Novel Approaches for BAV Aortopathy Prediction-Is There a Need for Cohort Studies and Biomarkers?

2022 ACC/AHA guideline for the diagnosis and management of aortic disease: A report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate.

STRUCTURE

Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate. Structure: Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate.

STRUCTURE

Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

Identification of hemodynamic biomarkers for bicuspid aortic valve induced aortic dilation using machine learning

Recent advances in medical imaging have confirmed the presence of altered hemodynamics in bicuspid aortic valve (BAV) patients. Therefore, there is a need for new hemodynamic biomarkers to refine disease monitoring and improve patient risk stratification. This research aims to analyze and extract multiple correlation patterns of hemodynamic parameters from 4D Flow MRI data and find which parameters allow an accurate classification between healthy volunteers (HV) and BAV patients with dilated and non-dilated ascending aorta using machine learning. Sixteen hemodynamic parameters were calculated in the ascending aorta (AAo) and aortic arch (AArch) at peak systole from 4D Flow MRI. We used sequential forward selection (SFS) and principal component analysis (PCA) as feature selection algorithms. Then, eleven machine-learning classifiers were implemented to separate HV and BAV patients (non- and dilated ascending aorta). Multiple correlation patterns from hemodynamic parameters were extracted using hierarchical clustering. The linear discriminant analysis and random forest are the best performing classifiers, using five hemodynamic parameters selected with SFS (velocity angle, forward velocity, vorticity, and backward velocity in AAo; and helicity density in AArch) a 96.31 ± 1.76% and 96.00 ± 0.83% accuracy, respectively. Hierarchical clustering revealed three groups of correlated features. According to this analysis, we observed that features selected by SFS have a better performance than those selected by PCA because the five selected parameters were distributed according to 3 different clusters. Based on the proposed method, we concluded that the feature selection method found five potentially hemodynamic biomarkers related to this disease.

Circulating soluble receptor of advanced glycation end product is associated with bicuspid aortic aneurysm progression via NF-κB pathway

 

OBJECTIVES

Patients with bicuspid aortic valve (BAV) have a high risk of aortic dilation and adverse vascular events. Previous studies had reported soluble receptor for advanced glycation end products (sRAGE) to compete with receptor of advanced glycation end products (RAGE) for ligand binding and inhibit the activation of nuclear-factor kappa-B (NF-κB) pathway and matrix metalloproteinases (MMP) transcription. Thus, sRAGE serum levels may contribute to the clinical diagnosis and monitoring of ascending aorta aneurysm in patients with BAV.

METHODS

To eliminate the confounding factors, 44 patients with BAV were divided into 3 subgroups according to the diameter of ascending aorta, and 20 patients with tricuspid aortic valve and normal-sized ascending aorta were selected as a control group. Protein levels and gene transcription of several variates were evaluated in the tissue and serum samples from these patients. Human aortic smooth muscle cells were treated with AGE-BSA in gradient concentrations, and changes in phenotype and protein and mRNA levels were detected.

RESULTS

Serum levels of sRAGE in the 3 BAV groups were obviously higher than those in the tricuspid aortic valve group, although there was negative correlation between the serum sRAGE levels and ascending aortic diameters among patients with BAV. Transcript expression levels of RAGE and NF-κBp65 mRNA were increased in the 3 BAV groups and RAGE/NF-κB pathway was activated with the progression of ascending aortic aneurysm. Abnormal activation of RAGE/NF-κB pathway was observed in AGE-BSA-treated human aortic smooth muscle cells.

CONCLUSIONS

Our study has shown a trend in serum levels of sRAGE among patients with BAV, and that the cellular and extracellular pathological processes are quite serious even in the normal-sized or slightly dilated aorta. Together, the findings indicated that sRAGE may be used as a biomarker to predict aneurysm expansion rates and the risk of adverse vascular events.

Non-Coding RNAs as Blood-Based Biomarkers in Cardiovascular Disease

In 2020, cardiovascular diseases (CVDs) remain a leading cause of mortality and morbidity, contributing to the burden of the already overloaded health system. Late or incorrect diagnosis of patients with CVDs compromises treatment efficiency and patient's outcome. Diagnosis of CVDs could be facilitated by detection of blood-based biomarkers that reliably reflect the current condition of the heart. In the last decade, non-coding RNAs (ncRNAs) present on human biofluids including serum, plasma, and blood have been reported as potential biomarkers for CVDs. This paper reviews recent studies that focus on the use of ncRNAs as biomarkers of CVDs.

Circulating microRNAs vs. aortic diameter in bicuspid aortic valve aortopathy

There is growing clinical need and interest to implement novel risk prediction tools in bicuspid aortic valve-associated proximal aortic disease, so-called bicuspid aortic valve aortopathy. Inherent limitations of the diameter-based risk stratification for adverse aortic events in bicuspid aortic valve aortopathy patients have recently been recognized. Therefore, alternative diagnostic tools and subsequent adjustments in the treatment guidelines are urgently needed. Herein, we summarize the current evidence on recent diagnostic developments to improve risk stratification in bicuspid aortic valve aortopathy, including circulating microRNAs as biomarkers to predict the progression of aortic disease.

An Exploratory Look at Bicuspid Aortic Valve (Bav) Aortopathy: Focus on Molecular and Cellular Mechanisms

Bicuspid aortic valve (BAV) is the most common congenital heart malformation. BAV patients are at increased risk for aortic valve disease (stenosis/regurgitation), infective endocarditis, thrombi formation and, in particular, aortic dilatation, aneurysm and dissection. This review aims at exploring the possible interplay among genetics, extracellular matrix remodeling, abnormal signaling pathways, oxidative stress and inflammation in contributing to BAV-associated aortopathy (BAV-A-A). Novel circulating biomarkers have been proposed as diagnostic tools able to improve risk stratification in BAV-A-A. However, to date, the precise molecular and cellular mechanisms that lead to BAV-A-A remain unknown. Genetic, hemodynamic and cardiovascular risk factors have been implicated in the development and progression of BAV-A-A. Oxidative stress may also play a role, similarly to what observed in atherosclerosis and vulnerable plaque formation. The identification of common pathways between these 2 conditions may provide a platform for future therapeutic solutions.

Epigenetic influences on genetically triggered thoracic aortic aneurysm

Genetically triggered thoracic aortic aneurysms (TAAs) account for 30% of all TAAs and can result in early morbidity and mortality in affected individuals. Epigenetic factors are now recognised to influence the phenotype of many genetically triggered conditions and have become an area of interest because of the potential for therapeutic manipulation. Major epigenetic modulators include DNA methylation, histone modification and non-coding RNA. This review examines epigenetic modulators that have been significantly associated with genetically triggered TAAs and their potential utility for translation to clinical practice.