Biomedical subjects

Jianmei Wang

Publications and source records attributed to Jianmei Wang.

5 recordsLinked to original sources

PubMed2006

In silico pharmacogenetics of warfarin metabolism.

Pharmacogenetic approaches can be instrumental for predicting individual differences in response to a therapeutic intervention. Here we used a recently developed murine haplotype-based computational method to identify a genetic factor regulating the metabolism of warfarin, a commonly prescribed anticoagulant with a narrow therapeutic index and a large variation in individual dosing. After quantification of warfarin and nine of its metabolites in plasma from 13 inbred mouse strains, we correlated strain-specific differences in 7-hydroxywarfarin accumulation with genetic variation within a chromosomal region encoding cytochrome P450 2C (Cyp2c) enzymes. This computational prediction was experimentally confirmed by showing that the rate-limiting step in biotransformation of warfarin to its 7-hydroxylated metabolite was inhibited by tolbutamide, a Cyp2c isoform-specific substrate, and that this transformation was mediated by expressed recombinant Cyp2c29. We show that genetic variants responsible for interindividual pharmacokinetic differences in drug metabolism can be identified by computational genetic analysis in mice.

Animals↗

PubMed2006

A genetic analysis of opioid-induced hyperalgesia in mice.

BACKGROUND: Opioid-induced hyperalgesia (OIH) is a syndrome of increased sensitivity to noxious stimuli, seen after both the acute and chronic administration of opioids, that has been observed in humans and rodent models. This syndrome may reduce the clinical utility of opioids in treating acute and chronic pain. METHODS: In these studies, the authors measured the propensity of 15 strains of inbred mice to develop mechanical manifestations of OIH. These data were subjected to in silico genetic analysis, which resulted in the association of haplotypic blocks within or near several known genes. Both pharmacologic agents and transgenic mice were used to confirm the functional association of the most strongly linked gene with OIH. RESULTS: Both baseline mechanical nociceptive thresholds and the percentage changes in these thresholds after 4 days of morphine treatment were found to be highly strain dependent. The haplotypic blocks most strongly associated with the mechanical OIH data were located within the beta2 adrenergic receptor gene (beta2-AR). Using the selective beta2-AR antagonist butoxamine, the authors observed a dose-dependent reversal of OIH. Furthermore, deletion of the beta2-AR gene sharply reduced the mechanical allodynia present after morphine treatment in the wild-type mouse strain. Analysis of the associated beta2-AR haplotypic block identified single nucleotide polymorphisms potentially explaining in part the strain specific differences in OIH. CONCLUSIONS: Genetic variants of the beta2-AR gene seem to explain some part of the differences between various strains of mice to develop OIH. The association of this gene with OIH suggests specific pharmacologic strategies for reducing the impact of OIH on patients consuming opioids.

Adrenergic beta-Antagonists↗

PubMed2006

Understanding our drugs and our diseases.

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.

Animals↗

PubMed2005

Computational genetics: from mouse to human?

In this article, we describe a novel computational-analysis method that rapidly identified the genetic basis for several trait differences among inbred mouse strains. This approach enables researchers to identify a causative genetic factor by correlating a pattern of observable physiological or pathological differences among selected inbred strains with a pattern of genetic variation. Compared with conventional methods used for mouse genetic analysis, which require many years to produce results, this haplotype-based computational analysis can be rapidly performed. We discuss the factors affecting the performance and precision of this computational method. Although it currently can analyze traits of limited genetic complexity in mouse, the potential application of this genetic-analysis method to other experimental organisms, and possibly humans, is evaluated.

Animals↗

PubMed2004

In silico genetics: identification of a functional element regulating H2-Ealpha gene expression.

Computational tools can markedly accelerate the rate at which murine genetic models can be analyzed. We developed a computational method for mapping phenotypic traits that vary among inbred strains onto haplotypic blocks. This method correctly predicted the genetic basis for strain-specific differences in several biologically important traits. It was also used to identify an allele-specific functional genomic element regulating H2-Ealpha gene expression. This functional element, which contained the binding sites for YY1 and a second transcription factor that is probably serum response factor, is located within the first intron of the H2-Ealpha gene. This computational method will greatly improve our ability to identify the genetic basis for a variety of phenotypic traits, ranging from qualitative trait information to quantitative gene expression data, which vary among inbred mouse strains.

Alleles↗