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Understanding our drugs and our diseases
Yingying Guo1, Paul Weller, John Allard
1Departments of Genetics and Genomics, Roche Palo Alto, Palo Alto, CA 94304, USA.
Proceedings of the American Thoracic Society
|June 27, 2006
Summary
Computational analysis of mouse genetic models accelerates discovery of disease insights. This method identified factors affecting drug metabolism and suggested new therapeutic strategies for addiction and osteoporosis.
Area of Science:
- Genetics
- Pharmacology
- Computational Biology
Background:
- Mouse genetic models offer insights into human disease pathogenesis.
- Traditional analysis of these models is time-consuming, inefficient, and costly.
- The 15-lipoxygenase (Alox15) gene variation impacts bone mass, with inhibitors improving bone quality in rodent models.
Purpose of the Study:
- To develop a computational method for accelerated analysis of mouse genetic models.
- To identify genetic factors influencing drug metabolism and disease treatment.
Main Methods:
- Development of a novel computational approach for analyzing mouse genetic data.
- Application of the computational method to identify genetic influences on warfarin metabolism.
- Utilizing computational analysis on a murine model of narcotic drug withdrawal.
Main Results:
- The computational method significantly speeds up genetic discovery.
- Identification of a genetic factor affecting warfarin metabolism rate.
- Computational analysis suggested novel therapeutic strategies for narcotic drug addiction.
Conclusions:
- Computational analysis of mouse genetic models enhances the pace of genetic discovery.
- This approach can reveal new treatment strategies for various conditions.
- Findings provide new information on the mechanisms of action for existing medications.
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