Huayu Qutan Recipe promotes lipophagy and cholesterol efflux through the mTORC1/TFEB/ABCA1-SCARB1 signal axis.

This study aims to investigate the mechanism of the anti-atherosclerosis effect of Huayu Qutan Recipe (HYQT) on the inhibition of foam cell formation. In vivo, the mice were randomly divided into three groups: CTRL group, MOD group and HYQT group. The HYQT group received HYQT oral administration twice a day (20.54 g/kg/d), and the plaque formation in ApoE-/- mice was observed using haematoxylin-eosin (HE) staining and oil red O (ORO) staining. The co-localization of aortic macrophages and lipid droplets (LDs) was examined using fluorescent labelling of CD11b and BODIPY fluorescence probe. In vitro, RAW 264.7 cells were exposed to 50 µg/mL ox-LDL for 48 h and then treated with HYQT for 24 h. The accumulation of LDs was evaluated using ORO and BODIPY. Cell viability was assessed using the CCK-8 assay. The co-localization of LC3b and BODIPY was detected via immunofluorescence and fluorescence probe. LysoTracker Red and BODIPY 493/503 were used as markers for lysosomes and LDs, respectively. Autophagosome formation were observed via transmission electron microscopy. The levels of LC3A/B II/LC3A/B I, p-mTOR/mTOR, p-4EBP1/4EBP1, p-P70S6K/P70S6K and TFEB protein level were examined via western blotting, while SQSTM1/p62, Beclin1, ABCA1, ABCG1 and SCARB1 were examined via qRT-PCR and western blotting. The nuclear translocation of TFEB was detected using immunofluorescence. The components of HYQT medicated serum were determined using Q-Orbitrap high-resolution MS analysis. Molecular docking was employed to identify the components of HYQT medicated serum responsible for the mTOR signalling pathway. The mechanism of taurine was illustrated. HYQT has a remarkable effect on atherosclerotic plaque formation and blood lipid level in ApoE-/- mice. HYQT decreased the co-localization of CD11b and BODIPY. HYQT (10% medicated serum) reduced the LDs accumulation in RAW 264.7 cells. HYQT and RAPA (rapamycin, a mTOR inhibitor) could promote cholesterol efflux, while chloroquine (CQ, an autophagy inhibitor) weakened the effect of HYQT. Moreover, MHY1485 (a mTOR agonist) also mitigated the effects of HYQT by reduced cholesterol efflux. qRT-PCR and WB results suggested that HYQT improved the expression of the proteins ABCA1, ABCG1 and SCARB1.HYQT regulates ABCA1 and SCARB1 protein depending on the mTORC1/TFEB signalling pathway. However, the activation of ABCG1 does not depend on this pathway. Q-Orbitrap high-resolution MS analysis results demonstrated that seven core compounds have good binding ability to the mTOR protein. Taurine may play an important role in the mechanism regulation. HYQT may reduce cardiovascular risk by promoting cholesterol efflux and degrading macrophage-derived foam cell formation. It has been observed that HYQT and ox-LDL regulate lipophagy through the mTOR/TFEB signalling pathway, rather than the mTOR/4EBP1/P70S6K pathway. Additionally, HYQT is found to regulate cholesterol efflux through the mTORC1/TFEB/ABCA1-SCARB1 signal axis, while taurine plays a significant role in lipophagy.

Identification of key genes for atherosclerosis in different arterial beds.

Atherosclerosis (AS) is the pathologic basis of various cardiovascular and cerebrovascular events, with a high degree of heterogeneity among different arterial beds. However, mechanistic differences between arterial beds remain unexplored. The aim of this study was to explore key genes and potential mechanistic differences between AS in different arterial beds through bioinformatics analysis. Carotid atherosclerosis (CAS), femoral atherosclerosis (FAS), infrapopliteal atherosclerosis (IPAS), abdominal aortic atherosclerosis (AAS), and AS-specific differentially expressed genes (DEGs) were screened from the GSE100927 and GSE57691 datasets. Immune infiltration analysis was used to identify AS immune cell infiltration differences. Unsupervised cluster analysis of AS samples from different regions based on macrophage polarization gene expression profiles. Weighted gene co-expression network analysis (WGCNA) was performed to identify the most relevant module genes with AS. Hub genes were then screened by LASSO regression, SVM-REF, and single-gene differential analysis, and a nomogram was constructed to predict the risk of AS development. The results showed that differential expression analysis identified 5, 4, 121, and 62 CAS, FAS, IPAS, AAS-specific DEGs, and 42 AS-common DEGs, respectively. Immune infiltration analysis demonstrated that the degree of macrophage and mast cell enrichment differed significantly in different regions of AS. The CAS, FAS, IPAS, and AAS could be distinguished into two different biologically functional and stable molecular clusters based on macrophage polarization gene expression profiles, especially for cardiomyopathy and glycolipid metabolic processes. Hub genes for 6 AS (ADAP2, CSF3R, FABP5, ITGAX, MYOC, and SPP1), 4 IPAS (CLECL1, DIO2, F2RL2, and GUCY1A2), and 3 AAS (RPL21, RPL26, and RPL10A) were obtained based on module gene, gender stratification, machine learning algorithms, and single-gene difference analysis, respectively, and these genes were effective in differentiating between different regions of AS. This study demonstrates that there are similarities and heterogeneities in the pathogenesis of AS between different arterial beds.