Network medicine analysis of chondrocyte proteins towards new treatments of osteoarthritis

Abstract

Osteoarthritis (OA) is a progressive disorder with high incidence in the ageing human population that still has no treatment currently. This disorder induces the breakdown of articular cartilage, leading to the exposure and damage of bone surfaces. For a global understanding of OA development, the systematic integration of known OA-related proteins with protein-protein interaction (PPI) networks is required. In this work, theOA-related interactomewas reconstructed usingmultiple data sources to have themost up-to-date information on OA-related proteins and their interactions. We then combined emergent concepts in network medicine to detect new unclassified OA-related proteins. The mapping of known OA-related proteins with PPI networks showed that these proteins are locally connected to each other and agglomerated in a large component. To expand this module, we applied a diffusion-based algorithm that probabilistically induces more searches in the vicinity of the seed OArelated proteins. As a result, the 10 topmost ranked proteins were connected to theOAdiseasemodule, supporting the local hypothesis.We computed structuralmodules and selected those that had the highest enrichment ofOA-related proteins. The identified molecules showa link between structural topology and disease dysfunctionality. Interestingly, the proteinQ6EEV6was highlighted for OA association by both methods, reinforcing the potential involvement of this protein. These results suggest that similar disease-connectedmodules may exist in different human disorders, which could lead to systematic identification of genes or proteins that have a joint role in specific disease phenotypes. © 2014 The Author(s) Published by the Royal Society. All rights reserved.