Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships

Comorbidity is a medical condition attracting increasing attention in healthcare and biomedical research. Little is known about the involvement of potential molecular factors leading to the emergence of a specific disease in patients affected by other conditions. We present here a disease interaction network inferred from similarities between patients' molecular profiles, which significantly recapitulates epidemiologically documented comorbidities. Furthermore, we identify disease patient-subgroups that present different molecular similarities with other diseases, some of them opposing the general tendencies observed at the disease level. Analyzing the generated patient-subgroup network, we identify genes involved in such relations, together with drugs whose effects are potentially associated with the observed comorbidities. All the obtained associations are available at the disease PERCEPTION portal (http://disease-perception.bsc.es). Disease comorbidity is attracting increasing attention, but the involvement of molecular factors in forecasting risk of a disease in the presence of other diseases is poorly understood. Here the authors build a disease interaction network based on gene expression profile and discover new comorbidity relationships in patient subgroups.