Fig. 5.

Disease similarity on the two networks. (A) RA disease similarities and possible comorbidities. Two diseases are connected if they have a negative separation (meaning that they co-exist in the same network neighborhood) and if their overlap is significant. RA Disease–Disease network (LCC P < 0.05, $S_{a,b}$   < 0, $S_{a,b}$   P < 0.05, Jaccard index > 0.05, hypergeometric test P < 0.05; all P values are FDR corrected) is shown for both the PPI and the PPI & NCI. Diseases are colored according to literature references for comorbidity. We find in the PPI that only CD is possible comorbidity, while the PPI & NCI predicts several other comorbid diseases, and most of them have a reported RR greater than 1, indicating comorbidity, few have RR smaller than 1, indicating a protective effect from those diseases. (B) RA comorbidities are also connected. Diseases that have high comorbidity with RA are also connected. Similar to A, we find an expansion of disease associations in the PPI & NCI. The PPI alone identifies two distinct clusters: A neoplasm and an inflammation module. The inclusion of ncRNA into the PPI helps us identify how those two clusters (neoplasm and inflammation) are also interconnected with each other. (C) Complete map of disease–disease relationships. We show the complete disease–disease network, unveiling the comorbidity map between 466 diseases. Each disease with a significant module (full dots) has its node size representing the size of the disease module, and the link width is relative to the normalized absolute $S_{a,b}$ value. Note that the PPI & NCI network forms a connected component with all the 213 diseases that have a significant LCC; moreover, we see that neoplasm (represented in blue) are close and form a module. The PPI, in its turn, forms a connected component with only 100 diseases, and the combination of both gives us a component that includes 249 diseases.