Discovery and Validation of Key Risk Genes in NAFLD Disease Progression
10.11969/j.issn.1673-548X.2024.12.015
- VernacularTitle:NAFLD疾病进程关键风险基因发现与验证
- Author:
Yongkang CUI
1
;
Xiaojun GOU
;
Shan CAO
Author Information
1. 201999 上海中医药大学附属宝山医院消化科
- Publication Type:Journal Article
- Keywords:
Nonalcoholic fatty liver disease;
Differential expression gene analysis;
KEGG pathway enrichment analysis;
PPI net-work analysis;
Disease progression;
Risk prediction model
- From:
Journal of Medical Research
2024;53(12):78-87
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the key genes of nonalcoholic fatty liver disease(NAFLD),construct and verify the risk predic-tion model of NAFLD disease process Methods Based on the existing genomic microarray data for NAFLD from the GEO database,utili-zing differential expression gene analysis,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis,protein-protein interaction(PPI)network analysis,and machine learning-based feature selection methods,key genes involved in the progression of NAFLD were identified,and a risk prediction model for the progression from simple steatosis(SS)to nonalcoholic steatohepatitis(NASH)was developed.Validation of these key genes was performed through molecular biology experiments in vitro.Results The re-sults of differential expression gene analysis in GEO database showed that there were 1247differential expression genes between the normal control(NC)group and the NASH group,1088differential expression genes between the NC group and the SS group,and 75differential expression genes between the SS group and NASH group.KEGG pathway enrichment analysis,informed by previous studies and litera-ture,identified 4 common signaling pathways related to NAFLD:cholesterol metabolism(hsa04979),galactose metabolism(hsa00052),PI3K/Akt signaling pathway(hsa04151),and PPAR signaling pathway(hsa03320).Using three distinct machine learning-based fea-ture selection methods,4 common genes were pinpointed:AKR1B10,COL1A2,HKDC1 and LAMC3.Molecular biology experiments in vitro showed that AKR1B10 and COL1A2 were significantly up-regulated in NAFLD,which was consistent with the bioinformatics analy-sis results.Conclusion This study identified key genes associated with the progression from SS to NASH and developed a risk prediction model for NAFLD disease progression.These findings offer valuable methods and technologies for the effective control,intervention,and clinical diagnosis and treatment of NAFLD.
