Bioinformatics analysis of key differential expressed genes related to stroke and osteoporosis

doi:10.3877/cma.j.issn.2096-0263.2021.06.008

Abstract

Abstract:

Objective

To analyse the key differential expressed genes and regulatory signaling pathways between stroke and osteoporosis by bioinformatics methods.

Methods

The microarray data of stroke and osteoporosis genes were retrieved from the GEO database of the National Center for Biotechnology Information (NCBI), and the microarray samples were screened according to the inclusion criteria. The data were aggregated and were normalized before analysis by the R language and the GEO2R online tool to obtain differential expressed genes between patients and controls. Then, the Gene Ontology database, Kyoto Gene and Genome Database (KEGG), WikiPathways, Reactome database, gene/protein interaction retrieval tool, R language, Cytoscape analysis software and Metascape databases and analysis tools were used to perform differentially expressed gene analysis, functional annotation, and enrichment analysis.

Results

A total of 72 DEGs associated with both stroke and osteoporosis were screened out. GO analysis showed that the biological function of DEGs was mainly involved in the negative regulation of stem cell differentiation. KEGG, WikiPathways, Reactome and other databases show that DEGs is mainly enriched in cytokine signal transductions and other signaling pathways in the immune system. Ten key genes, SMARCA4, SMARCA2, SMC1A, MSL3, CBX5, NFKB2, HIRA, CASP1, VCP and CD86, were screened by protein interaction network.

Conclusion

The DEGs screened by bioinformatics technology, which related to the pathogenesis of stroke patients and osteoporosis, mainly involved in cytokine signaling in immune system, providing new research clues and directions for further exploring the correlation between the occurrence and development of the two and their molecular mechanism.

Key words: Stroke, Osteoporosis, Differential gene expression, Bioinformatics

Qun Wei, Hang Zhao, Jing Zhao, Yongqiang Wu, Jing Ren, Huiyu Hou, Jingxian Hang, Yanmei Song, Wei Zhang. Bioinformatics analysis of key differential expressed genes related to stroke and osteoporosis[J]. Chinese Journal of Geriatric Orthopaedics and Rehabilitation(Electronic Edition), 2021, 07(06): 364-371.

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References 37

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名称	类别	描述	Gene Count	Log10(P)	Log10(q)
GO:2000737	GO生物进程	负调控干细胞分化	4	-6.47	-2.12
GO:0008134	GO分子功能	结合转录因子	10	-5.64	-1.59
GO:0034504	GO生物进程	蛋白核定位	7	-5.03	-1.28
GO:0016032	GO生物进程	病毒的过程	8	-4.95	-1.28
GO:0033151	GO生物进程	V（D）J再结合	3	-4.82	-1.28
GO:0007052	GO生物进程	有丝分裂纺锤体形成	5	-4.79	-1.28
GO:0042393	GO分子功能	结合组蛋白	6	-4.41	-1.07
GO:0003714	GO分子功能	转录抑制活性	5	-3.92	-0.85
GO:0006511	GO生物进程	泛素依赖的蛋白质降解过程	8	-3.66	-0.63
GO:0043122	GO生物进程	调控I-kappaB kinase/NF-kappaB信号通路	5	-3.35	-0.46
GO:0032768	GO生物进程	单加氧酶活性的调节	3	-3.33	-0.45
GO:0072657	GO生物进程	蛋白质膜定位	7	-3.18	-0.44
GO:0071396	GO生物进程	细胞对脂质的反应	7	-3.18	-0.44
GO:0019900	GO分子功能	结合激酶	8	-3.15	-0.44
GO:0005770	GO细胞组成	晚期内涵体	5	-3.1	-0.42
GO:0046332	GO分子功能	结合SMAD	3	-2.96	-0.33
GO:0019221	GO生物进程	细胞因子介导的信号通路	6	-2.88	-0.3
GO:0019080	GO生物进程	病毒基因表达	3	-2.74	-0.22
GO:0005262	GO分子功能	钙通道活性	3	-2.45	-0.01
GO:0071216	GO生物进程	细胞对生物刺激的反应	4	-2.44	0

名称	类别	描述	Gene Count	Log10(P)	Log10(q)
GO:2000737	GO生物进程	负调控干细胞分化	4	-6.47	-2.12
GO:0008134	GO分子功能	结合转录因子	10	-5.64	-1.59
GO:0034504	GO生物进程	蛋白核定位	7	-5.03	-1.28
GO:0016032	GO生物进程	病毒的过程	8	-4.95	-1.28
GO:0033151	GO生物进程	V（D）J再结合	3	-4.82	-1.28
GO:0007052	GO生物进程	有丝分裂纺锤体形成	5	-4.79	-1.28
GO:0042393	GO分子功能	结合组蛋白	6	-4.41	-1.07
GO:0003714	GO分子功能	转录抑制活性	5	-3.92	-0.85
GO:0006511	GO生物进程	泛素依赖的蛋白质降解过程	8	-3.66	-0.63
GO:0043122	GO生物进程	调控I-kappaB kinase/NF-kappaB信号通路	5	-3.35	-0.46
GO:0032768	GO生物进程	单加氧酶活性的调节	3	-3.33	-0.45
GO:0072657	GO生物进程	蛋白质膜定位	7	-3.18	-0.44
GO:0071396	GO生物进程	细胞对脂质的反应	7	-3.18	-0.44
GO:0019900	GO分子功能	结合激酶	8	-3.15	-0.44
GO:0005770	GO细胞组成	晚期内涵体	5	-3.1	-0.42
GO:0046332	GO分子功能	结合SMAD	3	-2.96	-0.33
GO:0019221	GO生物进程	细胞因子介导的信号通路	6	-2.88	-0.3
GO:0019080	GO生物进程	病毒基因表达	3	-2.74	-0.22
GO:0005262	GO分子功能	钙通道活性	3	-2.45	-0.01
GO:0071216	GO生物进程	细胞对生物刺激的反应	4	-2.44	0

名称	类别	描述	Gene Count	Log10(P)	Log10(q)
R-HSA-1280215	Reactome基因集	免疫系统中的细胞因子信号转导	14	-8.5	-4.6
CORUM:1230	CORUM	WINAC复合体	3	-5.2	-1.9
R-HSA-3108232	Reactome基因集	SUMO E3连接酶sumo化的靶蛋白	6	-5.1	-1.9
WP3657	WikiPathways	GABP α/β复合物调控造血干细胞基因	3	-4.6	-1.6
M145	Canonical信号通路	PID P53下游信号通路	5	-4.6	-1.6
R-HSA-162906	Reactome基因集	HIV感染	6	-4.5	-1.6
R-HSA-5673001	Reactome基因集	RAF/MAP激酶级联反应	6	-4.1	-1.3
ko04978	KEGG信号通路	矿物质养分吸收	3	-3.5	-0.9
ko05134	KEGG信号通路	军团菌病	3	-3.4	-0.85
R-HSA-9658195	Reactome基因集	Leishmania感染	5	-3.3	-0.8
R-HSA-5358351	Reactome基因集	Hedgehog调控的信号通路	4	-3.2	-0.74
M40	Canonical信号通路	PID E2F信号通路	3	-3.1	-0.63
R-HSA-1169410	Reactome基因集	干扰素刺激基因的抗病毒机制	3	-2.9	-0.54
ko05152	KEGG信号通路	结核病	4	-2.9	-0.54
ko05202	KEGG信号通路	癌症中的转录失调	4	-2.9	-0.54
R-HSA-6798695	Reactome基因集	中性粒细胞脱颗粒	6	-2.8	-0.49
WP4258	WikiPathways	lncRNA在典型Wnt信号通路和结直肠癌中的作用	3	-2.6	-0.34
R-HSA-382551	Reactome基因集	小分子运输	7	-2.6	-0.32
WP411	WikiPathways	mRNA加工	3	-2.3	-0.17
WP4657	WikiPathways	22q11.2拷贝数变异综合征	3	-2.2	-0.11

名称	类别	描述	Gene Count	Log10(P)	Log10(q)
R-HSA-1280215	Reactome基因集	免疫系统中的细胞因子信号转导	14	-8.5	-4.6
CORUM:1230	CORUM	WINAC复合体	3	-5.2	-1.9
R-HSA-3108232	Reactome基因集	SUMO E3连接酶sumo化的靶蛋白	6	-5.1	-1.9
WP3657	WikiPathways	GABP α/β复合物调控造血干细胞基因	3	-4.6	-1.6
M145	Canonical信号通路	PID P53下游信号通路	5	-4.6	-1.6
R-HSA-162906	Reactome基因集	HIV感染	6	-4.5	-1.6
R-HSA-5673001	Reactome基因集	RAF/MAP激酶级联反应	6	-4.1	-1.3
ko04978	KEGG信号通路	矿物质养分吸收	3	-3.5	-0.9
ko05134	KEGG信号通路	军团菌病	3	-3.4	-0.85
R-HSA-9658195	Reactome基因集	Leishmania感染	5	-3.3	-0.8
R-HSA-5358351	Reactome基因集	Hedgehog调控的信号通路	4	-3.2	-0.74
M40	Canonical信号通路	PID E2F信号通路	3	-3.1	-0.63
R-HSA-1169410	Reactome基因集	干扰素刺激基因的抗病毒机制	3	-2.9	-0.54
ko05152	KEGG信号通路	结核病	4	-2.9	-0.54
ko05202	KEGG信号通路	癌症中的转录失调	4	-2.9	-0.54
R-HSA-6798695	Reactome基因集	中性粒细胞脱颗粒	6	-2.8	-0.49
WP4258	WikiPathways	lncRNA在典型Wnt信号通路和结直肠癌中的作用	3	-2.6	-0.34
R-HSA-382551	Reactome基因集	小分子运输	7	-2.6	-0.32
WP411	WikiPathways	mRNA加工	3	-2.3	-0.17
WP4657	WikiPathways	22q11.2拷贝数变异综合征	3	-2.2	-0.11

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