ORIGINAL RESEARCH article
Front. Mol. Biosci.
Sec. RNA Networks and Biology
MiRNA-associated gene networks reveal potential candidate markers for Alzheimer's Disease
Shujuan Pan 1
Yanfang Zhou 1
Xiaoyu Wang 1
Jinghui Tong 1
Yanli Li 1
Junchao Huang 1
Song Chen 1
Yimin Cui 2
Zhiren Wang 1
Yunlong Tan 1
1. Beijing Huilongguan Hospital, Beijing, China
2. Peking University First Hospital, Beijing, China
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Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive decline. Recent studies highlight the significant role of microRNAs (miRNAs) in regulating genes related to AD. This research aims to develop miRNA-associated gene regulatory networks as candidate AD biomarkers. We recruited 85 AD patients and 74 healthy controls, conducting whole blood miRNA sequencing and applying machine learning to identify differentially expressed miRNAs, which were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used bioinformatics databases to predict target genes for these miRNAs and obtained gene expression data from the The Gene Expression Omnibus (GEO) database (GSE122063 and GSE18309). Using the ggplot2 package in R, we discovered the overlap between miRNA target genes and differentially expressed genes (DEGs) from the GSE datasets. Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses of the DEGs were then conducted using the Metascape database. Key hub genes were pinpointed by constructing a protein-protein interaction (PPI) network with the Retrieval of Interacting Genes (STRING) database and analyzing it with cytoHubba. Drug-gene interactions were predicted and examined using the Drug-Gene Interaction database (DGIdb) (http://www.dgidb.org/). Finally, qRT-PCR was used to confirm the expression of the hub genes. The results showed that four miRNAs (miR-192-5p, miR-484, miR-21-5p, and miR-24-2-5p) were downregulated, while two target RNAs (SLC32A1 and GAD1) were upregulated. This regulatory network, which is strongly linked to AD, has been initially identified as a candidate biomarker for AD. Our research provides new insights into the pathogenic mechanisms of AD, potentially improving the understanding of miRNAs' role in the disease.
Summary
Keywords
Alzheimer's disease, GAD1, gene networks, miRNA, SLC32A1
Received
05 September 2025
Accepted
16 December 2025
Copyright
© 2025 Pan, Zhou, Wang, Tong, Li, Huang, Chen, Cui, Wang and Tan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yunlong Tan
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