Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease

Objective. Alzheimer’s disease (AD) is associated with cell cycle reentry of mature neurons that subsequently undergo degeneration. This study is aimed to identify key regulators of the cell cycle and their underlying pathways for developing optimal treatment of AD. Methods. RNA sequencing data were...

Full description

Bibliographic Details
Main Authors: Zhike Zhou, Jun Bai, Shanshan Zhong, Rongwei Zhang, Kexin Kang, Xiaoqian Zhang, Ying Xu, Chuansheng Zhao, Mei Zhao
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Oxidative Medicine and Cellular Longevity
Online Access:http://dx.doi.org/10.1155/2021/5552623
id doaj-df3b847506e842508e415cdee0a984a5
record_format Article
spelling doaj-df3b847506e842508e415cdee0a984a52021-07-26T00:34:08ZengHindawi LimitedOxidative Medicine and Cellular Longevity1942-09942021-01-01202110.1155/2021/5552623Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s DiseaseZhike Zhou0Jun Bai1Shanshan Zhong2Rongwei Zhang3Kexin Kang4Xiaoqian Zhang5Ying Xu6Chuansheng Zhao7Mei Zhao8Department of GeriatricsCancer Systems Biology CenterDepartment of NeurologyDepartment of GeriatricsDepartment of GeriatricsDepartment of NeurologyCancer Systems Biology CenterDepartment of NeurologyDepartment of CardiologyObjective. Alzheimer’s disease (AD) is associated with cell cycle reentry of mature neurons that subsequently undergo degeneration. This study is aimed to identify key regulators of the cell cycle and their underlying pathways for developing optimal treatment of AD. Methods. RNA sequencing data were profiled to screen for differentially expressed genes in the cell cycle. Correlation of created modules with AD phenotype was computed by weight gene correlation network analysis (WGCNA). Signature genes for trophic factor receptors were determined using Pearson correlation coefficient (PCC) analysis. Results. Among the 13,679 background genes, 775 cell cycle genes and 77 trophic factor receptors were differentially expressed in AD versus nondementia controls. Four coexpression modules were constructed by WGCNA, among which the turquoise module had the strongest correlation with AD. According to PCC analysis, 10 signature trophic receptors most strongly interacting with cell cycle genes were filtered and subsequently displayed in the global regulatory network. Further cross-talking pathways of signature receptors, such as glutamatergic synapse, long-term potentiation, PI3K-Akt, and MAPK signaling pathways, were identified. Conclusions. Our findings highlighted the mechanistic pathways of signature trophic receptors in cell cycle perturbation underlying AD pathogenesis, thereby providing new molecular targets for therapeutic intervention in AD.http://dx.doi.org/10.1155/2021/5552623
collection DOAJ
language English
format Article
sources DOAJ
author Zhike Zhou
Jun Bai
Shanshan Zhong
Rongwei Zhang
Kexin Kang
Xiaoqian Zhang
Ying Xu
Chuansheng Zhao
Mei Zhao
spellingShingle Zhike Zhou
Jun Bai
Shanshan Zhong
Rongwei Zhang
Kexin Kang
Xiaoqian Zhang
Ying Xu
Chuansheng Zhao
Mei Zhao
Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
Oxidative Medicine and Cellular Longevity
author_facet Zhike Zhou
Jun Bai
Shanshan Zhong
Rongwei Zhang
Kexin Kang
Xiaoqian Zhang
Ying Xu
Chuansheng Zhao
Mei Zhao
author_sort Zhike Zhou
title Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
title_short Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
title_full Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
title_fullStr Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
title_full_unstemmed Integrative Functional Genomic Analysis of Molecular Signatures and Mechanistic Pathways in the Cell Cycle Underlying Alzheimer’s Disease
title_sort integrative functional genomic analysis of molecular signatures and mechanistic pathways in the cell cycle underlying alzheimer’s disease
publisher Hindawi Limited
series Oxidative Medicine and Cellular Longevity
issn 1942-0994
publishDate 2021-01-01
description Objective. Alzheimer’s disease (AD) is associated with cell cycle reentry of mature neurons that subsequently undergo degeneration. This study is aimed to identify key regulators of the cell cycle and their underlying pathways for developing optimal treatment of AD. Methods. RNA sequencing data were profiled to screen for differentially expressed genes in the cell cycle. Correlation of created modules with AD phenotype was computed by weight gene correlation network analysis (WGCNA). Signature genes for trophic factor receptors were determined using Pearson correlation coefficient (PCC) analysis. Results. Among the 13,679 background genes, 775 cell cycle genes and 77 trophic factor receptors were differentially expressed in AD versus nondementia controls. Four coexpression modules were constructed by WGCNA, among which the turquoise module had the strongest correlation with AD. According to PCC analysis, 10 signature trophic receptors most strongly interacting with cell cycle genes were filtered and subsequently displayed in the global regulatory network. Further cross-talking pathways of signature receptors, such as glutamatergic synapse, long-term potentiation, PI3K-Akt, and MAPK signaling pathways, were identified. Conclusions. Our findings highlighted the mechanistic pathways of signature trophic receptors in cell cycle perturbation underlying AD pathogenesis, thereby providing new molecular targets for therapeutic intervention in AD.
url http://dx.doi.org/10.1155/2021/5552623
work_keys_str_mv AT zhikezhou integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT junbai integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT shanshanzhong integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT rongweizhang integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT kexinkang integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT xiaoqianzhang integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT yingxu integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT chuanshengzhao integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
AT meizhao integrativefunctionalgenomicanalysisofmolecularsignaturesandmechanisticpathwaysinthecellcycleunderlyingalzheimersdisease
_version_ 1721282482909741056