Literature DB >> 30135001

Bioinformatics Analysis of Key Differentially Expressed Genes in Nonalcoholic Fatty Liver Disease Mice Models.

Chao Hou1, Wenwen Feng1, Shan Wei1, Yulin Wang1, Xiaoyi Xu1, Jin Wei1, Ziliang Ma1, Yongsheng Du1, Jialin Guo1, Yu He1, Fanyun Kong1, Renxian Tang1, Kuiyang Zheng1.   

Abstract

Nonalcoholic fatty liver disease (NAFLD) is a global health problem characterized by excessive accumulation of fat in the liver without effect of other pathological factors including hepatitis infection and alcohol abuse. Current studies indicate that gene factors play important roles in the development of NAFLD. However, the molecular characteristics of differentially expressed genes (DEGs) and associated mechanisms with NAFLD have not been well elucidated. Using two microarray data associated with the gene expression profiling in liver tissues of NAFLD mice models, we identified and selected several common key DEGs that contributed to NAFLD. Based on bioinformatics analysis, we discovered that the DEGs were associated with a variety of biological processes, cellular components, and molecular functions and were also related to several significant pathways. Via pathway crosstalk analysis based on overlapping DEGs, we observed that the identified pathways could form large and complex crosstalk networks. Besides, large and complex protein interaction networks of DEGs were further constructed. In addition, many hub host factors with a high degree of connectivity were identified based on interaction networks. Furthermore, significant modules in interaction networks were found, and the DEGs in the identified modules were found to be enriched with distinct pathways. Taken together, these results suggest that the key DEGs, associated pathways, and modules contribute to the development of NAFLD and might be used as novel molecular targets for the treatment of NAFLD.

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Year:  2018        PMID: 30135001      PMCID: PMC6290321          DOI: 10.3727/105221618X15341831737687

Source DB:  PubMed          Journal:  Gene Expr        ISSN: 1052-2166


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