Network properties of genes harboring inherited disease mutations
- *Department of Biomedical Informatics, Center of Computational Biology and Bioinformatics, Columbia University, New York, NY 10032; and
- †Computation Institute and Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL 60637
-
Edited by Randy Schekman, University of California, Berkeley, CA, and approved January 17, 2008 (received for review February 23, 2007)
Abstract
By analyzing, in parallel, large literature-derived and high-throughput experimental datasets we investigate genes harboring human inherited disease mutations in the context of molecular interaction networks. Our results demonstrate that network properties influence the likelihood and phenotypic consequences of disease mutations. Genes with intermediate connectivities have the highest probability of harboring germ-line disease mutations, suggesting that disease genes tend to occupy an intermediate niche in terms of their physiological and cellular importance. Our analysis of tissue expression profiles supports this view. We show that disease mutations are less likely to occur in essential genes compared with all human genes. Disease genes display significant functional clustering in the analyzed molecular network. For about one-third of known disorders with two or more associated genes we find physical clusters of genes with the same phenotype. These clusters are likely to represent disorder-specific functional modules and suggest a framework for identifying yet-undiscovered disease genes.
Footnotes
- ‡To whom correspondence may be addressed. E-mail: arzhetsky{at}uchicago.edu or dennis.vitkup{at}dbmi.columbia.edu
-
Author contributions: A.R. and D.V. designed research; I.F., A.R., and D.V. performed research; I.F., A.R., and D.V. analyzed data; and I.F., A.R., and D.V. wrote the paper.
-
The authors declare no conflict of interest.
-
This article is a PNAS Direct Submission.
-
This article contains supporting information online at www.pnas.org/cgi/content/full/0701722105/DC1.
- © 2008 by The National Academy of Sciences of the USA





