Non-coding RNA in Endothelial-to-Mesenchymal Transition

Endothelial-to-mesenchymal transition (EndMT) is the process wherein endothelial cells lose their typical endothelial cell markers and functions and adopt a mesenchymal-like phenotype. EndMT is required for development of the cardiac valves, the pulmonary and dorsal aorta and arterial maturation, but activation of the EndMT program during adulthood is believed to contribute to several pathologies including organ fibrosis, cardiovascular disease and cancer. Non-coding RNAs, including microRNAs, long non-coding RNAs and circular RNAs, modulate EndMT during development and disease. Here, we review the mechanisms by which non-coding RNAs facilitate or inhibit EndMT during development and disease and provide a perspective on the therapeutic application of non-coding RNAs to treat fibroproliferative cardiovascular disease

Genome-Wide Significant Loci: How Important Are They? Systems Genetics to Understand Heritability of Coronary Artery Disease and Other Common Complex Disorders

AbstractGenome-wide association studies (GWAS) have been extensively used to study common complex diseases such as coronary artery disease (CAD), revealing 153 suggestive CAD loci, of which at least 46 have been validated as having genome-wide significance. However, these loci collectively explain <10% of the genetic variance in CAD. Thus, we must address the key question of what factors constitute the remaining 90% of CAD heritability. We review possible limitations of GWAS, and contextually consider some candidate CAD loci identified by this method. Looking ahead, we propose systems genetics as a complementary approach to unlocking the CAD heritability and etiology. Systems genetics builds network models of relevant molecular processes by combining genetic and genomic datasets to ultimately identify key “drivers” of disease. By leveraging systems-based genetic approaches, we can help reveal the full genetic basis of common complex disorders, enabling novel diagnostic and therapeutic opportunities

Machine learning prediction of progressive subclinical myocardial dysfunction in moderate aortic stenosis

BackgroundModerate severity aortic stenosis (AS) is poorly understood, is associated with subclinical myocardial dysfunction, and can lead to adverse outcome rates that are comparable to severe AS. Factors associated with progressive myocardial dysfunction in moderate AS are not well described. Artificial neural networks (ANNs) can identify patterns, inform clinical risk, and identify features of importance in clinical datasets.MethodsWe conducted ANN analyses on longitudinal echocardiographic data collected from 66 individuals with moderate AS who underwent serial echocardiography at our institution. Image phenotyping involved left ventricular global longitudinal strain (GLS) and valve stenosis severity (including energetics) analysis. ANNs were constructed using two multilayer perceptron models. The first model was developed to predict change in GLS from baseline echocardiography alone and the second to predict change in GLS using data from baseline and serial echocardiography. ANNs used a single hidden layer architecture and a 70%:30% training/testing split.ResultsOver a median follow-up interval of 1.3 years, change in GLS (≤ or &gt;median change) could be predicted with accuracy rates of 95% in training and 93% in testing using ANN with inputs from baseline echocardiogram data alone (AUC: 0.997). The four most important predictive baseline features (reported as normalized % importance relative to most important feature) were peak gradient (100%), energy loss (93%), GLS (80%), and DI &lt; 0.25 (50%). When a further model was run including inputs from both baseline and serial echocardiography (AUC 0.844), the top four features of importance were change in dimensionless index between index and follow-up studies (100%), baseline peak gradient (79%), baseline energy loss (72%), and baseline GLS (63%).ConclusionsArtificial neural networks can predict progressive subclinical myocardial dysfunction with high accuracy in moderate AS and identify features of importance. Key features associated with classifying progression in subclinical myocardial dysfunction included peak gradient, dimensionless index, GLS, and hydraulic load (energy loss), suggesting that these features should be closely evaluated and monitored in AS

TCT-481 Treatment of "resistant" in-stent restenosis in the drug-eluting era: comparison of repeat stent versus balloon only strategy

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Subclinical Atherosclerosis in Young, Socioeconomically Vulnerable Hispanic and Non-Hispanic Black Adults.

BACKGROUND Non-Hispanic Black persons are at greater risk of cardiovascular (CV) events than other racial/ethnic groups; however, their differential vulnerability to early subclinical atherosclerosis is poorly understood. OBJECTIVES This work aims to study the impact of race/ethnicity on early subclinical atherosclerosis in young socioeconomically disadvantaged adults. METHODS Bilateral carotid and femoral 3-dimensional vascular ultrasound examinations were performed on 436 adults (parents/caregivers and staff) with a mean age of 38.0 ± 11.1 years, 82.3% female, 66% self-reported as Hispanic, 34% self-reported as non-Hispanic Black, and no history of CV disease recruited in the FAMILIA (Family-Based Approach in a Minority Community Integrating Systems-Biology for Promotion of Health) trial from 15 Head Start preschools in Harlem (neighborhood in New York, New York, USA). The 10-year Framingham CV risk score was calculated, and the relationship between race/ethnicity and the presence and extent of subclinical atherosclerosis was analyzed with multivariable logistic and linear regression models. RESULTS The mean 10-year Framingham CV risk was 4.0%, with no differences by racial/ethnic category. The overall prevalence of subclinical atherosclerosis was significantly higher in the non-Hispanic Black (12.9%) than in the Hispanic subpopulation (6.6%). After adjusting for 10-year Framingham CV risk score, body mass index, fruit and vegetable consumption, physical activity, and employment status, non-Hispanic Black individuals were more likely than Hispanic individuals to have subclinical atherosclerosis (OR: 3.45; 95% CI: 1.44-8.29; P = 0.006) and multiterritorial disease (P = 0.026). CONCLUSIONS After adjustment for classic CV risk, lifestyle, and socioeconomic factors, non-Hispanic Black younger adults seem more vulnerable to early subclinical atherosclerosis than their Hispanic peers, suggesting that the existence of emerging or undiscovered CV factors underlying the residual excess risk (Family-Based Approach in a Minority Community Integrating Systems-Biology for Promotion of Health [FAMILIA (Project 2)]; NCT02481401).This study was funded by the American Heart Association under grant No 14SFRN20490315 and the Stephen Gellman Children’s Outreach Program. Dr Fernandez-Jimenez is recipient of grant PI19/01704 funded by the Fondo de Investigación Sanitaria- Instituto de Salud Carlos III (ISCIII) and co-funded by the European Regional Development Fund/European Social Fund "A way to make Europe"/"Investing in your future." Dr Santos-Beneit is recipient of grant LCF/PR/MS19/ 12220001 funded by “la Caixa” Foundation (ID 100010434). The CNIC is supported by the ISCIII, the Ministerio de Ciencia e Innovación (MCIN) and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MICIN/AEI/10.13039/ 501100011033). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.S

Child health promotion in underserved communities: The FAMILIA trial

Background: Preschool-based interventions offer promise to instill healthy behaviors in children, which can be a strategy to reduce the burden of cardiovascular disease later. However, their efficacy in underserved communities is not well established. Objectives: The purpose of this study was to assess the impact of a preschool-based health promotion educational intervention in an underserved community. Methods: This cluster-randomized controlled study involved 15 Head Start preschools in Harlem, New York. Schools and their children were randomized 3:2 to receive either a 4-month (50 h) educational intervention to instill healthy behaviors in relation to diet, physical activity, body/heart awareness, and emotion management; or their standard curriculum (control). The primary outcome was the change from baseline in the overall knowledge, attitudes, and habits (KAH) score of the children at 5 months. As secondary outcomes, we evaluated the changes in KAH subcomponents and emotion comprehension. Linear mixed-effects models were used to test for intervention effects. Results: The authors enrolled 562 preschool children age 3 to 5 years, 51% female, 54% Hispanic/Latino, and 37% African-American. Compared with the control group, the mean relative change from baseline in the overall KAH score was ∼2.2 fold higher in the intervention group (average absolute difference of 2.86 points; 95% confidence interval: 0.58 to 5.14; p = 0.014). The maximal effect was observed in children who received >75% of the curriculum. Physical activity and body/heart awareness components, and knowledge and attitudes domains, were the main drivers of the effect (p values <0.05). Changes in emotion comprehension trended toward favoring intervened children. Conclusions: This multidimensional school-based educational intervention may be an effective strategy for establishing healthy behaviors among preschoolers from a diverse and socioeconomically disadvantaged community. Early primordial prevention strategies may contribute to reducing the global burden of cardiovascular disease. (Family-Based Approach in a Minority Community Integrating Systems-Biology for Promotion of Health [FAMILIAThis study is funded by the American Heart Association under grant No. 14SFRN20490315. The CNIC is supported by the Ministerio de Ciencia, Innovación y Universidades and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505). Dr. Fernandez-Jimenez is a recipient of funding from the European Union Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 707642. Dr. Bansilal is an employee of Bayer Pharmaceutical