Uncovering disease-disease relationships through the incomplete interactome

TLDR

A network approach to identifying disease modules shows that shared genes provide a limited view of mechanistic relationships, and the incompleteness of protein‑protein interaction maps hampers such analyses. The authors formulated mathematical conditions for observing disease modules and showed that only diseases with sufficient data coverage can have identifiable modules. Network‑based distances between disease modules revealed statistically significant molecular similarity—including protein components, gene expression, symptoms, and morbidity—among predicted overlapping pairs, and identified molecular links even between diseases without shared genes. Menche et al., Science, 10.1126/science.1257601.

Abstract

A network approach to finding disease modules Shared genes represent a powerful but limited representation of the mechanistic relationship between two diseases. However, the analysis of protein-protein interactions has been hampered by the incompleteness of interactome maps. Menche et al. formulated the mathematical conditions needed to allow a disease module (a localized region of connections between disease-related proteins) to be observed. Only diseases with data coverage that exceeds a specific threshold have identifiable disease modules. The network-based distance between two disease modules revealed that disease pairs that are predicted to have overlapping modules had statistically significant molecular similarity. These similarities encompassed their protein components, gene expression, symptoms, and morbidity. Molecular-level links between diseases lacking shared disease genes could also be identified. Science , this issue 10.1126/science.1257601