Peer Review #3 of "Effects of rheumatoid arthritis associated transcriptional changes on osteoclast differentiation network in the synovium (v0.2)" [peer_review]

2018 unpublished
Background. Osteoclast differentiation in the inflamed synovium of rheumatoid arthritis affected joints leads to the formation of bone lesions. Reconstruction and analysis of protein interaction networks underlying specific disease phenotypes are essential for designing therapeutic interventions. In this study we have created a network that captures signal flow leading to osteoclast differentiation. Based on transcriptome analysis, we have indicated the potential mechanisms responsible for the
more » ... esponsible for the phenotype in the rheumatoid arthritis affected synovium. Method. We collected information on gene expression, pathways and protein interactions related to rheumatoid arthritis from literature and databases namely Gene Expression Omnibus, KEGG pathway and STRING. Based on these information, we created a network for the differentiation of osteoclasts. We identified the differentially regulated network genes and reported the signaling that are responsible for the process in the rheumatoid arthritis affected synovium. Result. Our network reveals the mechanisms underlying the activation of the Neutrophil Cytosolic Factor complex in connection to osteoclastogenesis in rheumatoid arthritis. Additionally, the study reports the predominance of the canonical pathway of NF-κB activation in the diseased synovium. The network also confirms that the upregulation of T cell receptor signaling and downregulation of TGFβ signaling pathway favour osteoclastogenesis in Rheumatoid Arthritis. To the best of our knowledge, this is the first comprehensive protein-protein interaction network describing Rheumatoid Arthritis driven osteoclastogenesis in the synovium. Discussion. This study provides information that can be used to build models of the signal flow involved in the process of osteoclast differentiation. The models can further be used to design therapies to ameliorate bone destruction in the Rheumatoid Arthritis affected joints. PeerJ reviewing PDF | (Abstract 11 Background 12 Osteoclast differentiation in the inflamed synovium of Rheumatoid Arthritis affected joints leads 13 to the formation of bone lesions. Reconstruction and analysis of protein interaction networks 14 underlying specific disease phenotypes are essential for designing therapeutic interventions. In 15 this study we have created a network that captures signal flow leading to osteoclast 16 differentiation. Based on transcriptome analysis, we have indicated the potential mechanisms 17 responsible for the phenotype in the Rheumatoid Arthritis affected synovium. 18 Method 19 We collected information on gene expression, pathways and protein interactions related to 20 Rheumatoid Arthritis from literature and databases namely Gene Expression Omnibus, KEGG 21 pathway and STRING. Based on these information, we created a network for the differentiation 22 of osteoclasts. We identified the differentially regulated network genes and reported the 23 signaling that are responsible for the process in the Rheumatoid Arthritis affected synovium. 24 Result 25 Our network reveals the mechanisms underlying the activation of the Neutrophil Cytosolic 26 Factor complex in connection to osteoclastogenesis in Rheumatoid Arthritis. Additionally, the 27 study reports the predominance of the canonical pathway of NF-κB activation in the diseased 28 synovium. The network also confirms that the upregulation of T cell receptor signaling and 29 downregulation of TGFβ signaling pathway favour osteoclastogenesis in Rheumatoid Arthritis. PeerJ reviewing PDF | (Manuscript to be reviewed 30 To the best of our knowledge, this is the first comprehensive protein-protein interaction network 31 describing Rheumatoid Arthritis driven osteoclastogenesis in the synovium. 32 Discussion 33 This study provides information that can be used to build models of the signal flow involved in 34 the process of osteoclast differentiation. The models can further be used to design therapies to 35 ameliorate bone destruction in the Rheumatoid Arthritis affected joints. 36
doi:10.7287/peerj.5743v0.2/reviews/3 fatcat:hkjxdruhmbb2lo6j732eth7glu