Jonathan Usuka

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.

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 β2 adrenergic receptor gene (β2-AR). Using the selective β2-AR antagonist butoxamine, the authors observed a dose-dependent reversal of OIH. Furthermore, deletion of the β2-AR gene sharply reduced the mechanical allodynia present after morphine treatment in the wild-type mouse strain. Analysis of the associated β2-AR haplotypic block identified single nucleotide polymorphisms potentially explaining in part the strain specific differences in OIH. Conclusions:Genetic variants of the β2-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.

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.

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 16α-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.

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.

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.

2D NMR metabonomic analysis

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.

Haplotype Structure of the Mouse Genome

Commonly available inbred mouse strains can be used to genetically model traits that vary in the human population, including those associated with disease susceptibility. In order to understand how genetic differences regulate trait variation in humans, we must first develop a detailed understanding of how genetic variation in the mouse produces the phenotypic differences among inbred mouse strains. The information obtained from analysis of experimental murine genetic models can direct biological experimentation, clinical research, and human genetic analysis. This “mouse to man” approach will increase our knowledge of the genes and pathways regulating important biological processes and disease susceptibility.

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.