Project description:Myocardial infarction (MI), the most severe manifestation of coronary artery disease, is a multifactorial pathophysiologic process. Here, we constructed a MI mouse model through ligation of the proximal left anterior descending coronary artery. Then we detected and analysed multi-omics (transcriptome and proteome) at different time points (Control, 10 mininte, 1 hour, 6 hour, 24 hour and 72 hour) after MI. Immune-related pathway, pyroptosis pathway, and autophagy pathway r were significantly increased after MI.
Project description:This study used a trans-omics approach—combining genome-wide SNP analysis and metabolomics—to distinguish coronary artery disease (CAD) patients from high-risk and healthy individuals. It identified declining plasma phospholipids as potential biomarkers, linked key SNPs and genes (notably LPCAT1) to lipid changes, and developed a machine-learning model that accurately predicts CAD (AUC = 0.917). The results highlight the role of phospholipid metabolism and genetic variation in CAD progression.
Project description:The human LncRNA microarray analysis of the 6 monocytes samples from Coronary Artery Disease patients and non Coronary Artery Disease 3 Coronary Artery Disease patients and 3 non-Coronary Artery Disease donors