Background: Acute myocardial infarction (AMI) can occur in patients with atherosclerotic disease, with or without plaque rupture. Previous studies have indicated a set of immune responses to plaque rupture. However, the specific circulating immune cell subsets that mediate inflammatory plaque rupture remain elusive.Methods: Ten AMI patients were enrolled in our study (five with and five without plaque rupture; plaque characteristics were identified by optical coherence tomography). By single-cell RNA sequencing, we analyzed the transcriptomic profile of peripheral blood mononuclear cells.Results: We identified 27 cell clusters among 82,550 cells, including monocytes, T cells, NK cells, B cells, megakaryocytes, and CD34⁺ cells. Classical and non-classical monocytes constitute the major inflammatory cell types, and pro-inflammatory genes such as CCL5, TLR7, and CX3CR1 were significantly upregulated in patients with plaque rupture, while the neutrophil activation and degranulation genes FPR2, MMP9, and CLEC4D were significantly expressed in the intermediate monocytes derived from patients without plaque rupture. We also found that CD4⁺ effector T cells may contribute to plaque rupture by producing a range of cytokines and inflammatory-related chemokines, while CD8⁺ effector T cells express more effector molecules in patients without plaque rupture, such as GZMB, GNLY, and PRF1, which may contribute to the progress of plaque erosion. Additionally, NK and B cells played a significant role in activating inflammatory cells and promoting chemokine production in the plaque rupture. Cell–cell communication elaborated characteristics in signaling pathways dominated by inflammatory activation of classical monocytes in patients with plaque rupture.Conclusions: Our studies demonstrate that the circulating immune cells of patients with plaque rupture exhibit highly pro-inflammatory characteristics, while plaque erosion is mainly associated with intermediate monocyte amplification, neutrophil activation, and degranulation. These findings may provide novel targets for the precise treatment of patients with AMI.

Heavy metal exposure is an emerging environmental risk factor linked to cardiovascular disease (CVD) through its effects on vascular ageing. However, the relationship between heavy metal exposure and vascular age have not been fully elucidated. This cross-sectional study analyzed data from 3,772 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2016. We measured urinary concentrations of nine heavy metals and assessed their associations with vascular age, estimated pulse wave velocity (ePWV) and heart vascular age (HVA). Additionally, sex-stratified analyses, Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression were conducted to explore the effects of individual and mixed metal exposures. Exposure to metals such as cadmium (Cd) cesium (Cs), cobalt (Co), and lead (Pb) was significantly associated with increased vascular age, with odds ratios (OR) ranging from 1.05 to 3.48 in full adjusted models. Sex-stratified analyses indicated that individual metal including cobalt (Co) and cadmium (Cd) exposures had a more substantial impact on males. WQS analysis consistently showed combined heavy metals exposure had stronger associations with increased vascular age in men (OR for HVA = 3.89, 95% CI 2.91–5.28). This study highlights a significant association between heavy metal exposure and increased vascular age. Stratified analyses illustrated men might be more susceptible to the combined effects of multiple heavy metal exposure. The findings underscore the importance of considering sex-specific responses and interventions measures in cardiovascular risk assessments and managements. Further research is needed to validate these findings and to develop more precise public health strategies targeting environmental risks.

Introduction: The prognosis of new-onset atrial fibrillation (AF) compared with that of preexisting and non-AF remains controversial. The purpose of this study was to evaluate the effect of new-onset AF compared with preexisting and non-AF on hospital and 90-day mortality. Methods: A retrospective cohort study was performed using data obtained from the Medical Information Mart for Intensive Care III database. The primary outcome was 90-day mortality. Secondary outcomes included hospital mortality, hospital and intensive care unit (ICU) length of stay, and acute kidney injury. Logistic and Cox regression analyses were performed to evaluate the relationship between new-onset AF and study outcomes. Results: A total of 38,159 adult patients were included in the study. The incidence of new-onset AF was 9.4%. Ninety-day mortality, hospital mortality, and hospital and ICU length of stay in patients with new-onset and preexisting AF were significantly increased compared with those in patients with non-AF patients (all p < 0.001). After adjusting for patient characteristics, new-onset AF remained associated with increased 90-day mortality compared with non-AF (adjusted hazard ratio (HR) 1.37, 95% confidence interval (CI) 1.26 to 1.50; p < 0.01) and preexisting AF (adjusted HR 1.12; 95%-CI 1.02 to 1.23; p < 0.01). Patients in the surgical intensive care unit (SICU) had significantly higher 90-day mortality than patients in the coronary care unit (adjusted HR 1.30; 95% CI 1.31 to 1.51; p < 0.001). Conclusions: Critically ill patients with new-onset AF have significantly increased hospital and 90-day mortality compared with patients with preexisting and non-AF. Patients with new-onset AF in the ICU, especially those in the SICU, require robust management measures.

Background: Plaque rupture and acute atherothrombosis, resulting from continued progression of atherosclerotic plaques (APs), are major contributors to acute clinical events such as stroke or myocardial infarction. This article aimed to explore the gene signatures and potential molecular mechanisms in the progression and instability of APs and to identify novel biomarkers and interventional targets for AP rupture.Methods: The microarray data were downloaded from the Gene Expression Omnibus (GEO) database and grouped into discovery and validation cohorts. In the discovery cohort, Weighted Gene Co-Expression Network Analysis was performed for finding co-expression modules, and the Metascape database was used to perform functional enrichment analysis. Differential Expression Genes analysis subsequently was performed in the validation cohort for verification of the obtained results. Common genes were introduced into Metascape database for protein–protein interaction and functional enrichment analysis. We constructed the miRNAs–mRNAs network with the hub genes. Moreover, gene expression profiles of peripheral blood mononuclear cells (PBMCs) from peripheral blood of patients with plaque rupture were analyzed by high-throughput sequencing, and the diagnostic power of hub genes was verified by receiver operating characteristic (ROC) analysis.Results: In the discovery cohort, the brown module in GSE28829 and the turquoise module in GSE163154 were the most significant co-expression modules. Functional enrichment analysis of shared genes suggested that “Neutrophil degranulation” was the most significantly enriched pathway. These conclusions were also demonstrated by the validation cohort. A total of 16 hub genes were identified. The miRNA–mRNA network revealed that hsa-miR-665 and hsa-miR-512-3p might regulate the “Neutrophil degranulation” pathway through PLAU and SIRPA, which might play a significant role in AP progression and instability. Five hub genes, including PLAUR, FCER1G, PLAU, ITGB2, and SLC2A5, showed significantly increased expression in PBMCs from patients with plaque rupture compared with controls. ROC analysis finally identified three hub genes PLAUR, FCER1G, and PLAU that could effectively distinguish patients with APs rupture from controls.Conclusions: The present study demonstrated that the “neutrophil degranulation” signaling pathways and identified novel mRNA and miRNA candidates are closely associated with plaque progression and instability. The hub genes FCER1G, PLAUR, and PLAU may serve as biomarkers for the prospective prediction of AP rupture.

Background and objective: Acute myocardial infarction (AMI) complicated by cardiogenic shock (CS) carries a substantial risk of morbidity and mortality. However, a validated clinical prediction model for in-hospital mortality in these patients is still lacking. This study seeks to develop and validate a mortality risk prediction tool to assist clinicians in early identification of high-risk patients and guide personalized therapeutic interventions.Methods: We conducted a retrospective analysis of clinical data from 1,419 patients diagnosed with AMI. Of these, 150 patients with AMI complicated by CS were enrolled. Participants were randomly assigned to a training group (70%) or a testing group (30%). Following logistic regression analysis, variables were selected using LASSO regression. Seven candidate predictors were selected for inclusion in the final nomogram model. Model performance was assessed through the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and calibration curves.Results: A total of 150 patients with AMI complicated by CS were included in the study. In-hospital mortality occurred in 41 patients (27.33%). Eleven variables, including age, smokers, and left ventricular ejection fraction (LVEF), were identified as potential predictors of in-hospital mortality. The final nomogram incorporated the following independent predictors: age, LVEF, creatine kinase-MB (CK-MB), high-sensitivity C-reactive protein (Hs-CRP), β-blocker use, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) use, and statin use. During internal validation, the nomogram demonstrated AUC values of 0.941 in the training sets and 0.981 in the testing sets. Both calibration curves and DCA showed excellent agreement between predicted probabilities and observed outcomes.Conclusion: This study developed and internally validated a clinically applicable prediction model and nomogram for assessing the risk of in-hospital mortality among patients with AMI complicated by CS. The results offer readily applicable insights to guide clinical practitioners in implementing timely, personalized patient management strategies.

[This corrects the article DOI: 10.3389/fimmu.2022.908815.].