Bioinformatics analysis reveals novel core genes associated with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.

Nonalcoholic fatty liver disease (NAFLD) is the most frequent liver disease and associated with a wide spectrum of hepatic disorders ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). NASH is projected to become the most common indication for liver transplantation, and the annual incidence rate of NASH-related HCC is 5.29 cases per 1000 person-years. Owing to the epidemics of NAFLD and the unclear mechanism of NAFLD progression, it is important to elucidate the underlying NAFLD mechanisms in detail. NASH is mainly caused by the development of NAFL Therefore, it is also of great significance to understand the mechanism of progression from NAFL to NASH. Gene expression chip data for NAFLD and NASH were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between NAFLD and normal controls (called DEGs for NAFLD), as well as between NASH and normal tissue (called DEGs for NASH-Normal), and between NASH and NAFL tissue (called DEGs for NASH-NAFL). For DEGs for the NAFLD group, key genes were identified by studying the form of intersection. Potential functions of DEGs for NASH were then analyzed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A protein-protein interaction network (PPI) was constructed using the STRING database. A total of 249 DEGs and one key gene for NAFLD were identified. For NASH-Normal, 514 DEGs and 11 hub genes were identified, three of which were closely related to the survival analysis of HCC, and potentially closely related to progression from NASH to HCC. One key gene for NASH-NAFL (AKR1B10) was identified. These genes appear to mediate the molecular mechanism underlying NAFLD and may be promising biomarkers for the presence of NASH.

Feng G ，Li XP ，Niu CY ，Liu ML ，Yan QQ ，Fan LP ，Li Y ，Zhang KL ，Gao J ，Qian MR ，He N ，Mi M ... -  《-》

The role of differentially expressed genes and immune cell infiltration in the progression of nonalcoholic steatohepatitis (NASH) to hepatocellular carcinoma (HCC): a new exploration based on bioinformatics analysis.

Liu Y ，Yu X ，Wang Y ，Wu J ，Feng B ，Li M ... -  《-》

Microarray-based Detection of Critical Overexpressed Genes in the Progression of Hepatic Fibrosis in Non-alcoholic Fatty Liver Disease: A Protein-protein Interaction Network Analysis.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent cause of chronic liver disease and encompasses a broad spectrum of disorders, including simple steatosis, steatohepatitis, fibrosis, cirrhosis, and liver cancer. However, due to the global epidemic of NAFLD, where invasive liver biopsy is the gold standard for diagnosis, it is necessary to identify a more practical method for early NAFLD diagnosis with useful therapeutic targets; as such, molecular biomarkers could most readily serve these aims. To this end, we explored the hub genes and biological pathways in fibrosis progression in NAFLD patients. Raw data from microarray chips with GEO accession GSE49541 were downloaded from the Gene Expression Omnibus database, and the R package (Affy and Limma) was applied to investigate differentially expressed genes (DEGs) involved in the progress of low- (mild 0-1 fibrosis score) to high- (severe 3-4 fibrosis score) fibrosis stage NAFLD patients. Subsequently, significant DEGs with pathway enrichment were analyzed, including gene ontology (GO), KEGG and Wikipathway. In order to then explore critical genes, the protein-protein interaction network (PPI) was established and visualized using the STRING database, with further analysis undertaken using Cytoscape and Gephi software. Survival analysis was undertaken to determine the overall survival of the hub genes in the progression of NAFLD to hepatocellular carcinoma. A total of 311 significant genes were identified, with an expression of 278 being upregulated and 33 downregulated in the high vs. low group. Gene functional enrichment analysis of these significant genes demonstrated major involvement in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and the AGE-RAGE signaling pathway. The PPI network was constructed with 196 nodes and 572 edges with PPI enrichment using a p-value < 1.0 e-16. Based on this cut-off, we identified 12 genes with the highest score in four centralities: Degree, Betweenness, Closeness, and Eigenvector. Those twelve hub genes were CD34, THY1, CFTR, COL3A1, COL1A1, COL1A2, SPP1, THBS1, THBS2, LUM, VCAN, and VWF. Four of these hub genes, namely CD34, VWF, SPP1, and VCAN, showed significant association with the development of hepatocellular carcinoma. This PPI network analysis of DEGs identified critical hub genes involved in the progression of fibrosis and the biological pathways through which they exert their effects in NAFLD patients. Those 12 genes offer an excellent opportunity for further focused research to determine potential targets for therapeutic applications.

Mahmoudi A ，Butler AE ，De Vincentis A ，Jamialahmadi T ，Sahebkar A ... -  《-》

Integrated Multichip Analysis Identifies Potential Key Genes in the Pathogenesis of Nonalcoholic Steatohepatitis.

Nonalcoholic steatohepatitis (NASH) is rapidly becoming a major chronic liver disease worldwide. However, little is known concerning the pathogenesis and progression mechanism of NASH. Our aim here is to identify key genes and elucidate their biological function in the progression from hepatic steatosis to NASH. Gene expression datasets containing NASH patients, hepatic steatosis patients, and healthy subjects were downloaded from the Gene Expression Omnibus database, using the R packages biobase and GEOquery. Differentially expressed genes (DEGs) were identified using the R limma package. Functional annotation and enrichment analysis of DEGs were undertaken using the R package ClusterProfile. Protein-protein interaction (PPI) networks were constructed using the STRING database. Three microarray datasets GSE48452, GSE63067 and GSE89632 were selected. They included 45 NASH patients, 31 hepatic steatosis patients, and 43 healthy subjects. Two up-regulated and 24 down-regulated DEGs were found in both NASH patients vs. healthy controls and in steatosis subjects vs. healthy controls. The most significantly differentially expressed genes were FOSB (P = 3.43×10-15), followed by CYP7A1 (P = 2.87×10-11), and FOS (P = 6.26×10-11). Proximal promoter DNA-binding transcription activator activity, RNA polymerase II-specific (P = 1.30×10-5) was the most significantly enriched functional term in the gene ontology analysis. KEGG pathway enrichment analysis indicated that the MAPK signaling pathway (P = 3.11×10-4) was significantly enriched. This study characterized hub genes of the liver transcriptome, which may contribute functionally to NASH progression from hepatic steatosis.

Ye J ，Lin Y ，Wang Q ，Li Y ，Zhao Y ，Chen L ，Wu Q ，Xu C ，Zhou C ，Sun Y ，Ye W ，Bai F ，Zhou T ... -  《Frontiers in Endocrinology》

Key factors and potential drug combinations of nonalcoholic steatohepatitis: Bioinformatic analysis and experimental validation-based study.

Nonalcoholic fatty liver disease and its advanced stage, nonalcoholic steatohepatitis (NASH), are the major cause of hepatocellular carcinoma (HCC) and other end-stage liver disease. However, the potential mechanism and therapeutic strategies have not been clarified. This study aimed to identify potential roles of miRNA/mRNA axis in the pathogenesis and drug combinations in the treatment of NASH. Microarray GSE59045 and GSE48452 were downloaded from the Gene Expression Omnibus and analyzed using R. Then we obtained differentially expressed genes (DE-genes). DAVID database was used for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis. Protein-protein interaction (PPI) networks were used for the identification of hub genes. We found upstream regulators of hub genes using miRTarBase. The expression and correlation of key miRNA and its targets were detected by qPCR. Drug Pair Seeker was employed to predict drug combinations against NASH. The expression of miRNA and hub genes in HCC was identified in the Cancer Genome Atlas database and Human Protein Atlas database. Ninety-four DE-genes were accessed. GO and KEGG analysis showed that these predicted genes were linked to lipid metabolism. Eleven genes were identified as hub genes in PPI networks, and they were highly expressed in cells with vigorous lipid metabolism. hsa-miR-335-5p was the upstream regulator of 9 genes in the 11 hub genes, and it was identified as a key miRNA. The hub genes were highly expressed in NASH models, while hsa-miR-335-5p was lowly expressed. The correlation of miRNA-mRNA was established by qPCR. Functional verification indicated that hsa-miR-335-5p had inhibitory effect on the development of NASH. Finally, drug combinations were predicted and the expression of miRNA and hub genes in HCC was identified. In the study, potential miRNA-mRNA pathways related to NASH were identified. Targeting these pathways may be novel strategies against NASH.

Fan GH ，Wei RL ，Wei XY ，Zhang CZ ，Qi ZT ，Xie HY ，Zheng SS ，Xu X ... -  《Hepatobiliary & Pancreatic Diseases International》