Non-Coding RNAs Improve the Predictive Power of Network Medicine

TL;DR

This paper demonstrates that incorporating non-coding RNA interactions into network medicine significantly enhances the understanding of disease mechanisms, expands the interactome, and improves disease module detection and prediction of comorbidities.

Contribution

It is the first comprehensive integration of ncRNA-mediated interactions into human cellular networks, significantly expanding the interactome and improving disease module identification.

Findings

Increased genes in the interactome by 46%.

Expanded interactions by 107%.

Enabled detection of disease modules for 132 diseases.

Abstract

Network Medicine has improved the mechanistic understanding of disease, offering quantitative insights into disease mechanisms, comorbidities, and novel diagnostic tools and therapeutic treatments. Yet, most network-based approaches rely on a comprehensive map of protein-protein interactions, ignoring interactions mediated by non-coding RNAs (ncRNAs). Here, we systematically combine experimentally confirmed binding interactions mediated by ncRNA with protein-protein interactions, constructing the first comprehensive network of all physical interactions in the human cell. We find that the inclusion of ncRNA, expands the number of genes in the interactome by 46% and the number of interactions by 107%, significantly enhancing our ability to identify disease modules. Indeed, we find that 132 diseases, lacked a statistically significant disease module in the protein-based interactome, but have a statistically significant disease module after inclusion of ncRNA-mediated interactions, making these diseases accessible to the tools of network medicine. We show that the inclusion of ncRNAs helps unveil disease-disease relationships that were not detectable before and expands our ability to predict comorbidity patterns between diseases. Taken together, we find that including non-coding interactions improves both the breath and the predictive accuracy of network medicine.