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.Comment: Paper and S