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Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease

BACKGROUND: Alzheimer’s disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized. METHODS: Differentially expressed genes (DEGs) were identified usi...

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Autores principales: Liang, Lucong, Yan, Jing, Huang, Xiaohua, Zou, Chun, Chen, Liechun, Li, Rongjie, Xie, Jieqiong, Pan, Mika, Zou, Donghua, Liu, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386361/
https://www.ncbi.nlm.nih.gov/pubmed/35990086
http://dx.doi.org/10.3389/fpsyt.2022.925012
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author Liang, Lucong
Yan, Jing
Huang, Xiaohua
Zou, Chun
Chen, Liechun
Li, Rongjie
Xie, Jieqiong
Pan, Mika
Zou, Donghua
Liu, Ying
author_facet Liang, Lucong
Yan, Jing
Huang, Xiaohua
Zou, Chun
Chen, Liechun
Li, Rongjie
Xie, Jieqiong
Pan, Mika
Zou, Donghua
Liu, Ying
author_sort Liang, Lucong
collection PubMed
description BACKGROUND: Alzheimer’s disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized. METHODS: Differentially expressed genes (DEGs) were identified using publicly available human gene expression profiles GSE5281 for AD and GSE40562 for sleep disorder. DEGs common to the two datasets were used for enrichment analysis, and we performed multi-scale embedded gene co-expression network analysis (MEGENA) for common DEGs. Fast gene set enrichment analysis (fGSEA) was used to obtain common pathways, while gene set variation analysis (GSVA) was applied to quantify those pathways. Subsequently, we extracted the common genes between module genes identified by MEGENA and genes of the common pathways, and we constructed protein-protein interaction (PPI) networks. The top 10 genes with the highest degree of connectivity were classified as hub genes. Common genes were used to perform Metascape enrichment analysis for functional enrichment. Furthermore, we quantified infiltrating immune cells in patients with AD or sleep disorder and in controls. RESULTS: DEGs common to the two disorders were involved in the citrate cycle and the HIF-1 signaling pathway, and several common DEGs were related to signaling pathways regulating the pluripotency of stem cells, as well as 10 other pathways. Using MEGENA, we identified 29 modules and 1,498 module genes in GSE5281, and 55 modules and 1,791 module genes in GSE40562. Hub genes involved in AD and sleep disorder were ATP5A1, ATP5B, COX5A, GAPDH, NDUFA9, NDUFS3, NDUFV2, SOD1, UQCRC1, and UQCRC2. Plasmacytoid dendritic cells and T helper 17 cells had the most extensive infiltration in both AD and sleep disorder. CONCLUSION: AD pathology and pathways of neurodegeneration participate in processes contributing in AD and sleep disorder. Hub genes may be worth exploring as potential candidates for targeted therapy of AD and sleep disorder.
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spelling pubmed-93863612022-08-19 Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease Liang, Lucong Yan, Jing Huang, Xiaohua Zou, Chun Chen, Liechun Li, Rongjie Xie, Jieqiong Pan, Mika Zou, Donghua Liu, Ying Front Psychiatry Psychiatry BACKGROUND: Alzheimer’s disease (AD) and sleep disorders are both neurodegenerative conditions characterized by impaired or absent sleep. However, potential common pathogenetic mechanisms of these diseases are not well characterized. METHODS: Differentially expressed genes (DEGs) were identified using publicly available human gene expression profiles GSE5281 for AD and GSE40562 for sleep disorder. DEGs common to the two datasets were used for enrichment analysis, and we performed multi-scale embedded gene co-expression network analysis (MEGENA) for common DEGs. Fast gene set enrichment analysis (fGSEA) was used to obtain common pathways, while gene set variation analysis (GSVA) was applied to quantify those pathways. Subsequently, we extracted the common genes between module genes identified by MEGENA and genes of the common pathways, and we constructed protein-protein interaction (PPI) networks. The top 10 genes with the highest degree of connectivity were classified as hub genes. Common genes were used to perform Metascape enrichment analysis for functional enrichment. Furthermore, we quantified infiltrating immune cells in patients with AD or sleep disorder and in controls. RESULTS: DEGs common to the two disorders were involved in the citrate cycle and the HIF-1 signaling pathway, and several common DEGs were related to signaling pathways regulating the pluripotency of stem cells, as well as 10 other pathways. Using MEGENA, we identified 29 modules and 1,498 module genes in GSE5281, and 55 modules and 1,791 module genes in GSE40562. Hub genes involved in AD and sleep disorder were ATP5A1, ATP5B, COX5A, GAPDH, NDUFA9, NDUFS3, NDUFV2, SOD1, UQCRC1, and UQCRC2. Plasmacytoid dendritic cells and T helper 17 cells had the most extensive infiltration in both AD and sleep disorder. CONCLUSION: AD pathology and pathways of neurodegeneration participate in processes contributing in AD and sleep disorder. Hub genes may be worth exploring as potential candidates for targeted therapy of AD and sleep disorder. Frontiers Media S.A. 2022-08-04 /pmc/articles/PMC9386361/ /pubmed/35990086 http://dx.doi.org/10.3389/fpsyt.2022.925012 Text en Copyright © 2022 Liang, Yan, Huang, Zou, Chen, Li, Xie, Pan, Zou and Liu. https://creativecommons.org/licenses/by/4.0/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) and the copyright owner(s) 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.
spellingShingle Psychiatry
Liang, Lucong
Yan, Jing
Huang, Xiaohua
Zou, Chun
Chen, Liechun
Li, Rongjie
Xie, Jieqiong
Pan, Mika
Zou, Donghua
Liu, Ying
Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title_full Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title_fullStr Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title_full_unstemmed Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title_short Identification of molecular signatures associated with sleep disorder and Alzheimer’s disease
title_sort identification of molecular signatures associated with sleep disorder and alzheimer’s disease
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386361/
https://www.ncbi.nlm.nih.gov/pubmed/35990086
http://dx.doi.org/10.3389/fpsyt.2022.925012
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