Background and Objectives: Early diagnosis of patients with acute myocardial infarction (AMI) who are at a high risk of heart failure (HF) progression remains controversial. This study aimed at identifying new predictive biomarkers of post-AMI HF and at revealing the pathogenesis of HF involving these marker genes.Methods and Results: A transcriptomic dataset of whole blood cells from AMI patients with HF progression (post-AMI HF, n = 16) and without progression (post-AMI non-HF, n = 16) was analyzed using the weighted gene co-expression network analysis (WGCNA). The results indicated that one module consisting of 720 hub genes was significantly correlated with post-AMI HF. The hub genes were validated in another transcriptomic dataset of peripheral blood mononuclear cells (post-AMI HF, n = 9; post-AMI non-HF, n = 8). PRKAR1A, SDCBP, SPRED2, and VAMP3 were upregulated in the two datasets. Based on a single-cell RNA sequencing dataset of leukocytes from heart tissues of normal and infarcted mice, PRKAR1A was further verified to be upregulated in monocytes/macrophages on day 2, while SDCBP was highly expressed in neutrophils on day 2 and in monocytes/macrophages on day 3 after AMI. Cell–cell communication analysis via the “CellChat” package showed that, based on the interaction of ligand–receptor (L–R) pairs, there were increased autocrine/paracrine cross-talk networks of monocytes/macrophages and neutrophils in the acute stage of MI. Functional enrichment analysis of the abovementioned L–R genes together with PRKAR1A and SDCBP performed through the Metascape platform suggested that PRKAR1A and SDCBP were mainly involved in inflammation, apoptosis, and angiogenesis. The receiver operating characteristic (ROC) curve analysis demonstrated that PRKAR1A and SDCBP, as well as their combination, had a promising prognostic value in the identification of AMI patients who were at a high risk of HF progression.Conclusion: This study identified that PRKAR1A and SDCBP may serve as novel biomarkers for the early diagnosis of post-AMI HF and also revealed their potentially regulatory mechanism during HF progression.

Background: Acute myocardial infarction (AMI) is a major contributor of heart failure (HF). Peripheral blood mononuclear cells (PBMCs), mainly monocytes, are the essential initiators of AMI-induced HF. The powerful biomarkers for early identification of AMI patients at risk of HF remain elusive. We aimed to identify monocyte-related critical genes as predictive biomarkers for post-AMI HF.Methods: We performed weighted gene co-expression network analysis (WGCNA) on transcriptomics of PBMCs from AMI patients who developed HF or did not. Functional enrichment analysis of genes in significant modules was performed via Metascape. Then we obtained the single-cell RNA-sequencing data of recruited monocytes/macrophages from AMI and control mice using the Scanpy and screened 381 differentially expressed genes (DEGs) between the two groups. We validated the expression changes of the 25 genes in cardiac macrophages from AMI mice based on bulk RNA-sequencing data and PBMCs data mentioned above.Results: In our study, the results of WGCNA showed that two modules containing 827 hub genes were most significantly associated with post-AMI HF, which mainly participated in cell migration, inflammation, immunity, and apoptosis. There were 25 common genes between DEGs and hub genes, showing close relationship with inflammation and collagen metabolism. CUX1, CTSD and ADD3 exhibited consistent changes in three independent studies. Receiver operating characteristic curve analysis showed that each of the three genes had excellent performance in recognizing post-AMI HF patients.Conclusion: Our findings provided a set of three monocyte-related biomarkers for the early prediction of HF development after AMI as well as potential therapeutic targets of post-AMI HF.

Statin therapy plays a pivotal role in stabilizing the plaque for unstable angina (UA) patients although its mechanism(s) remains largely unexplored. Here we aim to identify microRNAs (miRNAs) mediating the protective effect of statins in UA patients. MiRNAs Array was carried out to compare the circulating whole blood miRNA profile of UA patients treated with (n = 10) and without statin (n = 10) and plasma miRNA profile UA patients treated with (n = 5) and without statin (n = 5). 22 whole blood miRNAs and 19 plasma miRNAs were found significantly upregulated in statin group. Targets of these miRNAs were predicted by algoritms: Targetscan, Miranda and Diana microT, then clustered according to functions and cell types by using the Database for Annotation, Visualization and Integrated Discovery (DAVID). To reveal the enriched function pathways in human atherosclerotic plaque, we analyzed microarray data from GEO database, Coronary atherosclerotic plaque (n = 80); macrophages in ruptured plaque (n = 11); carotid atheroma plaque (n = 64); advanced carotid atherosclerotic plaque (n = 29) using Reactome database. Integrated analysis indicated that statin induced miRNAs mainly regulate the signaling pathways of Rho GTPase and hemostasis in human atherosclerotic lesion. In vulnerable plaque, additional immune system signaling was also targeted. The data showed target genes regulated by these statin induced miRNAs majorly expressed in i) plaque macrophage and platelet, where they were involved in hemostasis process; ii) in monocyte to regulate NGF apoptosis; iii) and in endothelial cell function in Rho GTPase pathway. Integrate analysis indicated that statin induced miRNAs mainly regulate the signaling pathways of Rho GTPase and hemostasis in human atherosclerotic lesion. Our study suggest that statin induces the expression of multiple miRNAs in the circulation of UA patient, which play important roles by regulating signal pathways critical for the pathogenesis of UA.

Mitral valve prolapse is often benign, but progression to mitral regurgitation may require invasive intervention and there is no specific medical therapy. An association of mitral valve prolapse with Marfan syndrome resulting from pathogenic FBN1 variants supports the use of hypomorphic fibrillin-1 mgR mice to investigate mechanisms and therapy for mitral valve disease. mgR mice developed severe myxomatous mitral valve degeneration with mitral regurgitation by 12 weeks of age. Persistent activation of TGF-β and mTOR signaling along with macrophage recruitment preceded histological changes at 4 weeks of age. Short-term mTOR inhibition with rapamycin from 4 to 5 weeks of age prevented TGF-β overactivity and leukocytic infiltrates, while long-term inhibition of mTOR or TGF-β signaling from 4 to 12 weeks of age rescued mitral valve leaflet degeneration. Transcriptomic analysis identified integrins as key receptors in signaling interactions, and serologic neutralization of integrin signaling or a chimeric integrin receptor altering signaling prevented mTOR activation. We confirmed increased mTOR signaling and a conserved transcriptome signature in human specimens of sporadic mitral valve prolapse. Thus, mTOR activation from abnormal integrin-dependent cell–matrix interactions drives TGF-β overactivity and myxomatous mitral valve degeneration, and mTOR inhibition may prevent disease progression of mitral valve prolapse.

Herein, we designed several structures of GaAs/AlGaAs extended gate high electron mobility transistors (EG-HEMT) for cTnI detection, in order to explore the mechanism of bio-detection, the limit of detection (LOD) as well as the application in clinical detection. The experiment carried out that 50y structure of EG-HEMT biosensor, whose extended electrode is 50 times as large as the gate, has highest biological regulation ability ( δ). Meanwhile, the concentration range of cTnI detection using 50y EG-HEMT biosensor is about 100 fg ml ^-1 to 10 μg ml ^-1 , which is much broader than that of Unicel Dxl800 (usually be used in clinical detection). Furthermore, due to the influence of parasitic resistance and other factors, δ increases with the increase of y, but the rising rate of δ decreases at the same time. By comparing the detecting results of clinical samples, 30y EG-HEMT is the best in the detection of cTnI concentration with a relative error of 6%. In a higher concentration range, it is more accurate than that of the Unicel Dxl800, breaking through its limit.