# miRNA-associated gene networks reveal potential candidate markers for Alzheimer’s disease

**Authors:** Shujuan Pan, Yanfang Zhou, Xiaoyu Wang, Jinghui Tong, Yanli Li, Junchao Huang, Song Chen, Yimin Cui, Zhiren Wang, Yun-Long Tan

PMC · DOI: 10.3389/fmolb.2025.1699404 · Frontiers in Molecular Biosciences · 2026-03-06

## TL;DR

This study identifies miRNA-associated gene networks that could serve as potential biomarkers for Alzheimer’s disease.

## Contribution

The novel contribution is the identification of miRNA-target gene networks as candidate biomarkers for Alzheimer’s disease.

## Key findings

- Four miRNAs (miR-192-5p, miR-484, miR-21-5p, and miR-24-2-5p) were found to be downregulated in Alzheimer’s patients.
- Two target genes (SLC32A1 and GAD1) were upregulated, suggesting their involvement in AD pathogenesis.
- The miRNA-associated gene network was identified as a potential biomarker for Alzheimer’s disease.

## 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 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/).

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.

## Linked entities

- **Genes:** SLC32A1 (solute carrier family 32 member 1) [NCBI Gene 140679], GAD1 (glutamate decarboxylase 1) [NCBI Gene 2571]
- **Diseases:** Alzheimer’s disease (MONDO:0004975)

## Full-text entities

- **Genes:** SLC32A1 (solute carrier family 32 member 1) [NCBI Gene 140679] {aka DEE114, GEFSP12, VGAT, VIAAT, VIAAT GEFSP12}, MIR484 (microRNA 484) [NCBI Gene 619553] {aka MIRN484, hsa-mir-484, mir-484}, MIR215 (microRNA 215) [NCBI Gene 406997] {aka MIRN215, miRNA215, mir-215}
- **Diseases:** AD (MESH:D000544), neurodegenerative disorder (MESH:D019636), memory and cognitive decline (MESH:D003072)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

10 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13002409/full.md

## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC13002409/full.md

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Source: https://tomesphere.com/paper/PMC13002409