Exploring potential genes and pathways related to calcific aortic valve disease

Cathepsin D elevates the fibrocalcific activity in human aortic valve cells through the ERK1/2-Sox9 pathway

Background

Human Aortic valve interstitial cells (AVICs) from calcific aortic valve disease (CAVD)-affected valves exhibit elevated fibrocalcific activity although the underlying mechanism remains incompletely understood. This study aimed to identify endogenous factors that promote aortic valve fibrocalcification.

Methods and results

Proteomic analysis found increased cathepsin D levels in AVICs from CAVD-affected valves compared to AVICs from normal valves, and this finding was validated by immunoblotting. ELISA assay identified exacerbated release of cathepsin D by AVICs of diseased valves. Recombinant human cathepsin D upregulated the expression of runt-related transcription factor 2 (Runx2), alkaline phosphatase (ALP), collagen I and collagen IV in human AVICs, resulting in the deposition of calcium and collagen. Blocking of the ERK1/2-Sox9 signaling pathway markedly reduced the pro-fibrocalcific effect of cathepsin D. Moreover, normal AVICs express and release greater levels of cathepsin D when exposed to soluble matrilin 2. Knockdown of cathepsin D attenuated the fibrocalcific response induced by soluble matrilin 2.

Conclusion

AVICs of diseased aortic valves produce and release greater levels of cathepsin D that exerts a pro-fibrocalcific effect on AVICs through the ERK1/2-Sox9 pathway. Soluble matrilin 2 up-regulates cathepsin D to elevate AVIC fibrocalcific activity. Over-expression of cathepsin D in the aortic valve may enhance the pathobiological activities in AVICs.

Nesfatin-1 mitigates calcific aortic valve disease via suppressing ferroptosis mediated by GSH/GPX4 and ZIP8/SOD2 axes

OBJECTIVE

Calcific aortic valve disease (CAVD) predominantly affects the elderly and currently lacks effective medical treatments. Nesfatin-1, a peptide derived from the cleavage of Nucleobindin 2, has been implicated in various calcification processes, both physiological and pathological. This study explores the impact of Nesfatin-1 on the transformation of aortic valve interstitial cells (AVICs) in CAVD.

METHODS AND RESULTS

In vitro experiments showed that Nesfatin-1 treatment mitigated the osteogenic differentiation of AVICs. Corresponding in vivo studies demonstrated a deceleration in the progression of CAVD. RNA-sequencing of AVICs treated with and without Nesfatin-1 highlighted an enrichment of the Ferroptosis pathway among the top pathways identified by the Kyoto Encyclopedia of Genes and Genomes analysis. Further examination confirmed increased ferroptosis in both calcified valves and osteoblast-like AVICs, with a reduction in ferroptosis following Nesfatin-1 treatment. Within the Ferroptosis pathway, ZIP8 showed the most notable modulation by Nesfatin-1. Silencing ZIP8 in AVICs increased ferroptosis and osteogenic differentiation, decreased intracellular Mn2+ concentration, and reduced the expression and activity of superoxide dismutase (SOD2). Furthermore, the silencing of SOD2 exacerbated ferroptosis and osteogenic differentiation. Nesfatin-1 treatment was found to elevate the expression of glutathione peroxidase 4 (GPX4) and levels of glutathione (GSH), as confirmed by Western blotting and GSH concentration assays.

CONCLUSION

In summary, Nesfatin-1 effectively inhibits the osteogenic differentiation of AVICs by attenuating ferroptosis, primarily through the GSH/GPX4 and ZIP8/SOD2 pathways.

Gallic acid pretreatment mitigates parathyroid ischemia-reperfusion injury through signaling pathway modulation

Thyroid surgery often results in ischemia-reperfusion injury (IRI) to the parathyroid glands, yet the mechanisms underlying this and how to ameliorate IRI remain incompletely explored. Our study identifies a polyphenolic herbal extract-gallic acid (GA)-with antioxidative properties against IRI. Through flow cytometry and CCK8 assays, we investigate the protective effects of GA pretreatment on a parathyroid IRI model and decode its potential mechanisms via RNA-seq and bioinformatics analysis. Results reveal increased apoptosis, pronounced G1 phase arrest, and significantly reduced cell proliferation in the hypoxia/reoxygenation group compared to the hypoxia group, which GA pretreatment mitigates. RNA-seq and bioinformatics analysis indicate GA's modulation of various signaling pathways, including IL-17, AMPK, MAPK, transient receptor potential channels, cAMP, and Rap1. In summary, GA pretreatment demonstrates potential in protecting parathyroid cells from IRI by influencing various genes and signaling pathways. These findings offer a promising therapeutic strategy for hypoparathyroidism treatment.

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.

Atorvastatin reduces calcification in valve interstitial cells via the NF-κB signalling pathway by promoting Atg5-mediated autophagy

Aortic valve calcification (AVC) is a common cardiovascular disease and a risk factor for sudden death. However, the potential mechanisms and effective therapeutic drugs need to be explored. Atorvastatin is a statin that can effectively prevent cardiovascular events by lowering cholesterol levels. However, whether atorvastatin can inhibit AVC by reducing low-density lipoprotein (LDL) and its possible mechanism of action require further exploration. In the current study, we constructed an in vitro AVC model by inducing calcification of the valve interstitial cells. We found that atorvastatin significantly inhibited osteogenic differentiation, reduced the deposition of calcium nodules in valve interstitial cells, and enhanced autophagy in calcified valve interstitial cells, manifested by increased expression levels of the autophagy proteins Atg5 and LC3B-II/I and the formation of smooth autophagic flow. Atorvastatin inhibited the NF-κB signalling pathway and the expression of inflammatory factors mediated by NF-κB in calcified valve interstitial cells. The activation of the NF-κB signalling pathway led to the reversal of atorvastatin's effect on enhancing autophagy and alleviating valve interstitial cell calcification. In conclusion, atorvastatin inhibited the NF-κB signalling pathway by upregulating autophagy, thereby alleviating valve interstitial cell calcification, which was conducive to improving AVC.

Indoxyl Sulfate-Induced Valve Endothelial Cell Endothelial-to-Mesenchymal Transition and Calcification in an Integrin-Linked Kinase-Dependent Manner

Calcific Aortic Valve Disease (CAVD) is a significant concern for cardiovascular health and is closely associated with chronic kidney disease (CKD). Aortic valve endothelial cells (VECs) play a significant role in the onset and progression of CAVD. Previous research has suggested that uremic toxins, particularly indoxyl sulfate (IS), induce vascular calcification and endothelial dysfunction, but the effect of IS on valve endothelial cells (VECs) and its contribution to CAVD is unclear. Our results show that IS reduced human VEC viability and increased pro-calcific markers RUNX2 and alkaline phosphatase (ALP) expression. Additionally, IS-exposed VECs cultured in pro-osteogenic media showed increased calcification. Mechanistically, IS induced endothelial-to-mesenchymal transition (EndMT), evidenced by the loss of endothelial markers and increased expression of mesenchymal markers. IS triggered VEC inflammation, as revealed by NF-kB activation, and decreased integrin-linked kinase (ILK) expression. ILK overexpression reversed the loss of endothelial phenotype and RUNX2, emphasizing its relevance in the pathogenesis of CAVD in CKD. Conversely, a lower dose of IS intensified some of the effects in EndMT caused by silencing ILK. These findings imply that IS affects valve endothelium directly, contributing to CAVD by inducing EndMT and calcification, with ILK acting as a crucial modulator.

Lp(a) in the Pathogenesis of Aortic Stenosis and Approach to Therapy with Antisense Oligonucleotides or Short Interfering RNA

To date, no medical therapy can slow the progression of aortic stenosis. Fibrocalcific stenosis is the most frequent form in the general population and affects about 6% of the elderly population. Over the years, diagnosis has evolved thanks to echocardiography and computed tomography assessments. The application of artificial intelligence to electrocardiography could further implement early diagnosis. Patients with severe aortic stenosis, especially symptomatic patients, have valve repair as their only therapeutic option by surgical or percutaneous technique (TAVI). The discovery that the pathogenetic mechanism of aortic stenosis is similar to the atherosclerosis process has made it possible to evaluate the hypothesis of medical therapy for aortic stenosis. Several drugs have been tested to reduce low-density lipoprotein (LDL) and lipoprotein(a) (Lp(a)) levels, inflammation, and calcification. The Proprotein Convertase Subtilisin/Kexin type 9 inhibitors (PCSK9-i) could decrease the progression of aortic stenosis and the requirement for valve implantation. Great interest is related to circulating Lp(a) levels as causally linked to degenerative aortic stenosis. New therapies with ASO (antisense oligonucleotides) and siRNA (small interfering RNA) are currently being tested. Olpasiran and pelacarsen reduce circulating Lp(a) levels by 85-90%. Phase 3 studies are underway to evaluate the effect of these drugs on cardiovascular events (cardiovascular death, non-fatal myocardial injury, and non-fatal stroke) in patients with elevated Lp(a) and CVD (cardiovascular diseases). For instance, if a reduction in Lp(a) levels is associated with aortic stenosis prevention or progression, further prospective clinical trials are warranted to confirm this observation in this high-risk population.

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.

CircRNA/lncRNA-miRNA-mRNA network and gene landscape in calcific aortic valve disease

BACKGROUND

Calcific aortic valve disease (CAVD) is a common valve disease with an increasing incidence, but no effective drugs as of yet. With the development of sequencing technology, non-coding RNAs have been found to play roles in many diseases as well as CAVD, but no circRNA/lncRNA-miRNA-mRNA interaction axis has been established. Moreover, valve interstitial cells (VICs) and valvular endothelial cells (VECs) play important roles in CAVD, and CAVD differed between leaflet phenotypes and genders. This work aims to explore the mechanism of circRNA/lncRNA-miRNA-mRNA network in CAVD, and perform subgroup analysis on the important characteristics of CAVD, such as key cells, leaflet phenotypes and genders.

RESULTS

We identified 158 differentially expressed circRNAs (DEcircRNAs), 397 DElncRNAs, 45 DEmiRNAs and 167 DEmRNAs, and constructed a hsa-circ-0073813/hsa-circ-0027587-hsa-miR-525-5p-SPP1/HMOX1/CD28 network in CAVD after qRT-PCR verification. Additionally, 17 differentially expressed genes (DEGs) in VICs, 9 DEGs in VECs, 7 DEGs between different leaflet phenotypes and 24 DEGs between different genders were identified. Enrichment analysis suggested the potentially important pathways in inflammation and fibro-calcification during the pathogenesis of CAVD, and immune cell patterns in CAVD suggest that M0 macrophages and memory B cells memory were significantly increased, and many genes in immune cells were also differently expressed.

CONCLUSIONS

The circRNA/lncRNA-miRNA-mRNA interaction axis constructed in this work and the DEGs identified between different characteristics of CAVD provide a direction for a deeper understanding of CAVD and provide possible diagnostic markers and treatment targets for CAVD in the future.

Oxidized phospholipids facilitate calcific aortic valve disease by elevating ATF4 through the PERK/eIF2α axis

In this study we sought to analyze the critical role of oxidized phospholipid (OxPL) in the progression of calcific aortic valve disease (CAVD) with the involvement of activating transcription factor 4 (ATF4). Differentially expressed genes related to CAVD were identified using bioinformatics analysis. Expression of ATF4 was examined in mouse models of aortic valve calcification (AVC) induced by the high cholesterol (HC) diet. Valvular interstitial cells (VICs) were then isolated from mouse non-calcified valve tissues, induced by osteogenic induction medium (OIM) and co-cultured with OxPAPC-stimulated macrophages. The effect of OxPLs regulating ATF4 on the macrophage polarization and osteogenic differentiation of VICs was examined with gain- and loss-of-function experiments in VICs and in vivo. In aortic valve tissues and OIM-induced VICs, ATF4 was highly expressed. ATF4 knockdown alleviated the osteogenic differentiation of VICs, as evidenced by reduced expression of bone morphogenetic protein-2 (BMP2), osteopontin (OPN), and osteocalcin. In addition, knockdown of ATF4 arrested the AVC in vivo. Meanwhile, OxPL promoted M1 polarization of macrophages and mediated osteogenic differentiation of VICs. Furthermore, OxPL up-regulated ATF4 expression through protein kinase R-like endoplasmic reticulum kinase (PERK)/eukaryotic translation initiation factor 2 subunit alpha (eIF2α) pathway. In conclusion, OxPL can potentially up-regulate the expression of ATF4, inducing macrophages polarized to M1 phenotype, osteogenic differentiation of VICs and AVC, thus accelerating the progression of CAVD.

Multiscale model for blood flow after a bileaflet artificial aortic valve implantation

Cardiovascular diseases are the leading cause of mortality in the world, mainly due to atherosclerosis and its consequences. The article presents the numerical model of the blood flow through artificial aortic valve. The overset mesh approach was applied to simulate the valve leaflets motion and to realize the moving mesh, in the aortic arch and the main branches of cardiovascular system. To capture the cardiac system's response and the effect of vessel compliance on the outlet pressure, the lumped parameter model has been also included within the solution procedure. Three different turbulence modeling approaches were used and compared - the laminar, k-ϵ and k-ω model. The simulation results were also compared with the model excluding the moving valve geometry and the importance of the lumped parameter model for the outlet boundary condition was analyzed. Proposed numerical model and protocol was found as suitable for performing the virtual operations on the real patient vasculature geometry. The time-efficient turbulence model and overall solving procedure allows to support the clinicians in making decisions about the patient treatment and to predict the results of the future surgery.

Molecular Mechanisms Underlying the Progression of Aortic Valve Stenosis: Bioinformatic Analysis of Signal Pathways and Hub Genes

The calcification of the aortic valve causes increased leaflet stiffness and leads to the development and progression of stenotic aortic valve disease. However, the molecular and cellular mechanisms underlying stenotic calcification remain poorly understood. Herein, we examined the gene expression associated with valve calcification and the progression of calcific aortic valve stenosis. We downloaded two publicly available gene expression profiles (GSE83453 and GSE51472) from NCBI-Gene Expression Omnibus database for the combined analysis of samples from human aortic stenosis and normal aortic valve tissue. After identifying the differentially expressed genes (DEGs) using the GEO2R online tool, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We also analyzed the protein-protein interactions (PPIs) of the DEGs using the NetworkAnalyst online tool. We identified 4603 upregulated and 6272 downregulated DEGs, which were enriched in the positive regulation of cell adhesion, leukocyte-mediated immunity, response to hormones, cytokine signaling in the immune system, lymphocyte activation, and growth hormone receptor signaling. PPI network analysis identified 10 hub genes: VCAM1, FHL2, RUNX1, TNFSF10, PLAU, SPOCK1, CD74, SIPA1L2, TRIB1, and CXCL12. Through bioinformatic analysis, we identified potential biomarkers and therapeutic targets for aortic stenosis, providing a theoretical basis for future studies.

Exploration and validation of the influence of angiogenesis-related factors in aortic valve calcification

Over the years, bioinformatics tools have been used to identify functional genes. In the present study, bioinformatics analyses were conducted to explore the underlying molecular mechanisms of angiogenic factors in calcific aortic valve disease (CAVD). The raw gene expression profiles were from datasets GSE153555, GSE83453, and GSE51472, and the angiogenesis-related gene set was from the Gene Set Enrichment Analysis database (GSEA). In this study, R was used to screen for differentially expressed genes (DEGs) and co-expressed genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) Pathway enrichment analysis were performed on DEGs and validated in clinical samples. DEGs in CAVD were significantly enriched in numerous immune response pathways, inflammatory response pathways and angiogenesis-related pathways. Nine highly expressed angiogenesis-related genes were identified, of which secretogranin II (SCG2) was the most critical gene. MiRNA and transcription factors (TFs) networks were established centered on five DEGs, and zinc finger E-box binding homeobox 1 (ZEB1) was the most important transcription factor, verified by PCR, immunohistochemical staining and western blotting experiments. Overall, this study identified key genes and TFs that may be involved in the pathogenesis of CAVD and may have promising applications in the treatment of CAVD.

Development and analysis of a comprehensive diagnostic model for aortic valve calcification using machine learning methods and artificial neural networks

BACKGROUND

Although advanced surgical and interventional treatments are available for advanced aortic valve calcification (AVC) with severe clinical symptoms, early diagnosis, and intervention is critical in order to reduce calcification progression and improve patient prognosis. The aim of this study was to develop therapeutic targets for improving outcomes for patients with AVC.

MATERIALS AND METHODS

We used the public expression profiles of individuals with AVC (GSE12644 and GSE51472) to identify potential diagnostic markers. First, the R software was used to identify differentially expressed genes (DEGs) and perform functional enrichment analysis. Next, we combined bioinformatics techniques with machine learning methodologies such as random forest algorithms and support vector machines to screen for and identify diagnostic markers of AVC. Subsequently, artificial neural networks were employed to filter and model the diagnostic characteristics for AVC incidence. The diagnostic values were determined using the receiver operating characteristic (ROC) curves. Furthermore, CIBERSORT immune infiltration analysis was used to determine the expression of different immune cells in the AVC. Finally, the CMap database was used to predict candidate small compounds as prospective AVC therapeutics.

RESULTS

A total of 78 strong DEGs were identified. The leukocyte migration and pid integrin 1 pathways were highly enriched for AVC-specific DEGs. CXCL16, GPM6A, BEX2, S100A9, and SCARA5 genes were all regarded diagnostic markers for AVC. The model was effectively constructed using a molecular diagnostic score system with significant diagnostic value (AUC = 0.987) and verified using the independent dataset GSE83453 (AUC = 0.986). Immune cell infiltration research revealed that B cell naive, B cell memory, plasma cells, NK cell activated, monocytes, and macrophage M0 may be involved in the development of AVC. Additionally, all diagnostic characteristics may have varying degrees of correlation with immune cells. The most promising small molecule medicines for reversing AVC gene expression are Doxazosin and Terfenadine.

CONCLUSION

It was identified that CXCL16, GPM6A, BEX2, S100A9, and SCARA5 are potentially beneficial for diagnosing and treating AVC. A diagnostic model was constructed based on a molecular prognostic score system using machine learning. The aforementioned immune cell infiltration may have a significant influence on the development and incidence of AVC.

Integrated identification of key immune related genes and patterns of immune infiltration in calcified aortic valvular disease: A network based meta-analysis

Background: As the most prevalent valvular heart disease, calcific aortic valve disease (CAVD) has become a primary cause of aortic valve stenosis and insufficiency. We aim to illustrate the roles of immune related genes (IRGs) and immune cells infiltration in the occurrence of CAVD.

Methods: Integrative meta-analysis of expression data (INMEX) was adopted to incorporate multiple gene expression datasets of CAVD from Gene Expression Omnibus (GEO) database. By matching the differentially expressed genes (DEGs) to IRGs from “ImmPort” database, differentially expressed immune related genes (DEIRGs) were screened out. We performed enrichment analysis and found that DEIRGs in CAVD were closely related to inflammatory response and immune cells infiltration. We also constructed protein–protein interaction (PPI) network of DEIRGs and identified 5 key DEIRGs in CAVD according to the mixed character calculation results. Moreover, CIBERSORT algorithm was used to explore the profile of infiltrating immune cells in CAVD. Based on Spearman’s rank correlation method, correlation analysis between key DEIRGs and infiltrating immune cells was performed.

Results: A total of 220 DEIRGs were identified and the enrichment analysis of DEIRGs showed that they were significantly enriched in inflammatory responses. PPI network was constructed and PTPN11, GRB2, SYK, PTPN6 and SHC1 were identified as key DEIRGs. Compared with normal aortic valve tissue samples, the proportion of neutrophils, T cells CD4 memory activated and macrophages M0 was elevated in calcified aortic valves tissue samples, as well as reduced infiltration of macrophages M2 and NK cells activated. Furthermore, key DEIRGs identified in the present study, including PTPN11, GRB2, PTPN6, SYK, and SHC1, were all significantly correlated with infiltration of various immune cells.

Conclusion: This meta-analysis suggested that PTPN11, GRB2, PTPN6, SYK, and SHC1 might be key DEIRGs associated with immune cells infiltration, which play a pivotal role in pathogenesis of CAVD.

Identification of Key Non-coding RNAs and Transcription Factors in Calcific Aortic Valve Disease

Background

Calcific aortic valve disease (CAVD) is one of the most frequently occurring valvular heart diseases among the aging population. Currently, there is no known pharmacological treatment available to delay or reverse CAVD progression. The regulation of gene expression could contribute to the initiation, progression, and treatment of CAVD. Non-coding RNAs (ncRNAs) and transcription factors play essential regulatory roles in gene expression in CAVD; thus, further research is urgently needed.

Materials and Methods

The gene-expression profiles of GSE51472 and GSE12644 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) were identified in each dataset. A protein-protein-interaction (PPI) network of DEGs was then constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and functional modules were analyzed with ClusterOne plugin in Cytoscape. Furthermore, Gene Ontology-functional annotation and Kyoto Encyclopedia of Genes and Genomes-pathway analysis were conducted for each functional module. Most crucially, ncRNAs and transcription factors acting on each functional module were separately identified using the RNAInter and TRRUST databases. The expression of predicted transcription factors and key genes was validated using GSE51472 and GSE12644. Furthermore, quantitative real-time PCR (qRT-PCR) experiments were performed to validate the differential expression of most promising candidates in human CAVD and control samples.

Results

Among 552 DEGs, 383 were upregulated and 169 were downregulated. In the PPI network, 15 functional modules involving 182 genes and proteins were identified. After hypergeometric testing, 45 ncRNAs and 33 transcription factors were obtained. Among the predicted transcription factors, CIITA, HIF1A, JUN, POU2F2, and STAT6 were differentially expressed in both the training and validation sets. In addition, we found that key genes, namely, CD2, CD86, CXCL8, FCGR3B, GZMB, ITGB2, LY86, MMP9, PPBP, and TYROBP were also differentially expressed in both the training and validation sets. Among the most promising candidates, differential expressions of ETS1, JUN, NFKB1, RELA, SP1, STAT1, ANCR, and LOC101927497 were identified via qRT-PCR experiments.

Conclusion

In this study, we identified functional modules with ncRNAs and transcription factors involved in CAVD pathogenesis. The current results suggest candidate molecules for further research on CAVD.

PPBP gene as a biomarker for coronary heart disease risk in postmenopausal Thai women

Background

Estrogen is an important ovarian hormone with anti-atherogenic and cardioprotective effects. Postmenopausal women have lower estrogen levels, associated with significantly higher risks of coronary heart disease (CHD) and CHD-related death. Effective biomarkers for the diagnosis, prediction, and treatment of CHD are needed to address this problem and thus reduce the mortality due to CHD in postmenopausal women. We recently reported that the PPBP and DEFA1/DEFA3 genes may be feasible synergistic biomarkers for CHD risk in Thai men with hyperlipidemia. The PPBP gene encodes pro-platelet basic protein (PPBP) from activated platelets, and DEFA1/DEFA3 encodes human neutrophil peptides (HNP) 1-3, mainly produced by activated neutrophils. Both platelets and neutrophils are involved in chronic inflammation during the development of atherogenesis and CHD. This study investigated the potential roles of PPBP and DEFA1/DEFA3 and their proteins as biomarkers for CHD risk in postmenopausal Thai women.

Methods

This cross-sectional study enrolled 90 postmenopausal Thai women, including 12 healthy controls (N), 18 patients with hyperlipidemia (H), and 21 patients diagnosed with CHD. The remaining 39 women were receiving cholesterol-lowering drugs for hyperlipidemia (HD) were excluded from the study. All CHD patients underwent coronary bypass grafting or coronary angioplasty. PPBP and DEFA1/DEFA3 mRNA expression levels in peripheral blood mononuclear cells isolated from heparinized blood were determined by quantitative reverse-transcription polymerase chain reaction. Levels of PPBP and HNP-1-3 proteins in corresponding plasma samples were assessed by enzyme-linked immunosorbent assay. Differences in parameters were compared among groups and correlations between parameters and clinical manifestations were analyzed.

Results

PPBP mRNA and protein levels were significantly increased in the CHD group compared with the N and H groups. In contrast, DEFA1/DEFA3 mRNA and HNP-1-3 protein levels did not differ significantly among the groups. None of the levels were associated with any of the clinical parameters analyzed in this study.

Conclusion

The results indicate that gene and protein expression levels of PPBP, but not DEFA1/DEFA3, and HNP-1-3, may be feasible biomarkers for assessing CHD risk in postmenopausal Thai women with hyperlipidemia.

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Background

Calcified aortic valve disease (CAVD) is one of the most common valvular heart diseases in the elderly population. However, no effective medical treatments have been found to interfere with the progression of CAVD, and specific molecular mechanisms of CAVD remain unclear.

Materials and Methods

Transcriptome sequencing data of GSE55492 and GSE148219 were downloaded from the European Nucleotide Archive, and the microarray dataset, GSE12644 was acquired from the Gene Expression Omnibus database. Software, including FastQC, HISAT2, samtools, and featureCounts was applied to generate the read count matrix. The “Limma” package in R was utilized to analyze differentially expressed genes (DEGs). Thereafter, weighted gene co-expression network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network were used to identify hub genes associated with CAVD, which were further validated by receiver operating characteristic curve (ROC) analysis using GSE12644. The long non-coding RNA (LncRNA)-mediated regulatory network was established based on the differentially expressed LncRNAs and hub genes, which were detected using quantitative real-time PCR (qRT-PCR) in clinical samples and valve interstitial cells. Moreover, CIBERSORT was used to calculate the expression distribution of immune cell infiltration in CAVD.

Results

A total of 126 DEGs were included in the PPI network. PI3K-Akt signaling pathway, ECM-receptor interaction, hematopoietic cell lineage, cell adhesion molecules, and focal adhesion were the most enriched pathways revealed by KEGG. Four LncRNAs, including TRHDE-AS1, LINC00092, LINC01094, and LINC00702 were considered the differentially expressed LncRNA. SPP1, TREM1, GPM6A, CCL19, CR1, NCAM1, CNTN1, TLR8, SDC1, and COL6A6 were the 10 hub genes identified to be associated with CAVD. Moreover, the calcified aortic valve samples had a greater level of Tregs, naïve B cells, and M0 macrophages than the noncalcified ones, whereas CAVD samples had a lower M2 macrophage expression compared to the noncalcified valve tissues.

Conclusion

The current study identified SPP1, TREM1, TLR8, SDC1, GPM6A, and CNTN1 as hub genes that could potentially be associated with CAVD. The LINC00702–miR-181b-5p–SPP1 axis might participate in the development of CAVD. Additionally, M2 macrophages, Tregs, naïve B cells, and M0 macrophages might possibly play a role in the initiation of CAVD.

Flow-Responsive Noncoding RNAs in the Vascular System: Basic Mechanisms for the Clinician

The vascular system is largely exposed to the effect of changing flow conditions. Vascular cells can sense flow and its changes. Flow sensing is of pivotal importance for vascular remodeling. In fact, it influences the development and progression of atherosclerosis, controls its location and has a major influx on the development of local complications. Despite its importance, the research community has traditionally paid scarce attention to studying the association between different flow conditions and vascular biology. More recently, a growing body of evidence has been accumulating, revealing that ncRNAs play a key role in the modulation of several biological processes linking flow-sensing to vascular pathophysiology. This review summarizes the most relevant evidence on ncRNAs that are directly or indirectly responsive to flow conditions to the benefit of the clinician, with a focus on the underpinning mechanisms and their potential application as disease biomarkers.

Pathogenesis and Molecular Immune Mechanism of Calcified Aortic Valve Disease

Calcified aortic valve disease (CAVD) was previously regarded as a passive process associated with valve degeneration and calcium deposition. However, recent studies have shown that the occurrence of CAVD is an active process involving complex changes such as endothelial injury, chronic inflammation, matrix remodeling, and neovascularization. CAVD is the ectopic accumulation of calcium nodules on the surface of the aortic valve, which leads to aortic valve thickening, functional stenosis, and ultimately hemodynamic disorders. CAVD has become an important cause of death from cardiovascular disease. The discovery of therapeutic targets to delay or block the progression of CAVD and the clinical application of transcatheter aortic valve implantation (TAVI) provide new ideas for the prevention and treatment of CAVD. This article summarizes the pathogenesis of CAVD and provides insight into the future directions of CAVD diagnosis and treatment.