The endothelial-mesenchymal transition (EndMT) is involved in the development of atherosclerosis (AS) and is a key process in vascular endothelial injury. Oxidative stress, inflammation, and apoptosis are common causes of EndMT, and EndMT progression can further accelerate the development of AS. The metabolite trimethylamine N-oxide (TMAO) is produced by the gut microbiome and is implicated in the development of several diseases, including diabetes and chronic kidney disease. However, the impact of TMAO on transforming growth factor β1(TGF-β1)-induced EndMT remains unclear. We hypothesize that TMAO exacerbates plaque formation and cardiac function impairment by promoting EndMT. Herein, we showed that high serum TMAO levels caused plaque formation, cardiac function damage and haemodynamic changes in ApoE^-/- mice. In vitro, TMAO upregulated mesenchymal markers and downregulated endothelial markers in HAECs. Furthermore, TMAO increased the migratory capacity of EndMT cells. Mechanistically, we found that PERK downregulation could alleviate TMAO-induced oxidative stress, EndMT, plaque formation and cardiac function damage. Further study showed that activated transcription factor 3 (ATF3), the downstream molecule of protein kinase RNA-like endoplasmic reticulum kinase (PERK), could bind with TGF-β1/2 and affect EndMT. Overall, TMAO promotes EndMT, possibly through the PERK-eIF2α-ATF4-CHOP or the PERk-eIF2α-ATF3-TGF-β signalling pathways.

Background: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD’s involvement in HF pathogenesis and identify candidate biomarkers for the diagnosis of MDD with HF. Methods: GWAS data for MDD and HF were collected, and Mendelian randomization (MR) analysis was performed to investigate the causal relationship between MDD and HF. Differential expression analysis (DEA) and WGCNA were used to detect HF key genes and MDD-associated secretory proteins. Protein–protein interaction (PPI), functional enrichment, and cMAP analysis were used to reveal potential mechanisms and drugs for MDD-related HF. Then, four machine learning (ML) algorithms (including GLM, RF, SVM, and XGB) were used to screen candidate biomarkers, construct diagnostic nomograms, and predict MDD-related HF. Furthermore, the MCPcounter algorithm was used to explore immune cell infiltration in HF, and MR analysis was performed to explore the causal effect of immunophenotypes on HF. Finally, the validation of the association of MDD with reduced left ventricular ejection fraction (LVEF) and the performance assessment of diagnostic biomarkers was accomplished based on animal models mimicking MDD. Results: The MR analysis showed that the MDD was linked to an increased risk of HF (OR = 1.129, p < 0.001). DEA combined with WGCNA and secretory protein gene set identified 315 HF key genes and 332 MDD-associated secretory proteins, respectively. Through PPI and MCODE analysis, 78 genes were pinpointed as MDD-related pathogenic genes for HF. The enrichment analysis revealed that these genes were predominantly enriched in immune and inflammatory regulation. Through four ML algorithms, two hub genes (ISLR/SFRP4) were identified as candidate HF biomarkers, and a nomogram was developed. ROC analysis showed that the AUC of the nomogram was higher than 0.90 in both the HF combined dataset and two external cohorts. In addition, an immune cell infiltration analysis revealed the immune dysregulation in HF, with ISLR/SFRP4 displaying notable associations with the infiltration of B cells, CD8 T cells, and fibroblasts. More importantly, animal experiments showed that the expression levels of ISLR (r = −0.653, p < 0.001) and SFRP4 (r = −0.476, p = 0.008) were significantly negatively correlated with LVEF. Conclusions: The MR analysis indicated that MDD is a risk factor for HF at the genetic level. Bioinformatics analysis and the ML results suggest that ISLR and SFRP4 have the potential to serve as diagnostic biomarkers for HF. Animal experiments showed a negative correlation between the serum levels of ISLR/SFRP4 and LVEF, emphasizing the need for additional clinical studies to elucidate their diagnostic value.

Chromatin regulators are indispensable upstream epigenetic regulators.The emergence and progression of atherosclerosis has been demonstrated to be influenced by smooth muscle-related chromatin regulators, such as ZEB2 and MAFF. However, specific chromatin regulators and their possible roles have not been clarified. Information was gathered from 51 patients diagnosed with coronary artery disease (CAD) and 50 individuals in good health from the GEO database. 440 genes were identified as having differential expression across the two datasets, and these genes were linked to cellular reactions. Enrichment of pathways related to histone modification and transcriptional regulatory factors was observed in GO and KEGG analyses. Four machine learning models (RF, SVM, GLM, and XGB) were developed using the expression profiles of 440 chromatin-associated genes in the CAD cohort to pinpoint genes with significant diagnostic potential. After evaluating residuals, root mean square errors, receiver operating characteristic curves, and immune-infiltration, four key genes (HCFC1, RNF8, TNP1, and SET) were identified. Gene expression in different blood vessel levels in atherosclerotic plaques in a mouse model of coronary artery disease showed significant variations. The gene expression levels in macrophages aligned with clinical data from the GEO database as expected. This discovery is crucial for future analysis and the prediction of drug and miRNA targets. In conclusion, we found that the four hub genes are important in the mechanism of CAD. These findings provide new ideas for the study of potential epigenetic predictive markers and therapeutic targets to be used in determining a treatment strategy for CAD.

Cuproptosis-related key genes play a significant role in the pathological processes of acute myocardial infarction (AMI). However, a complete understanding of the molecular mechanisms behind this participation remains elusive. This study was designed to identify genes and immune cells critical to AMI pathogenesis. Based on the GSE48060 dataset (31 AMI patients and 21 healthy persons, GPL570-55999), we identified genes associated with dysregulated cuproptosis and the activation of immune responses between normal subjects and patients with a first myocardial attack. Two molecular clusters associated with cuproptosis were defined in patients with AMI. Immune infiltration analysis showed that there was significant immunity heterogeneity among different clusters. Multiple immune responses were closely associated with Cluster2-specific differentially expressed genes (DEGs). The generalized linear model machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.870). A final two-gene-based generalized linear model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.719, GSE66360 and AUC = 0.856, GSE123342). Column graph, calibration curve, and decision curve analyses also proved the accuracy of AMI prediction. We also constructed a mouse C57BL/6 model of AMI (3 h, 48 h, and 1 week) and used qRT-PCR and immunofluorescence to detect the expression changes of CBLB and ZNF302. In this study, we present a systematic analysis of the complex relationship between cuproptosis and a first AMI attack, and provide new insights into the diagnosis and treatment of AMI.

Chronic psychological stress is closely related to myocardial diseases, but the pathological processes and related mechanisms are not yet clear. In this study, 5 batches of animal experiments are conducted to reveal the pathological process of chronic psychological stress on the heart, and found that cardiomyocyte hypertrophy is an early manifestation of cardiac damage. Furthermore, it is discovered that corticosterone and glucocorticoid receptor (GR) play an important role in mediating this phenomenon. Additionally, a new direct target gene of GR, Lama5 , is identified and confirmed in vivo and in vitro that the corticosterone‐GR‐LAMA5 axis is a significant pathway mediating chronic psychological stress‐induced cardiomyocyte hypertrophy. Moreover, the potential of LAMA5 is validated as a biomarker for myocardial hypertrophy and impaired cardiac function in patients with depression. In summary, a novel hypertrophy‐related gene, Lama5 has been identified, that may play an important role in chronic psychological stress‐induced cardiomyocyte hypertrophy.