Identification and characterization of dynamically regulated hepatitis-related genes in a concanavalin A-induced liver injury model.
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ABSTRACT: Background
Concanavalin A (ConA)-induced liver damage of mice is a well-established murine model mimicking the human autoimmune hepatitis (AIH). However, the pathogenic genes of the liver injury remain to be revealed.Methods
Using time-series liver transcriptome, top dynamic genes were inferred from a set of segmented regression models, and cross-checked by weighted correlation network analysis (WGCNA). AIH murine models created by ConA were used to verify the in vivo effect of these genes.Results
We identified 115 top dynamic genes, of which most were overlapped with the hub genes determined by WGCNA. The expression of several top dynamic genes including Cd63, Saa3, Slc10a1, Nrxn1, Ugt2a3, were verified in vivo. Further, Cluster determinant 63 (Cd63) knockdown in mice treated with ConA showed significantly less liver pathology and inflammation as well as higher survival rates than the corresponding controls.Conclusion
We have identified the top dynamic genes related to the process of acute liver injury, and highlighted a targeted strategy for Cd63 might have utility for the protection of hepatocellular damage.
SUBMITTER: Chen A
PROVIDER: S-EPMC7746381 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Identification and characterization of dynamically regulated hepatitis-related genes in a concanavalin A-induced liver injury model.
Chen Anna A Wang Yidong Y Wu Jiaqi J Tang Dong D Zhu Qianru Q Lu Anqian A Yang Jin J Cai Zhejun Z Shi Junping J
Aging 20201118 22
<h4>Background</h4>Concanavalin A (ConA)-induced liver damage of mice is a well-established murine model mimicking the human autoimmune hepatitis (AIH). However, the pathogenic genes of the liver injury remain to be revealed.<h4>Methods</h4>Using time-series liver transcriptome, top dynamic genes were inferred from a set of segmented regression models, and cross-checked by weighted correlation network analysis (WGCNA). AIH murine models created by ConA were used to verify the <i>in vivo</i> effe ...[more]
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