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ARTICLE
Received 7 Nov 2013 | Accepted 27 May 2014 | Published 26 Jun 2014 DOI: 10.1038/ncomms5212
Human symptoms–disease network
1,2,3, ¨ 2,3,4, ´ ´ ´ 2,3,4,5,6 2,3,6
XueZhong Zhou *, Jorg Menche *, Albert-Laszlo Barabasi Amitabh Sharma
In the post-genomic era, the elucidation of the relationship between the molecular origins of
diseases and their resulting phenotypes is a crucial task for medical research. Here, we use a
large-scale biomedical literature database to construct a symptom-based human disease
network and investigate the connection between clinical manifestations of diseases and their
underlying molecular interactions. We find that the symptom-based similarity of two diseases
correlates strongly with the number of shared genetic associations and the extent to which
their associated proteins interact. Moreover, the diversity of the clinical manifestations of a
disease can be related to the connectivity patterns of the underlying protein interaction
network. The comprehensive, high-quality map of disease–symptom relations can further be
used as a resource helping to address important questions in the field of systems medicine,
for example, the identification of unexpected associations between diseases, disease etiology
research or drug design.
1 School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China.
2 Center for Complex Network Research, Northeastern University Physics Department, 111 DA/Physics Dept., 110 Forsyth Street, Boston, Massachusetts
02115, USA. 3 Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Smith Bldg., Rm. 858A, 450 Brookline Ave, Boston, Massachusetts 02215,
USA. 4
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