Table_1_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.

背景：非酒精性脂肪性肝病（Non-alcoholic fatty liver disease, NAFLD）是公认的肝功能异常诱因，现已成为多国高发的慢性肝脏疾病。然而，其发病的内在分子机制尚未完全阐明。
方法：本研究通过基因表达综合数据库（Gene Expression Omnibus, GEO）获取非酒精性脂肪性肝病的基因表达数据集。随后采用稳健秩聚合（Robust rank aggregation, RRA）方法筛选非酒精性脂肪性肝病患者与健康对照者之间的差异表达基因（differentially expressed genes, DEGs）。通过基因功能注释与蛋白质相互作用（Protein-Protein Interaction, PPI）网络分析，探究差异表达基因的潜在功能。最后，使用测序数据集GSE126848对本研究结果进行验证。
结果：本研究纳入GSE48452、GSE66676、GSE72756、GSE63067、GSE89632及GSE107231共6个数据集，包含125例非酒精性脂肪性肝病患者与116例健康对照者。经稳健秩聚合整合分析，共筛选得到96个显著差异表达基因（其中50个上调表达，46个下调表达）；非酒精性脂肪性肝病中异常表达最显著的基因为ENO3（P值=7.17×10^-5），其次为CYP7A1（P值=9.04×10^-5）与P4HA1（P值=1.67×10^-4）。基因本体（Gene Ontology, GO）富集分析显示，最显著富集的生物过程为羧酸代谢过程（GO:0019752；P值=1.39×10^-3）。京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析结果显示，类固醇激素生物合成通路（hsa00140；P值=6.68×10^-3）与过氧化物酶体增殖物激活受体（Peroxisome proliferator-activated receptor, PPAR）信号通路（hsa03320；P值=9.95×10^-3）显著富集。结合蛋白质相互作用网络与稳健秩聚合分析结果，本研究最终确定4个关键基因作为核心基因，分别为ENO3、CYP7A1、P4HA1与CYP1A1。
结论：本整合分析筛选得到全新的基因特征，有助于深入理解非酒精性脂肪性肝病的全面分子变化。