Screening for Core Genes Related to Pathogenesis of Alzheimer's Disease.
Screening for Core Genes Related to Pathogenesis of Alzheimer's Disease.
复制标题
筛选与阿尔茨海默病发病机制相关的核心基因。
DOI：
10.3389/fcell.2021.668738
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发表时间：
2021
影响因子：
5.5
通讯作者：
Jian C
中科院分区：
文献类型：
--
作者：
Yang L;Qin Y;Jian C
阿尔茨海默病（Alzheimer's disease，AD）是一种神经系统疾病，目前缺乏有效的治疗方法。RNA表达是调节生命活动的基本途径，识别AD患者的相关特征有助于探索AD的发病机制和治疗。本研究开发了一个能够准确区分AD患者和健康人的分类器，进而获得了3个可能与AD发病相关的核心基因。为此，首先从GEO数据库中下载AD患者颞中回的RNA表达数据，然后使用limma包对数据进行归一化，并通过k-最近邻（KNN）算法补充缺失数据。然后，通过最大相关最小冗余度（mRMR）分析得到特征重要性最高的前500个基因，并基于这些基因，采用支持向量机（SVM）、随机森林（RF）和KNN算法构建了一系列AD分类器。然后，在增量特征选择（IFS）分析中，由14个基因组成的具有最高马修斯相关系数（MCC）值的KNN分类器被确定为最佳AD分类器。分析表明，这14个基因在AD发病中起着关键作用，可能是AD发病的核心基因。最后，应用蛋白质相互作用网络（PPI）和重启随机游走（RWR）分析方法，获得核心基因相关基因，并进一步分析AD相关的关键通路。本研究有助于加深对AD发病机制的认识，为相关研究和实验提供理论指导。
Alzheimer’s disease (AD), a nervous system disease, lacks effective therapies at present. RNA expression is the basic way to regulate life activities, and identifying related characteristics in AD patients may aid the exploration of AD pathogenesis and treatment. This study developed a classifier that could accurately classify AD patients and healthy people, and then obtained 3 core genes that may be related to the pathogenesis of AD. To this end, RNA expression data of the middle temporal gyrus of AD patients were firstly downloaded from GEO database, and the data were then normalized using limma package following a supplementation of missing data by k-Nearest Neighbor (KNN) algorithm. Afterwards, the top 500 genes of the most feature importance were obtained through Max-Relevance and Min-Redundancy (mRMR) analysis, and based on these genes, a series of AD classifiers were constructed through Support Vector Machine (SVM), Random Forest (RF), and KNN algorithms. Then, the KNN classifier with the highest Matthews correlation coefficient (MCC) value composed of 14 genes in incremental feature selection (IFS) analysis was identified as the best AD classifier. As analyzed, the 14 genes played a pivotal role in determination of AD and may be core genes associated with the pathogenesis of AD. Finally, protein-protein interaction (PPI) network and Random Walk with Restart (RWR) analysis were applied to obtain core gene-associated genes, and key pathways related to AD were further analyzed. Overall, this study contributed to a deeper understanding of AD pathogenesis and provided theoretical guidance for related research and experiments.
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影响因子：
2.9
作者：
Feng L;Jin F
通讯作者：
Jin F
影响因子：
12.6
作者：
Du X;Wang X;Geng M
通讯作者：
Geng M
DOI：
10.3233/jad-161118
发表时间：
2017
期刊：
Journal of Alzheimer's disease : JAD
影响因子：
--
作者：
Kandimalla R;Reddy PH
通讯作者：
Reddy PH
影响因子：
5.5
作者：
Kulkarni, Hemant;Thangam, Manoj;Amin, Amit P.
通讯作者：
Amin, Amit P.
DOI：
10.1016/s0140-6736(16)31275-2
发表时间：
2016-12-10
期刊：
Lancet (London, England)
影响因子：
--
作者：
Gauthier S;Feldman HH;Schneider LS;Wilcock GK;Frisoni GB;Hardlund JH;Moebius HJ;Bentham P;Kook KA;Wischik DJ;Schelter BO;Davis CS;Staff RT;Bracoud L;Shamsi K;Storey JM;Harrington CR;Wischik CM
通讯作者：
Wischik CM