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南方医科大学公共卫生学院流行病学系,广州 510515
钟逸诗,Email:jacky19970422@163.com,研究方向:认知功能受损疾病研究。
吴娴波,Email:wuxb1010@smu.edu.cn。
收稿:2023-09-16,
修回:2023-11-17,
录用:2023-12-02,
纸质出版:2023-12-28
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钟逸诗,吴茵如,高健,等.阿尔茨海默病患者外周血和海马组织共表达差异基因的生物信息学分析[J].重庆医科大学学报,2023,48(12):1507-1513.
Zhong Yishi,Wu Yinru,Gao Jian,et al.Bioinformatics analysis of differentially co-expressed genes in peripheral blood and hippocampal tissue of patients with Alzheimer’s disease[J].Journal of Chongqing Medical University,2023,48(12):1507-1513.
钟逸诗,吴茵如,高健,等.阿尔茨海默病患者外周血和海马组织共表达差异基因的生物信息学分析[J].重庆医科大学学报,2023,48(12):1507-1513. DOI: 10.13406/j.cnki.cyxb.003383.
Zhong Yishi,Wu Yinru,Gao Jian,et al.Bioinformatics analysis of differentially co-expressed genes in peripheral blood and hippocampal tissue of patients with Alzheimer’s disease[J].Journal of Chongqing Medical University,2023,48(12):1507-1513. DOI: 10.13406/j.cnki.cyxb.003383.
目的
2
基于生物信息学筛选阿尔茨海默病(Alzheimer's disease,AD)患者外周血和海马组织中有共同表达趋势的差异基因,为AD的诊断、治疗靶点的筛选提供新的思路。
方法
2
从基因表达综合数据库(Gene Expression Omnibus,GEO)下载关于AD的数据集GSE97760(9例AD、10例健康对照)、GSE5281(10例AD、13例健康对照)进行生物信息学分析。分别筛选AD患者外周血和海马组织的差异表达基因(differentially expressed genes,DEGs),并确定2个数据集中有共同表达趋势的DEGs。对共表达DEGs进行基因本体论(Gene Ontology,GO)富集分析和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路分析,构建蛋白互作(protein-protein interaction,PPI)网络进一步筛选关键基因,并对关键基因进行验证。
结果
2
基于对2个GEO数据集的综合分析,共筛选出669个共表达DEGs,包括64个上调DEGs、605个下调DEGs,GO和KEGG分析分别揭示了174个关键条目、40个关键通路,主要在RNA聚合酶的转录调控、神经胶质瘤通路等方面显著富集。通过PPI网络进一步筛选出10个与AD相关的关键基因
TP53、PTEN、HNRNPC、EIF4G1、SF3B1、SRSF11、PIK3R1、RBM39、LUC7L3、RBM25
,其中
PTEN、HNRNPC、SF3B1、PIK3R1、LUC7L3
在数据集GSE48350中得到了验证。
结论
2
本研究筛选得出的5个值得进一步研究的关键基因(
PTEN、HNRNPC、SF3B1、PIK3R1、LUC7L3
),可作为AD诊断的潜在生物标志物。
Objective
2
To determine differentially co-expressed genes in the peripheral blood and hippocampal tissue of patients with Alzheimer’s disease(AD) by bioinformatics analysis,and to provide new ideas for AD diagnosis and therapeutic target selection.
Methods
2
We downloaded the AD-associated datasets GSE97760(9 cases of AD and 10 healthy controls) and GSE5281(10 cases of AD and 13 healthy controls) from the Gene Expression Omnibus(GEO) database for bioinformatics analysis. We selected differentially expressed genes(DEGs) in the peripheral blood and hippocampal tissues of patients with AD separately;identified the co-expressed DEGs in the two datasets; then performed Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis on the co-expressed DEGs;and constructed a protein-protein interaction(PPI) network to further determine the key genes,followed by validation.
Results
2
Through the comprehensive analysis of the two GEO datasets,a total of 669 co-expressed DEGs were selected,including 64 up-regulated DEGs and 605 down-regulated DEGs. The GO and KEGG analyses selected 174 key items and
40 key pathways,respectively,which were significantly enriched mainly in the transcriptional regulation of RNA polymerase and glioma pathway. The PPI network determined 10 key AD-related genes:
TP53
,
PTEN
,
HNRNPC
,
EIF4G1
,
SF3B1
,
SRSF11
,
PIK3R1
,
RBM39
,
LUC7L3
,and
RBM25
,of which
PTEN
,
HNRNPC
,
SF3B1
,
PIK3R1
,and
LUC7L3
were validated in the dataset GSE48350.
Conclusion
2
The five key genes(
PTEN
,
HNRNPC
,
SF3B1
,
PIK3R1
,and
LUC7L3
) selected in this study may serve as potential biomarkers for AD diagnosis,which deserve further research.
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