Candidate genes investigation for severe nonalcoholic fatty liver disease based on bioinformatics analysis

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Abstract

Background:

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver condition worldwide. However, its etiology and fundamental pathophysiology for the disease process are poorly understood. In this study, we thus used bioinformatics to identify candidate genes potentially causative of severe NAFLD.

Methods:

Gene expression profile data GSE49541 were downloaded from the Gene Expression Omnibus database. Tissues samples from 32 severe and 40 mild NAFLD patients were evaluated to identify differentially expressed genes (DEGs) between the 2 groups, followed by analyses of Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes pathways. Then, a weighted protein–protein interaction (PPI) network was constructed, and subnetworks and candidate genes were screened. Moreover, the GSE48452 data (14 normal liver tissue samples and 18 nonalcoholic steatohepatitis samples) were used to verify the results obtained from the above analyses.

Results:

A total of 100 upregulated genes and 24 downregulated ones were identified in severe NAFLD. Functional enrichment and pathway analyses showed that these DEGs were mainly associated with cell adhesion, inflammatory response, and chemokine activity. The top 5 subnetworks were selected based on the PPI network. A total of 5 hub genes, including ubiquilin 4 (UBQLN4), amyloid-beta precursor protein (APP), sex hormone–binding globulin (SHBG), cadherin-associated protein beta 1 (CTNNB1) and collagen type I alpha 1 (COL1A1), were considered to be candidate genes for NAFLD. In addition, the verification data confirmed the status of COL1A1, SHBG, and APP as candidate genes.

Conclusion:

UBQLN4, APP, CTNNB1, SHBG, and COL1A1 might be involved in the development of NAFLD, and are proposed as the potential markers for predicting the development of this condition.

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