Abstract:Objective: To analyze the biological processes and signal pathways of differential genes related to ferroptosis in the liver of ApoE-/-hyperlipidemic mice, to construct a molecular regulatory network of liver ferroptosis, and to reveal the pathogenesis of hyperlipidemia at the transcriptional level. Methods: This study selected 7 C57BL/6J mice as control group and 7 ApoE-/-mice as model group. The control group and model group were fed with normal diet and high-fat diet respectively. After 16 weeks, the serum levels of triglyceride (TG), cholesterol (TC), low-density lipoprotein (LDL-C) and high-density lipoprotein (HDL-C) were detected, and the liver samples were analyzed by HE staining and transcriptome analysis. The distribution of ferroptosis-related differential genes was analyzed by Graph-Pad Prism 8.0.2 software. The protein-protein interaction network model was constructed by STRING11.0 platform. GO biological function enrichment and KEGG pathway enrichment were carried out in DAVID database. The ClueGO plug-in of Cytoscape was used to visually analyze the function and metabolic pathway of ferroptosis-related differential genes. Results: Compared with the control group, TG (1.19±0.09), TC (2.31±0.15), LDL-C (0.29±0.05), HDL-C (1.68±0.06), the levels of TG (1.75±0.08), TC (38.80±4.03), LDL-C (36.27±3.80) in the model group significantly increased (P=0.000, 0.000, 0.000), and the level of HDL-C (1.26±0.05) significantly decreased (P=0.000) . The results of HE staining showed that compared with the control group, the swelling and degeneration of hepatocytes in the model group was obvious and accompanied by a large number of fat vacuoles. Three differential genes of ferroptosis, IREB2 (iron-responsive element-binding protein 2), FTL (ferritin light chain), and FTH1 (ferritin heavy chain 1), were screened by liver transcriptome analysis and calibrated in liver differential genes by PPI network analysis. A total of 23 ferroptosis related genes were screened, including6up-regulatedgenesand20down-regulated genes. Network relationship analysis showed that ferroptosis-related differential gene proteins were interrelated and regulated with each other. Through DAVID database, 36 biological processes and 5 signaling pathways participating in ferroptosis were screened out. Conclusion: It is revealed that ferroptosis in liver tissue can regulate hyperlipidemia through multi-processes and multi-pathways, and high fat can promote the occurrence of ferroptosis, which provides a reference basis for revealing the pathogenesis of hyperlipidemia at the transcriptional level.
