基于生物信息学整合分析探讨青光眼高压反应性视神经星形胶质细胞相关核心基因
Hub Genes of Astrocyte Involved in Glaucoma with Ocular Hypertension by Integrated Bioinformatics Analysis
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摘要:目的本研究旨在挖掘星形胶质细胞对于青光眼伴高眼压影响的潜在关键候选基因和相关通路。方法整合并深入分析表达谱GSE2378和GSE758，其中包括26例正常对照的27例高压反应性视神经星形胶质细胞（ONHA）。对差异表达的基因（DEG）进行分选，分析候选基因和富集途径，并进行DEGs相关的蛋白质相互作用（PPI）网络分析。结果从281个常见变化的DEG中共鉴定出119个一致表达的基因，其中包括68个表达上调基因和51个表达下调基因。119个表达一致的基因中，有75个（43个表达上调基因和32个表达下调基因）构成PPI网络，形成了117个蛋白相互作用的关系，并鉴定了10个核心基因。经PPI网络互作分析鉴定了3个相关性模块，通路富集分析显示模块1与细胞外的外泌体相关，模块2主要与抗体依赖性细胞毒性（ADCC）相关，模块3主要与Hippo信号传导途径相关。结论采用整合生物信息学分析，确定了星形胶质细胞参与青光眼合并高眼压的DEGs相关候选基因和相关通路，这可以提高我们对病因和潜在分子事件的认识，这些候选基因和通路可能是青光眼的治疗靶点。
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关键词:
- 青光眼 /
- 眼高压 /
- 反应性视神经乳头星形胶质细胞 /
- 核心基因 /
- 通路富集
Abstract:ObjectiveThis study was conducted to elucidate the potential key candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension.MethodsExpression profiles GSE2378 and GSE758 including 27 reactive optic nerve head astrocytes (ONHAs) by hypertensions and 26 normal controls, were integrated and deeply analyzed. Differentially expressed genes (DEGs) were sorted and candidate genes and pathways enrichment were analyzed. DEGs-associated protein-protein interaction network (PPI) was performed.ResultsA total of 119 consistently expressed genes were identified from 281 commonly changed DEGs, including 68 up-regulated genes and 51 down-regulated genes. PPI network complex filtered 75 DEGs (43 up-regulated and 32 down-regulated genes) of the 119 consistently altered DEGs and developed 117 edges, and 10 hub genes were identified. The most significant 3 modules were filtered from PPI, pathway enrichment analysis showed that module 1 was associated with extracellular exosome. Module 2 was mainly associated with antibody-dependent cellular cytotoxicity (ADCC) and module 3 was mainly associated with Hippo signaling pathway.ConclusionTaken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension, which could improve our understanding of the cause and underlying molecular events, and these candidate genes and pathways could be therapeutic targets for glaucoma. -
1. Introduction
Glaucoma is a group of eye diseases with many different risk factors resulting in loss of retinal ganglion cells of the retina and deficits in the visual field [1, 2]. Ocular hypertension has demonstrated to be one of the risk factors for glaucoma [3, 4]. Results from the clinical study and animal models' researches indicated that high intraocular pressure (IOP) were associated with progressive visual field deterioration, and current medications focus on lower intraocular pressure are predictable retinal ganglion cell loss [1, 4, 5].
Astrocyte also known as astroglia, counts for 20% to 40% of all glial cells in the adult central nervous system [6]. Astrocytes support the axons in a normal state, but in response to injury/disease, they remodel and become reactive, inducing changes in morphology, gene expression and function that have the potential for both beneficial and detrimental effects [7, 8]. Astrocytes become reactive and respond in a typical manner characterized by proliferation and extensive hypertrophy, termed astrogliosis [9]. Astrogliosis is a reliable and sensitive marker of diseased tissue and changes the molecular expression and morphology of astrocytes [10, 11]. Recently, extensive studies have identified modules of astrocytes interaction with glaucoma [12-14]. However, the regulation of astrocyte response to injury in glaucoma with high intraocular pressure remains elusive.
Gene chip is a detection technique that can detect all the time-point differentially expressed genes (DEGs) information within the same sample [15]. However, due to sample heterogeneity or different sequencing platform, the results for the expressed mRNAs are inconsistent with different gene profile. Therefore, the integrated bioinformatics methods will solve the disadvantages and identify the more reliable hub genes in astrocytes involved in glaucoma.
In this work, we have downloaded two microarray datasets GSE2378 [16] and GSE758 [17] from NCBI-Gene Expression Omnibus (NCBI-GEO) database and screened out DEGs between reactive optic nerve head astrocytes (ONHAs) by hypertensions and normal controls. Gene ontology (GO) and pathways enrichment analysis of DEGs were applied and functional module analysis of the protein-protein interaction (PPI) network was also constructed. The study aimed to identify hub genes and explore the intrinsic molecular mechanisms of astrocyte involved in glaucoma.
2. Materials and Methods
2.1 Information of microarray data
GEO is a public database repository for gene profile. Gene expression datasets GSE2378 and GSE758 were downloaded from the GEO dataset (http://www.ncbi.nlm.nih.gov/geo). Both the microarray data of GSE2378 and GSE758 were based on GPL8300 (Affymetrix Human Genome U95 Version 2 Array) platform. The microarray data of GSE2378 include 7 reactive ONHAs from glaucoma and 6 normal controls, the microarray data of GSE758 include 7, 8 and 5 reactive ONHAs exposed to hypertensions for 6 h, 24 h and 48 h, respectively, and the matched number of controls.
2.2 Data processing and identification of DEGs
The raw data were normalized and preprocessed by affy package in R software and limma package in R software [18, 19]. R software was used to analyze the preprocessed data to identify the up-regulated and down-regulated DEGs between reactive ONHAs and normal controls. |logFC| > 1 and P < 0.05 were used as cut-off criterion to identify DEGs.
2.3 GO functional enrichment analysis
Candidate DEGs functions and pathways enrichment were analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (Available online: https://david.ncifcrf.gov/), and Kyoto Encyclopedia of Genes and Genomes (KEGG) PATHWAY (Available online: http://www.genome.jp/kegg/) [20, 21]. In the present study, GO enrichment and KEGG pathway analysis of DEGs were conducted using the DAVID online tool. GO analysis included categories of biological processes (BP), cellular component (CC) and molecular function (MF). Pathway analysis is a functional analysis that maps genes to KEGG pathways. And gene count > 2 and P < 0.05 were set as the cut-off point.
2.4 Integration of PPI network
Based on the data in the STRING database (Available online: http://string-db.org), we constructed a PPI network [22]. Then we imported the interaction data into the Cytoscape software to map a PPI network [23]. We used Molecular Complex Detection (MCODE), an app plug-in Cytoscape software, to calculate node degree. That was, the numbers of inter-connections to filter hub genes of PPI. We analyzed the interaction relationship of the DEGs encoding proteins and screening hub genes. The cut-off points were set as following: degree cut-off = 2, node score cut-off = 0.2, k-core = 2, and max depth = 100.
3. Results
3.1 Identification of DEGs in ONHAs from glaucoma
GSE2378 includes 7 reactive ONHAs from glaucoma and 6 normal control. GSE758 includes reactive ONHAs exposed to hypertensions for 6 h, 24 h and 48 h, and 7 normal controls. Respectively, we extracted 281 DEGs from the expression profile datasets GSE2378 and GSE758 by using P < 0.05 and |logFC| > 1 as the cut-off criterion (Fig. 1). After integrated analysis, a total of 119 consistently expressed genes were identified from the two profile datasets, including 68 up-regulated genes and 51 down-regulated genes in reactive ONHAs from glaucoma samples compared to normal samples (Table 1).
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Figure 1. Identification of 281 commonly changes DEGs from the two cohort profile datasets (GSE2378 and GSE758)Table 1. 119 consistently expressed DEGs were identified from the two profile datasetsDEG Gene symbol Up-regulated genes GRIA3, HLA-DQB1, GRIK1, UTP20, PARD6B, GPC5, GPR183, CRHBP, GZMB, RASSF8, INHBA, CDH8, P2RY14, ADH7, RAB9BP1, HTN3, UGP2, GABRA2, CUL3, CA6, BCL11A, GABRA5, PLCB4, BCL6, TNKS, MYL1, ATP8A1, GNAO1, MEF2C, GRIA1, GCNT2, P2RX3, UNC13A, PRKCE, VWF, MYH11, RUNX1, LDB3, KDM5D, ITGA4, MARK2, ABCA12, OLR1, COBL, IFNG, PTPRZ1, BMP5, CD163, GEM, ACSBG1, LTF, ADCY8, PIK3R3, PRUNE1, DTNA, SIM1, ALB, AQP1, GP5, PLK4, HSPA6, FRY, ATP6V0A1, PDE6H, DPP6, PTPRR, ZNF80, MAP2 Down-regulated genes AKR1C1, CLU, FLRT2, DOK5, CFH, MDK, PLPP3, ADH1B, PTN, WNT5A, PDE1A, FOS, GAS1, KCTD12, PTGES, ST3GAL4, SH3BGR, BMP4, CEBPD, PGD, CFB, CTSK, EMP1, ASS1, RGN, SELENBP1, PBX1, EFNB2, PTGDS, PLTP, HOXB2, C1R, KCNK2, CEMIP, EFNB1, MID1, ALDH3A2, TMEM158, TYRO3, SH3BP5, ID1, C1S, RARRES3, MAPK10, RNF13, PDE5A, FGFR3, EFS, MAP3K8, EFEMP1, MAF Note: a total of 119 consistently expressed were identified from GSE2378 and GSE758, including 68 up-regulated genes and 51 down-regulated genes. Different color areas represented different datasets. The cross areas meant the commonly changed DEGs. DEGs were identified with classical t-test, statistically significant DEGs were defined with P < 0.05 and |logFC| > 1 as the cut-off criterion.
3.2 GO functional enrichment analysis
Candidate DEGs functions and pathways enrichment were analyzed using multiple online databases, including DAVID and KEGG PATHWAY. GO function enrichment was analyzed by DAVID online tool, and the DEGs functions were classified into three groups as follows: BP, CC and MF (Table 2A and 2B, Figure 2). As shown in figure 2 and table 2A and 2B, in the BP group, up-regulated genes mainly enriched in humoral immune response, regulation of NMDA receptor, cellular response to stress, chloride transport, regulation of synaptic plasticity, gamma-aminobutyric acid signaling pathway, retina homeostasis and learning or memory, and the down-regulated genes mainly enriched in regulation of prostatic bud formation complement activation, regulation of cartilage development, type B pancreatic cell development, regulation of chondrocyte differentiation, regulation of endothelial cell migration, ureteric bud morphogenesis, regulation of protein kinase C activity, regulation of MAPK cascade, SMAD protein signal transduction and regulation of apoptotic process. In the CC group, up-regulated genes mainly enriched in cell junction, extracellular region, extracellular space, extracellular exosome, GABA-A receptor complex, Post synapse and dendrite, and the down-regulated genes mainly enriched in extracellular region, extracellular space and blood microparticle. In the MF group, up-regulated genes mainly enriched in extracellular-glutamate-gated ion channel activity, and the down-regulated genes mainly enriched in BMP receptor binding, ephrin receptor binding and phosphodiesterase activity.
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Figure 2. Gene Ontology analysis and significant enriched GO terms of DEGs in retinitis pigmentosaa: GO analysis classified the DEGs into 3 groups (i.e., BP, CC and MF); b: significant enriched GO terms of DEGs in retinitis pigmentosa based on their functions; c: significant enriched pathway of DEGs in glaucoma with ocular hypertension.2A. The significant enriched analysis of up-regulated DEGs in glaucoma with ocular hypertensionCategory Term Description Gene-count P-value* Up-regulated genes Biological Process
(BP)GO:0006959 Humoral immune response 3 0.0156 GO:2000310 Regulation of NMDA receptor 2 0.0215 GO:0033554 Cellular response to stress 2 0.0215 GO:0006821 Chloride transport 2 0.0285 GO:0048167 Regulation of synaptic plasticity 2 0.039 GO:0007214 Gamma-aminobutyric acid signaling pathway 2 0.0425 GO:0001895 Retina homeostasis 2 0.0459 GO:0007611 Learning or memory 2 0.0494 Cellular Component
(CC)GO:0030054 Cell junction 5 0.0003 GO:0005576 Extracellular region 7 0.002 GO:0005615 Extracellular space 8 0.0111 GO:0070062 Extracellular exosome 11 0.0294 GO:1902711 GABA-A receptor complex 2 0.0354 GO:0098794 Post synapse 2 0.038 GO:0030425 Dendrite 3 0.0494 Molecular Function
(MF)GO:0005234 Extracellular-glutamate-gated ion channel activity 2 0.04 Note: *P < 0.05 as the cut-off criterion. 2B. The significant enriched analysis of down-regulated DEGs in glaucoma with ocular hypertensionCategory Term Description Gene-count P-value* Down-regulated genes Biological Process
(BP)GO:0060686 Regulation of prostatic bud formation 3 0.0001 GO:0006956 Complement activation 3 0.0005 GO:0061036 Regulation of cartilage development 3 0.0006 GO:0003323 Type B pancreatic cell development 3 0.0008 GO:0032331 Regulate chondrocyte differentiation 3 0.0015 GO:0010595 Regulate endothelial cell migration 3 0.0036 GO:0001658 Ureteric bud morphogenesis 3 0.0047 GO:1900020 Regulate protein kinase C activity 2 0.0064 GO:0043408 Regulation of MAPK cascade 2 0.0088 GO:0060395 SMAD protein signal transduction 3 0.0135 GO:0043066 Regulation of apoptotic process 3 0.0324 Cellular Component
(CC)GO:0005576 Extracellular region 7 0.0003 GO:0005615 Extracellular space 8 0.0127 GO:0072562 blood microparticle 3 0.0236 Molecular Function
(MF)GO:0070700 BMP receptor binding 2 0.0229 GO:0046875 Ephrin receptor binding 2 0.0261 GO:0004114 Phosphodiesterase activity 2 0.0484 Note: *P < 0.05 as the cut-off criterion. 3.3 Signaling pathway analysis
DEGs functional and signaling pathway enrichment analyses were conducted using online websites of KEGG. After the pathway enrichment analysis, down-regulated genes were mainly enriched in Retrograde endocannabinoid signaling, Nicotine addiction, Neuroactive ligand-receptor interaction, Glutamatergic synapse, Long-term depression, Transcriptional mis-regulation in cancer, Circadian entrainment, Dopaminergic synapse, TGF-beta signaling pathway and Toll-like receptor signaling pathway (Table 3, Fig. 3).
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Figure 3. DEGs PPI network complex analysisNote: using the STRING online database, total of 75 DEGs (43 up-regulated and 32 down-regulated genes) of the 119 consistently altered DEGs were filtered into the DEGs PPI network complex, containing 75 nodes and 117 edges.Table 3. The significant pathway enrichment anlalysis of DEGs in glaucoma with ocular hypertensionCategory Term Description Gene-count P-value* Up-regulated genes hsa04723 Retrograde endocannabinoid signaling 6 0.00005 hsa05033 Nicotine addiction 4 0.0004 hsa04080 Neuroactive ligand-receptor interaction 7 0.0011 hsa04724 Glutamatergic synapse 5 0.0022 hsa04730 Long-term depression 4 0.0024 hsa05202 Transcriptional mis-regulation in cancer 5 0.0048 hsa04713 Circadian entrainment 4 0.0096 hsa04728 Dopaminergic synapse 4 0.0162 hsa04350 TGF-beta signaling pathway 3 0.0479 Down-regulated hsa04620 Toll-like receptor signaling pathway 5 0.0003 Note: *P < 0.05 as the cut-off criterion. 3.4 PPI network and modular analysis
Using the STRING database and Cytoscape software, total of 75 DEGs (43 up-regulated and 32 down-regulated genes) of the 119 consistently altered DEGs were filtered into the DEGs PPI network complex, containing 75 nodes and 117 edges (Fig. 3), and 44 of the 119 DEGs did not fall into the DEGs PPI network. Among the 75 genes, the top 10 hub genes were identified according to connectivity, including ALB, FOS, FGFR3, GNAO1, BMP4, MAPK10, VWF, IFNG, PG5 and PRKCE. ALB showed the highest degree (degree = 19). The top three module with score > 3 were shown in figure 4. Pathway enrichment analysis showed that module 1 was associated with extracellular exosome. Module 2 was mainly associated with antibody-dependent cellular cytotoxicity (ADCC) and module 3 was mainly associated with Hippo signaling pathway.
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Figure 4. Three most significant modulesNotes: module 1 contains 4 nodes and 5 edges, associated with extracellular exosome; module 2 contains 3 nodes and 3 edges, mainly associated with antibody-dependent cellular cytotoxicity (ADCC); module 3 contains 3 nodes and 3 edges, mainly associated with Hippo signaling pathway.4. Discussion
Glaucoma is defined as a progressive optic neuropathy and is characterized by an irreversible loss of retinal ganglion cells. The main risk factor to develop glaucoma is an increased IOP, and current medications focus on lowering the IOP. IOP-lowering treatments just address a risk factor; there are profound alterations in tissue composition and architecture, disruptions in axonal transport, and critical axonal insult [24, 25]. Therefore, studying the potential role of nonneuronal cell in supporting the ganglion cells, including glial cells such as astrocytes, is an important step to better understand the pathogenic mechanisms underlying glaucoma. In this study, we have identified 281 commonly changed DEGs from the two cohort profile data sets (GSE2378 and GSE758). A total of 119 consistently expressed genes were identified from 281 commonly changed DEGs, including 68 up-regulated genes and 51 down-regulated genes in reactive ONHAs from glaucoma samples compare to normal samples by using integrated bioinformatics analysis. PPI network complex filtered 75 DEGs (43 up-regulated and 32 down-regulated genes) of the 119 consistently altered DEGs and developed 117 edges, and 10 hub genes were identified.
The DEGs in glaucoma with ocular hypertension analyzed by GO functional enrichment analysis showed that down-regulated DEGs were mainly enriched in immune response, cell migration and differentiation, and extracellular matrix, while up-regulated DEGs were shown to be concerned with immune response, cell stress response and neurotransmitter pathway regulation. The results of the current study are accordance with our knowledge that immune response, cell stress response, cell migration and extracellular matrix are the main mechanisms of glaucoma development and astrocyte activation [26-29]. Reactive astrocytes are generally characterized by hypertrophy, hyperplasia, as well as increased expression of GFAP and vimentin. In glaucoma or with experimentally elevated IOP, ONH astrocytes in the prelaminar ONH round up and migrate, abandoning their columnar organization.
The PPI network was constructed with DEGs, and the top 10 hub genes were as follows: ALB, FOS, FGFR3, GNAO1, BMP4, MAPK10, VWF, IFNG, PG5 and PRKCE. Module analysis of the PPI network suggested that extracellular exosome, ADCC and Hippo signaling pathway might be involved in glaucoma with ocular hypertension. Extracellular exosome are cell-derived vesicles have specialized functions and play a key role in processes such as immune system, coagulation and intercellular signaling [30, 31]. Increased tissue stress in the ONH from elevated IOP may be detected by glial cells via transmembrane integrin receptor signaling, and providing receptors for fibrillar and basement membrane collagens, fibronectin, matrix metalloproteinases, reelin and astrocytic hemidesmosomes [28, 32]. While integrins act as mechanoreceptors, transducing the stresses induced by elevated IOP, the matrix metalloproteinases (MMP) are key elements in the regulation of ECM remodeling [33]. The ADCC is a mechanism of cell-mediated immune defense. The astrocytes of the ONH undergo a reactivation in glaucoma with ocular hypertension, which was characterized by morphologic alterations and expression changes, they expressed major histocompatibility complex class Ⅱ proteins and became more potent inducers of T-cell activation [29]. Further, ADCC mediated by activation of macrophages and neutrophils cells [34, 35]. The Hippo signaling pathway regulates cell proliferation and apoptosis. At three days following IOP elevation in a rat glaucoma model, the labeling of anterior ONH glial nuclei with antibodies to proliferating cell nuclear antigen coincided with the first alterations in connexin-43 labeling and preceded obvious morphological alterations in the glial columns [36]. A near doubling of optic nerve astrocytes in a mouse glaucoma model was also indicated ocular hypertension induced cell proliferation [37]. Undergo with hypoxia, metabolic or something lead to cellular stress, reactive oxygen species may accumulate to a point that critical cellular are apoptosis.
In summary, by means of data processing, the hub genes and candidate pathway may have the potential to be used as underlying mechanism affected glaucoma with ocular hypertension. Although several hub genes and pathways were identified in our study, there were still some limitations: small sample size was used for the analyses and lack of further experiment. Further experimental studies with larger sample size are needed to confirm the results of the current study.
Acknowledgements
We thank for the finding support from the China National Natural Science Foundation Funding Project (NO. 81804150); Hunan University of Chinese Medicine, National Key Discipline of TCM Diagnostics Foundation Funding Project (No. 2015ZYZD02); The Domestic First-class Discipline Construction Project of Chinese Medicine of Hunan University of Chinese Medicine; Hunan Provincial Department of Education Innovation Platform Open Fund Project (16K065); Chinese Medicine Key Laboratory of Prevention and Treatment of Disease in Hunan Province (2017TP1018); Changsha Science and Technology Plan Project (KC1704005); Hunan Engineering Technology Research Center for the Prevention and Treatment of Otorhinolaryngologic Diseases and Protection of Visual Function with Chinese Medicine; Hunan Provincial Research Innovation Project for Graduate students (CX2017B426).
Competing Interests
The authors declare no conflict of interest.
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Figure 1. Identification of 281 commonly changes DEGs from the two cohort profile datasets (GSE2378 and GSE758)
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Figure 2. Gene Ontology analysis and significant enriched GO terms of DEGs in retinitis pigmentosa
a: GO analysis classified the DEGs into 3 groups (i.e., BP, CC and MF); b: significant enriched GO terms of DEGs in retinitis pigmentosa based on their functions; c: significant enriched pathway of DEGs in glaucoma with ocular hypertension.
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Figure 3. DEGs PPI network complex analysis
Note: using the STRING online database, total of 75 DEGs (43 up-regulated and 32 down-regulated genes) of the 119 consistently altered DEGs were filtered into the DEGs PPI network complex, containing 75 nodes and 117 edges.
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Figure 4. Three most significant modules
Notes: module 1 contains 4 nodes and 5 edges, associated with extracellular exosome; module 2 contains 3 nodes and 3 edges, mainly associated with antibody-dependent cellular cytotoxicity (ADCC); module 3 contains 3 nodes and 3 edges, mainly associated with Hippo signaling pathway.
Table 1 119 consistently expressed DEGs were identified from the two profile datasets
DEG Gene symbol Up-regulated genes GRIA3, HLA-DQB1, GRIK1, UTP20, PARD6B, GPC5, GPR183, CRHBP, GZMB, RASSF8, INHBA, CDH8, P2RY14, ADH7, RAB9BP1, HTN3, UGP2, GABRA2, CUL3, CA6, BCL11A, GABRA5, PLCB4, BCL6, TNKS, MYL1, ATP8A1, GNAO1, MEF2C, GRIA1, GCNT2, P2RX3, UNC13A, PRKCE, VWF, MYH11, RUNX1, LDB3, KDM5D, ITGA4, MARK2, ABCA12, OLR1, COBL, IFNG, PTPRZ1, BMP5, CD163, GEM, ACSBG1, LTF, ADCY8, PIK3R3, PRUNE1, DTNA, SIM1, ALB, AQP1, GP5, PLK4, HSPA6, FRY, ATP6V0A1, PDE6H, DPP6, PTPRR, ZNF80, MAP2 Down-regulated genes AKR1C1, CLU, FLRT2, DOK5, CFH, MDK, PLPP3, ADH1B, PTN, WNT5A, PDE1A, FOS, GAS1, KCTD12, PTGES, ST3GAL4, SH3BGR, BMP4, CEBPD, PGD, CFB, CTSK, EMP1, ASS1, RGN, SELENBP1, PBX1, EFNB2, PTGDS, PLTP, HOXB2, C1R, KCNK2, CEMIP, EFNB1, MID1, ALDH3A2, TMEM158, TYRO3, SH3BP5, ID1, C1S, RARRES3, MAPK10, RNF13, PDE5A, FGFR3, EFS, MAP3K8, EFEMP1, MAF Note: a total of 119 consistently expressed were identified from GSE2378 and GSE758, including 68 up-regulated genes and 51 down-regulated genes. 
下载: 导出CSV
2A The significant enriched analysis of up-regulated DEGs in glaucoma with ocular hypertension
Category Term Description Gene-count P-value* Up-regulated genes Biological Process
(BP)GO:0006959 Humoral immune response 3 0.0156 GO:2000310 Regulation of NMDA receptor 2 0.0215 GO:0033554 Cellular response to stress 2 0.0215 GO:0006821 Chloride transport 2 0.0285 GO:0048167 Regulation of synaptic plasticity 2 0.039 GO:0007214 Gamma-aminobutyric acid signaling pathway 2 0.0425 GO:0001895 Retina homeostasis 2 0.0459 GO:0007611 Learning or memory 2 0.0494 Cellular Component
(CC)GO:0030054 Cell junction 5 0.0003 GO:0005576 Extracellular region 7 0.002 GO:0005615 Extracellular space 8 0.0111 GO:0070062 Extracellular exosome 11 0.0294 GO:1902711 GABA-A receptor complex 2 0.0354 GO:0098794 Post synapse 2 0.038 GO:0030425 Dendrite 3 0.0494 Molecular Function
(MF)GO:0005234 Extracellular-glutamate-gated ion channel activity 2 0.04 Note: *P < 0.05 as the cut-off criterion.
下载: 导出CSV
2B The significant enriched analysis of down-regulated DEGs in glaucoma with ocular hypertension
Category Term Description Gene-count P-value* Down-regulated genes Biological Process
(BP)GO:0060686 Regulation of prostatic bud formation 3 0.0001 GO:0006956 Complement activation 3 0.0005 GO:0061036 Regulation of cartilage development 3 0.0006 GO:0003323 Type B pancreatic cell development 3 0.0008 GO:0032331 Regulate chondrocyte differentiation 3 0.0015 GO:0010595 Regulate endothelial cell migration 3 0.0036 GO:0001658 Ureteric bud morphogenesis 3 0.0047 GO:1900020 Regulate protein kinase C activity 2 0.0064 GO:0043408 Regulation of MAPK cascade 2 0.0088 GO:0060395 SMAD protein signal transduction 3 0.0135 GO:0043066 Regulation of apoptotic process 3 0.0324 Cellular Component
(CC)GO:0005576 Extracellular region 7 0.0003 GO:0005615 Extracellular space 8 0.0127 GO:0072562 blood microparticle 3 0.0236 Molecular Function
(MF)GO:0070700 BMP receptor binding 2 0.0229 GO:0046875 Ephrin receptor binding 2 0.0261 GO:0004114 Phosphodiesterase activity 2 0.0484 Note: *P < 0.05 as the cut-off criterion.
下载: 导出CSV
Table 3 The significant pathway enrichment anlalysis of DEGs in glaucoma with ocular hypertension
Category Term Description Gene-count P-value* Up-regulated genes hsa04723 Retrograde endocannabinoid signaling 6 0.00005 hsa05033 Nicotine addiction 4 0.0004 hsa04080 Neuroactive ligand-receptor interaction 7 0.0011 hsa04724 Glutamatergic synapse 5 0.0022 hsa04730 Long-term depression 4 0.0024 hsa05202 Transcriptional mis-regulation in cancer 5 0.0048 hsa04713 Circadian entrainment 4 0.0096 hsa04728 Dopaminergic synapse 4 0.0162 hsa04350 TGF-beta signaling pathway 3 0.0479 Down-regulated hsa04620 Toll-like receptor signaling pathway 5 0.0003 Note: *P < 0.05 as the cut-off criterion.
下载: 导出CSV
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