Putative Target Identification for Gout; A Network Biology Approach

Sao, Prachi; Kishore, I.; Singh, Sachidanand; Panneerselvam, Kalpana; Kumar, Atul; Chaudhuri, Tuhin K.

doi:10.1166/jbns.2013.1166

Cited by 5 publications

(2 citation statements)

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“…Multiple-associated diseases analyzed by integrating different microarray expression profiles have already shown huge success in the identification of biomarkers and targets [ 15 , 34 ]. Incorporating protein-protein interaction networks with the above-mentioned concept helps in explaining different forms of biological processes, and in predicting molecular functions that have already existed in previous research work and textbooks [ 31 , 35 , 36 , 37 ]. There are instances in which proteins and genes may not be related directly but interact in the same pathway, or may work in tandem with each other in different phenomena in the same biological processes [ 38 ].…”

Section: Introductionmentioning

confidence: 99%

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

Sao

Chand

Al-Keridis

et al. 2022

CIMB

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Rheumatoid arthritis (RA), osteoarthritis (OA), and periodontal disease (PD) are chronic inflammatory diseases that are globally prevalent, and pose a public health concern. The search for a potential mechanism linking PD to RA and OA continues, as it could play a significant role in disease prevention and treatment. Recent studies have linked RA, OA, and PD to Porphyromonas gingivalis (PG), a periodontal bacterium, through a similar dysregulation in an inflammatory mechanism. This study aimed to identify potential gene signatures that could assist in early diagnosis as well as gain insight into the molecular mechanisms of these diseases. The expression data sets with the series IDs GSE97779, GSE123492, and GSE24897 for macrophages of RA, OA synovium, and PG stimulated macrophages (PG-SM), respectively, were retrieved and screened for differentially expressed genes (DEGs). The 72 common DEGs among RA, OA, and PG-SM were further subjected to gene–gene correlation analysis. A GeneMANIA interaction network of the 47 highly correlated DEGs comprises 53 nodes and 271 edges. Network centrality analysis identified 15 hub genes, 6 of which are DEGs (API5, ATE1, CCNG1, EHD1, RIN2, and STK39). Additionally, two significantly up-regulated non-hub genes (IER3 and RGS16) showed interactions with hub genes. Functional enrichment analysis of the genes showed that “apoptotic regulation” and “inflammasomes” were among the major pathways. These eight genes can serve as important signatures/targets, and provide new insights into the molecular mechanism of PG-induced RA, OA, and PD.

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Section: Introductionmentioning

confidence: 99%

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

Sao

Chand

Al-Keridis

et al. 2022

CIMB

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“…The current objective of RA treatment is to suppress inflammation, pain, and prevent bone destruction. While the symptoms of RA are similar to those of other types of arthritis, such as Rheumatic Fever, Arthralgia, gouty arthritis, and they all have a high rate of morbidity and disability, it is important to distinguish between them 2,3,4 .Both doctors and patients are misled about the disparities in diagnostic capabilities and treatment options available to them 5 . It is critical to comprehend the disease at the molecular level, specifically at the amino acid level, in order to provide correct diagnosis and therapy options.…”

Section: Introductionmentioning

confidence: 99%

Predicting Rheumatoid Arthritis Associated Significant Amino-Acid Residues Using Residue-Residue Interaction Analysis

Sao

Singh²,

Singh

2022

Bangladesh J Med Sci

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Rheumatoid Arthritis (RA) is a prevalent autoimmune and inflammatory disease that requires restructuring. A lot of research information is available, but a clear etiology and drug target information is still unclear. A bottom-up approach can add more information to existing knowledge about RA. One better way of understanding the disease-related mechanism and drug objectives can be a detailed residue-residue interaction of the proteins involved with RA. In the current research work, we have studied the significant proteins reported in the Indian population that are involved in RA progression and have represented each of them as a complex network of amino acid residues to understand the significance of individual residues in the network. We implied the graph theory approach to identity central important residue, based on topological properties of the network. This approach allows us to look at a more precise method to identify potential drug targets. Our result identified leucine, phenylalanine, tyrosine, and tryptophan as essential nodes in the network, their activity was mainly connected with immune system. Understanding the function of these amino acids in CTLA4, CD40, IRF5, IL2RB, and TRAF could lead to a new treatment options in the fight against Rheumatoid Arthritis. Bangladesh Journal of Medical Science Vol. 21 No. 04 October’22 Page : 698-710

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Porphyromonas gingivalis resistance and virulence: An integrated functional network analysis

Sao

Vats

Singh

2022

Gene

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Putative Target Identification for Gout; A Network Biology Approach

Cited by 5 publications

References 0 publications

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

Classifying Integrated Signature Molecules in Macrophages of Rheumatoid Arthritis, Osteoarthritis, and Periodontal Disease: An Omics-Based Study

Predicting Rheumatoid Arthritis Associated Significant Amino-Acid Residues Using Residue-Residue Interaction Analysis

Porphyromonas gingivalis resistance and virulence: An integrated functional network analysis

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