Identification of Ferroptosis-Related Genes in Alzheimer’s Disease Based on Bioinformatic Analysis

小桶 基因 生物 计算生物学 微阵列分析技术 微阵列 疾病 遗传学 转录组 基因表达 医学 病理
作者
Ying Wāng,Guohua Chen,Wei Shao
出处
期刊:Frontiers in Neuroscience [Frontiers Media]
卷期号:16: 823741-823741 被引量:55
标识
DOI:10.3389/fnins.2022.823741
摘要

Introduction Alzheimer’s disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD. Materials and Methods Three microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls. Results 53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P < 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P < 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD. Conclusion We identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
bird完成签到 ,获得积分10
刚刚
roy_chiang发布了新的文献求助10
1秒前
小兔叽完成签到 ,获得积分10
1秒前
ayawbb完成签到,获得积分10
1秒前
小吴完成签到,获得积分10
2秒前
yiming完成签到,获得积分10
2秒前
无奈白竹完成签到,获得积分10
2秒前
沛蓝完成签到,获得积分10
4秒前
勤奋的菠萝完成签到 ,获得积分10
4秒前
kun完成签到,获得积分10
4秒前
明月完成签到,获得积分10
5秒前
糟糕的修杰完成签到,获得积分10
5秒前
绵绵完成签到,获得积分10
6秒前
呆萌的尔云完成签到 ,获得积分10
6秒前
as完成签到,获得积分10
6秒前
KK卮完成签到,获得积分10
7秒前
zyw完成签到,获得积分10
7秒前
益生菌发布了新的文献求助10
7秒前
平常的雁凡完成签到,获得积分10
7秒前
7秒前
bkagyin的应助被赤心采纳,获得10
8秒前
氯化钠完成签到 ,获得积分10
8秒前
roy_chiang完成签到,获得积分10
9秒前
竹签子完成签到 ,获得积分10
9秒前
Lh6610完成签到,获得积分0
9秒前
王耑完成签到 ,获得积分10
10秒前
10秒前
Jally完成签到 ,获得积分10
12秒前
gyyy完成签到,获得积分10
12秒前
善良茗茗完成签到,获得积分10
13秒前
leng的应助被尖椒干豆腐采纳,获得10
13秒前
无私羽毛完成签到,获得积分10
15秒前
Borw完成签到,获得积分10
15秒前
菜菜完成签到 ,获得积分10
15秒前
wu完成签到,获得积分10
16秒前
最落幕完成签到 ,获得积分10
16秒前
16秒前
w1kend完成签到,获得积分10
17秒前
三杠完成签到 ,获得积分10
18秒前
席冥完成签到,获得积分0
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Modern Artificial Intelligence 1000
Особенности технологий и методов информационно-психологических войн СССР с Великобританией и США в период 1939-1953 гг 1000
Das Matthäusevangelium: Kapitel 1:1–17 1000
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Entre Praga y Madrid : los contactos checoslovaco-españoles (1948-1977) 600
A REVIEW OF THE V-22 DYNAMICS VALIDATION PROGRAM 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8129920
求助须知:如何正确求助?哪些是违规求助? 9532296
关于积分的说明 21593986
捐赠科研通 7711747
什么是DOI,文献DOI怎么找? 3418056
关于科研通互助平台的介绍 2543742
邀请新用户注册赠送积分活动 2459259