Bioinformatics Analysis of Key Differentially Expressed Genes in Nonalcoholic Fatty Liver Disease Mice Models
| Autor: | Fanyun Kong, Jialin Guo, Yulin Wang, Jin Wei, Wenwen Feng, Chao Hou, Ziliang Ma, Kuiyang Zheng, Yu He, Yongsheng Du, Shan Wei, Xiaoyi Xu, Renxian Tang |
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| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Bioinformatics analysis Computational biology Biology Article Mice 03 medical and health sciences Non-alcoholic Fatty Liver Disease Databases Genetic Nonalcoholic fatty liver disease Genetics medicine Animals Gene Regulatory Networks Protein Interaction Maps Molecular Biology Gene Hepatitis Microarray analysis techniques Gene Expression Profiling Computational Biology medicine.disease Mice Inbred C57BL Gene expression profiling Disease Models Animal Crosstalk (biology) Gene Ontology 030104 developmental biology Differentially expressed genes Gene Expression Regulation Transcriptome |
| Zdroj: | Gene Expression. 19:25-35 |
| ISSN: | 1052-2166 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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