Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Stevens, Adam; Meyer, Stefan; Hanson, Daniel; Clayton, Peter E.; Donn, Rachelle

doi:10.1186/ar4559

Cited by 11 publications

(13 citation statements)

References 65 publications

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“…The cell types where disease-associated variants might drive disease can be identified by comparing with histone modification profiles that mark that cell lineage-specific regulatory elements [ 8 , 13 ]. To better understand the relationships that exist between disease associated genes, they can be painted onto gene interaction networks, such as protein-protein interaction networks [ 14 , 15 ]. However, these strategies have not yet been applied to RA FLS.…”

Section: Introductionmentioning

confidence: 99%

Integrative Omics Analysis of Rheumatoid Arthritis Identifies Non-Obvious Therapeutic Targets

Whitaker¹,

Boyle

Bartók

et al. 2015

PLoS ONE

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Identifying novel therapeutic targets for the treatment of disease is challenging. To this end, we developed a genome-wide approach of candidate gene prioritization. We independently collocated sets of genes that were implicated in rheumatoid arthritis (RA) pathogenicity through three genome-wide assays: (i) genome-wide association studies (GWAS), (ii) differentially expression in RA fibroblast-like synoviocytes (FLS), and (iii) differentially methylation in RA FLS. Integrated analysis of these complementary data sets identified a significant enrichment of multi-evidence genes (MEGs) within pathways relating to RA pathogenicity. One MEG is Engulfment and Cell Motility Protein-1 (ELMO1), a gene not previously considered as a therapeutic target in RA FLS. We demonstrated in RA FLS that ELMO1 is: (i) expressed, (ii) promotes cell migration and invasion, and (iii) regulates Rac1 activity. Thus, we created links between ELMO1 and RA pathogenicity, which in turn validates ELMO1 as a potential RA therapeutic target. This study illustrated the power of MEG-based approaches for therapeutic target identification.

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Section: Introductionmentioning

confidence: 99%

Integrative Omics Analysis of Rheumatoid Arthritis Identifies Non-Obvious Therapeutic Targets

Whitaker¹,

Boyle

Bartók

et al. 2015

PLoS ONE

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“…14,19 The 437 genes were processed using the PGM impact analysis, and an interactome was generated with the top 10% (122 nodes 248 edges). 21 Then, they were grouped by modularity, 20 and the resulting modules are shown in Figure 7. The size of the nodes is proportional to the PIS (the complete data of Table 1 is provided in the Supplementary materials).…”

Section: Discussionmentioning

confidence: 99%

“…cytoscape.org/download.php, and this one of ReactomeFIViz [also called Reactome Cytoscape Plugin or ReactomeFIPl-ugIn] http://apps.cytoscape.org/apps/reactomefiplugin), 14,19,20 where an interactome was generated with the top 10% differences. 21 Then, we ran a network clustering algorithm on the interactome to identify working subnetworks. 20 The tool provides predicted functional impact scores by integrating all observed variations to assess whether the activities of each gene are increased, decreased, or unaffected.…”

Section: Probabilistic Graphical Model Impact Analysismentioning

confidence: 99%

“…The top 10% of nodes, classified by differences in protein impact score (PIS) were selected to generate a minimal essential network (MEN; Figure 7). 21 The size of the nodes in the interactome is proportional to their PIS; this value is obtained not only by the expression of the gene but also by their known interactions. 14,19 It is important to mention that the app generates a comparison against random samples from its database in order to provide the results.…”

Section: Pgm Impact Analysismentioning

confidence: 99%

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Adhesion, proliferation, and apoptosis in different molecular portraits of breast cancer treated with silver nanoparticles and its pathway-network analysis

Rodríguez-Razón

Yáñez-Sánchez

Ramos-Santillan

et al. 2018

IJN

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BackgroundSilver nanoparticles (AgNPs) have attracted considerable attention due to the variety of their applications in medicine and other sciences. AgNPs have been used in vitro for treatment of various diseases, such as hepatitis B and herpes simplex infections as well as colon, cervical, and lung cancers. In this study, we assessed the effect on proliferation, adhesion, and apoptosis in breast cancer cell lines of different molecular profiles (MCF7, HCC1954, and HCC70) exposed to AgNPs (2–9 nm).MethodsBreast cancer cell lines were incubated in vitro; MTT assay was used to assess proliferation. Adhesion was determined by real-time analysis with the xCELLingence system. Propidium iodide and fluorescein isothiocyanate-Annexin V assay were used to measure apoptosis. The transcriptome was assessed by gene expression microarray and Probabilistic Graphical Model (PGM) analyses.ResultsThe results showed a decreased adhesion in breast cancer cell lines and the control exposed to AgNPs was noted in 24 hours (p≤0.05). We observed a significant reduction in the proliferation of MCF7 and HCC70, but not in HCC1954. Apoptotic activity was seen in all cell lines exposed to AgNPs, with an apoptosis percentage of more than 60% in cancer cell lines and less than 60% in the control. PGM analysis confirmed, to some extent, the effects of AgNPs primarily on adhesion by changes in the extracellular matrix.ConclusionExposure to AgNPs causes an antiproliferative, apoptotic, and anti-adhesive effect in breast cancer cell lines cultured in vitro. More research is needed to evaluate the potential use of AgNPs to treat different molecular profiles of breast cancer in humans.

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“…Recently, new approaches are being applied in the field of neuropsychiatry to identify indirect associations through a variant’s effect at the mRNA and protein level through interaction networks and pathway enrichment analyses 10 11 12 13 . A few previous attempts were made with immune mediated diseases to detect disease relevant pathways and to capture risk loci through the interconnectedness of genes assessed by protein-protein interactions 9 14 15 16 17 . Importantly, those studies provided information either from a single interactome dataset with a limited number of interactions 15 or investigated a limited number of autoimmune risk genes 14 17 .…”

mentioning

confidence: 99%

Integrated Genomics Identifies Convergence of Ankylosing Spondylitis with Global Immune Mediated Disease Pathways

Uddin

Codner

Hasan

et al. 2015

Sci Rep

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Ankylosing spondylitis(AS), a highly heritable complex inflammatory arthritis. Although, a handful of non-HLA risk loci have been identified, capturing the unexplained genetic contribution to AS pathogenesis remains a challenge attributed to additive, pleiotropic and epistatic-interactions at the molecular level. Here, we developed multiple integrated genomic approaches to quantify molecular convergence of non-HLA loci with global immune mediated diseases. We show that non-HLA genes are significantly sensitive to deleterious mutation accumulation in the general population compared with tolerant genes. Human developmental proteomics (prenatal to adult) analysis revealed that proteins encoded by non-HLA AS risk loci are 2-fold more expressed in adult hematopoietic cells.Enrichment analysis revealed AS risk genes overlap with a significant number of immune related pathways (p < 0.0001 to 9.8 × 10-12). Protein-protein interaction analysis revealed non-shared AS risk genes are highly clustered seeds that significantly converge (empirical; p < 0.01 to 1.6 × 10-4) into networks of global immune mediated disease risk loci. We have also provided initial evidence for the involvement of STAT2/3 in AS pathogenesis. Collectively, these findings highlight molecular insight on non-HLA AS risk loci that are not exclusively connected with overlapping immune mediated diseases; rather a component of common pathophysiological pathways with other immune mediated diseases. This information will be pivotal to fully explain AS pathogenesis and identify new therapeutic targets.

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Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Cited by 11 publications

References 65 publications

Integrative Omics Analysis of Rheumatoid Arthritis Identifies Non-Obvious Therapeutic Targets

Integrative Omics Analysis of Rheumatoid Arthritis Identifies Non-Obvious Therapeutic Targets

Adhesion, proliferation, and apoptosis in different molecular portraits of breast cancer treated with silver nanoparticles and its pathway-network analysis

Integrated Genomics Identifies Convergence of Ankylosing Spondylitis with Global Immune Mediated Disease Pathways

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