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BioMed Research International Volume 2019 ,2019-07-14
The Model of Aging Acceleration Network Reveals the Correlation of Alzheimer’s Disease and Aging at System Level
Research Article
Mengyu Zhou 1 Xiaoqiong Xia 1 Hao Yan 1 Sijia Li 1 Shiyu Bian 2 Xianzheng Sha 1 Yin Wang 1 , 3
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DOI:10.1155/2019/4273108
Received 2019-01-26, accepted for publication 2019-07-02, Published 2019-07-02
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摘要

As the incidence of senile dementia continues to increase, researches on Alzheimer’s disease (AD) have become more and more important. Several studies have reported that there is a close relationship between AD and aging. Some researchers even pointed out that if we wanted to understand AD in depth, mechanisms of AD based on accelerated aging must be studied. Nowadays, machine learning techniques have been utilized to deal with large and complex profiles, thus playing an important role in disease researches (i.e., modelling biological systems, identifying key modules based on biological networks, and so on). Here, we developed an aging predictor and an AD predictor using machine learning techniques, respectively. Both aging and AD biomarkers were identified to provide insights into genes associated with AD. Besides, aging scores were calculated to reflect the aging process of brain tissues. As a result, the aging acceleration network and the aging-AD bipartite graph were constructed to delve into the relationship between AD and aging. Finally, a series of network and enrichment analyses were also conducted to gain further insights into the mechanisms of AD based on accelerated aging. In a word, our results indicated that aging may contribute to the development of AD by affecting the function of the immune system and the energy metabolism process, where the immune system may play a more prominent role in AD.

授权许可

Copyright © 2019 Mengyu Zhou et al. 2019
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

通讯作者

1. Xianzheng Sha.Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang 110122, Liaoning Province, China, cmu.edu.cn.xzsha@cmu.edu.cn
2. Yin Wang.Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang 110122, Liaoning Province, China, cmu.edu.cn;Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Affiliated Hospital of China Medical University, 155# North Nanjing Street, Heping District, Shenyang 110001, Liaoning Province, China, cmu.edu.cn.chinawangyin@foxmail.com

推荐引用方式

Mengyu Zhou,Xiaoqiong Xia,Hao Yan,Sijia Li,Shiyu Bian,Xianzheng Sha,Yin Wang. The Model of Aging Acceleration Network Reveals the Correlation of Alzheimer’s Disease and Aging at System Level. BioMed Research International ,Vol.2019(2019)

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