Protein-protein interaction network analysis of osteoarthritis-related differentially expressed genes

Zhu, Yujie; Deng, Biyong; Zhang, L.G.; Xu, Peng; Du, Xiaoping; Zhang, Q.G.; Yang, Boning

doi:10.4238/2014.november.11.1

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…Currently, network-based analysis has become more powerful in exploring disease mechanisms (Bradley et al, 2008). Recently, protein-protein interaction (PPI) networks, gene interaction networks, and transcriptome networks have proven to be effective in characterizing cellular processes in various diseases (Chen et al, 2013;Zhu et al, 2014;Zhang et al, 2015). PPI network analysis differs from pathway analysis in that it uses comprehensive networks to gain system-level biological meanings (Wu and Chen, 2009).…”

Section: Introductionmentioning

confidence: 99%

Identification of altered pathways in hypertrophic cardiomyopathy based on combined data of protein-protein interactions and molecular pathways

Sw¹,

Wang²,

Pan³

2016

Genet. Mol. Res.

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ABSTRACT. The purpose of our study was to identify molecular pathways altered during the pathogenesis of hypertrophic cardiomyopathy (HCM) based on data from the STRING proteinprotein interaction (PPI) database and the REACTOME pathway database. Identification of differentially expressed genes (DEGs) was carried out, followed by construction of a targeted network and selection of hub genes in this network. PPI pairs in each pathway were extracted, and altered pathways were identified when the said pathway differed from common interactions within the targeted network with a P value of less than 0.05. These altered pathways were further validated based on enrichment of hub genes in pathways within the targeted network. Through this method, we identified 1085 DEGs. The DEGs were inputted into the STRING database, and the resulting targeted network was composed of 3631 interactions. Based on the selection criteria, 30 significantly changed pathways were screened in total. Among these, the top five pathways were found to be involved in immune modulation, signal transduction, hemostasis, and G protein-coupled receptor signaling. Similarly, enrichment in hub gene interactions was also found in members within the altered pathways, including those involved in the innate immune system, the immune system, and signal transduction pathways. These altered pathways are important for understanding the underlying mechanisms of HCM, and can be used for clinical application of treatments in the future.

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Section: Introductionmentioning

confidence: 99%

Identification of altered pathways in hypertrophic cardiomyopathy based on combined data of protein-protein interactions and molecular pathways

Sw¹,

Wang²,

Pan³

2016

Genet. Mol. Res.

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“…CXCL12 functions as the natural ligand for the G-protein coupled receptor, chemokine (C-X-C motif) receptor 4 (CXCR4) and plays a role in many diverse cellular functions, including inflammation response (28). The work of Zhu et al showed that the G protein-coupled receptor pathway might play significant roles in the progression of the early and late stages of OA (8). Recently, He et al found that CXCL12 levels in the plasma and synovial fluid might serve as effective biomarkers for the severity of OA (29).…”

Section: Gene Changementioning

confidence: 99%

“…In the present study, we downloaded the microarray data of GSE32317 from a public database. With the same microarray data, Zhu et al demonstrated that Tachykinin, Precursor 1 (TAC1) and the G protein-coupled receptor pathway might play significant roles in the progression of the early and late stages of OA (8). In addition, the work of Ma et al showed that the genes related immune response, cartilage development, and genes involve in the Toll-like receptor (TLR) signaling pathway and Wnt signaling pathway might be the potential target genes for the OA treatment (9).…”

Section: Introductionmentioning

confidence: 99%

Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis

Zhi

Zhang

et al. 2017

Molecular Medicine Reports

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The aim of the present study was to investigate the molecular circuitry of osteoarthritis (OA) and identify more potential target genes for OA treatment. Microarray data of GSE32317 was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in samples of synovial membrane from patients with early stage of knee OA (OA_Early) and late stage of knee OA (OA_End) that were compared with healthy specimens. Bioinformatics analysis was applied to analyze the significant functions and pathways that were enriched by the common DEGs identified in OA_Early and OA_End samples. Furthermore, a protein‑protein interaction (PPI) network was constructed and significant modules were extracted. Transcription factors (TFs) that could regulate genes in the significant modules were identified. A total of 1,207 and 1,575 DEGs were identified in OA_Early and OA_End samples compared with healthy samples, respectively. A total of 740 genes were upregulated and 308 genes were downregulated across the OA_Early and OA_End samples. These common DEGs were enriched in different gene ontology terms and pathways, such as immune response. Angiotensinogen (AGT) and C‑X‑C motif chemokine ligand 12 (CXCL12) were identified to be hub proteins in the PPI network or in the selected module 1. In addition, the DEG lysine demethylase 2B (KDM2B) was identified as a TF that can regulate genes in the significant modules 2 and 3. In conclusion, the present study has identified AGT, CXCL12 and KDM2B as potentially essential genes associated with the pathogenesis of knee OA.

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“…STRING database currently covers 5,214,234 genes/proteins from 1133 organisms which are derived from four sources such as, genomic contexts, high throughput experiments, conserved co expression and literature studies. In the present study drug targets with confidence score more than 0.400 were selected [22,23]. The interactions not more than 50 were also included in the interaction network.…”

Section: Protein Network Analysismentioning

confidence: 99%

Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

Hema¹,

Priyadarshini²

2015

Biochem Anal Biochem

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Atherosclerosis is a chronic inflammatory artery disease, responsible for both cardiovascular (heart) and cerebrovascular (brain) stroke with high morbidity and mortality worldwide. Infectious pathogens such as Chlamydophila pneumoniae, Porphyromonas gingivalis and Helicobacter pylori are shown to be associated with the disease in recent epidemiological studies. Therefore, identification of common drug targets and vaccine candidates against these three pathogens would be vital towards therapy and management of atherosclerosis. Chlamydophila pneumonia was selected as a reference organism due to its predominant role in atherosclerosis. Implementing comparative genomic approach, subtractive genomic approach, metabolic pathway analysis, non-homologous gut flora analysis and domain search analysis, 35 common putative drug targets were identified against pathogens of atherosclerosis. Subcellular localization studies were performed and identified UvrABC protein as vaccine candidate. Metabolic pathway analysis has showed that, out of 35 drug targets, 14 enzymes were participating in key pathways linked to pathogen's survival, proliferation and pathogenesis without any alternative mechanism to synthesize the product. The gut microbiota analysis was performed to identify the drug targets which do not affect the microbiota in the humans. Domain search was performed for the identified 14 drug targets using Pfam and SMART databases and protein network analysis was carried out using STRING and Cytoscape v3.2.0. The drug targets and vaccine candidates proposed in the present study would serve as basis to design potent inhibitors and subunit vaccines through in silico approach for combating atherosclerosis caused by infectious pathogens.

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Protein-protein interaction network analysis of osteoarthritis-related differentially expressed genes

Cited by 4 publications

References 23 publications

Identification of altered pathways in hypertrophic cardiomyopathy based on combined data of protein-protein interactions and molecular pathways

Identification of altered pathways in hypertrophic cardiomyopathy based on combined data of protein-protein interactions and molecular pathways

Identification of potential target genes associated with the pathogenesis of osteoarthritis using microarray based analysis

Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

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