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The multiplex network of human diseases.

Arda HaluManlio De DomenicoAlexandre ArenasAmitabh Sharma
Published in: NPJ systems biology and applications (2019)
Untangling the complex interplay between phenotype and genotype is crucial to the effective characterization and subtyping of diseases. Here we build and analyze the multiplex network of 779 human diseases, which consists of a genotype-based layer and a phenotype-based layer. We show that diseases with common genetic constituents tend to share symptoms, and uncover how phenotype information helps boost genotype information. Moreover, we offer a flexible classification of diseases that considers their molecular underpinnings alongside their clinical manifestations. We detect cohesive groups of diseases that have high intra-group similarity at both the molecular and the phenotypic level. Inspecting these disease communities, we demonstrate the underlying pathways that connect diseases mechanistically. We observe monogenic disorders grouped together with complex diseases for which they increase the risk factor. We propose potentially new disease associations that arise as a unique feature of the information flow within and across the two layers.
Keyphrases
  • machine learning
  • healthcare
  • risk factors
  • gene expression
  • deep learning
  • high throughput
  • health information
  • induced pluripotent stem cells
  • single molecule
  • single cell