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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
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 |
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author | Li, Yinghao Shi, Hongshuo Chen, Tingting Xue, Jingcai Wang, Chuchu Peng, Min Si, Guomin |
author_facet | Li, Yinghao Shi, Hongshuo Chen, Tingting Xue, Jingcai Wang, Chuchu Peng, Min Si, Guomin |
author_sort | Li, Yinghao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8848454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-88484542022-03-10 Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease Li, Yinghao Shi, Hongshuo Chen, Tingting Xue, Jingcai Wang, Chuchu Peng, Min Si, Guomin Ann Transl Med Original Article 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. AME Publishing Company 2022-01 /pmc/articles/PMC8848454/ /pubmed/35282112 http://dx.doi.org/10.21037/atm-21-6762 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Li, Yinghao Shi, Hongshuo Chen, Tingting Xue, Jingcai Wang, Chuchu Peng, Min Si, Guomin Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title | Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title_full | Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title_fullStr | Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title_full_unstemmed | Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title_short | Establishing a competing endogenous RNA (ceRNA)-immunoregulatory network associated with the progression of Alzheimer’s disease |
title_sort | establishing a competing endogenous rna (cerna)-immunoregulatory network associated with the progression of alzheimer’s disease |
topic | Original Article |
url | 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 |
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