The human disease network
Edited by H. Eugene Stanley, Boston University, Boston, MA, and approved April 3, 2007
Abstract
A network of disorders and disease genes linked by known disorder–gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.
Acknowledgments
We thank Victor McKusick, Ada Hamosh, Joanna Amberger, and the rest of the OMIM team for their hard work and dedication and Tom Deisboeck, Zoltán Oltvai, Joanna Amberger, Todd Golub, Gerardo Jimenez-Sanchez and the members of the M.V. laboratory and the Center for Cancer Systems Biology, especially David E. Hill, for useful discussions. K.-I.G. and A.-L.B. were supported by National Institutes of Health (NIH) Grants IH U01 A1070499-01 and U56 CA113004 and National Science Foundation Grant ITR DMR-0926737 IIS-0513650. This work was supported by the Dana–Farber Cancer Institute (DFCI) Strategic Initiative (M.V.) and grants from the W. M. Keck Foundation (to M.V.) and the NIH/National Human Genome Research Institute and NIH/National Institute of General Medical Sciences (to M.V.).
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© 2007 by The National Academy of Sciences of the USA.
Submission history
Received: February 14, 2007
Published online: May 22, 2007
Published in issue: May 22, 2007
Keywords
Acknowledgments
We thank Victor McKusick, Ada Hamosh, Joanna Amberger, and the rest of the OMIM team for their hard work and dedication and Tom Deisboeck, Zoltán Oltvai, Joanna Amberger, Todd Golub, Gerardo Jimenez-Sanchez and the members of the M.V. laboratory and the Center for Cancer Systems Biology, especially David E. Hill, for useful discussions. K.-I.G. and A.-L.B. were supported by National Institutes of Health (NIH) Grants IH U01 A1070499-01 and U56 CA113004 and National Science Foundation Grant ITR DMR-0926737 IIS-0513650. This work was supported by the Dana–Farber Cancer Institute (DFCI) Strategic Initiative (M.V.) and grants from the W. M. Keck Foundation (to M.V.) and the NIH/National Human Genome Research Institute and NIH/National Institute of General Medical Sciences (to M.V.).
Notes
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0701361104/DC1 .
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The authors declare no conflict of interest.
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