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Identification of differentially expressed miRNAs and key genes involved in the progression of alcoholic fatty liver disease using rat models - 24/11/22

Doi : 10.1016/j.clinre.2022.102012 
Xuemei Zhang a, b, 1, Wenqi Song c, 1, Mingxuan Zhang c, Yuanhang Song a, Yuzhu Di d, Bo Chen e, Hao Tian f, Xixian Yuan a, Shizhu Jin d,
a Department of Gastroenterology, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang 154002, China 
b Department of Gastroenterology and Hepatology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, China 
c School of Basic Medicine, Jiamusi University, Jiamusi 154000, China 
d Department of Gastroenterology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, China 
e Department of Medical Imaging, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154002, China 
f Department of General surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154002 China 

Corresponding author at: Department of Gastroenterology, The 2nd Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nangang District, Harbin, Heilongjiang 150001, ChinaDepartment of GastroenterologyThe 2nd Affiliated Hospital of Harbin Medical UniversityNo. 246, Xuefu Road, Nangang DistrictHarbinHeilongjiang150001China

Highlights

The AFLD animal models were established to explore the liver miRNAs expression profiles.
GO and KEGG enrichment identified some AFLD-related metabolic pathways and differential genes.
Twelve genes were identified that were closely related to the pathogenesis of AFLD.

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Abstract

Background

Alcoholic fatty liver disease (AFLD) is a liver disease caused by prolonged heavy drinking and has a poor prognosis in the clinic. This study aimed to explore the differential miRNAs expression profiles in the AFLD rat model.

Methods

The rat model of AFLD was established by ethanol intragastric administration and was used to explore the differential miRNAs expression profiles. We further analyzed the potential target mRNAs using the bioinformatics technique. GO and KEGG pathway enrichment analyses were carried out to better understand the biological function of differential expression genes (DEGs). We used the human Gene Expression Omnibus (GEO) dataset GSE28619 to further screen the key differentially expressed genes. The integration between the differentially expressed genes from the AFLD model and GEO was conducted and the key genes were identified.

Results

The serum ALT, AST, TG, and TC levels in the AFLD model group were significantly higher than those in the normal control group. There are 45 miRNAs with significant changes including 26 upregulated and 19 down-regulated miRNAs. GO and KEGG enrichment showed various metabolic processes and signaling pathways were enriched in the progression of AFLD. After integrating the results of GSE28619 and DEGs, we observed that there are 12 genes with significant changes in two data sets, including PSAT1, TKFC, PTTG1, LCN2, CXCL1, NR4A1, RGS1, VCAN, FOS, CXCL10, ATF3, and CYP1A1.

Conclusion

AFLD showed differentially expressed miRNAs, which may be involved in the occurrence and progression of AFLD. Meanwhile, some signal metabolic pathways may be related to the pathogenesis of AFLD.

Le texte complet de cet article est disponible en PDF.

Keywords : AFLD, Bioinformatics analysis, Sequencing, Gene expression omnibus (GEO)


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Vol 46 - N° 10

Article 102012- décembre 2022 Retour au numéro
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