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Shuangyu Tiaozhi decoction alleviates non-alcoholic fatty liver disease by improving lipid deposition, insulin resistance, and inflammation in vitro and in vivo

Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Yin, Guoliang;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Liang, Hongyi;
Affiliation
Department of Nursing ,Taishan Vocational College of Nursing ,Taian ,China
Sun, Wenxiu;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Zhang, Shizhao;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Feng, Yanan;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Liang, Pengpeng;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Chen, Suwen;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Liu, Xiangyi;
Affiliation
The First Clinical Medical School, Shandong University of Traditional Chinese Medicine ,Jinan ,China
Pan, Wenchao;
Affiliation
Department of Neurology ,Affiliated Hospital of Shandong University of Traditional Chinese Medicine ,Jinan ,China
Zhang, Fengxia

Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases worldwide. Our previous studies have found that Shuangyu Tiaozhi Decoction (SYTZD) could produce an improvement in NAFLD-related indicators, but the underlying mechanism associated with this improvement remains unclear. The study aimed to investigate the potential mechanism of SYTZD against NAFLD through network pharmacology and experimental verification. The components of SYTZD and SYTZD drug containing serum were analyzed using ultra-performance liquid chromatography to quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS). Active components and targets of SYTZD were screened by the traditional Chinese medical systems pharmacology (TCMSP) and encyclopedia of traditional Chinese medicine (ETCM) databases. NAFLD-related targets were collected from the GeneCards and DisGeNET databases. The component-disease targets were mapped to identify the common targets of SYTZD against NAFLD. Protein–protein interaction (PPI) network of the common targets was constructed for selecting the core targets. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets was performed using the database for annotation, visualization, and integrated discovery (DAVID) database. Furthermore, animal and cell models were constructed for validating the predictions of network pharmacology. Lipid accumulation, liver histopathology, insulin resistance, and core gene expression were measured by oil red O staining, hematoxylin and eosin staining, insulin tolerance test, real-time quantitative polymerase chain reaction, and Western blotting, respectively. Two components and 22 targets of SYTZD against NAFLD were identified by UPLC-Q/TOF-MS and relevant databases. PPI analysis found that ESR1, FASN, mTOR, HIF-1α, VEGFA, and GSK-3β might be the core targets of SYTZD against NAFLD, which were mainly enriched in the thyroid hormone pathway, insulin resistance pathway, HIF-1 pathway, mTOR pathway, and AMPK pathway. Experimental results revealed that SYTZD might exert multiple anti-NAFLD mechanisms, including improvements in lipid deposition, inflammation, and insulin resistance. SYTZD treatment led to decreases in the lipid profiles, hepatic enzyme levels, inflammatory cytokines, and homeostatic model assessment for insulin resistance (HOMA-IR). SYTZD treatment affected relative mRNA and protein levels associated with various pathways. Our findings reveal that SYTZD could alleviate NAFLD through a multi-component, multi-target, and multi-pathway mechanism of action.

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License Holder: Copyright © 2022 Yin, Liang, Sun, Zhang, Feng, Liang, Chen, Liu, Pan and Zhang.

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