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

Author:

Girdauskas Evaldas,Petersen Johannes,Neumann Niklas,Naito Shiho,Gross Tatiana,Jagodzinski Annika,Reichenspurner Hermann,Zeller Tanja

Abstract

Bicuspid aortic valve (BAV) disease is the most common congenital malformation of the human heart with a prevalence of 1–2% in the general population. More than half of patients with a BAV present with a dilated proximal aorta (so-called bicuspid aortopathy) which is associated with an enhanced risk of life-threatening aortic complications. Up to now, the pathogenesis of bicuspid aortopathy as well as the risk stratification of aortic complications has not yet been sufficiently clarified. Recent findings have shown that bicuspid aortopathy features phenotypic heterogeneity. Two distinct valvulo-aortic phenotypes, the so-called root phenotype, as well as a dilation of the tubular ascending aorta, coincide with a significantly different risk for aortal complications. However, the phenotype-based classification that is only based on these two clinical forms is not sufficient to estimate the risk of aortal complications in a prognostically relevant way. Therefore, there is growing clinical interest to assess novel approaches in BAV research and to introduce circulating biomarkers as an elegant diagnostic tool to improve risk stratification in BAV aortopathy. A large scale epidemiological cohort study, ranking from apparently healthy individuals to disease patients, and comprehensive biobanks provide the opportunity to study BAV disease and its complications and to identify novel biomarkers for BAV aortopathy surveillance and prognosis. Firstly, the data indicate that several protein-based biomarkers and non-coding RNA molecules, in particular circulating microRNAs, can serve as relevant molecular biomarkers to predict the course of BAV-associated aortopathy. Here, we review the current literature and knowledge about BAV from a clinical point of view, and report about novel approaches in BAV biomarker research.

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry

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