Transcriptional Profiling of Normal, Stenotic, and Regurgitant Human Aortic Valves

Integrated bioinformatics analysis identified leucine rich repeat containing 15 and secreted phosphoprotein 1 as hub genes for calcific aortic valve disease and osteoarthritis

Calcific aortic valve disease (CAVD) and osteoarthritis (OA) are common diseases in the ageing population and share similar pathogenesis, especially in inflammation. This study aims to discover potential diagnostic and therapeutic targets in patients with CAVD and OA. Three CAVD datasets and one OA dataset were obtained from the Gene Expression Omnibus database. We used bioinformatics methods to search for key genes and immune infiltration, and established a ceRNA network. Immunohistochemical staining was performed to verify the expression of candidate genes in human and mice aortic valve tissues. Two key genes obtained, leucine rich repeat containing 15 (LRRC15) and secreted phosphoprotein 1 (SPP1), were further screened using machine learning and verified in human and mice aortic valve tissues. Compared to normal tissues, the infiltration of immune cells in CAVD tissues was significantly higher, and the expressions of LRRC15 and SPP1 were positively correlated with immune cells infiltration. Moreover, the ceRNA network showed extensive regulatory interactions based on LRRC15 and SPP1. The authors' findings identified LRRC15 and SPP1 as hub genes in immunological mechanisms during CAVD and OA initiation and progression, as well as potential targets for drug development.

Transcriptomic Analysis of Mineralized Adipose-Derived Stem Cell Tissues for Calcific Valve Disease Modelling

Calcific aortic valve disease (CAVD) is characterized by the fibrosis and mineralization of the aortic valve, which leads to aortic stenosis and heart failure. At the cellular level, this is due to the osteoblastic-like differentiation of valve interstitial cells (VICs), resulting in the calcification of the tissue. Unfortunately, human VICs are not readily available to study CAVD pathogenesis and the implicated mechanisms in vitro; however, adipose-derived stromal/stem cells (ASCs), carrying the patient's specific genomic features, have emerged as a promising cell source to model cardiovascular diseases due to their multipotent nature, availability, and patient-specific characteristics. In this study, we describe a comprehensive transcriptomic analysis of tissue-engineered, scaffold-free, ASC-embedded mineralized tissue sheets using bulk RNA sequencing. Bioinformatic and gene set enrichment analyses revealed the up-regulation of genes associated with the organization of the extracellular matrix (ECM), suggesting that the ECM could play a vital role in the enhanced mineralization observed in these tissue-engineered ASC-embedded sheets. Upon comparison with publicly available gene expression datasets from CAVD patients, striking similarities emerged regarding cardiovascular diseases and ECM functions, suggesting a potential link between ECM gene expression and CAVDs pathogenesis. A matrisome-related sub-analysis revealed the ECM microenvironment promotes the transcriptional activation of the master gene runt-related transcription factor 2 (RUNX2), which is essential in CAVD development. Tissue-engineered ASC-embedded sheets with enhanced mineralization could be a valuable tool for research and a promising avenue for the identification of more effective aortic valve replacement therapies.

Identification of hub genes and key signaling pathways by weighted gene co-expression network analysis for human aortic stenosis and insufficiency

Background

Human aortic valve stenosis (AS) and insufficiency (AI) are common diseases in aging population. Identifying the molecular regulatory networks of AS and AI is expected to offer novel perspectives for AS and AI treatment.

Methods

Highly correlated modules with the progression of AS and AI were identified by weighted genes co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by the clusterProfiler program package. Differentially expressed genes (DEGs) were identified by the DESeqDataSetFromMatrix function of the DESeq2 program package. The protein-protein interaction (PPI) network analyses were implemented using the STRING online tool and visualized with Cytoscape software. The DEGs in AS and AI groups were overlapped with the top 30 genes with highest connectivity to screen out ten hub genes. The ten hub genes were verified by analyzing the data in high throughput RNA-sequencing dataset and real-time PCR assay using AS and AI aortic valve samples.

Results

By WGCNA algorithm, 302 highly correlated genes with the degree of AS, degree of AI, and heart failure were identified from highly correlated modules. GO analyses showed that highly correlated genes had close relationship with collagen fibril organization, extracellular matrix organization and extracellular structure organization. KEGG analyses also manifested that protein digestion and absorption, and glutathione metabolism were probably involved in AS and AI pathological courses. Moreover, DEGs were picked out for 302 highly correlated genes in AS and AI groups relative to the normal control group. The PPI network analyses indicated the connectivity among these highly correlated genes. Finally, ten hub genes (CD74, COL1A1, TXNRD1, CCND1, COL5A1, SERPINH1, BCL6, ITGA10, FOS, and JUNB) in AS and AI were found out and verified.

Conclusion

Our study may provide the underlying molecular targets for the mechanism research, diagnosis, and treatment of AS and AI in the future.

Focusing on the Native Matrix Proteins in Calcific Aortic Valve Stenosis

Calcific aortic valve stenosis (CAVS) is a widespread valvular heart disease affecting people in aging societies, primarily characterized by fibrosis, inflammation, and progressive calcification, leading to valve orifice stenosis. Understanding the factors associated with CAVS onset and progression is crucial to develop effective future pharmaceutical therapies. In CAVS, native extracellular matrix proteins modifications, play a significant role in calcification in vitro and in vivo. This work aimed to review the evidence on the alterations of structural native extracellular matrix proteins involved in calcification development during CAVS and highlight its link to deregulated biomechanical function.

Differential expression profiles and functional analysis of long non-coding RNAs in calcific aortic valve disease

AIM

To evaluate the expression profile of long non-coding RNAs (lncRNAs) in calcific aortic valve disease (CAVD) and explore their potential mechanism of action.

METHODS

The gene expression profiles (GSE153555, GSE148219, GSE199718) were downloaded from the Gene Expression Omnibus (GEO) database and FastQC was run for quality control checks. After filtering and classifying candidate lncRNAs by differentially expressed genes (DEGs) and weighted co-expression networks (WGCNA) in GSE153555, we predicted the potential cis- or trans-regulatory target genes of differentially expressed lncRNAs (DELs) by using FEELnc and established the competitive endogenous RNA (ceRNA) network by miRanda, more over functional enrichment was analyzed using the ClusterProfiler package in R Bioconductor. The hub cis- or trans-regulatory genes were verified in GSE148219 and GSE199718 respectively.

RESULTS

There were 340 up-regulated lncRNAs identified in AS group compared with the control group (|log₂Fold Change| ≥ 1.0 and P_adj ≤ 0.05), and 460 down-regulated lncRNAs. Based on target gene prediction and co-expression network construction, twelve Long non-coding RNAs (CDKN2B-AS1, AC244453.2, APCDD1L-DT, SLC12A5-AS1, TGFB3, AC243829.4, MIR4435-2HG, FAM225A, BHLHE40-AS1, LINC01614, AL356417.2, LINC01150) were identified as the hub cis- or trans-regulatory genes in the pathogenesis of CAVD which were validated in GSE148219 and GSE19971. Additionally, we found that MIR4435-2HG was the top hub trans-acting lncRNA which also plays a crucial role by ceRNA pattern.

CONCLUSION

LncRNAs may play an important role in CAVD and may provide a new perspective on the pathogenesis, diagnosis, and treatment of this disease. Further studies are required to illuminate the underlying mechanisms and provide potential therapeutic targets.

Transcriptomic profiling of calcified aortic valves in clonal hematopoiesis of indeterminate potential carriers

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by the presence of clones of mutated blood cells without overt blood diseases. In the last few years, it has emerged that CHIP is associated with atherosclerosis and coronary calcification and that it is an independent determinant of cardiovascular mortality. Recently, CHIP has been found to occur frequently in patients with calcific aortic valve disease (CAVD) and it is associated with a poor prognosis after valve replacement. We assessed the frequency of CHIP by DNA sequencing in the blood cells of 168 CAVD patients undergoing surgical aortic valve replacement or transcatheter aortic valve implantation and investigated the effect of CHIP on 12 months survival. To investigate the pathological process of CAVD in CHIP carriers, we compared by RNA-Seq the aortic valve transcriptome of patients with or without CHIP and non-calcific controls. Transcriptomics data were validated by immunohistochemistry on formalin-embedded aortic valve samples. We confirm that CHIP is common in CAVD patients and that its presence is associated with higher mortality following valve replacement. Additionally, we show, for the first time, that CHIP is often accompanied by a broad cellular and humoral immune response in the explanted aortic valve. Our results suggest that an excessive inflammatory response in CHIP patients may be related to the onset and/or progression of CAVD and point to B cells as possible new effectors of CHIP-induced inflammation.

Identifying hub genes of calcific aortic valve disease and revealing the immune infiltration landscape based on multiple WGCNA and single-cell sequence analysis

BACKGROUND

Calcific aortic valve disease (CAVD) is a progressive fibrocalcific disease that can be treated only through valve replacement. This study aimed to determine the role of hub genes and immune cell infiltration in CAVD progression.

METHODS

In this study, bioinformatics analysis was used to identify hub genes involved in CAVD. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. Gene expression differences were evaluated via pathway and Gene Ontology analyses. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes were used to screen hub genes. The CIBERSORT algorithm was used to compare immune infiltration into the calcified aortic valve based on the hub genes between high- and low-expression groups. We also performed single-cell RNA sequencing based on six different human aortic valve leaflets. The expression of hub genes was identified in human and mouse samples through quantitative real-time polymerase chain reaction (qPCR), immunohistochemistry, immunofluorescence, and ELISA, and clinical features of the patients were investigated.

RESULTS

In total, 454 differentially expressed genes were obtained from the GEO database. WGCNA was used to find 12 co-expression modules in the Array Express database, of which one hub module (brown module) was most correlated with CAVD. Two hub genes were identified after combining the differentially expressed genes S100A8 and S100A9. Regarding these genes, the immune infiltration profiles varied between high- and low-expression groups. Compared with that in the low hub gene expression group, the high hub gene expression group had a higher proportion of activated NK cells (p < 0.01) and M1 macrophages (p < 0.05). The expression of S100A8 and S100A9 was consistent with single-gene RNA sequencing results, confirming that the expression levels of these two hub genes are significantly upregulated in patients with CAVD (p < 0.01). Furthermore, these results were verified using mouse and human samples by performing immunofluorescence, immunohistochemistry, qPCR, and ELISA analyses. Finally, the localization of S100A8 and S100A9 in monocytes and macrophages was confirmed via immunofluorescence using human aortic valves.

CONCLUSION

These results demonstrate that S100A8 and S100A9 are two hub genes involved in CAVD, which might play an important role in its development through immune-related signaling pathways.

Identification of a novel tumour microenvironment-based prognostic biomarker in skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)-based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype-Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16-15, PRSS35, SLC7A10, IGHV1-69D and IGHV2-26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME-based prognostic biomarker in SKCM, and functional analysis enriched immune-related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.

CARDIOKIN1: Computational Assessment of Myocardial Metabolic Capability in Healthy Controls and Patients With Valve Diseases

Supplemental Digital Content is available in the text.

Background:

Many heart diseases can result in reduced pumping capacity of the heart muscle. A mismatch between ATP demand and ATP production of cardiomyocytes is one of the possible causes. Assessment of the relation between myocardial ATP production (MV_ATP) and cardiac workload is important for better understanding disease development and choice of nutritional or pharmacologic treatment strategies. Because there is no method for measuring MV_ATP in vivo, the use of physiology-based metabolic models in conjunction with protein abundance data is an attractive approach.

METHOD:

We developed a comprehensive kinetic model of cardiac energy metabolism (CARDIOKIN1) that recapitulates numerous experimental findings on cardiac metabolism obtained with isolated cardiomyocytes, perfused animal hearts, and in vivo studies with humans. We used the model to assess the energy status of the left ventricle of healthy participants and patients with aortic stenosis and mitral valve insufficiency. Maximal enzyme activities were individually scaled by means of protein abundances in left ventricle tissue samples. The energy status of the left ventricle was quantified by the ATP consumption at rest (MV_ATP[rest]), at maximal workload (MV_ATP[max]), and by the myocardial ATP production reserve, representing the span between MV_ATP(rest) and MV_ATP(max).

Results:

Compared with controls, in both groups of patients, MV_ATP(rest) was increased and MV_ATP(max) was decreased, resulting in a decreased myocardial ATP production reserve, although all patients had preserved ejection fraction. The variance of the energetic status was high, ranging from decreased to normal values. In both patient groups, the energetic status was tightly associated with mechanic energy demand. A decrease of MV_ATP(max) was associated with a decrease of the cardiac output, indicating that cardiac functionality and energetic performance of the ventricle are closely coupled.

Conclusions:

Our analysis suggests that the ATP-producing capacity of the left ventricle of patients with valvular dysfunction is generally diminished and correlates positively with mechanical energy demand and cardiac output. However, large differences exist in the energetic state of the myocardium even in patients with similar clinical or image-based markers of hypertrophy and pump function.

Registration:

URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03172338 and NCT04068740.

Aortic valve disease in diabetes: Molecular mechanisms and novel therapies

Valve disease and particularly calcific aortic valve disease (CAVD) and diabetes (DM) are progressive diseases constituting a global health burden for all aging societies (Progress in Cardiovascular Diseases. 2014;56(6):565: Circulation Research. 2021;128(9):1344). Compared to non‐diabetic individuals (The Lancet. 2008;371(9626):1800: The American Journal of Cardiology. 1983;51(3):403: Journal of the American College of Cardiology. 2017;69(12):1523), the diabetic patients have a significantly greater propensity for cardiovascular disorders and faster degeneration of implanted bioprosthetic aortic valves. Previously, using an original experimental model, the diabetic‐hyperlipemic hamsters, we have shown that the earliest alterations induced by these conditions occur at the level of the aortic valves and, with time these changes lead to calcifications and CAVD. However, there are no pharmacological treatments available to reverse or retard the progression of aortic valve disease in diabetes, despite the significant advances in the field. Therefore, it is critical to uncover the mechanisms of valve disease progression, find biomarkers for diagnosis and new targets for therapies. This review aims at presenting an update on the basic research in CAVD in the context of diabetes. We provide an insight into the accumulated data including our results on diabetes‐induced progressive cell and molecular alterations in the aortic valve, new potential biomarkers to assess the evolution and therapy of the disease, advancement in targeted nanotherapies, tissue engineering and the potential use of circulating endothelial progenitor cells in CAVD.

Proteomics Analysis Reveals Diverse Molecular Characteristics between Endocardial and Aortic-Valvular Endothelium

The variations in the protein profile of aortic-valvular (AVE) and endocardial endothelial (EE) cells are currently unknown. The current study's objective is to identify differentially expressed proteins and associated pathways in both the endothelial cells. We used endothelial cells isolated from the porcine (Sus scrofa) aortic valve and endocardium for the profiling of proteins. Label-free proteomics was performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our proteomics analysis revealed that 29 proteins were highly expressed, and 25 proteins were less expressed in the valve than the endocardial endothelium. The cell surface markers, such as CD63, ICAM1, PECAM1, PROCR, and TFRC, were highly expressed in EE. In contrast, CD44 was highly expressed in AVE. The pathway analysis showed that metabolic process-related proteins and extracellular matrix-related proteins were enriched in valves. Differential enrichment of signaling pathways was observed in the endocardium. The hemostasis function-related proteins were increased in both endothelial cells. The proteins and pathways enriched in aortic-valvular and endocardial endothelial cells revealed the distinct phenotype of these two closely related cells.

Label-Free Multiphoton Microscopy for the Detection and Monitoring of Calcific Aortic Valve Disease

Calcific aortic valve disease (CAVD) is the most common valvular heart disease. CAVD results in a considerable socio-economic burden, especially considering the aging population in Europe and North America. The only treatment standard is surgical valve replacement as early diagnostic, mitigation, and drug strategies remain underdeveloped. Novel diagnostic techniques and biomarkers for early detection and monitoring of CAVD progression are thus a pressing need. Additionally, non-destructive tools are required for longitudinal in vitro and in vivo assessment of CAVD initiation and progression that can be translated into clinical practice in the future. Multiphoton microscopy (MPM) facilitates label-free and non-destructive imaging to obtain quantitative, optical biomarkers that have been shown to correlate with key events during CAVD progression. MPM can also be used to obtain spatiotemporal readouts of metabolic changes that occur in the cells. While cellular metabolism has been extensively explored for various cardiovascular disorders like atherosclerosis, hypertension, and heart failure, and has shown potential in elucidating key pathophysiological processes in heart valve diseases, it has yet to gain traction in the study of CAVD. Furthermore, MPM also provides structural, functional, and metabolic readouts that have the potential to correlate with key pathophysiological events in CAVD progression. This review outlines the applicability of MPM and its derived quantitative metrics for the detection and monitoring of early CAVD progression. The review will further focus on the MPM-detectable metabolic biomarkers that correlate with key biological events during valve pathogenesis and their potential role in assessing CAVD pathophysiology.

TNRC6C Functions as a Tumor Suppressor and Is Frequently Downregulated in Papillary Thyroid Cancer

Our previous study found that trinucleotide repeat containing adaptor 6C (TNRC6C) may act as a tumor suppressor in papillary thyroid cancer (PTC). In this study, we aimed to confirm the effect of TNRC6C on PTC and investigate the underlying molecular mechanism. The difference of mRNA level of TNRC6C between PTC tissue and noncancerous thyroid tissue and the association of expression level of TNRC6C with clinicopathological features of PTC were analyzed using TCGA data. Immunohistochemical assay was performed to detect the protein expression of TNRC6C in PTC and its adjacent noncancerous tissue. Cell proliferation, migration, invasion, and apoptosis were analyzed after knockdown or overexpression of TNRC6C in BCPAP cells. RNA-sequencing was performed to find the target genes of TNRC6C, and potential targets were validated in BCPAP and TPC1 cells. Our results showed that TNRC6C was downregulated in PTC, and lower expression level of TNRC6C was associated with worse clinicopathological features. Overexpression of TNRC6C significantly inhibited proliferation, migration, and invasion of BCPAP cells and promoted its apoptosis, while knockdown of TNRC6C acted the opposite role. By analyzing RNA-sequencing data and TCGA data, 12 genes (SCD, CRLF1, APCDD1L, CTHRC1, PTPRU, ALDH1A3, VCAN, TNC, ECE1, COL1A1, CAMK2N2, and MMP14) were considered as potential target genes of TNRC6C, and most of them were associated with clinicopathological features of PTC in TCGA. All of them except CAMK2N2 were significantly downregulated after overexpressing TNRC6C. Our study demonstrated that TNRC6C functions as a tumor suppressor in PTC and may serve as a useful therapeutic target and prognostic marker for PTC patients.