The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.
If you have any questions or comments, please contact us.
The limited availability of human heart tissue and its complex cell composition are major limiting factors for the reliable testing of drug efficacy and toxicity. Recently, we developed functional human and pig heart slice biomimetic culture systems that preserve the viability and functionality of 300 μm heart slices for up to 6 days. Here, we tested the reliability of this culture system for testing the cardiotoxicity of anti-cancer drugs. We tested three anti-cancer drugs (doxorubicin, trastuzumab, and sunitinib) with known different mechanisms of cardiotoxicity at three concentrations and assessed the effect of these drugs on heart slice viability, structure, function and gene expression. Slices incubated with any of these drugs for 48 h showed diminished in viability as well as loss of cardiomyocyte structure and function. Mechanistically, RNA sequencing of doxorubicin-treated tissues demonstrated a significant downregulation of cardiac genes and upregulation of oxidative stress responses. Trastuzumab treatment downregulated cardiac muscle contraction-related genes consistent with its clinically known effect on cardiomyocytes. Interestingly, sunitinib treatment resulted in significant downregulation of angiogenesis-related genes, in line with its mechanism of action. Similar to hiPS-derived-cardiomyocytes, heart slices recapitulated the expected toxicity of doxorubicin and trastuzumab, however, slices were superior in detecting sunitinib cardiotoxicity and mechanism in the clinically relevant concentration range of 0.1-1 μM. These results indicate that heart slice culture models have the potential to become a reliable platform for testing and elucidating mechanisms of drug cardiotoxicity.
Copyright © 2020 Elsevier Inc. All rights reserved.
BACKGROUND - Cardiac injury, as measured by troponin elevation, has been reported among hospitalized coronavirus disease 2019 (COVID-19) patients and portends a poor prognosis. However, how the dynamics of troponin elevation interplay with inflammation and coagulation biomarkers over time is unknown. We assessed longitudinal follow-up of cardiac injury, inflammation and coagulation markers in relation to disease severity and outcome.
METHODS - We retrospectively assessed 2068 patients with laboratory-confirmed COVID-19 between January 29 and April 1, 2020 at Tongji Hospital in Wuhan, China. We defined cardiac injury as an increase in high sensitivity cardiac troponin-I (hs-cTnI) above the 99th of the upper reference limit. We explored the dynamics of elevation in hs-cTnI and the relationship with inflammation (interleukin [IL]-6, IL-8, IL-10, IL-2 receptor, tumor necrosis factor-α, C-reactive protein) and coagulation (d-dimer, fibrinogen, international normalized ratio) markers in non-critically ill versus critically ill patients longitudinally and further correlated these markers to survivors and non-survivors.
RESULTS - Median age was 63 years (first to third quartile 51-70 years), 51.4% of whom were women. When compared to non-critically ill patients (N = 1592, 77.0%), critically ill (defined as requiring mechanical ventilation, in shock or multiorgan failure) patients (N = 476, 23.0%), had more frequent cardiac injury on admission (30.3% vs. 2.3%, p < 0.001), with increased mortality during hospitalization (38.4% vs. 0%, p < 0.001). Among critically ill patients, non-survivors (N = 183) had a continuous increase in hs-cTnI levels during hospitalization, while survivors (N = 293) showed a decrease in hs-cTnI level between day 4 and 7 after admission. Specifically, cardiac injury is an independent marker of mortality among critically ill patients at admission, day 4-7 and 8-14. Consistent positive correlations between hs-cTnI and interleukin (IL)-6 on admission (r = 0.59), day 4-7 (r = 0.66) and day 8-14 (r = 0.61; all p < 0.001) and d-dimer (at the same timepoints r = 0.54; 0.65; 0.61, all p < 0.001) were observed. A similar behavior was observed between hs-cTnI and most of other biomarkers of inflammation and coagulation.
CONCLUSIONS - Cardiac injury commonly occurs in critically ill COVID-19 patients, with increased levels of hs-cTnI beyond day 3 since admission portending a poor prognosis. A consistent positive correlation of hs-cTnI with IL-6 and d-dimer at several timepoints along hospitalization could suggest nonspecific cytokine-mediated cardiotoxicity.
Copyright © 2020. Published by Elsevier Ltd.
Heart failure with preserved ejection fraction (HFpEF), a major public health problem that is rising in prevalence, is associated with high morbidity and mortality and is considered to be the greatest unmet need in cardiovascular medicine today because of a general lack of effective treatments. To address this challenging syndrome, the National Heart, Lung, and Blood Institute convened a working group made up of experts in HFpEF and novel research methodologies to discuss research gaps and to prioritize research directions over the next decade. Here, we summarize the discussion of the working group, followed by key recommendations for future research priorities. There was uniform recognition that HFpEF is a highly integrated, multiorgan, systemic disorder requiring a multipronged investigative approach in both humans and animal models to improve understanding of mechanisms and treatment of HFpEF. It was recognized that advances in the understanding of basic mechanisms and the roles of inflammation, macrovascular and microvascular dysfunction, fibrosis, and tissue remodeling are needed and ideally would be obtained from (1) improved animal models, including large animal models, which incorporate the effects of aging and associated comorbid conditions; (2) repositories of deeply phenotyped physiological data and human tissue, made accessible to researchers to enhance collaboration and research advances; and (3) novel research methods that take advantage of computational advances and multiscale modeling for the analysis of complex, high-density data across multiple domains. The working group emphasized the need for interactions among basic, translational, clinical, and epidemiological scientists and across organ systems and cell types, leveraging different areas or research focus, and between research centers. A network of collaborative centers to accelerate basic, translational, and clinical research of pathobiological mechanisms and treatment strategies in HFpEF was discussed as an example of a strategy to advance research progress. This resource would facilitate comprehensive, deep phenotyping of a multicenter HFpEF patient cohort with standardized protocols and a robust biorepository. The research priorities outlined in this document are meant to stimulate scientific advances in HFpEF by providing a road map for future collaborative investigations among a diverse group of scientists across multiple domains.
Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which manifest as structured spatial patterns of temporal correlations between distant brain regions. Here, we investigated whether such "physiological networks"-sets of segregated brain regions that exhibit similar responses following slow changes in systemic physiology-resemble patterns associated with large-scale networks typically attributed to remotely synchronized neuronal activity. By analyzing a large group of subjects from the 3T Human Connectome Project (HCP) database, we demonstrate brain-wide and noticeably heterogenous dynamics tightly coupled to either respiratory variation or heart rate changes. We show, using synthesized data generated from physiological recordings across subjects, that these physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks. Further, we show that such physiologically-relevant connectivity estimates appear to dominate the overall connectivity observations in multiple HCP subjects, and that this apparent "physiological connectivity" cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiologically-coupled responses. Our results challenge previous notions that physiological confounds are either localized to large veins or globally coherent across the cortex, therefore emphasizing the necessity to consider potential physiological contributions in fMRI-based functional connectivity studies. The rich spatiotemporal patterns carried by such "physiological" dynamics also suggest great potential for clinical biomarkers that are complementary to large-scale neuronal networks.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.
BACKGROUND - The National Comprehensive Cancer Network and American Society of Clinical Oncology recommend consideration of the use of echocardiography 6 to 12 months after completion of anthracycline-based chemotherapy in at-risk populations. Assessment of BNP (B-type natriuretic peptide) has also been suggested by the American College of Cardiology/American Heart Association/Heart Failure Society of America for the identification of Stage A (at risk) heart failure patients. The real-world frequency of the use of these tests in patients after receipt of anthracycline therapy, however, has not been studied previously.
METHODS AND RESULTS - In this retrospective study, using administrative claims data from the OptumLabs Data Warehouse, we identified 31 447 breast cancer and lymphoma patients (age ≥18 years) who were treated with an anthracycline in the United States between January 1, 2008 and January 31, 2018. Continuous medical and pharmacy coverage was required for at least 6 months before the initial anthracycline dose and 12 months after the final dose. Only 36.1% of patients had any type of cardiac surveillance (echocardiography, BNP, or cardiac imaging) in the year following completion of anthracycline therapy (29.7% echocardiography). Surveillance rate increased from 37.5% in 2008 to 42.7% in 2018 (25.6% in 2008 to 40.5% echocardiography in 2018). Lymphoma patients had a lower likelihood of any surveillance compared with patients with breast cancer (odds ratio, 0.79 [95% CI, 0.74-0.85]; <0.001). Patients with preexisting diagnoses of coronary artery disease and arrhythmia had the highest likelihood of cardiac surveillance (odds ratio, 1.54 [95% CI, 1.39-1.69] and odds ratio, 1.42 [95% CI, 1.3-1.53]; <0.001 for both), although no single comorbidity was associated with a >50% rate of surveillance.
CONCLUSIONS - The majority of survivors of breast cancer and lymphoma who have received anthracycline-based chemotherapy do not undergo cardiac surveillance after treatment, including those with a history of cardiovascular comorbidities, such as heart failure.
Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method for automatic calcium scoring across a wide range of CT examination types and to investigate whether the method can adapt to different types of CT examinations when representative images are added to the existing training data set. Materials and Methods The study included 7240 participants who underwent various types of nonenhanced CT examinations that included the heart: coronary artery calcium (CAC) scoring CT, diagnostic CT of the chest, PET attenuation correction CT, radiation therapy treatment planning CT, CAC screening CT, and low-dose CT of the chest. CAC and thoracic aorta calcification (TAC) were quantified using a convolutional neural network trained with 1181 low-dose chest CT examinations (baseline), a small set of examinations of the respective type supplemented to the baseline (data specific), and a combination of examinations of all available types (combined). Supplemental training sets contained 199-568 CT images depending on the calcium burden of each population. The DL algorithm performance was evaluated with intraclass correlation coefficients (ICCs) between DL and manual (Agatston) CAC and (volume) TAC scoring and with linearly weighted κ values for cardiovascular risk categories (Agatston score; cardiovascular disease risk categories: 0, 1-10, 11-100, 101-400, >400). Results At baseline, the DL algorithm yielded ICCs of 0.79-0.97 for CAC and 0.66-0.98 for TAC across the range of different types of CT examinations. ICCs improved to 0.84-0.99 (CAC) and 0.92-0.99 (TAC) for CT protocol-specific training and to 0.85-0.99 (CAC) and 0.96-0.99 (TAC) for combined training. For assignment of cardiovascular disease risk category, the κ value for all test CT scans was 0.90 (95% confidence interval [CI]: 0.89, 0.91) for the baseline training. It increased to 0.92 (95% CI: 0.91, 0.93) for both data-specific and combined training. Conclusion A deep learning calcium scoring algorithm for quantification of coronary and thoracic calcium was robust, despite substantial differences in CT protocol and variations in subject population. Augmenting the algorithm training with CT protocol-specific images further improved algorithm performance. © RSNA, 2020 See also the editorial by Vannier in this issue.
BACKGROUND - The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
METHODS - The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.
RESULTS - Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
CONCLUSIONS - The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
Cancer and cardiovascular (CV) disease are the most prevalent diseases in the developed world. Evidence increasingly shows that these conditions are interlinked through common risk factors, coincident in an ageing population, and are connected biologically through some deleterious effects of anticancer treatment on CV health. Anticancer therapies can cause a wide spectrum of short- and long-term cardiotoxic effects. An explosion of novel cancer therapies has revolutionised this field and dramatically altered cancer prognosis. Nevertheless, these new therapies have introduced unexpected CV complications beyond heart failure. Common CV toxicities related to cancer therapy are defined, along with suggested strategies for prevention, detection and treatment. This ESMO consensus article proposes to define CV toxicities related to cancer or its therapies and provide guidance regarding prevention, screening, monitoring and treatment of CV toxicity. The majority of anticancer therapies are associated with some CV toxicity, ranging from asymptomatic and transient to more clinically significant and long-lasting cardiac events. It is critical however, that concerns about potential CV damage resulting from anticancer therapies should be weighed against the potential benefits of cancer therapy, including benefits in overall survival. CV disease in patients with cancer is complex and treatment needs to be individualised. The scope of cardio-oncology is wide and includes prevention, detection, monitoring and treatment of CV toxicity related to cancer therapy, and also ensuring the safe development of future novel cancer treatments that minimise the impact on CV health. It is anticipated that the management strategies discussed herein will be suitable for the majority of patients. Nonetheless, the clinical judgment of physicians remains extremely important; hence, when using these best clinical practices to inform treatment options and decisions, practitioners should also consider the individual circumstances of their patients on a case-by-case basis.
Copyright © 2019 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.
BACKGROUND - Insight into type 5 long QT syndrome (LQT5) has been limited to case reports and small family series. Improved understanding of the clinical phenotype and genetic features associated with rare variants implicated in LQT5 was sought through an international multicenter collaboration.
METHODS - Patients with either presumed autosomal dominant LQT5 (N = 229) or the recessive Type 2 Jervell and Lange-Nielsen syndrome (N = 19) were enrolled from 22 genetic arrhythmia clinics and 4 registries from 9 countries. variants were evaluated for ECG penetrance (defined as QTc >460 ms on presenting ECG) and genotype-phenotype segregation. Multivariable Cox regression was used to compare the associations between clinical and genetic variables with a composite primary outcome of definite arrhythmic events, including appropriate implantable cardioverter-defibrillator shocks, aborted cardiac arrest, and sudden cardiac death.
RESULTS - A total of 32 distinct rare variants were identified in 89 probands and 140 genotype positive family members with presumed LQT5 and an additional 19 Type 2 Jervell and Lange-Nielsen syndrome patients. Among presumed LQT5 patients, the mean QTc on presenting ECG was significantly longer in probands (476.9±38.6 ms) compared with genotype positive family members (441.8±30.9 ms, <0.001). ECG penetrance for heterozygous genotype positive family members was 20.7% (29/140). A definite arrhythmic event was experienced in 16.9% (15/89) of heterozygous probands in comparison with 1.4% (2/140) of family members (adjusted hazard ratio [HR] 11.6 [95% CI, 2.6-52.2]; =0.001). Event incidence did not differ significantly for Type 2 Jervell and Lange-Nielsen syndrome patients relative to the overall heterozygous cohort (10.5% [2/19]; HR 1.7 [95% CI, 0.3-10.8], =0.590). The cumulative prevalence of the 32 variants in the Genome Aggregation Database, which is a human database of exome and genome sequencing data from now over 140 000 individuals, was 238-fold greater than the anticipated prevalence of all LQT5 combined (0.238% vs 0.001%).
CONCLUSIONS - The present study suggests that putative/confirmed loss-of-function variants predispose to QT prolongation, however, the low ECG penetrance observed suggests they do not manifest clinically in the majority of individuals, aligning with the mild phenotype observed for Type 2 Jervell and Lange-Nielsen syndrome patients.