The goal of this research project is to demonstrate that genetic information can improve drug treatment regimens. The pharmacokinetic parameters for at least 4 different therapeutic agents will be measured across 11 inbred mouse strains. The strain-specific pharmacokinetic data will be evaluated using a haplotype-based computational method to identify the genetic loci responsible for the variation in pharmacokinetic responses. The computational predictions will be initially evaluated by correlation of allelic and gene expression patterns across inbred mouse strains, and with known information on the metabolism of these drugs. The effect that genetic alterations within the computationally predicted genes have on the metabolism of these drugs will be evaluated using in vitro and in vivo methodology. This experimental system will enable the factors effecting the metabolism of a drug to be efficiently and rapidly identified. Dosing regimens in mice based on information obtained from genotyping key loci will be developed and prospectively tested to evaluate the utility of genetically guided therapeutics. This model murine genetic system will assess the impact of genetically guided dose adjustment within a treatment population. If this approach is successfully applied to human therapy, it would have a significant impact on human health. To enable this, the following will be completed: 1) Polymorphisms in 150 murine genes effecting drug metabolism will be identified. 2) The pharmacokinetic profile (parent and metabolites) of coumadin, bleomycin, isoniazid and ritonavir will be measured in 11 inbred mouse strains. The genetic factors effecting this response will be computationally identified, and the effect that the predicted genes have on the metabolism of these drugs will be analyzed in vitro and in vivo. 3) One drug will be selected for evaluation of the utility of genetically guided dosing, and a clinical trial using genetically guided dosing will be performed in an experimental murine model.
| Zhang, X; Liu, H-H; Weller, P et al. (2011) In silico and in vitro pharmacogenetics: aldehyde oxidase rapidly metabolizes a p38 kinase inhibitor. Pharmacogenomics J 11:15-24 |
| Tregoning, John S; Yamaguchi, Yuko; Wang, Belinda et al. (2010) Genetic susceptibility to the delayed sequelae of neonatal respiratory syncytial virus infection is MHC dependent. J Immunol 185:5384-91 |
| Liu, Hong-Hsing; Lu, Peng; Guo, Yingying et al. (2010) An integrative genomic analysis identifies Bhmt2 as a diet-dependent genetic factor protecting against acetaminophen-induced liver toxicity. Genome Res 20:28-35 |
| Zheng, Ming; Lu, Peng; Liu, Yanzhou et al. (2007) 2D NMR metabonomic analysis: a novel method for automated peak alignment. Bioinformatics 23:2926-33 |
| Guo, Yingying; Lu, Peng; Farrell, Erin et al. (2007) In silico and in vitro pharmacogenetic analysis in mice. Proc Natl Acad Sci U S A 104:17735-40 |
| Liang, De-Yong; Liao, Guochun; Lighthall, Geoff K et al. (2006) Genetic variants of the P-glycoprotein gene Abcb1b modulate opioid-induced hyperalgesia, tolerance and dependence. Pharmacogenet Genomics 16:825-35 |
| Liang, De-Yong; Liao, Guochun; Wang, Jianmei et al. (2006) A genetic analysis of opioid-induced hyperalgesia in mice. Anesthesiology 104:1054-62 |
| Guo, Yingying; Weller, Paul; Farrell, Erin et al. (2006) In silico pharmacogenetics of warfarin metabolism. Nat Biotechnol 24:531-6 |
| Guo, Yingying; Weller, Paul; Allard, John et al. (2006) Understanding our drugs and our diseases. Proc Am Thorac Soc 3:409-12 |
| Guo, Yingying; Shafer, Steven; Weller, Paul et al. (2005) Pharmacogenomics and drug development. Pharmacogenomics 6:857-64 |
