Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network
- 1 Department of Biomedical Informatics, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032, USA;
- 2 Department of Statistics, Columbia University, New York, New York 10027, USA;
- 3 Department of Psychiatry, Columbia University, New York, New York 10032, USA;
- 4 Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA;
- 5 Department of Medicine, Institute for Genomics & Systems Biology, Computation Institute, University of Chicago, Chicago, Illinois 60637, USA
Abstract
Common hereditary neurodevelopmental disorders such as autism, bipolar disorder, and schizophrenia are most likely both genetically multifactorial and heterogeneous. Because of these characteristics traditional methods for genetic analysis fail when applied to such diseases. To address the problem we propose a novel probabilistic framework that combines the standard genetic linkage formalism with whole-genome molecular-interaction data to predict pathways or networks of interacting genes that contribute to common heritable disorders. We apply the model to three large genotype–phenotype data sets, identify a small number of significant candidate genes for autism (24), bipolar disorder (21), and schizophrenia (25), and predict a number of gene targets likely to be shared among the disorders.
Footnotes
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↵6 Corresponding author.
↵6 E-mail arzhetsky{at}uchicago.edu; fax (773) 834-2877.
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[Supplemental material is available online at www.genome.org.]
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Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.075622.107.
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- Received December 15, 2007.
- Accepted April 1, 2008.
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Freely available online through the Genome Research Open Access option.
- Copyright © 2008, Cold Spring Harbor Laboratory Press
