Jun Mm Ouyang

Cardiovascular diseases are the leading causes of death worldwide. However, there are still shortcomings in the currently employed treatment methods for these diseases. Therefore, exploring the molecular mechanisms underlying cardiovascular diseases is an important avenue for developing new treatment strategies. Previous studies have confirmed that metabolic and epigenetic alterations are often involved in cardiovascular diseases across patients. Moreover, metabolic and epigenetic factors interact with each other and affect the progression of cardiovascular diseases in a coordinated manner. Lactylation is a novel posttranslational modification (PTM) that links metabolism with epigenetics and affects disease progression. Therefore, analyzing the crosstalk between cellular metabolic and epigenetic factors in cardiovascular diseases is expected to provide insights for the development of new treatment strategies. The purpose of this review is to describe the relationship between metabolic and epigenetic factors in heart development and cardiovascular diseases such as heart failure, myocardial infarction, and atherosclerosis, with a focus on acylation and methylation, and to propose potential therapeutic measures.

This study aims to explore predictors of high-grade atherosclerotic renal artery stenosis (ARAS) in patients with chronic kidney disease (CKD). This was a retrospective study, and univariate analysis such as independent-sample t test or nonparametric test where appropriate was used to explore variables with significant difference between patients with high-grade ARAS and patients with low-grade ARAS. Then, multivariate logistic regression and receiver operating characteristic curve (ROC) analysis were performed for further research. In univariate analysis, we found that there was a significant difference in smoking history, estimated glomerular filtration rate (eGFR), cystatin C, fasting blood glucose and lymphocyte-to-monocyte ratio (LMR) between the 2 groups. Multivariate logistic regression analysis showed that eGFR (OR = 0.979, 95% CI: 0.962–0.996, P = .017), cystatin C (OR = 2.123, 95% CI: 1.118–4.030, P = .021) and LMR (OR = 0.639, 95% CI: 0.421–0.969, P = .035) were still associated with high-grade ARAS in patients with CKD. ROC analysis showed that eGFR (AUC: 0.681; sensitivity: 64.1%, specificity: 65.1%), cystatin C (AUC: 0.658; sensitivity: 74.6%, specificity: 53.85%) and LMR (AUC: 0.650; sensitivity: 66.70%, specificity: 62.00%). In patients with CKD, eGFR, and cystatin C and LMR were predictive parameters of high-grade ARAS, and among them, eGFR and LMR held the greatest predictive value for high-grade ARAS in patients with CKD.