An integrative genomic analysis identifies Bhmt2 as a diet-dependent genetic factor protecting against acetaminophen-induced liver toxicity.

Acetaminophen-induced liver toxicity is the most frequent precipitating cause of acute liver failure and liver transplant, but contemporary medical practice has mainly focused on patient management after a liver injury has been induced. An integrative genetic, transcriptional, and two-dimensional NMR-based metabolomic analysis performed using multiple inbred mouse strains, along with knowledge-based filtering of these data, identified betaine-homocysteine methyltransferase 2 (Bhmt2) as a diet-dependent genetic factor that affected susceptibility to acetaminophen-induced liver toxicity in mice. Through an effect on methionine and glutathione biosynthesis, Bhmt2 could utilize its substrate (S-methylmethionine [SMM]) to confer protection against acetaminophen-induced injury in vivo. Since SMM is only synthesized in plants, Bhmt2 exerts its beneficial effect in a diet-dependent manner. Identification of Bhmt2 and the affected biosynthetic pathway demonstrates how a novel method of integrative genomic analysis in mice can provide a unique and clinically applicable approach to a major public health problem.

Plasminogen alleles influence susceptibility to invasive aspergillosis.

Invasive aspergillosis (IA) is a common and life-threatening infection in immunocompromised individuals. A number of environmental and epidemiologic risk factors for developing IA have been identified. However, genetic factors that affect risk for developing IA have not been clearly identified. We report that host genetic differences influence outcome following establishment of pulmonary aspergillosis in an exogenously immune suppressed mouse model. Computational haplotype-based genetic analysis indicated that genetic variation within the biologically plausible positional candidate gene plasminogen (Plg; Gene ID 18855) correlated with murine outcome. There was a single nonsynonymous coding change (Gly110Ser) where the minor allele was found in all of the susceptible strains, but not in the resistant strains. A nonsynonymous single nucleotide polymorphism (Asp472Asn) was also identified in the human homolog (PLG; Gene ID 5340). An association study within a cohort of 236 allogeneic hematopoietic stem cell transplant (HSCT) recipients revealed that alleles at this SNP significantly affected the risk of developing IA after HSCT. Furthermore, we demonstrated that plasminogen directly binds to Aspergillus fumigatus. We propose that genetic variation within the plasminogen pathway influences the pathogenesis of this invasive fungal infection.

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.

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.

2D NMR metabonomic analysis: a novel method for automated peak alignment.

MOTIVATION: Comparative metabolic profiling by nuclear magnetic resonance (NMR) is showing increasing promise for identifying inter-individual differences to drug response. Two dimensional (2D) (1)H (13)C NMR can reduce spectral overlap, a common problem of 1D (1)H NMR. However, the peak alignment tools for 1D NMR spectra are not well suited for 2D NMR. An automated and statistically robust method for aligning 2D NMR peaks is required to enable comparative metabonomic analysis using 2D NMR. RESULTS: A novel statistical method was developed to align NMR peaks that represent the same chemical groups across multiple 2D NMR spectra. The degree of local pattern match among peaks in different spectra is assessed using a similarity measure, and a heuristic algorithm maximizes the similarity measure for peaks across the whole spectrum. This peak alignment method was used to align peaks in 2D NMR spectra of endogenous metabolites in liver extracts obtained from four inbred mouse strains in the study of acetaminophen-induced liver toxicity. This automated alignment method was validated by manual examination of the top 50 peaks as ranked by signal intensity. Manual inspection of 1872 peaks in 39 different spectra demonstrated that the automated algorithm correctly aligned 1810 (96.7%) peaks. AVAILABILITY: Algorithm is available upon request.

From mouse genetics to human therapeutics.

This review examines how and where genomic and genetic research will impact pharmaceutical research and development, and emphasizes how mouse genomics and genetics can improve the understanding of human disease pathobiology and drug metabolism, and identify new targets for therapeutic intervention. Although important discoveries can be made from mouse genetic analysis, its utility has been limited by the high cost and long time lines required for such research. A recently developed computational method that markedly accelerates the pace of genetic discovery and reduces its cost is also described.

Pharmacogenomics and drug development.

It is generally anticipated that pharmacogenomic information will have a large impact on drug development and will facilitate individualized drug treatment. However, there has been relatively little quantitative modeling to assess how pharmacogenomic information could be best utilized in clinical practice. Using a quantitative model, this review demonstrates that efficacy is increased and toxicity is reduced when a genetically-guided dose adjustment strategy is utilized in a clinical trial. However, there is limited information available regarding the genetic variables affecting the disposition or mechanism of action of most commonly used medications. These genetic factors must be identified to enable pharmacogenomic testing to be routinely used in the clinic. A recently described murine haplotype-based computational genetic analysis method provides one strategy for identifying genetic factors regulating the pharmacokinetics and pharmacodynamics of commonly used medications.

Pharmacogenomics and drug development: the impact of US FDA postapproval tracking on clinical pharmacology.

Severe adverse drug reactions to commonly prescribed drugs such as Vioxx® have led to a call for increased scrutiny in deciding which patients are given which drugs, and how much drug they should receive. A personalized approach to medicine offers a larger variety of drugs and doses that would be prescribed only to a subgroup of patients. Pharmacogenomics could help divide patients into these subgroups based on variation in the genes either causing the disease or encoding the principle drug-metabolizing enzymes. Given the cost and infrastructure associated with assembling genetic data, drug sponsors, regulatory agencies and clinicians each play a role in the collection, storage and oversight of pharmacogenetic information. The 110th Congress is in the process of making changes to the drug-approval process and the role of genetics in that process.

In silico and in vitro pharmacogenetic analysis in mice.

Combining the experimental efficiency of a murine hepatic in vitro drug biotransformation system with in silico genetic analysis produces a model system that can rapidly analyze interindividual differences in drug metabolism. This model system was tested by using two clinically important drugs, testosterone and irinotecan, whose metabolism was previously well characterized. The metabolites produced after these drugs were incubated with hepatic in vitro biotransformation systems prepared from the 15 inbred mouse strains were measured. Strain-specific differences in the rate of 16 alpha-hydroxytestosterone generation and irinotecan glucuronidation correlated with the pattern of genetic variation within Cyp2b9 and Ugt1a loci, respectively. These computational predictions were experimentally confirmed using expressed recombinant enzymes. The genetic changes affecting irinotecan metabolism in mice mirrored those in humans that are known to affect the pharmacokinetics and incidence of adverse responses to this medication.

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.

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.

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.

Ozone-induced acute pulmonary injury in inbred mouse strains.

To determine if host factors influence the time course and extent of lung injury after acute inhalation of ozone (O3), we evaluated the physiologic and biologic response of nine genetically diverse inbred strains of mice (C57BL/6J, 129/SvIm, BTBR, BALB/cJ, DBA/2J, A/J, FVB/NJ, CAST/Ei, and C3H/HeJ) exposed to O3 (2.0 ppm x 3 h). Whole lung lavage determined that 129/Svlm, BTBR, DBA/2J, and FVB/NJ had a peak increase in polymorphonuclear cells (PMNs) at 6 h, whereas C57BL/6J and CAST/Ei had a peak increase at 24 h after exposure; airway PMNs were minimally elevated in A/J and C3H/HeJ; BALB/cJ had a predominant lymphocytic influx. Interleukin-6 concentration in the lavage fluid was associated with the influx of PMNs, whereas the total protein in the lavage fluid did not always correlate with lavage cellularity. Respiratory responses were monitored using whole body plethysmography and enhanced pause index. C57BL/6J, BALB/cJ, 129/SvIm, and BTBR were highly sensitive to O3 and exhibited significant increases in enhanced pause to methacholine aerosol stimulation at 6 and 24 h after exposure to O3. In contrast, DBA/2J, A/J, FVB/NJ, CAST/Ei, and C3H/HeJ strains had demonstrated increases in sensitivity to MCh at 6 h after exposure, but responses had returned to near baseline by 24 h after exposure to O3. Epithelial cell proliferation as assessed by proliferating cell nuclear antigen staining was evident at 24 h after exposure to O3. C57BL/6J and A/J showed 4% proliferating cell nuclear antigen-positive cells; 129/SvIm, DBA/2J, and FVB/NJ had 1-3%; and BTBR, BALB/cJ, CAST/Ei, and C3H/HeJ had < 1%. Phenotypic measurements in six inbred strains were used for an in silico genome analysis based on the Roche mouse database. Consistent loci on chromosomes 1, 7, and 15 were among those identified to have a significant association with the phenotypes studied. In aggregate, our approach has identified O3-resistant (C3H/HeJ and A/J) and -vulnerable (C57BL/6J and 129/SvIm) strains of mice, and determined novel genomic loci, suggesting a clear genetic basis for the lung response to inhaled O3.