文献类型：期刊文献

英文题名：Identification of HIBCH and MGME1 as Mitochondrial Dynamics-Related Biomarkers in Alzheimer's Disease Via Integrated Bioinformatics Analysis

作者：Li, Hailong[1,2];Feng, Fei[3];Xie, Shoupin[4];Ma, Yanping[2];Wang, Yafeng[2];Zhang, Fan[2];Wu, Hongyan[5];Huang, Shenghui[6]

第一作者：Li, Hailong;李海龙

通信作者：Li, HL[1];Li, HL[2];Huang, SH[3]

机构：[1]Shantou Univ, Luohu Clin Coll, Sch Med, Dept Gen Practice, Shenzhen, Peoples R China;[2]Gansu Univ Tradit Chinese Med, Affiliated Hosp, Dept Geriatr, Lanzhou, Peoples R China;[3]Shenzhen Kangning Hosp, Sleep Med Ward, Shenzhen, Peoples R China;[4]Lanzhou First Peoples Hosp, Dept Neurol, Lanzhou, Peoples R China;[5]Luohu Dist Hosp Tradit Chinese Med, Dept Geriatr, Shenzhen, Peoples R China;[6]Gansu Prov Hosp Tradit Chinese Med, Dept Mental Hlth & Sleep Ctr, Lanzhou, Peoples R China

第一机构：Shantou Univ, Luohu Clin Coll, Sch Med, Dept Gen Practice, Shenzhen, Peoples R China

通信机构：[1]corresponding author), Shantou Univ, Luohu Clin Coll, Sch Med, Dept Gen Practice, Shenzhen, Peoples R China;[2]corresponding author), Gansu Univ Tradit Chinese Med, Affiliated Hosp, Dept Geriatr, Lanzhou, Peoples R China;[3]corresponding author), Gansu Prov Hosp Tradit Chinese Med, Dept Mental Hlth & Sleep Ctr, Lanzhou, Peoples R China.|[10735b845793de6ae2b30]甘肃中医药大学第二附属医院;[10735]甘肃中医药大学;

年份：2025

卷号：19

期号：1

外文期刊名：IET SYSTEMS BIOLOGY

收录：;EI(收录号：20251818336371);Scopus(收录号：2-s2.0-105003796894);WOS:【SCI-EXPANDED(收录号:WOS:001524085500005)】；

基金：The authors have nothing to report.

语种：英文

外文关键词：bioinformatics; biomechanics; brain; data analysis; network analysis

摘要：Mitochondrial dynamics (MD) play a crucial role in the genesis of Alzheimer's disease (AD); however, the molecular mechanisms underlying MD dysregulation in AD remain unclear. This study aimed to identify critical molecules of MD that contribute to AD progression using GEO data and bioinformatics approaches. The GSE63061 dataset comparing AD patients with healthy controls was analysed, WGCNA was employed to identify co-expression modules and differentially expressed genes (DEGs) and LASSO model was developed and verified using the DEGs to screen for potential biomarkers. A PPI network was built to predict upstream miRNAs, which were experimentally validated using luciferase reporter assays. A total of 3518 DEGs were identified (2209 upregulated, 1309 downregulated; |log(2)FC| > 1.5, adjusted p < 0.05). WGCNA revealed 160 MD-related genes. LASSO regression selected HIBCH and MGME1 as novel biomarkers with significant downregulation in AD (fold change > 2, p < 0.001). KEGG enrichment analysis highlighted pathways associated with neurodegeneration. Luciferase assays confirmed direct binding of miR-922 to the 3 ' UTR of MGME1. HIBCH and MGME1 are promising diagnostic biomarkers for AD with AUC values of 0.73 and 0.74. Mechanistically, miR-922 was experimentally validated to directly bind MGME1 3 ' UTR.