Open AccessBioinformatics Analysis of Key Differentially Expressed Genes in Nonalcoholic Fatty Liver Disease Mice Models
Author(s) -
Chao Hou,
Wei Feng,
Wei Shan,
Yulin Wang,
Xiaoyi Xu,
Wei Jin,
Zaiyong Ma,
Yongsheng Du,
Jialin Guo,
Yu He,
Fanyun Kong,
Renxian Tang,
Kuiyang Zheng
Publication year - 2019
Publication title -
gene expression
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.591
H-Index - 46
eISSN - 1555-3884
pISSN - 1052-2166
DOI - 10.3727/105221618x15341831737687
Subject(s) - nonalcoholic fatty liver disease , crosstalk , gene , fatty liver , computational biology , biology , microarray , gene expression profiling , biological pathway , bioinformatics , microarray analysis techniques , gene expression , disease , genetics , medicine , physics , optics
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.