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02-07-2016 | Juvenile idiopathic arthritis | Review | Article

Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification

Journal: Pediatric Rheumatology

Authors: Rachelle Donn, Chiara De Leonibus, Stefan Meyer, Adam Stevens

Publisher: BioMed Central

Abstract

Juvenile idiopathic arthritis (JIA) is a clinically diverse and genetically complex autoimmune disease. Currently, there is very limited understanding of the potential underlying mechanisms that result in the range of phenotypes which constitute JIA.

The elucidation of the functional relevance of genetic associations with phenotypic traits is a fundamental problem that hampers the translation of genetic observations to plausible medical interventions. Genome wide association studies, and subsequent fine-mapping studies in JIA patients, have identified many genetic variants associated with disease. Such approaches rely on ‘tag’ single nucleotide polymorphisms (SNPs). The associated SNPs are rarely functional variants, so the extrapolation of genetic association data to the identification of biologically meaningful findings can be a protracted undertaking. Integrative genomics aims to bridge the gap between genotype and phenotype.

Systems biology, principally through network analysis, is emerging as a valuable way to identify biological pathways of relevance to complex genetic diseases. This review aims to highlight recent findings in systems biology related to JIA in an attempt to assist in the understanding of JIA pathogenesis and therapeutic target identification.

Systems Biology

Integration of complex data in biological systems from diverse experimental sources using interdisciplinary tools.

Network Biology

Biology related to interactions between multiple genes and/or proteins.

Network Analysis

Studies the relationship between the structural properties of a network and biological function.

Interactome

Biological network representing a whole set of direct or indirect interactions related to a specific biological function.

Cluster Modularity

Distinct grouping of protein-protein or protein-gene interactions within a network.

Node

A protein or gene positioned within a network.

Hub

A highly connected node within a network.

Node Centrality

Measures the centrality of nodes, with the identification of which nodes are more “central” than others. Degree centrality of a node refers to the number of edges attached to the node.

Network Robustness

It is a mathematical description of how the integrity of a network responds to the random removal of single nodes.

Network Motifs

Recurrent and statistically significant sub-graphs or patterns within a network.

Network Alignment and Comparison

Used to describe similarities between independent networks.

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Medicine Matters Rheumatology

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