Plasma Metabolomic Profiling Associates Bicuspid Aortic Valve Disease and Ascending Aortic Dilation with a Decrease in Antioxidant Capacity

Specific Multiomic Profiling in Aortic Stenosis in Bicuspid Aortic Valve Disease

INTRODUCTION AND PURPOSE

Bicuspid aortic valve (BAV) disease is associated with faster aortic valve degeneration and a high incidence of aortic stenosis (AS). In this study, we aimed to identify differences in the pathophysiology of AS between BAV and tricuspid aortic valve (TAV) patients in a multiomics study integrating metabolomics and transcriptomics as well as clinical data.

METHODS

Eighteen patients underwent aortic valve replacement due to severe aortic stenosis: 8 of them had a TAV, while 10 of them had a BAV. RNA sequencing (RNA-seq) and proton nuclear magnetic resonance spectroscopy (1H-NMR) were performed on these tissue samples to obtain the RNA profile and lipid and low-molecular-weight metabolites. These results combined with clinical data were posteriorly compared, and a multiomic profile specific to AS in BAV disease was obtained.

RESULTS

H-NMR results showed that BAV patients with AS had different metabolic profiles than TAV patients. RNA-seq also showed differential RNA expression between the groups. Functional analysis helped connect this RNA pattern to mitochondrial dysfunction. Integration of RNA-seq, 1H-NMR and clinical data helped create a multiomic profile that suggested that mitochondrial dysfunction and oxidative stress are key players in the pathophysiology of AS in BAV disease.

CONCLUSIONS

The pathophysiology of AS in BAV disease differs from patients with a TAV and has a specific RNA and metabolic profile. This profile was associated with mitochondrial dysfunction and increased oxidative stress.

miR-130a expression is related to aortic dilation in bicuspid aortic valve children

BACKGROUND

Bicuspid aortic valve disease (BAV) is present in 0.5-2% of the population and can promote aortic dilation, eventually leading to fatal consequences. Although some biomarkers have been proposed in adults, no studies have tested these candidates in children. We aimed to evaluate four miRNAs previously described to be related to BAV disease and aortic dilation in adults in a paediatric cohort.

METHODS

Eighty participants ≤17 years old (4-17; mean 12) were included. From the BAV group, 40% had a dilated aorta (z score >2). RT‒qPCR were performed in plasma samples to quantify miR-122, miR-130a, miR-486, and miR-718 using the delta-delta Ct method. Functional and enrichment analyses of miR-130a were also performed.

RESULTS

miR-130a expression in plasma was found to be significantly lower in BAV patients with a dilated aorta versus nondilated patients (p = 0.008) and healthy TAV controls (p = 0.004). Furthermore, miR-130a expression in plasma was inversely correlated with ascending aorta (r = 0.318, p = 0.004) and aortic root z scores (r = 0.322; p = 0.004). Enrichment analysis showed that miR-130a target genes are related to the TGFβ signalling pathway.

CONCLUSIONS

miR-130a expression in plasma is decreased in aortic-dilated BAV children compared to nondilated BAV children, helping differentiate low- to high-risk patients.

IMPACT

miR-130a expression in plasma is related to aortic dilation in bicuspid aortic valve (BAV) children. To our knowledge, this is the first study that analyses miRNA patterns in bicuspid aortic valve children with aortic dilation. miR-130a expression in plasma could be a biomarker in order to help differentiate low-to high-risk BAV children, which is vitally important for advanced care planning.

Glycoprotein and Lipoprotein Profiles Assessed by 1H-NMR and Its Relation to Ascending Aortic Dilatation in Bicuspid Aortic Valve Disease

INTRODUCTION

The bicuspid aortic valve (BAV) confers a high risk of ascending aorta dilatation (AAoD), although its progression seems highly variable. Furthermore, the implication of lipoprotein metabolism and inflammation in the mechanisms that underlie AAoD is not fully established. The aim of this study consisted of evaluating the impact of the lipoprotein and glycoprotein profiles in AAOD as well as its progression in BAV aortopathy.

METHODS

Using 1H-nuclear magnetic resonance (1H-NMR), we analyzed and compared the lipoprotein and glycoprotein profiles of plasma samples from 152 BAV patients with dilated and nondilated ascending aorta. Additionally, these profiles were also compared for 119 of these patients who were prospectively followed-up clinically and by echocardiography in the long-term (5 years). Ascending aorta dilation velocity (mm/year) was calculated for this analysis.

RESULTS

Several parameters related to the lipoprotein profile including remnant cholesterol, small LDL and IDL-cholesterol were found to be significantly increased in the dilated group compared to those in the nondilated group. The glycoprotein A-nuclear magnetic resonance (NMR) signal, a novel inflammation biomarker, was also observed to be increased in the dilated group. After performing multivariate analysis, remnant cholesterol remained an independent variable related to AAoD. In the long-term follow-up, proatherogenic lipoprotein parameters were related to ascending aorta dilatation velocity ascending. After a lineal regression analysis, non-HDL particles remained as an independent predictor of ascending aorta dilation velocity.

CONCLUSIONS

Patients with BAV and AAoD presented a more pro-atherogenic profile assessed by 1H-NMR, especially related to triglyceride-rich lipoproteins. This pro-atherogenic profile seems to contribute to the higher growth rate of ascending aorta diameter.

The Predictive Role of Plasma Biomarkers in the Evolution of Aortopathies Associated with Congenital Heart Malformations

Dilatation of the aorta is a constantly evolving condition that can lead to the ultimate life-threatening event, acute aortic dissection. Recent research has tried to identify quantifiable biomarkers, with both diagnostic and prognostic roles in different aortopathies. Most studies have focused on the bicuspid aortic valve, the most frequent congenital heart disease (CHD), and majorly evolved around matrix metalloproteinases (MMPs). Other candidate biomarkers, such as asymmetric dimethylarginine, soluble receptor for advanced glycation end-products or transforming growth factor beta have also gained a lot of attention recently. Most of the aortic anomalies and dilatation-related studies have reported expression variation of tissular biomarkers. The ultimate goal remains, though, the identification of biomarkers among the serum plasma, with the upregulation of circulating MMP-1, MMP-2, MMP-9, tissue inhibitor of metalloproteinase-1 (TIMP-1), asymmetric dimethylarginine (ADMA), soluble receptor for advanced glycation end-products (sRAGE) and transforming growth factor beta (TGF-β) being reported in association to several aortopathies and related complications in recent research. These molecules are apparently quantifiable from the early ages and have been linked to several CHDs and hereditary aortopathies. Pediatric data on the matter is still limited, and further studies are warranted to elucidate the role of plasmatic biomarkers in the long term follow-up of potentially evolving congenital aortopathies.

Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease

Bicuspid aortic valve (BAV) is the most common congenital heart defect responsible for valvular and aortic complications in affected patients. Causes and mechanisms of this pathology are still elusive and thus the lack of early detection biomarkers leads to challenges in its diagnosis and prevention of associated cardiovascular anomalies. The aim of this study was to explore the potential use of urine Nuclear Magnetic Resonance (NMR) metabolomics to evaluate a molecular fingerprint of BAV. Both multivariate and univariate statistical analyses were performed to compare the urinary metabolome of 20 patients with BAV with that of 24 matched controls. Orthogonal partial least squared discriminant analysis (OPLS-DA) showed statistically significant discrimination between cases and controls, suggesting seven metabolites (3-hydroxybutyrate, alanine, betaine, creatine, glycine, hippurate, and taurine) as potential biomarkers. Among these, glycine, hippurate and taurine individually displayed medium sensitivity and specificity by receiver operating characteristic (ROC) analysis. Pathway analysis indicated two metabolic pathways likely perturbed in BAV subjects. Possible contributions of gut microbiota activity and energy imbalance are also discussed. These results constitute encouraging preliminary findings in favor of the use of urine-based metabolomics for early diagnosis of BAV.

Update in Biomolecular and Genetic Bases of Bicuspid Aortopathy

Bicuspid aortic valve (BAV) associated with aortopathy is the most common congenital heart disease in the general population. Far from being a simple harmless valve malformation, it can be a complex and heterogeneous disease and a source of chronic and acute pathology (early valvular disease, aneurysm, dissection). In the previous years, intense research has been carried out to find out and understand its mechanisms, but the pathophysiology of the disease is still not fully understood and many questions remain open. Recent studies have discovered several genetic mutations involved in the development of valvular and aortic malformations, but still cannot explain more than 5–10% of cases. Other studies have also focused on molecular alterations and cellular processes (TGF-β pathway, microRNAs, degradation of the extracellular matrix, metalloproteinases, etc.), being a field in constant search and development, looking for a therapeutic target to prevent the development of the disease. Increased knowledge about this multifaceted disorder, derived from both basic and clinical research, may influence the diagnosis, follow-up, prognosis, and therapies of affected patients in the near future. This review focuses on the latest and outstanding developments on the molecular and genetic investigations of the bicuspid aortopathy.

Multi-Omics Approaches to Define Calcific Aortic Valve Disease Pathogenesis

Calcific aortic valve disease sits at the confluence of multiple world-wide epidemics of aging, obesity, diabetes, and renal dysfunction, and its prevalence is expected to nearly triple over the next 3 decades. This is of particularly dire clinical relevance, as calcific aortic valve disease can progress rapidly to aortic stenosis, heart failure, and eventually premature death. Unlike in atherosclerosis, and despite the heavy clinical toll, to date, no pharmacotherapy has proven effective to halt calcific aortic valve disease progression, with invasive and costly aortic valve replacement representing the only treatment option currently available. This substantial gap in care is largely because of our still-limited understanding of both normal aortic valve biology and the key regulatory mechanisms that drive disease initiation and progression. Drug discovery is further hampered by the inherent intricacy of the valvular microenvironment: a unique anatomic structure, a complex mixture of dynamic biomechanical forces, and diverse and multipotent cell populations collectively contributing to this currently intractable problem. One promising and rapidly evolving tactic is the application of multiomics approaches to fully define disease pathogenesis. Herein, we summarize the application of (epi)genomics, transcriptomics, proteomics, and metabolomics to the study of valvular heart disease. We also discuss recent forays toward the omics-based characterization of valvular (patho)biology at single-cell resolution; these efforts promise to shed new light on cellular heterogeneity in healthy and diseased valvular tissues and represent the potential to efficaciously target and treat key cell subpopulations. Last, we discuss systems biology- and network medicine-based strategies to extract meaning, mechanisms, and prioritized drug targets from multiomics datasets.