Local and global growth and remodeling in calcific aortic valve disease and aging

2021 ◽  
pp. 110773
Author(s):  
Mohammadreza Soltany Sadrabadi ◽  
Mona Eskandari ◽  
Heidi P. Feigenbaum ◽  
Amirhossein Arzani
Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 57
Author(s):  
Bongkun Choi ◽  
Eun-Young Kim ◽  
Ji-Eun Kim ◽  
Soyoon Oh ◽  
Si-On Park ◽  
...  

Calcific aortic valve disease (CAVD) accompanies inflammatory cell infiltration, fibrosis, and ultimately calcification of the valve leaflets. We previously demonstrated that dipeptidyl peptidase-4 (DPP-4) is responsible for the progression of aortic valvular calcification in CAVD animal models. As evogliptin, one of the DPP-4 inhibitors displays high specific accumulation in cardiac tissue, we here evaluated its therapeutic potency for attenuating valvular calcification in CAVD animal models. Evogliptin administration markedly reduced calcific deposition accompanied by a reduction in proinflammatory cytokine expression in endothelial nitric oxide synthase-deficient mice in vivo, and significantly ameliorated the mineralization of the primary human valvular interstitial cells (VICs), with a reduction in the mRNA expression of bone-associated and fibrosis-related genes in vitro. In addition, evogliptin ameliorated the rate of change in the transaortic peak velocity and mean pressure gradients in our rabbit model as assessed by echocardiography. Importantly, evogliptin administration in a rabbit model was found to suppress the effects of a high-cholesterol diet and of vitamin D2-driven fibrosis in association with a reduction in macrophage infiltration and calcific deposition in aortic valves. These results have indicated that evogliptin prohibits inflammatory cytokine expression, fibrosis, and calcification in a CAVD animal model, suggesting its potential as a selective therapeutic agent for the inhibition of valvular calcification during CAVD progression.


2021 ◽  
Vol 22 (7) ◽  
pp. 3569
Author(s):  
Beau Olivier van van Driel ◽  
Maike Schuldt ◽  
Sila Algül ◽  
Evgeni Levin ◽  
Ahmet Güclü ◽  
...  

Background: Calcific aortic valve disease (CAVD) is a rapidly growing global health problem with an estimated 12.6 million cases globally in 2017 and a 112% increase of deaths since 1990 due to aging and population growth. CAVD may develop into aortic stenosis (AS) by progressive narrowing of the aortic valve. AS is underdiagnosed, and if treatment by aortic valve replacement (AVR) is delayed, this leads to poor recovery of cardiac function, absence of symptomatic improvement and marked increase of mortality. Considering the current limitations to define the stage of AS-induced cardiac remodeling, there is need for a novel method to aid in the diagnosis of AS and timing of intervention, which may be found in metabolomics profiling of patients. Methods: Serum samples of nine healthy controls and 10 AS patients before and after AVR were analyzed by untargeted mass spectrometry. Multivariate modeling was performed to determine a metabolic profile of 30 serum metabolites which distinguishes AS patients from controls. Human cardiac microvascular endothelial cells (CMECs) were incubated with serum of the AS patients and then stained for ICAM-1 with Western Blot to analyze the effect of AS patient serum on endothelial cell activation. Results: The top 30 metabolic profile strongly distinguishes AS patients from healthy controls and includes 17 metabolites related to nitric oxide metabolism and 12 metabolites related to inflammation, in line with the known pathomechanism for calcific aortic valve disease. Nine metabolites correlate strongly with left ventricular mass, of which three show reversal back to control values after AVR. Western blot analysis of CMECs incubated with AS patient sera shows a significant reduction (14%) in ICAM-1 in AS samples taken after AVR compared to AS patient sera before AVR. Conclusion: Our study defined a top 30 metabolic profile with biological and clinical relevance, which may be used as blood biomarker to identify AS patients in need of cardiac surgery. Future studies are warranted in patients with mild-to-moderate AS to determine if these metabolites reflect disease severity and can be used to identify AS patients in need of cardiac surgery.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jin-Yu Sun ◽  
Yang Hua ◽  
Hui Shen ◽  
Qiang Qu ◽  
Jun-Yan Kan ◽  
...  

Abstract Background Calcific aortic valve disease (CAVD) is the most common subclass of valve heart disease in the elderly population and a primary cause of aortic valve stenosis. However, the underlying mechanisms remain unclear. Methods The gene expression profiles of GSE83453, GSE51472, and GSE12644 were analyzed by ‘limma’ and ‘weighted gene co-expression network analysis (WGCNA)’ package in R to identify differentially expressed genes (DEGs) and key modules associated with CAVD, respectively. Then, enrichment analysis was performed based on Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, DisGeNET, and TRRUST database. Protein–protein interaction network was constructed using the overlapped genes of DEGs and key modules, and we identified the top 5 hub genes by mixed character calculation. Results We identified the blue and yellow modules as the key modules. Enrichment analysis showed that leukocyte migration, extracellular matrix, and extracellular matrix structural constituent were significantly enriched. SPP1, TNC, SCG2, FAM20A, and CD52 were identified as hub genes, and their expression levels in calcified or normal aortic valve samples were illustrated, respectively. Conclusions This study suggested that SPP1, TNC, SCG2, FAM20A, and CD52 might be hub genes associated with CAVD. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.


2017 ◽  
Vol 115 (3) ◽  
pp. E363-E371 ◽  
Author(s):  
Ana M. Porras ◽  
Jennifer A. Westlund ◽  
Austin D. Evans ◽  
Kristyn S. Masters

An insufficient understanding of calcific aortic valve disease (CAVD) pathogenesis remains a major obstacle in developing treatment strategies for this disease. The aim of the present study was to create engineered environments that mimic the earliest known features of CAVD and apply this in vitro platform to decipher relationships relevant to early valve lesion pathobiology. Glycosaminoglycan (GAG) enrichment is a dominant hallmark of early CAVD, but culture of valvular interstitial cells (VICs) in biomaterial environments containing pathological amounts of hyaluronic acid (HA) or chondroitin sulfate (CS) did not directly increase indicators of disease progression such as VIC activation or inflammatory cytokine production. However, HA-enriched matrices increased production of vascular endothelial growth factor (VEGF), while matrices displaying pathological levels of CS were effective at retaining lipoproteins, whose deposition is also found in early CAVD. Retained oxidized low-density lipoprotein (oxLDL), in turn, stimulated myofibroblastic VIC differentiation and secretion of numerous inflammatory cytokines. OxLDL also increased VIC deposition of GAGs, thereby creating a positive feedback loop to further enrich GAG content and promote disease progression. Using this disease-inspired in vitro platform, we were able to model a complex, multistep pathological sequence, with our findings suggesting distinct roles for individual GAGs in outcomes related to valve lesion progression, as well as key differences in cell–lipoprotein interactions compared with atherosclerosis. We propose a pathogenesis cascade that may be relevant to understanding early CAVD and envision the extension of such models to investigate other tissue pathologies or test pharmacological treatments.


Circulation ◽  
2005 ◽  
Vol 111 (24) ◽  
pp. 3316-3326 ◽  
Author(s):  
Rosario V. Freeman ◽  
Catherine M. Otto

Author(s):  
Ramy Abdelmaseih ◽  
Ravi Thakker ◽  
Randa Abdelmasih ◽  
Arroj Ali ◽  
Mustajab Hasan

2021 ◽  
Vol 52 ◽  
pp. 107318
Author(s):  
Kei Shing Oh ◽  
Christopher A. Febres-Aldana ◽  
Nicholas Kuritzky ◽  
Francisco Ujueta ◽  
Ivan A. Arenas ◽  
...  

Oncotarget ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 8665-8674 ◽  
Author(s):  
Guandi Wu ◽  
Jiayi Xian ◽  
Xi Yang ◽  
Jiaying Li ◽  
Jichen Liu ◽  
...  

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