Comorbidity Prediction and Validation using a Disease Gene Graph and Public Health Data

In this paper, we use known disease-gene associations to construct an undirected graph that represents a disease-disease network. From the edges of this graph, we infer co-occurrences of different diseases in the same individual, known as comorbidities. These in silico comorbidities are compared with those present in a Brazilian Public Health database. We then attempt to predict missing edges in the in silico comorbidity graph. These predictions are validated against the same database. Some validated comorbidities are briefly described. The therapeutic relevance, extensions, and limitations of this approach are discussed.

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