Metabolomic Signature of Human Aortic Valve Stenosis

Insights into the Inherited Basis of Valvular Heart Disease

PURPOSE OF REVIEW: Increases in the availability of genetic data and advances in the tools and methods for their analyses have enabled well-powered genetic association studies that have significantly enhanced our understanding of the genetic factors underlying both rare and common valve diseases. Valvular heart diseases, such as congenital valve malformations and degenerative valve lesions, increase the risk of heart failure, arrhythmias, and sudden death. In this review, we provide an updated overview of our current understanding of the genetic mechanisms underlying valvular heart diseases. With a focus on discoveries from the past 5 years, we describe recent insights into genetic risk and underlying biological pathways. RECENT FINDINGS: Recently acquired knowledge around valvular heart disease genetics has provided important insights into novel mechanisms related to disease pathogenesis. Newly identified risk loci associated valvular heart disease mainly regulate the composition of the extracellular matrix, accelerate the endothelial-to-mesenchymal transition, contribute to cilia formation processes, and play roles in lipid metabolism. Large-scale genomic analyses have identified numerous risk loci, genes, and biological pathways associated with degenerative valve disease and congenital valve malformations. Shared risk genes suggest common mechanistic pathways for various valve pathologies. More recent studies have combined cardiac magnetic resonance imaging and machine learning to offer a novel approach for exploring genotype-phenotype relationships regarding valve disease. Progress in the field holds promise for targeted prevention, particularly through the application of polygenic risk scores, and innovative therapies based on the biological mechanisms for predominant forms of valvular heart diseases.

The future of valvular heart disease assessment and therapy

Valvular heart disease (VHD) is becoming more prevalent in an ageing population, leading to challenges in diagnosis and management. This two-part Series offers a comprehensive review of changing concepts in VHD, covering diagnosis, intervention timing, novel management strategies, and the current state of research. The first paper highlights the remarkable progress made in imaging and transcatheter techniques, effectively addressing the treatment paradox wherein populations at the highest risk of VHD often receive the least treatment. These advances have attracted the attention of clinicians, researchers, engineers, device manufacturers, and investors, leading to the exploration and proposal of treatment approaches grounded in pathophysiology and multidisciplinary strategies for VHD management. This Series paper focuses on innovations involving computational, pharmacological, and bioengineering approaches that are transforming the diagnosis and management of patients with VHD. Artificial intelligence and digital methods are enhancing screening, diagnosis, and planning procedures, and the integration of imaging and clinical data is improving the classification of VHD severity. The emergence of artificial intelligence techniques, including so-called digital twins-eg, computer-generated replicas of the heart-is aiding the development of new strategies for enhanced risk stratification, prognostication, and individualised therapeutic targeting. Various new molecular targets and novel pharmacological strategies are being developed, including multiomics-ie, analytical methods used to integrate complex biological big data to find novel pathways to halt the progression of VHD. In addition, efforts have been undertaken to engineer heart valve tissue and provide a living valve conduit capable of growth and biological integration. Overall, these advances emphasise the importance of early detection, personalised management, and cutting-edge interventions to optimise outcomes amid the evolving landscape of VHD. Although several challenges must be overcome, these breakthroughs represent opportunities to advance patient-centred investigations.

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates, such as fatty acids, carbohydrates, lipids, and amino acids, to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities, which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection: direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF-MS/MS). Using DI-FTICR MS, 9644 metabolic features were detected where 7156 were assigned a molecular formula and 1107 were annotated by accurate mass assignment. Using LC-Q-TOF-MS/MS, 21,428 metabolic features were detected where 285 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 1340 heart metabolites were identified in this study, which span a wide range of polarities including polar (benzenoids, carbohydrates, and nucleosides) as well as nonpolar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results from this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.

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.

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates such as fatty acids, carbohydrates, lipids, and amino acids to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic extractions) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection - direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF MS/MS). Using DI-FTICR MS, 9,521 metabolic features were detected where 7,699 were assigned a chemical formula and 1,756 were assigned an annotated by accurate mass assignment. Using LC-Q-TOF MS/MS, 21,428 metabolic features were detected where 626 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 2276 heart metabolites were identified in this study which span a wide range of polarities including polar (benzenoids, alkaloids and derivatives and nucleosides) as well as non-polar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results of this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.

Metabolic systems approaches update molecular insights of clinical phenotypes and cardiovascular risk in patients with homozygous familial hypercholesterolemia

BACKGROUND

Homozygous familial hypercholesterolemia (HoFH) is an orphan metabolic disease characterized by extremely elevated low-density lipoprotein cholesterol (LDL-C), xanthomas, aortic stenosis, and premature atherosclerotic cardiovascular disease (ASCVD). In addition to LDL-C, studies in experimental models and small clinical populations have suggested that other types of metabolic molecules might also be risk factors responsible for cardiovascular complications in HoFH, but definitive evidence from large-scale human studies is still lacking. Herein, we aimed to comprehensively characterize the metabolic features and risk factors of human HoFH by using metabolic systems strategies.

METHODS

Two independent multi-center cohorts with a total of 868 individuals were included in the cross-sectional study. First, comprehensive serum metabolome/lipidome-wide analyses were employed to identify the metabolomic patterns for differentiating HoFH patients (n = 184) from heterozygous FH (HeFH, n = 376) and non-FH (n = 100) subjects in the discovery cohort. Then, the metabolomic patterns were verified in the validation cohort with 48 HoFH patients, 110 HeFH patients, and 50 non-FH individuals. Subsequently, correlation/regression analyses were performed to investigate the associations of clinical/metabolic alterations with typical phenotypes of HoFH. In the prospective study, a total of 84 HoFH patients with available follow-up were enrolled from the discovery cohort. Targeted metabolomics, deep proteomics, and random forest approaches were performed to investigate the ASCVD-associated biomarkers in HoFH patients.

RESULTS

Beyond LDL-C, various bioactive metabolites in multiple pathways were discovered and validated for differentiating HoFH from HoFH and non-FH. Our results demonstrated that the inflammation and oxidative stress-related metabolites in the pathways of arachidonic acid and lipoprotein(a) metabolism were independently associated with the prevalence of corneal arcus, xanthomas, and supravalvular/valvular aortic stenosis in HoFH patients. Our results also identified a small marker panel consisting of high-density lipoprotein cholesterol, lipoprotein(a), apolipoprotein A1, and eight proinflammatory and proatherogenic metabolites in the pathways of arachidonic acid, phospholipid, carnitine, and sphingolipid metabolism that exhibited significant performances on predicting first ASCVD events in HoFH patients.

CONCLUSIONS

Our findings demonstrate that human HoFH is associated with a variety of metabolic abnormalities and is more complex than previously known. Furthermore, this study provides additional metabolic alterations that hold promise as residual risk factors in HoFH population.

Network-Guided Multiomic Mapping of Aortic Valve Calcification

Despite devastating clinical sequelae of calcific aortic valve disease that range from left ventricular remodeling to arrhythmias, heart failure, and early death, the molecular insights into disease initiation and progression are limited and pharmacotherapies remain unavailable. The pathobiology of calcific aortic valve disease is complex and comprehensive studies are challenging valvular calcification is heterogeneous and occurs preferentially on the aortic surface, along a fibrocalcific spectrum. Here, we review efforts to study (epi-)genomic, transcriptomic, proteomic, and metabolomic aspects of aortic valve calcification in combination with network medicine-/systems biology-based strategies to integrate multilayered omics datasets and prioritize druggable targets for experimental validation studies. Ultimately, such holistic approach efforts may open therapeutic avenues that go beyond invasive and costly valve replacement therapy.

Atractylodin targets GLA to regulate D-mannose metabolism to inhibit osteogenic differentiation of human valve interstitial cells and ameliorate aortic valve calcification

Atractylodin (ATL) has been reported to exert anti-inflammatory effects. Osteogenic changes induced by inflammation in valve interstitial cells (VICs) play a key role in the development of calcified aortic valve disease (CAVD). This study aimed to investigate the anti-calcification effects of ATL on aortic valves. Human VICs (hVICs) were exposed to osteogenic induction medium (OM) containing ATL to investigate cell viability, osteogenic gene and protein expression, and anti-calcification effects. Gas chromatography-mass spectroscopy (GC-MS) metabolomics analysis was used to detect changes in the metabolites of hVICs stimulated with OM before and after ATL administration. The compound-reaction-enzyme-gene network was used to identify drug targets. Gene interference was used to verify the targets. ApoE-/- mice fed a high-fat (HF) diet were used to evaluate the inhibition of aortic valve calcification by ATL. Treatment with 20 μM ATL in OM prevented calcified nodule accumulation and decreases in the gene and protein expression levels of ALP, RUNX2, and IL-1β. Differential metabolite analysis showed that D-mannose was highly associated with the anti-calcification effect of ATL. The addition of D-mannose prevented calcified nodule accumulation and inhibited succinate-mediated HIF-1α activation and IL-1β production. The target of ATL was identified as GLA. Silencing of the GLA gene (si-GLA) reversed the anti-osteogenic differentiation of ATL. In vivo, ATL ameliorated aortic valve calcification by preventing decreases in GLA expression and the up-regulation of IL-1β expression synchronously. In conclusion, ATL is a potential drug for the treatment of CAVD by targeting GLA to regulate D-mannose metabolism, thereby inhibiting succinate-mediated HIF-1α activation and IL-1β production.

Integrated proteomic and metabolomic profile analyses of cardiac valves revealed molecular mechanisms and targets in calcific aortic valve disease

Background

This study aimed to define changes in the metabolic and protein profiles of patients with calcific aortic valve disease (CAVD).

Methods and results

We analyzed cardiac valve samples of patients with and without (control) CAVD (n = 24 per group) using untargeted metabolomics and tandem mass tag-based quantitative proteomics. Significantly different metabolites and proteins between the CAVD and control groups were screened; then, functional enrichment was analyzed. We analyzed co-expressed differential metabolites and proteins, and constructed a metabolite-protein-pathway network. The expression of key proteins was validated using western blotting. Differential analysis identified 229 metabolites in CAVD among which, 2-aminophenol, hydroxykynurenine, erythritol, carnosine, and choline were the top five. Proteomic analysis identified 549 differentially expressed proteins in CAVD, most of which were localized in the nuclear, cytoplasmic, extracellular, and plasma membranes. Levels of selenium binding protein 1 (SELENBP1) positively correlated with multiple metabolites. Adenosine triphosphate-binding cassette transporters, starch and sucrose metabolism, hypoxia-inducible factor 1 (HIF-1) signaling, and purine metabolism were key pathways in the network. Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), calcium²⁺/calmodulin-dependent protein kinase II delta (CAMK2D), and ATP binding cassette subfamily a member 8 (ABCA8) were identified as hub proteins in the metabolite-protein-pathway network as they interacted with ADP, glucose 6-phosphate, choline, and other proteins. Western blotting confirmed that ENPP1 was upregulated, whereas ABCA8 and CAMK2D were downregulated in CAVD samples.

Conclusion

The metabolic and protein profiles of cardiac valves from patients with CAVD significantly changed. The present findings provide a holistic view of the molecular mechanisms underlying CAVD that may lead to the development of novel diagnostic biomarkers and therapeutic targets to treat CAVD.

Lipids and cardiovascular calcification: contributions to plaque vulnerability

PURPOSE OF REVIEW

Cardiovascular calcification, a common feature of atherosclerotic lesions, has long been known to associate with cardiovascular risk. The roles of lipoproteins in atherosclerosis are also established, and lipid-modifying therapies have shown capacity for plaque regression. However, the association of lipid-modifying therapies with calcification is more complex, and currently no medical therapies have been found to reverse or attenuate calcification in patients. In this review, we summarize recent developments in our understanding of the interplay between lipids and cardiovascular calcification, as well as new imaging modalities for assessing calcified atherosclerotic plaque vulnerability.

RECENT FINDINGS

Recent clinical studies have highlighted the associations of lipoprotein subtypes, such as low-density and high-density lipoprotein particles, as well as lipoprotein (a) [Lp(a)], with coronary calcification and calcific aortic valve disease. Further, evidence continues to emerge for the utility of fused 18F-sodium fluoride positron-emission tomographic and computed tomographic (18F-NaF PET/CT) imaging in characterizing the microarchitecture and vulnerability of atherosclerotic plaque, in both humans and animal models.

SUMMARY

The relationship between lipids and cardiovascular calcification is complex, and new imaging techniques, such as 18F-NaF PET/CT imaging, may allow for better identification of disease-modifying therapies and prediction of calcified plaque progression and stability to help guide clinical management.

Diabetes Mellitus and Its Implications in Aortic Stenosis Patients

Aortic stenosis (AS) and diabetes mellitus (DM) are both progressive diseases that if left untreated, result in significant morbidity and mortality. Several studies revealed that the prevalence of DM is substantially higher in patients with AS and, thus, the progression from mild to severe AS is greater in those patients with DM. DM and common comorbidities associated with both diseases, DM and AS, increase patient management complexity and make aortic valve replacement the only effective treatment. For that reason, a better understanding of the pathogenesis underlying both these diseases and the relationships between them is necessary to design more appropriate preventive and therapeutic approaches. In this review, we provided an overview of the main aspects of the relationship between AS and DM, including common comorbidities and risk factors. We also discuss the established treatments/therapies in patients with AS and DM.

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.