TY - JOUR
T1 - Uncovering disease-disease relationships through the incomplete interactome
AU - Menche, Jörg
AU - Sharma, Amitabh
AU - Kitsak, Maksim
AU - Ghiassian, Susan Dina
AU - Vidal, Marc
AU - Loscalzo, Joseph
AU - Barabási, Albert László
PY - 2015/2/20
Y1 - 2015/2/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84923306828&partnerID=8YFLogxK
U2 - 10.1126/science.1257601
DO - 10.1126/science.1257601
M3 - Article
C2 - 25700523
AN - SCOPUS:84923306828
SN - 0036-8075
VL - 347
SP - 841
JO - Science
JF - Science
IS - 6224
ER -