WGCNA combined with machine learning algorithms for analyzing key genes and immune cell infiltration in heart failure due to ischemic cardiomyopathy.

Background: Ischemic cardiomyopathy (ICM) induced heart failure (HF) is one of the most common causes of death worldwide. This study aimed to find candidate genes for ICM-HF and to identify relevant biomarkers by machine learning (ML). Methods: The expression data of ICM-HF and normal samples were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between ICM-HF and normal group were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and gene ontology (GO) annotation analysis, protein-protein interaction (PPI) network, gene pathway enrichment analysis (GSEA), and single-sample gene set enrichment analysis (ssGSEA) were performed. Weighted gene co-expression network analysis (WGCNA) was applied to screen for disease-associated modules, and relevant genes were derived using four ML algorithms. The diagnostic values of candidate genes were assessed using receiver operating characteristic (ROC) curves. The immune cell infiltration analysis was performed between the ICM-HF and normal group. Validation was performed using another gene set. Results: A total of 313 DEGs were identified between ICM-HF and normal group of GSE57345, which were mainly enriched in biological processes and pathways related to cell cycle regulation, lipid metabolism pathways, immune response pathways, and intrinsic organelle damage regulation. GSEA results showed positive correlations with pathways such as cholesterol metabolism in the ICM-HF group compared to normal group and lipid metabolism in adipocytes. GSEA results also showed a positive correlation with pathways such as cholesterol metabolism and a negative correlation with pathways such as lipolytic presentation in adipocytes compared to normal group. Combining multiple ML and cytohubba algorithms yielded 11 relevant genes. After validation using the GSE42955 validation sets, the 7 genes obtained by the machine learning algorithm were well verified. The immune cell infiltration analysis showed significant differences in mast cells, plasma cells, naive B cells, and NK cells. Conclusion: Combined analysis using WGCNA and ML identified coiled-coil-helix-coiled-coil-helix domain containing 4 (CHCHD4), transmembrane protein 53 (TMEM53), acid phosphatase 3 (ACPP), aminoadipate-semialdehyde dehydrogenase (AASDH), purinergic receptor P2Y1 (P2RY1), caspase 3 (CASP3) and aquaporin 7 (AQP7) as potential biomarkers of ICM-HF. ICM-HF may be closely related to pathways such as mitochondrial damage and disorders of lipid metabolism, while the infiltration of multiple immune cells was identified to play a critical role in the progression of the disease.

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.

Cardiac computed tomography based analysis of mitral annulus, coronary sinus and left circumflex artery in patients with mitral regurgitation: Implications for transcatheter mitral annuloplasty techniques.

INTRODUCTION: CT imaging analysis of mitral annulus (MA), coronary sinus (CS) and left circumflex artery (LCX) is critical to transcatheter mitral annuloplasty (TMA), which, however, is scantly reported. We aimed to comprehensively assess MA, CS and LCX anatomy and geometry in mitral regurgitation (MR) based on 3-D reconstruction of cardiac CT images. METHODS: Patients with primary or secondary MR and patients without MR were recruited and underwent cardiac CT examination. MR severity was evaluated by echocardiography. 3-D reconstruction of cardiac CT images was done by the Mimics Research 21.0 software. A MA-centered two dimensional coordinate system, a CS plane, a MA plane and a series of auxiliary planes along the posterior MA were created for the measurement of parameters defining MA, CS and LCX anatomy and geometry during the cardiac cycle. RESULTS: The secondary MR group had a significantly higher MA perimeter index than the other two groups during the cardiac cycle. The CS diameters at most sites, and the posterior MA radian were substantially greater in the two MR groups. Distances between the CS and MA at some locations were significant different among the three groups. The secondary MR group had a significantly smaller CS-MA plane angle than the other two groups during systole, and than control group during diastole. The site where the CS crossed LCX was pinpointed. CONCLUSION: The comprehensive information from this study may help improve the results of TMA and enhance the design of devices for a better annuloplasty effect.

Surgical repair of inferior sinus venosus defects: a novel approach with unsnared inferior vena cava.

BACKGROUND: Inferior sinus venosus defects (SVD) are very rare and difficult to image from transthoracic echocardiography. Surgical errors were occasionally reported in the repair of inferior SVDs. RESULTS: The authors have operated on 12 inferior SVD patients using bicaval cannulation with unsnared inferior vena cava (IVC) and proved successful. CONCLUSION: This technique guaranteed a better exposure of surgical field and facilitate identifying the anatomical relationship between lower part of the SVD and IVC orifice, thus avoiding postoperative IVC - left atrial shunt and other surgical mistakes.