Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease

BACKGROUND: Alzheimer’s disease (AD) is closely related to immunity and competitive endogenous RNAs (ceRNAs) are believed to play a key role in the development of AD. Therefore, understanding the ceRNA network related to AD immunity will contribute to the identification of novel immunotherapeutic ta...

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Detalles Bibliográficos
Autores principales: Li, Yinghao, Shi, Hongshuo, Chen, Tingting, Xue, Jingcai, Wang, Chuchu, Peng, Min, Si, Guomin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848454/
https://www.ncbi.nlm.nih.gov/pubmed/35282112
http://dx.doi.org/10.21037/atm-21-6762
Descripción
Sumario:BACKGROUND: Alzheimer’s disease (AD) is closely related to immunity and competitive endogenous RNAs (ceRNAs) are believed to play a key role in the development of AD. Therefore, understanding the ceRNA network related to AD immunity will contribute to the identification of novel immunotherapeutic targets and provide new insights into AD from an immunological perspective. METHODS: Weighted gene coexpression network analysis (WGCNA) and Enrichr enrichment analysis were performed to identify the immune-related gene coexpression modules through microarray datasets from the Gene Expression Omnibus (GEO) database. The differentially expressed long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) were identified from the microarray through differential analysis and mapped with related databases. Cytoscape was used to construct a lncRNA-miRNA-mRNA network. Subsequently, ImmuCellAI immune infiltration analysis was performed and a ceRNA sub-network of related core immune cells was constructed. Finally, the potential pathways related to these core factors were determined through gene set enrichment analysis (GSEA). RESULTS: Through WGCNA analysis and enrichment analysis, the blue module and the green module were identified as key modules related to AD immunity. Naïve CD8 cells were shown to be the key immune cells related to AD. Correlation analysis and receiver operating characteristic (ROC) curves verified lncRNA Long Intergenic Non-Protein Coding RNA 472 (LINC00472), lncRNA HLA Complex Group 18 (HCG18), RUNX Family Transcription Factor 3 (RUNX3), Tensionin 1 (TNS1), Linker For Activation Of T Cells Family Member 2 (LAT2), and Solute Carrier Family 38 Member 2 (SLC38A2) as possible key targets related to AD immunity. CONCLUSIONS: The lncRNA LINC00472, lncRNA HCG18, RUNX3, TNS1, LAT2, and SLC38A2 identified in this study may be key targets related to AD immunity. These insights will provide future directions for the further AD research.

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