Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease affecting the elderly, characterized by decreased cognitive function. Non-coding RNAs contribute to AD pathogenesis. Objective: To identify potential therapeutic targets for AD, competing endogenous RNA (ceRNA) networks were constructed using the hippocampus of 6-month-old amyloid precursor protein/presenilin 1 double transgenic (APP/PS1) and wild-type mice. Methods: RNA-seq data (GSE158995), generated from the hippocampus of APP/PS1 and wild-type mice, were analyzed with the limma R package to identify significantly differentially expressed mRNAs and circRNAs (DEMs and DECs, respectively). DEM Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using Enrichr (https://maayanlab.cloud/Enrichr/). Correlations between DEMs and DECs were determined using the ggcorrplot R package. Main clusters and hub DEMs were selected using the STRING database and Cytoscape software. ceRNA interactions were predicted with the miRTarbase and Starbase tools and constructed with the ggalluvial R package and Cytoscape software. ceRNA networks were validated using the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot. Results: 198 DEMs and 90 DECs were differentially expressed in APP/PS1 vs. wild-type hippocampus. DEM GO analysis revealed significant enrichment in transcription regulation, which was subdivided into three main clusters: transcription regulation, synaptic plasticity, and protein refolding. Within the transcription regulation cluster, AP-1 transcription factor components serve as hub genes. The mmu_circ_0001787(circGLCE)/miR-339-5p/Junb and mmu_circ_0001899(circFAM120C)/ miR-181a-5p/Egr1 ceRNA networks were established based on qRT-PCR and Western blot analysis. Conclusion: Two AP-1 transcription factor component-related ceRNA networks, circGLCE/miR-339-5p/Junb and circFAM120C/miR-181a-5p/Egr1, were constructed using a mouse model of AD. These ceRNA networks may contribute to transcription regulation in AD and provide potential biomarkers for AD diagnosis and treatment.