Discovering comorbid diseases using an inter-disease interactivity network based on biobank-scale PheWAS data.

ABSTRACT:

Motivation

Understanding comorbidity is essential for disease prevention, treatment and prognosis. In particular, insight into which pairs of diseases are likely or unlikely to co-occur may help elucidate the potential relationships between complex diseases. Here, we introduce the use of an inter-disease interactivity network to discover/prioritize comorbidities. Specifically, we determine disease associations by accounting for the direction of effects of genetic components shared between diseases, and categorize those associations as synergistic or antagonistic. We further develop a comorbidity scoring algorithm to predict whether diseases are more or less likely to co-occur in the presence of a given index disease. This algorithm can handle networks that incorporate relationships

SUBMITTER: Nam Y 

PROVIDER: S-EPMC9825330 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature