Fei Chen

Background: In critically ill patients, the non-linear relationship between body mass index (BMI) and survival has persisted across studies, but whether it is affected by the triglyceride–glucose (TyG) index is unclear. Methods: We extracted critically ill patients without diabetes mellitus from the Medical Information Mart for Intensive Care (MIMIC)-IV database and categorized them into T1, T2, and T3 groups according to the TyG index tertiles, with the primary outcome of 365-day all-cause mortality. We used Kaplan–Meier (KM) survival curves, COX regression analyses, and restricted cubic spline curves (RCS) to assess the effect of TyG on the risk of BMI-related mortality. Estimation of optimal change points using segmented linear models. Results: The final analytic cohort comprised 6933 critically ill patients with a median age of 66 (54, 76) years, showing male predominance (60.9%). KM curves showed a lower protective effect of obesity in the high-TyG group. COX regression analyses showed that overweight and obesity were associated with lower 365-day all-cause mortality in the T1 and T2 groups and not in the T3 group. RCS analyses showed a U-shaped association between BMI and 365-day all-cause mortality in the T1 and T2 groups and a J-shaped association in the T3 group. The optimal BMI change points were 33 kg/m² (T1), 32.5 kg/m² (T2) and 29.7 kg/m² (T3). Conclusions: Our findings demonstrate that the protective effect of obesity was significantly reduced in patients with high TyG levels. Consequently, it is necessary to consider the TyG index in the weight management of critically ill patients.

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.

Magnesium, an essential dietary trace element, plays a crucial role in numerous physiological processes, and its deficiency has been associated with the development of hyperlipidemia. However, its potential to predict long-term outcomes and inform risk stratification in hyperlipidemic patients remains underexplored. This retrospective cohort study introduces the magnesium depletion score (MgDS), a novel index for quantifying magnesium deficiency, and investigates its association with mortality outcomes in individuals with hyperlipidemia. Data from 12,592 participants in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 were analyzed. Advanced statistical methods, including weighted Cox proportional hazards models, restricted cubic spline (RCS) analysis, Kaplan–Meier survival curves, and receiver operating characteristic (ROC) analysis, were employed to assess the association between MgDS and mortality risks. The results indicate that higher MgDS is significantly associated with increased risks of both all-cause and cardiovascular mortality in individuals with hyperlipidemia, even after adjusting for confounders. Subgroup analyses identified prediabetes, smoking, and alcohol consumption as significant modifiers of this association. RCS analysis confirmed a linear relationship between MgDS and mortality, further supporting its value as a reliable predictor of long-term outcomes. ROC analysis demonstrated the potential of MgDS as an independent tool for predicting mortality at 1, 3, and 5 years. Notably, high MgDS levels in hyperlipidemic individuals with binge drinking habits were associated with significantly higher mortality risks. These results establish MgDS as a promising biomarker for mortality risk stratification in patients with hyperlipidemia. This novel index offers important insights for clinical practice and could facilitate the development of tailored management strategies, particularly for high-risk hyperlipidemia populations, to mitigate long-term health risks.

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

Background: Inflammation is one of the significant consequences of ox-LDL-induced endothelial cell (EC) dysfunction. The senescence-associated secretory phenotype (SASP) is a critical source of inflammation factors. However, the molecular mechanism by which the SASP is regulated in ECs under ox-LDL conditions remains unknown. Results: The level of SASP was increased in ox-LDL-treated ECs, which could be augmented by KLF4 knockdown whereas restored by KLF4 knock-in. Furthermore, we found that KLF4 directly promoted PDGFRA transcription and confirmed the central role of the NAPMT/mitochondrial ROS pathway in KLF4/PDGFRA-mediated inhibition of SASP. Animal experiments showed a higher SASP HFD-fed mice, compared with normal feed (ND)-fed mice, and the endothelium of EC-specific KLF4-/- mice exhibited a higher proportion of SA-β-gal-positive cells and lower PDGFRA/NAMPT expression. Conclusions: Our results revealed that KLF4 inhibits the SASP of endothelial cells under ox-LDL conditions through the PDGFRA/NAMPT/mitochondrial ROS. Methods: Ox-LDL-treated ECs and HFD-fed mice were used as endothelial senescence models in vitro and in vivo. SA-β-gal stain, detection of SAHF and the expression of inflammatory factors determined SASP and senescence of ECs. The direct interaction of KLF4 and PDGFRA promotor was analyzed by EMSA and fluorescent dual luciferase reporting analysis.

Myocardial infarction (MI) is a leading cause of mortality. To better understand its molecular and cellular mechanisms, we used bioinformatic tools and molecular experiments to explore the pathogenesis and prognostic markers. Differential gene expression analysis was conducted using GSE60993 and GSE66360 datasets. Hub genes were identified through pathway enrichment analysis and PPI network construction, and four hub genes (AQP9, MMP9, FPR1, and TREM1) were evaluated for their predictive performance using AUC and qRT-PCR. miR-206 was identified as a potential regulator of TREM1. Finally, miR-206 was found to induce EC senescence and ER stress through upregulating mitochondrial ROS levels via TREM1. These findings may contribute to understanding the pathogenesis of MI and identifying potential prognostic markers.

Background: The risk of acute myocardial infarction (AMI) is elevated in patients with systemic lupus erythematosus (SLE), and it is of great clinical value to identify potential molecular mechanisms and diagnostic markers of AMI associated with SLE by analyzing public database data and transcriptome sequencing data. Methods: AMI and SLE-related sequencing datasets GSE62646, GSE60993, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database and divided into prediction and validation cohorts. To identify the key genes associated with AMI related to SLE, WGCNA and DEGs analysis were performed for the prediction and validation cohorts, respectively. The related signaling pathways were identified by GO/KEGG enrichment analysis. Peripheral blood mononuclear cells (PBMCs) from patients with AMI were collected for transcriptome sequencing to validate the expression of key genes in patients with AMI. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to screen diagnostic biomarkers. The diagnostic efficacy of biomarkers was validated by ROC analysis, and the CIBERSORTx platform was used to analyze the composition of immune cells in AMI and SLE. Results: A total of 108 genes closely related to AMI and SLE were identified in the prediction cohort, and GO/KEGG analysis showed significantly enriched signaling pathways. The results of differential analysis in validation cohort were consistent with them. By transcriptional sequencing of PBMCs from peripheral blood of AMI patients, combined with the results of prediction and validation cohort analysis, seven genes were finally screened out. LASSO analysis finally identifies DYSF, LRG1 and CSF3R as diagnostic biomarkers of SLE-related-AMI. CIBERSORTx analysis revealed that the biomarkers were highly correlated with neutrophils. Conclusion: Neutrophil degranulation and NETs formation play important roles in SLE-related AMI, and DYSF, LRG1 and CSF3R were identified as important diagnostic markers for the development and progression of SLE-related AMI.

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.

Homocysteine (Hcy) is an intermediate amino acid formed during the conversion from methionine to cysteine. When the fasting plasma Hcy level is higher than 15 μmol/L, it is considered as hyperhomocysteinemia (HHcy). The vascular endothelium is an important barrier to vascular homeostasis, and its impairment is the initiation of atherosclerosis (AS). HHcy is an important risk factor for AS, which can promote the development of AS and the occurrence of cardiovascular events, and Hcy damage to the endothelium is considered to play a very important role. However, the mechanism by which Hcy damages the endothelium is still not fully understood. This review summarizes the mechanism of Hcy-induced endothelial injury and the treatment methods to alleviate the Hcy induced endothelial dysfunction, in order to provide new thoughts for the diagnosis and treatment of Hcy-induced endothelial injury and subsequent AS-related diseases.

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.