Table_2_Integrated Analysis of Multiple Microarray Studies to Identify Novel Gene Signatures in Non-alcoholic Fatty Liver Disease.docx

Background: Non-alcoholic fatty liver disease (NAFLD) is a well-known cause of liver dysfunction and has become a common chronic liver disease in many countries. However, the intrinsic molecular mechanisms underlying the pathogenesis of NAFLD have not yet been fully elucidated.
Methods: We obtained the gene expression datasets of NAFLD through the Gene Expression Omnibus (GEO) database. Subsequently, robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between NAFLD patients and controls. Gene functional annotation and PPI network analysis were performed to explore the potential function of the DEGs. Finally, we used a sequencing dataset GSE126848 to validate our results.
Results: In this study, GSE48452, GSE66676, GSE72756, GSE63067, GSE89632, and GSE107231 were included, including 125 NAFLD patients and 116 control patients. The RRA integrated analysis determined 96 significant DEGs (50 up-regulated and 46 down-regulated) and the most significant gene aberrantly expressed in NAFLD was ENO3 (P-value = 7.17E-05), followed by CYP7A1 (P-value = 9.04E-05), and P4HA1 (P-value = 1.67E-04). Carboxylic acid metabolic process (GO:0019752; P-value = 1.39E-03) was the most significantly enriched for biological process in GO (gene ontology) analysis. KEGG pathway enrichment analysis showed that steroid hormone biosynthesis (hsa00140; P-value = 6.68E-03) and PPAR signaling pathway (hsa03320; P-value = 9.95E-03) were significantly enriched. Based on the results of the PPI and the results of the RRA, we finally defined the four most critical genes as the hub genes, including ENO3, CYP7A1, P4HA1, and CYP1A1.
Conclusions: Our integrated analysis identified novel gene signatures and will contribute to the understanding of comprehensive molecular changes in NAFLD.