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Uncovering disease-disease relationships through the incomplete interactome

  • Jörg Menche
  • , Amitabh Sharma
  • , Maksim Kitsak
  • , Susan Dina Ghiassian
  • , Marc Vidal
  • , Joseph Loscalzo
  • , Albert László Barabási*
  • *Corresponding author for this work
  • Northeastern University
  • Dana-Farber Cancer Institute
  • Central European University
  • Harvard University
  • Brigham and Women’s Hospital

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

According to the diseasemodule hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, themap of biologically relevant molecular interactions.Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct.These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.

Original languageEnglish
Pages (from-to)841
Number of pages1
JournalScience
Volume347
Issue number6224
DOIs
StatePublished - 20 Feb 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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