At present, due to the limitations of drug therapy targets for atherosclerosis, some patients fail to achieve satisfactory efficacy. Cholesterol efflux dysfunction and endothelial cell inflammation are considered to be important factors in the development of atherosclerosis. Peroxisome proliferator-activated receptor gamma (PPARγ), a promising therapeutic target for atherosclerosis, plays a dual role in regulating cholesterol efflux and endothelial cell inflammation. However, the use of PPARγ agonist in clinical practice is greatly limited as it could lead to water and sodium retention and hence result in congestive heart failure. Qihuang Zhuyu Formula (QHZYF) is a hospital preparation of Jiangsu Province Hospital of Chinese Medicine which has definite effect in the treatment of atherosclerosis, but its pharmacological mechanism has not been clear. In this study, we successfully predicted that QHZYF might regulate cholesterol efflux and endothelial inflammation via targeting PPARγ-mediated PPARγ/LXRα/ABCA1-ABCG1 and PPARγ/NF-κB p65 pathways by using UPLC-Q-TOF/MS, network pharmacology, bioinformatics analysis, and molecular docking technology. Subsequently, we confirmed in vivo that QHZYF could attenuate atherosclerosis in ApoE−/− mice and regulate the expression levels of related molecules in PPARγ/LXRα/ABCA1-ABCG1 and PPARγ/NF-κB p65 pathways of ApoE−/− mice and C57BL/6 wild-type mice. Finally, in in vitro experiments, we found that QHZYF could reduce lipid content and increase cholesterol efflux rate of RAW 264.7 cells, inhibit the inflammatory response of HUVECs, and regulate the expression levels of related molecules in the two pathways. In addition, the above effects of QHZYF were significantly weakened after PPARγ knockdown in the two kinds of cells. In conclusion, our study revealed that QHZYF attenuates atherosclerosis via targeting PPARγ-mediated PPARγ/LXRα/ABCA1-ABCG1 and PPARγ/NF-κB p65 pathways to regulate cholesterol efflux and endothelial cell inflammation. More importantly, our study offers a promising complementary and alternative therapy which is expected to make up for the limitation of current drug treatment methods and provide a valuable reference for new drugs development in the future.
Background: Heart failure with reduced ejection fraction (HFrEF) is a complex, chronic disease and is among the top causes of morbidity and mortality. Angiotensin receptor-neprilysin inhibitor drugs represented by sacubitril/valsartan are the key drugs for the treatment of HFrEF in western medicine, and Qili Qiangxin Capsule (QQC) is a vital drug for the treatment of HFrEF in Chinese medicine. In recent years, there have been many relevant clinical studies on the combination of the two in the treatment of HFrEF. There are no systematic reviews or meta-analyses specific to sacubitril/valsartan combined with QQC for the treatment of HFrEF, so there is an urgent need to evaluate the effectiveness and safety of these two drugs.Objective: To systematically assess the safety and effectiveness of QQC combined with sacubitril/valsartan in the treatment of HFrEF through a meta-analysis.Methods: Searching studies on the combination of QQC and sacubitril/valsartan in the treatment of HFrEF, from databases such as PubMed, Cochrane Library, Web of Science, Wanfang Databases, Chinese Biomedical Literature Database, China Science and Technology Journal Database, and China National Knowledge Infrastructure, prior to 31 October 2021. Two reviewers regulated research selection, data extraction, and risk of bias assessment. Review Manager Software 5.4 was used for meta-analysis.Results: There were 26 studies with 2,427 patients included in total. The meta-analysis showed the combination therapy has significant advantages in improving the clinical efficacy, 6-MWT (RR = 1.18, 95% CI: 1.11–1.26, MD = 70.65, 95% CI: 23.92–117.39), superior in ameliorating LVEF, LVEDD, LVESD, and SV (LVEF: MD = 5.41, 95% CI: 4.74–6.08; LVEDD: MD = −4.41, 95% CI: −6.19 to −2.64; LVESD: MD = −3.56, 95% CI: −4.58 to −2.54; and SV: MD = 5.04, 95% CI: 3.67–6.40), and in improving BNP, NT-proBNP, AngII, and ALD (BNP: MD = −97.55, 95% CI: −112.79 to −82.31; NT-proBNP: MD = −277.22, 95% CI: −348.44 to −206.01; AngII: MD = −11.48, 95% CI: −15.21 to −7.76; and ALD: MD = −26.03, 95% CI: −38.91 to −13.15), and all the differences have statistical advantages (p < 0.05). There are no advantages in improving CO and adverse events (MD = 0.66, 95% CI: −0.12 to 1.43 and RR = 0.62, 95% CI: 0.37–1.04, respectively), and the differences have no statistical advantages.Conclusion: Compared with the control group, QQC combined with sacubitril/valsartan may be effective in the treatment of HFrEF. However, the conclusion of this study must be interpreted carefully due to the high risk and ambiguity of bias in the included trials.
BackgroundThe pathogenesis of myocardial infarction complicating depression is still not fully understood. Bioinformatics is an effective method to study the shared pathogenesis of multiple diseases and has important application value in myocardial infarction complicating depression.MethodsThe differentially expressed genes (DEGs) between control group and myocardial infarction group (M-DEGs), control group and depression group (D-DEGs) were identified in the training set. M-DEGs and D-DEGs were intersected to obtain DEGs shared by the two diseases (S-DEGs). The GO, KEGG, GSEA and correlation analysis were conducted to analyze the function of DEGs. The biological function differences of myocardial infarction and depression were analyzed by GSVA and immune cell infiltration analysis. Four machine learning methods, nomogram, ROC analysis, calibration curve and decision curve were conducted to identify hub S-DEGs and predict depression risk. The unsupervised cluster analysis was constructed to identify myocardial infarction molecular subtype clusters based on hub S-DEGs. Finally, the value of these genes was verified in the validation set, and blood samples were collected for RT-qPCR experiments to further verify the changes in expression levels of these genes in myocardial infarction and depression.ResultsA total of 803 M-DEGs, 214 D-DEGs, 13 S-DEGs and 6 hub S-DEGs (CD24, CSTA, EXTL3, RPS7, SLC25A5 and ZMAT3) were obtained in the training set and they were all involved in immune inflammatory response. The GSVA and immune cell infiltration analysis results also suggested that immune inflammation may be the shared pathogenesis of myocardial infarction and depression. The diagnostic models based on 6 hub S-DEGs found that these genes showed satisfactory combined diagnostic performance for depression. Then, two molecular subtypes clusters of myocardial infarction were identified, many differences in immune inflammation related-biological functions were found between them, and the hub S-DEGs had satisfactory molecular subtypes identification performance. Finally, the analysis results of the validation set further confirmed the value of these hub genes, and the RT-qPCR results of blood samples further confirmed the expression levels of these hub genes in myocardial infarction and depression.ConclusionImmune inflammation may be the shared pathogenesis of myocardial infarction and depression. Meanwhile, hub S-DEGs may be potential biomarkers for the diagnosis and molecular subtype identification of myocardial infarction and depression.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.