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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/115597
Genetic and functional characterization of disease associations explains comorbidity
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Understanding relationships between diseases, such as
comorbidities, has important socio-economic implications,
ranging from clinical study design to health care planning. Most
studies characterize disease comorbidity using shared genetic
origins, ignoring pathway-based commonalities between diseases.
In this study, we define the disease pathways using an
interactome-based extension of known disease-genes and introduce
several measures of functional overlap. The analysis reveals 206
significant links among 94 diseases, giving rise to a highly
clustered disease association network. We observe that around
95% of the links in the disease network, though not identified
by genetic overlap, are discovered by functional overlap. This
disease network portraits rheumatoid arthritis, asthma,
atherosclerosis, pulmonary diseases and Crohn's disease as hubs
and thus pointing to common inflammatory processes underlying
disease pathophysiology. We identify several described
associations such as the inverse comorbidity relationship
between Alzheimer's disease and neoplasms. Furthermore, we
investigate the disruptions in protein interactions by mapping
mutations onto the domains involved in the interaction,
suggesting hypotheses on the causal link between diseases.
Finally, we provide several proof-of-principle examples in which
we model the effect of the mutation and the change of the
association strength, which could explain the observed
comorbidity between diseases caused by the same genetic
alterations.
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RUBIO PEREZ, Carlota, et al. Genetic and functional characterization of disease associations
explains comorbidity. Scientific Reports. 2017. Vol. 7, num. 1, pags. 6207. ISSN 2045-2322. [consulted: 7 of October of 2026]. Available at: https://hdl.handle.net/2445/115597