Latent disease similarities and therapeutic repurposing possibilities uncovered by multi-modal generative topic modeling of human diseases.

Motivation: Human diseases are characterized by multiple features such as their pathophysiological, molecular and genetic changes. The rapid expansion of such multi-modal disease-omics space provides an opportunity to re-classify diverse human diseases and to uncover their latent molecular similarities, which could be exploited to repurpose a therapeutic-target for one disease to another.

Results: Herein, we probe this underexplored space by soft-clustering 6955 human diseases by multi-modal generative topic modeling.