Cardiomyocyte apoptosis and autophagy play important roles in acute myocardial infarction (AMI), but the effect of leucine-rich alpha-2-glycoprotein 1 (LRG1) on the apoptosis and autophagy of H9c2 has not yet been reported. It was found through differential gene analysis and LASSO analysis that LRG1 was the key gene in AMI. In this study, western blot was applied to detect the protein expression of Bax, Bcl2, LC3, p62, LRG1 and hypoxia-inducible factor-1α (HIF-1α); CCK-8 assay was employed to detect cell viability; Annexin V-FITC/PI staining was adopted to evaluate apoptosis, and immunofluorescence assay was applied to detect autophagy. Under hypoxia conditions in H9c2 cells, LRG1 protein levels were increased, the cell activity was decreased, and apoptosis and autophagy were promoted; the downregulated LRG1 significantly enhanced cell viability but inhibited apoptosis and autophagy. When knocking down HIF-1α in the overexpressed LRG1 cells, the effects of LRG1 were reversed under hypoxia condition. In conclusion, LRG1/HIF-1α promoted H9c2 cell apoptosis and autophagy in hypoxia, potentially providing new ideas for the determination and treatment of AMI.
Abbreviation:
LRG1: Leucine-rich alpha-2-glycoprotein 1; LRR: leucine-rich repeat; HIF-1α: Hypoxia-inducible factor-1α; AMI: acute myocardial infarction
BackgroundAcute exacerbation of chronic heart failure contributes to substantial increases in major adverse cardiovascular events (MACE). The study developed a risk score to evaluate the severity of heart failure which was related to the risk of MACE.MethodsThis single-center retrospective observational study included 5,777 patients with heart failure. A credible random split-sample method was used to divide data into training and validation dataset (split ratio = 0.7:0.3). Least absolute shrinkage and selection operator (Lasso) logistic regression was applied to select predictors and develop the risk score to predict the severity category of heart failure. Receiver operating characteristic (ROC) curves, and calibration curves were used to assess the model’s discrimination and accuracy.ResultsBody-mass index (BMI), ejection fraction (EF), serum creatinine, hemoglobin, C-reactive protein (CRP), and neutrophil lymphocyte ratio (NLR) were identified as predictors and assembled into the risk score (P < 0.05), which showed good discrimination with AUC in the training dataset (0.770, 95% CI:0.746–0.794) and validation dataset (0.756, 95% CI:0.717–0.795) and was well calibrated in both datasets (all P > 0.05). As the severity of heart failure worsened according to risk score, the incidence of MACE, length of hospital stay, and treatment cost increased (P < 0.001).ConclusionA risk score incorporating BMI, EF, serum creatinine, hemoglobin, CRP, and NLR, was developed and validated. It effectively evaluated individuals’ severity classification of heart failure, closely related to MACE.
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