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The Proceedings of the American Thoracic Society 3:409-412 (2006)
© 2006 The American Thoracic Society

Understanding Our Drugs and Our Diseases

Yingying Guo, Paul Weller, John Allard, Jonathan Usuka, Mohammad Masjedizadeh, Shao-Yong Wu, Bill Fitch, Douglas Clark, J. David Clark, Steve Shafer, Jianmei Wang, Guochun Liao and Gary Peltz

Departments of Genetics and Genomics, Drug Metabolism and Pharmacokinetics, and Chemical Services, Roche Palo Alto; Veterans Affairs Palo Alto Health Care System; and Department of Anesthesiology, Stanford University, Palo Alto, California

Correspondence and requests for reprints should be addressed to Gary Peltz, M.D., Ph.D., Roche Palo Alto S3-1, 3431 Hillview Avenue, Palo Alto, CA 94304. E-mail: gary.peltz{at}roche.com

ABSTRACT

Analysis of mouse genetic models of human disease–associated traits has provided important insight into the pathogenesis of human disease. As one example, analysis of a murine genetic model of osteoporosis demonstrated that genetic variation within the 15-lipoxygenase (Alox15) gene affected peak bone mass, and that treatment with inhibitors of this enzyme improved bone mass and quality in rodent models. However, the method that has been used to analyze mouse genetic models is very time consuming, inefficient, and costly. To overcome these limitations, a computational method for analysis of mouse genetic models was developed that markedly accelerates the pace of genetic discovery. It was used to identify a genetic factor affecting the rate of metabolism of warfarin, an anticoagulant that is commonly used to treat clotting disorders. Computational analysis of a murine genetic model of narcotic drug withdrawal suggested a potential new approach for treatment of narcotic drug addiction. Thus, the results derived from computational mouse genetic analysis can suggest new treatment strategies, and can provide new information about currently available medicines.

Key Words: computational biology • genetics • pharmacogenetics






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