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Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis

BACKGROUND: 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: The primary purpose of this study is to explore...

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Autores principales: Ye, Xian-wen, Liu, Meng-nan, Wang, Xuan, Cheng, Shui-qing, Li, Chun-shuai, Bai, Yu-ying, Yang, Lin-lin, Wang, Xu-xing, Wen, Jia, Xu, Wen-juan, Zhang, Shu-yan, Xu, Xin-fang, Li, Xiang-ri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008874/
https://www.ncbi.nlm.nih.gov/pubmed/36923118
http://dx.doi.org/10.3389/fnagi.2023.1071391
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author Ye, Xian-wen
Liu, Meng-nan
Wang, Xuan
Cheng, Shui-qing
Li, Chun-shuai
Bai, Yu-ying
Yang, Lin-lin
Wang, Xu-xing
Wen, Jia
Xu, Wen-juan
Zhang, Shu-yan
Xu, Xin-fang
Li, Xiang-ri
author_facet Ye, Xian-wen
Liu, Meng-nan
Wang, Xuan
Cheng, Shui-qing
Li, Chun-shuai
Bai, Yu-ying
Yang, Lin-lin
Wang, Xu-xing
Wen, Jia
Xu, Wen-juan
Zhang, Shu-yan
Xu, Xin-fang
Li, Xiang-ri
author_sort Ye, Xian-wen
collection PubMed
description BACKGROUND: 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: The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM. METHODS: 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: 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 PTGS2, RAB10, LRRK2, SOS1, EEA1, NF1, RAB14, ADCY5, RAPGEF3, and PRKACG. For the characteristic Aβ and Tau pathology of AD, RAPGEF3 was associated significantly positively with AD and NF1 significantly negatively with AD. In addition, we also found ADCY5 and NF1 significant correlations with DM phenotypes. Other datasets verified that NF1, RAB14, ADCY5, and RAPGEF3 could be used as key markers of DM complicated with AD. Meanwhile, the immune cell infiltration score reflects the different cellular immune microenvironments of the two diseases. CONCLUSION: 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.
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spelling pubmed-100088742023-03-14 Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis Ye, Xian-wen Liu, Meng-nan Wang, Xuan Cheng, Shui-qing Li, Chun-shuai Bai, Yu-ying Yang, Lin-lin Wang, Xu-xing Wen, Jia Xu, Wen-juan Zhang, Shu-yan Xu, Xin-fang Li, Xiang-ri Front Aging Neurosci Aging Neuroscience BACKGROUND: 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: The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM. METHODS: 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: 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 PTGS2, RAB10, LRRK2, SOS1, EEA1, NF1, RAB14, ADCY5, RAPGEF3, and PRKACG. For the characteristic Aβ and Tau pathology of AD, RAPGEF3 was associated significantly positively with AD and NF1 significantly negatively with AD. In addition, we also found ADCY5 and NF1 significant correlations with DM phenotypes. Other datasets verified that NF1, RAB14, ADCY5, and RAPGEF3 could be used as key markers of DM complicated with AD. Meanwhile, the immune cell infiltration score reflects the different cellular immune microenvironments of the two diseases. CONCLUSION: 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. Frontiers Media S.A. 2023-02-27 /pmc/articles/PMC10008874/ /pubmed/36923118 http://dx.doi.org/10.3389/fnagi.2023.1071391 Text en Copyright © 2023 Ye, Liu, Wang, Cheng, Li, Bai, Yang, Wang, Wen, Xu, Zhang, Xu and Li. 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 Aging Neuroscience
Ye, Xian-wen
Liu, Meng-nan
Wang, Xuan
Cheng, Shui-qing
Li, Chun-shuai
Bai, Yu-ying
Yang, Lin-lin
Wang, Xu-xing
Wen, Jia
Xu, Wen-juan
Zhang, Shu-yan
Xu, Xin-fang
Li, Xiang-ri
Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title_full Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title_fullStr Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title_full_unstemmed Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title_short Exploring the common pathogenesis of Alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
title_sort exploring the common pathogenesis of alzheimer’s disease and type 2 diabetes mellitus via microarray data analysis
topic Aging Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008874/
https://www.ncbi.nlm.nih.gov/pubmed/36923118
http://dx.doi.org/10.3389/fnagi.2023.1071391
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