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Human symptoms-disease network.

XueZhong Zhou1, Jörg Menche2, Albert-László Barabási3

  • 11] 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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Summary
This summary is machine-generated.

Disease symptoms are linked to molecular interactions. Similar symptoms in diseases often indicate shared genetic links and protein interactions, offering insights for systems medicine and drug discovery.

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Area of Science:

  • Biomedical research
  • Systems medicine
  • Computational biology

Background:

  • Understanding the link between molecular disease origins and phenotypes is vital in the post-genomic era.
  • Biomedical research requires methods to connect clinical manifestations with underlying molecular mechanisms.

Purpose of the Study:

  • To construct a human disease network based on symptoms using a large biomedical literature database.
  • To investigate the relationship between disease clinical manifestations and molecular interactions.
  • To explore the utility of a disease-symptom relation map for systems medicine.

Main Methods:

  • Utilized a large-scale biomedical literature database.
  • Constructed a symptom-based human disease network.
  • Analyzed correlations between symptom similarity, shared genetic associations, and protein-protein interactions.

Main Results:

  • Symptom-based disease similarity strongly correlates with shared genetic associations.
  • Symptom similarity also correlates with the extent of protein interactions between associated genes.
  • Disease clinical manifestation diversity relates to protein interaction network connectivity patterns.

Conclusions:

  • Disease symptoms are robust indicators of underlying molecular connections.
  • A comprehensive disease-symptom map aids in identifying novel disease associations and understanding disease etiology.
  • This network serves as a valuable resource for drug design and systems medicine research.