Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy.

Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.

MicroRNA-181 in cardiovascular disease: Emerging biomarkers and therapeutic targets.

Cardiovascular disease (CVD) is the leading cause of death worldwide. MicroRNAs (MiRNAs) have attracted considerable attention for their roles in several cardiovascular disease states, including both the physiological and pathological processes. In this review, we will briefly describe microRNA-181 (miR-181) transcription and regulation and summarize recent findings on the roles of miR-181 family members as biomarkers or therapeutic targets in different cardiovascular-related conditions, including atherosclerosis, myocardial infarction, hypertension, and heart failure. Lessons learned from these studies may provide new theoretical foundations for CVD.

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.

Assessment value of the modified early warning score for long-term prognosis of older patients with chronic heart failure.

AIM: The aim of the study was to explore the assessment value of the modified early warning score (MEWS) for the long-term prognosis of older patients with chronic heart failure (CHF). METHODS: A total of 180 CHF patients, treated from January 2016 to January 2018, were divided into a grade I group (n = 28), a grade II group (n = 37), a grade III group (n = 68) and a grade IV group (n = 47) according to the New York Heart Association (NYHA) functional classification. The MEWS was compared on admission and discharge. Based on the clinical outcomes during follow up, the patients were divided into a non-survival group (n = 48) and a survival group (n = 132). Their general clinical data and the MEWS were compared. The predictive values of the MEWS, troponin I (cTnI) and B-type natriuretic (BNP) peptide for long-term prognosis were assessed using receiver operator characteristic (ROC) curves. RESULTS: The MEWS on patient discharge was significantly lower than that on admission, and it increased with increasing NYHA grade (p < 0.05). The MEWS in the non-survival group was significantly higher than that in the survival group. Different clinical outcomes were positively correlated with NYHA grade, MEWS, six-minute walking distance and left ventricular ejection fraction (r = 0.368, r = 0.471, r = 0.387, r = 0.423, p < 0.05), and negatively correlated with cTnI and BNP (r = -0.411, r = -0.425). The area under the ROC curve of the MEWS was 0.852, indicating higher accuracy. The optimal cut-off value, sensitivity and specificity of the MEWS for determining prognosis were 5.6, 0.854 and 0.797 points, respectively. CONCLUSION: The MEWS rose with increasing NYHA grade and reflected the severity of CHF in older patients, which has higher predictive value for long-term prognosis.

Single-cell landscape dissecting the transcription and heterogeneity of innate lymphoid cells in ischemic heart.

Background: Until now, few articles have revealed the potential roles of innate lymphoid cells (ILCs) in cardiovascular diseases. However, the infiltration of ILC subsets in ischemic myocardium, the roles of ILC subsets in myocardial infarction (MI) and myocardial ischemia-reperfusion injury (MIRI) and the related cellular and molecular mechanisms have not been described with a sufficient level of detail. Method: In the current study, 8-week-old male C57BL/6J mice were divided into three groups: MI, MIRI and sham group. Single-cell sequencing technology was used to perform dimensionality reduction clustering of ILC to analyze the ILC subset landscape at a single-cell resolution, and finally flow cytometry was used to confirm the existence of the new ILC subsets in different disease groups. Results: Five ILC subsets were found, including ILC1, ILC2a, ILC2b, ILCdc and ILCt. It is worth noting that ILCdc, ILC2b and ILCt were identified as new ILC subclusters in the heart. The cellular landscapes of ILCs were revealed and signal pathways were predicted. Furthermore, pseudotime trajectory analysis exhibited different ILC statuses and traced related gene expression in normal and ischemic conditions. In addition, we established a ligand-receptor-transcription factor-target gene regulatory network to disclose cell communications among ILC clusters. Moreover, we further revealed the transcriptional features of the ILCdc and ILC2a subsets. Finally, the existence of ILCdc was confirmed by flow cytometry. Conclusion: Collectively, by characterizing the spectrums of ILC subclusters, our results provide a new blueprint for understanding ILC subclusters' roles in myocardial ischemia diseases and further potential treatment targets.

The Landscape of Circular RNAs in Cardiovascular Diseases.

Cardiovascular disease (CVD) remains the leading cause of mortality globally. Circular RNAs (circRNAs) have attracted extensive attention for their roles in the physiological and pathological processes of various cardiovascular diseases (CVDs). In this review, we briefly describe the current understanding of circRNA biogenesis and functions and summarize recent significant findings regarding the roles of circRNAs in CVDs. These results provide a new theoretical basis for diagnosing and treating CVDs.

Two-sample Mendelian randomization to study the causal association between gut microbiota and atherosclerosis.

Background: According to some recent observational studies, the gut microbiota influences atherosclerosis via the gut microbiota-artery axis. However, the causal role of the gut microbiota in atherosclerosis remains unclear. Therefore, we used a Mendelian randomization (MR) strategy to try to dissect this causative link. Methods: The biggest known genome-wide association study (GWAS) (n = 13,266) from the MiBioGen collaboration was used to provide summary data on the gut microbiota for a two-sample MR research. Data on atherosclerosis were obtained from publicly available GWAS data from the FinnGen consortium, including cerebral atherosclerosis (104 cases and 218,688 controls), coronary atherosclerosis (23,363 cases and 187,840 controls), and peripheral atherosclerosis (6631 cases and 162,201 controls). The causal link between gut microbiota and atherosclerosis was investigated using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode approaches, among which inverse variance weighting was the main research method. Cochran's Q statistic was used to quantify the heterogeneity of instrumental variables (IVs), and the MR Egger intercept test was used to assess the pleiotropy of IVs. Results: Inverse-variance-weighted (IVW) estimation showed that genus Ruminiclostridium 9 had a protective influence on cerebral atherosclerosis (OR = 0.10, 95% CI: 0.01-0.67, P = 0.018), while family Rikenellaceae (OR = 5.39, 95% CI: 1.50-19.37, P = 0.010), family Streptococcaceae (OR = 6.87, 95% CI: 1.60-29.49, P = 0.010), genus Paraprevotella (OR = 2.88, 95% CI: 1.18-7.05, P = 0.021), and genus Streptococcus (OR = 5.26, 95% CI: 1.28-21.61, P = 0.021) had pathogenic effects on cerebral atherosclerosis. For family Acidaminococcaceae (OR = 0.87, 95% CI: 0.76-0.99, P = 0.039), the genus Desulfovibrio (OR = 0.89, 95% CI: 0.80-1.00, P = 0.048), the genus RuminococcaceaeUCG010 (OR = 0.80, 95% CI: 0.69-0.94, P = 0.006), and the Firmicutes phyla (OR = 0.87, 95% CI: 0.77-0.98, P = 0.023) were protective against coronary atherosclerosis. However, the genus Catenibacterium (OR = 1.12, 95% CI: 1.00-1.24, P = 0.049) had a pathogenic effect on coronary atherosclerosis. Finally, class Actinobacteria (OR = 0.83, 95% CI: 0.69-0.99, P = 0.036), family Acidaminococcaceae (OR = 0.76, 95% CI: 0.61-0.94, P = 0.013), genus Coprococcus2 (OR = 0.76, 95% CI: 0.60-0.96, P = 0.022), and genus RuminococcaceaeUCG010 (OR = 0.65, 95% CI: 0.46-0.92, P = 0.013), these four microbiota have a protective effect on peripheral atherosclerosis. However, for the genus Lachnoclostridium (OR = 1.25, 95% CI: 1.01-1.56, P = 0.040) and the genus LachnospiraceaeUCG001 (OR = 1.22, 95% CI: 1.04-1.42, P = 0.016), there is a pathogenic role for peripheral atherosclerosis. No heterogeneity was found for instrumental variables, and no considerable horizontal pleiotropy was observed. Conclusion: We discovered that the presence of probiotics and pathogens in the host is causally associated with atherosclerosis, and atherosclerosis at different sites is causally linked to specific gut microbiota. The specific gut microbiota associated with atherosclerosis identified by Mendelian randomization studies provides precise clinical targets for the treatment of atherosclerosis. In the future, we can further examine the gut microbiota's therapeutic potential for atherosclerosis if we have a better grasp of the causal relationship between it and atherosclerosis.

Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction.

Background: Acute myocardial infarction (AMI) is one of the main fatal diseases of cardiovascular diseases. Circular RNA (circRNA) is a non-coding RNA (ncRNA), which plays a role in cardiovascular disease as a competitive endogenous RNA (ceRNA). However, their role in AMI has not been fully clarified. This study aims to explore the mechanism of circRNA-related ceRNA network in AMI, and to identify the corresponding immune infiltration characteristics. Materials and Methods: The circRNA (GSE160717), miRNA (GSE24548), and mRNA (GSE60993) microarray datasets of AMI were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were identified by the "limma" package. After integrating the circRNA, miRNA and mRNA interaction, we constructed a circRNA-miRNA-mRNA network. The "clusterProfiler" package and String database were used for functional enrichment analysis and protein-protein interaction (PPI) analysis, respectively. After that, we constructed a circRNA-miRNA-hub gene network and validated the circRNAs and mRNAs using an independent dataset (GSE61144) as well as qRT-PCR. Finally, we used CIBERSORTx database to analyze the immune infiltration characteristics of AMI and the correlation between hub genes and immune cells. Results: Using the "limma" package of the R, 83 DEcircRNAs, 54 DEmiRNAs, and 754 DEmRNAs were identified in the microarray datasets of AMI. Among 83 DEcircRNAs, there are 55 exonic DEcircRNAs. Then, a circRNA-miRNA-mRNA network consists of 21 DEcircRNAs, 11 DEmiRNAs, and 106 DEmRNAs were predicted by the database. After that, 10 hub genes from the PPI network were identified. Then, a new circRNA-miRNA-hub gene network consists of 14 DEcircRNAs, 7 DEmiRNAs, and 9 DEmRNAs was constructed. After that, three key circRNAs (hsa_circ_0009018, hsa_circ_0030569 and hsa_circ_0031017) and three hub genes (BCL6, PTGS2 and PTEN) were identified from the network by qRT-PCR. Finally, immune infiltration analysis showed that hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. Conclusion: Our study constructed a circRNA-related ceRNA networks in AMI, consists of hsa_circ_0031017/hsa-miR-142-5p/PTEN axis, hsa_circ_0030569/hsa-miR-545/PTGS2 axis and hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis. These three hub genes were significantly positively correlated with up-regulated immune cells (neutrophils, macrophages and plasma cells) in AMI. It helps improve understanding of AMI mechanism and provides future potential therapeutic targets.

Innate Lymphoid Cells and Myocardial Infarction.

Myocardial infarction results from obstruction of a coronary artery that causes insufficient blood supply to the myocardium and leads to ischemic necrosis. It is one of the most common diseases threatening human health and is characterized by high morbidity and mortality. Atherosclerosis is the pathological basis of myocardial infarction, and its pathogenesis has not been fully elucidated. Innate lymphoid cells (ILCs) are an important part of the human immune system and participate in many processes, including inflammation, metabolism and tissue remodeling, and play an important role in atherosclerosis. However, their specific roles in myocardial infarction are unclear. This review describes the current understanding of the relationship between innate lymphoid cells and myocardial infarction during the acute phase of myocardial infarction, myocardial ischemia-reperfusion injury, and heart repair and regeneration following myocardial infarction. We suggest that this review may provide new potential intervention targets and ideas for treatment and prevention of myocardial infarction.