding of inflammation.
Copyright © 2018 Elsevier Inc. All rights reserved.