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

Single-cell analysis reveals the loss of FABP4-positive proliferating valvular endothelial cells relates to functional mitral regurgitation

BACKGROUND

Functional mitral regurgitation (MR) is a common form of mitral valve dysfunction that often persists even after surgical intervention, requiring reoperation in some cases. To advance our understanding of the pathogenesis of functional MR, it is crucial to characterize the cellular composition of the mitral valve leaflet and identify molecular changes in each cell subtype within the mitral valves of MR patients. Therefore, we aimed to comprehensively examine the cellular and molecular components of mitral valves in patients with MR.

METHODS

We conducted a single-cell RNA sequencing (scRNA-seq) analysis of mitral valve leaflets extracted from six patients who underwent heart transplantation. The cohort comprised three individuals with moderate-to-severe functional MR (MR group) and three non-diseased controls (NC group). Bioinformatics was applied to identify cell types, delineate cell functions, and explore cellular developmental trajectories and interactions. Key findings from the scRNA-seq analysis were validated using pathological staining to visualize key markers in the mitral valve leaflets. Additionally, in vitro experiments with human primary valvular endothelial cells were conducted to further support our results.

RESULTS

Our study revealed that valve interstitial cells are critical for adaptive valve remodelling, as they secrete extracellular matrix proteins and promote fibrosis. We discovered an abnormal decrease in a subpopulation of FABP4 (fatty acid binding protein 4)-positive proliferating valvular endothelial cells. The trajectory analysis identifies this subcluster as the origin of VECs. Immunohistochemistry on the expanded cohort showed a reduction of FABP4-positive VECs in patients with functional MR. Intervention experiments with primary cells indicated that FABP4 promotes proliferation and migration in mitral valve VECs and enhances TGFβ-induced differentiation.

CONCLUSIONS

Our study presented a comprehensive assessment of the mitral valve cellular landscape of patients with MR and sheds light on the molecular changes occurring in human mitral valves during functional MR. We found a notable reduction in the proliferating endothelial cell subpopulation of valve leaflets, and FABP4 was identified as one of their markers. Therefore, FABP4 positive VECs served as proliferating endothelial cells relates to functional mitral regurgitation. These VECs exhibited high proliferative and differentiative properties. Their reduction was associated with the occurrence of functional MR.

Macrophages in Calcific Aortic Valve Disease: Paracrine and Juxtacrine Disease Drivers

A significant role in the pathogenesis of CAVD is played by innate immunity cells, such as macrophages. In stenotic valves, macrophages have enhanced inflammatory activity, and the population's balance is shifted toward pro-inflammatory ones. Pro-inflammatory macrophages release cytokines, chemokines, and microRNA, which can directly affect the resident valvular cells and cause valve calcification. In CAVD patients, macrophages may have more pronounced pro-inflammatory properties, enhanced not only by paracrine signals but also by juxtacrine Notch signaling and epigenetic factors, which influence the maturation of macrophages' progenitors. In this review, we observe the accumulated data on the involvement of macrophages in CAVD development via paracrine and juxtacrine interactions.

Integrated analysis of single-cell RNA sequencing and bulk transcriptome data identifies a pyroptosis-associated diagnostic model for Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by an insidious onset. Despite the emphasis on motor symptom-based diagnosis, there remains an unmet clinical need for effective diagnostic approaches during the prodromal phase of PD. Recent advances in single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses of PD patients open avenues for identifying potential diagnostic biomarkers. A comprehensive cell trajectory analysis was conducted using scRNA-seq datasets to identify gene expressions associated with the cellular transition from healthy to PD-associated states. Integration of scRNA-seq datasets with weighted gene co-expression network analysis (WGCNA) allowed extraction of pyroptosis-associated differentially expressed genes (PDEGs). Using LASSO logistic regression, support vector machine recursive feature elimination (SVM-RFE) and random forest methods, we developed a diagnostic model centred on PDEGs. In addition, immunoinfiltration, inflammatory signalling pathways and intercellular communication were detected by scRNA-seq analyses. In PD patients, the number of cells including metencephalic-like cells, excitatory neurons, inhibitory neurons and MHB-like cells was significantly reduced, whereas the proportion of astrocytes and microglia, immunoinfiltration and inflammatory signalling pathways were upregulated compared to healthy individuals. Using scRNA-seq and WGCNA analyses, two pyroptosis-related diagnostic genes, POLR2K and TIMM8B, were identified and a diagnostic model based on them was constructed, which showed promising performance upon validation. This study established a pyroptosis-related diagnostic model for PD through the analyses of scRNA-seq combined with bulk transcriptome data, which improved the understanding of the role of PDEGs in PD and provided new insights into the diagnostic strategies for this neurodegenerative disease.

Identification of BANF1 as a novel prognostic biomarker in gastric cancer and validation via in-vitro and in-vivo experiments

Gastric cancer (GC) is a widespread malignancy characterized by a notably high incidence rate and an unfavorable prognosis. We conducted a meticulous analysis of GC high-throughput sequencing data downloaded from the Gene Expression Omnibus (GEO) repository to pinpoint distinctive genes associated with GC. Our investigation successfully identified three signature genes implicated in GC, with a specific focus on the barrier to autointegration factor 1 (BANF1), which exhibits elevated expression across various cancer types, including GC. Bioinformatic analysis has highlighted BANF1 as a prognostic indicator for patients with GC, with direct implications for immune cell infiltration. To gain a more comprehensive understanding of the significance of BANF1 in GC, we performed a series of in vitro experiments to confirm its high expression in GC tissues and cellular components. Intriguingly, the induction of BANF1 knockdown resulted in a marked attenuation of proliferation, migratory capacity, and invasive potential in GC cells. Moreover, our in vivo experiments using nude mouse models revealed a notable impediment in tumor growth following BANF1 knockdown. These insights underscore the feasibility of BANF1 as a novel therapeutic target for GC.

Identification of crucial modules and genes associated with backfat tissue development by WGCNA in Ningxiang pigs

Fat deposition is an economically important trait in pigs. Ningxiang pig, one of the four famous indigenous breeds in China, is characterized by high fat content. The underlying gene expression pattern in different developmental periods of backfat tissue remains unclear, and the purpose of this investigation is to explore the potential molecular regulators of backfat tissue development in Ningxiang pigs. Backfat tissue (three samples for each stage) was initially collected from different developmental stages (60, 120, 180, 240, 300, and 360 days after birth), and histological analysis and RNA sequencing (RNA-seq) were then conducted. Fragments per kilobase of transcript per million (FPKM) method was used to qualify gene expressions, and differentially expressed genes (DEGs) were identified. Furthermore, strongly co-expressed genes in modules, which were named by color, were clustered by Weighted gene co-expression network analysis (WGCNA) based on dynamic tree cutting algorithm. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment were subsequently implemented, and hub genes were described in each module. Finally, QPCR analysis was employed to validate RNA-seq data. The results showed that adipocyte area increased and adipocyte number decreased with development of backfat tissue. A total of 1,024 DEGs were identified in five comparison groups (120 days vs. 60 days, 180 days vs. 120 days, 240 days vs. 180 days, 300 days vs. 240 days, and 360 days vs. 300 days). The turquoise, red, pink, paleturquoise, darkorange, and darkgreen module had the highest correlation coefficient with 60, 120, 180, 240, 300, and 360 days developmental stage, while the tan, black and turquoise module had strong relationship with backfat thickness, adipocyte area, and adipocyte number, respectively. Thirteen hub genes (ACSL1, ACOX1, FN1, DCN, CHST13, COL1A1, COL1A2, COL6A3, COL5A1, COL14A1, OAZ3, DNM1, and SELP) were recognized. ACSL1 and ACOX1 might perform function in the early developmental stage of backfat tissue (60 days), and FN1, DCN, COL1A1, COL1A2, COL5A1, COL6A3, and COL14A1 have unignorable position in backfat tissue around 120 days developmental stage. Besides, hub genes SELP and DNM1 in modules significantly associated with backfat thickness and adipocyte area might be involved in the process of backfat tissue development. These findings contribute to understand the integrated mechanism underlying backfat tissue development and promote the progress of genetic improvement in Ningxiang pigs.

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.