Exploring the common pathogenesis of Alzheimer's disease and type 2 diabetes mellitus

Alzheimer’s disease bioinformatics analysis network pharmacology pathophysiological mechanisms type 2 diabetes mellitus

Journal

Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824

Informations de publication

Date de publication:
2023
Historique:
received: 16 10 2022
accepted: 03 02 2023
entrez: 16 3 2023
pubmed: 17 3 2023
medline: 17 3 2023
Statut: epublish

Résumé

Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (DM) have an increased incidence in modern society. Although more and more evidence has supported that DM is prone to AD, the interrelational mechanisms remain fully elucidated. The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM. Download the expression matrix of AD and DM from the Gene Expression Omnibus (GEO) database with sequence numbers GSE97760 and GSE95849, respectively. The common differentially expressed genes (DEGs) were identified by limma package analysis. Then we analyzed the six kinds of module analysis: gene functional annotation, protein-protein interaction (PPI) network, potential drug screening, immune cell infiltration, hub genes identification and validation, and prediction of transcription factors (TFs). The subsequent analyses included 339 common DEGs, and the importance of immunity, hormone, cytokines, neurotransmitters, and insulin in these diseases was underscored by functional analysis. In addition, serotonergic synapse, ovarian steroidogenesis, estrogen signaling pathway, and regulation of lipolysis are closely related to both. DEGs were input into the CMap database to screen small molecule compounds with the potential to reverse AD and DM pathological functions. L-690488, exemestane, and BMS-345541 ranked top three among the screened small molecule compounds. Finally, 10 essential hub genes were identified using cytoHubba, including The common pathogenesis of AD and DM was revealed in our research. These common pathways and hub genes directions for further exploration of the pathogenesis or treatment of these two diseases.

Sections du résumé

Background UNASSIGNED
Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (DM) have an increased incidence in modern society. Although more and more evidence has supported that DM is prone to AD, the interrelational mechanisms remain fully elucidated.
Purpose UNASSIGNED
The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM.
Methods UNASSIGNED
Download the expression matrix of AD and DM from the Gene Expression Omnibus (GEO) database with sequence numbers GSE97760 and GSE95849, respectively. The common differentially expressed genes (DEGs) were identified by limma package analysis. Then we analyzed the six kinds of module analysis: gene functional annotation, protein-protein interaction (PPI) network, potential drug screening, immune cell infiltration, hub genes identification and validation, and prediction of transcription factors (TFs).
Results UNASSIGNED
The subsequent analyses included 339 common DEGs, and the importance of immunity, hormone, cytokines, neurotransmitters, and insulin in these diseases was underscored by functional analysis. In addition, serotonergic synapse, ovarian steroidogenesis, estrogen signaling pathway, and regulation of lipolysis are closely related to both. DEGs were input into the CMap database to screen small molecule compounds with the potential to reverse AD and DM pathological functions. L-690488, exemestane, and BMS-345541 ranked top three among the screened small molecule compounds. Finally, 10 essential hub genes were identified using cytoHubba, including
Conclusion UNASSIGNED
The common pathogenesis of AD and DM was revealed in our research. These common pathways and hub genes directions for further exploration of the pathogenesis or treatment of these two diseases.

Identifiants

pubmed: 36923118
doi: 10.3389/fnagi.2023.1071391
pmc: PMC10008874
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1071391

Informations de copyright

Copyright © 2023 Ye, Liu, Wang, Cheng, Li, Bai, Yang, Wang, Wen, Xu, Zhang, Xu and Li.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Xian-Wen Ye (XW)

Centre of TCM Processing Research, Beijing University of Chinese Medicine, Beijing, China.
Beijing Key Laboratory for Quality Evaluation of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Meng-Nan Liu (MN)

Centre of TCM Processing Research, Beijing University of Chinese Medicine, Beijing, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Xuan Wang (X)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Shui-Qing Cheng (SQ)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Chun-Shuai Li (CS)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Yu-Ying Bai (YY)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Lin-Lin Yang (LL)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Xu-Xing Wang (XX)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Jia Wen (J)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Wen-Juan Xu (WJ)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Shu-Yan Zhang (SY)

School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Xin-Fang Xu (XF)

Centre of TCM Processing Research, Beijing University of Chinese Medicine, Beijing, China.
Beijing Key Laboratory for Quality Evaluation of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Xiang-Ri Li (XR)

Centre of TCM Processing Research, Beijing University of Chinese Medicine, Beijing, China.
Beijing Key Laboratory for Quality Evaluation of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Classifications MeSH