Identification of Genes Implicated in Methapyrilene-Induced Hepatotoxicity by Comparing Differential Gene Expression in Target and Nontarget Tissue

BACKGROUND: Toxicogenomics experiments often reveal thousands of transcript alterations that are related to multiple processes, making it difficult to identify key gene changes that are related to the toxicity of interest. OBJECTIVES: The objective of this study was to compare gene expression changes in a nontarget tissue to the target tissue for toxicity to help identify toxicity-related genes. METHODS: Male rats were given the hepatotoxicant methapyrilene at two dose levels, with livers and kidneys removed 24 hr after one, three, and seven doses for gene expression analysis. To identify gene changes likely to be related to toxicity, we analyzed genes on the basis of their temporal pattern of change using a program developed at the National Institute of Environmental Health Sciences, termed “EPIG” (extracting gene expression patterns and identifying co-expressed genes). RESULTS: High-dose methapyrilene elicited hepatic damage that increased in severity with the number of doses, whereas no treatment-related lesions were observed in the kidney. High-dose methapyrilene elicited thousands of gene changes in the liver at each time point, whereas many fewer gene changes were observed in the kidney. EPIG analysis identified patterns of gene expression correlated to the observed toxicity, including genes associated with endoplasmic reticulum stress and the unfolded protein response. CONCLUSIONS: By factoring in dose level, number of doses, and tissue into the analysis of gene expression elicited by methapyrilene, we were able to identify genes likely to not be implicated in toxicity, thereby allowing us to focus on a subset of genes to identify toxicity-related processes

Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

<p>Abstract</p> <p>Background</p> <p>Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies.</p> <p>Methods</p> <p>Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL.</p> <p>Results</p> <p>The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets.</p> <p>Conclusions</p> <p>The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally inexpensive, they may serve as valuable tools for preselection of attributes to be used in more complex, computationally intensive approaches. Whether used in isolation or in conjunction with other tools, rule based classifiers are an important addition to the armamentarium of tools available for analyses of complex genetic association studies.</p

Microscope-integrated optical coherence tomography: A new surgical tool in vitreoretinal surgery

Optical coherence tomography (OCT) has revolutionized imaging of ocular structures and various disease conditions. Though it has been used in the clinic for some decades, the OCT has only recently found its way into the operating theater. Early attempts at intraoperative OCT, hand-held and microscope mounted, have already improved our understanding of the surgical pathology and the role it might play in surgical decision-making. The microscope-integrated OCT now allows seamless, high-resolution, real-time imaging of surgical maneuvers from the incision to wound closure. Visualization of instruments and intraoperative tissue manipulation are possible with this in vivo modality and, therefore, help improve the outcome of surgery. In this article, we describe the advantages it offers during various vitreoretinal procedures

Toxicogenomics of nevirapine-associated cutaneous and hepatic adverse events among populations of African, Asian, and European descent

OBJECTIVE Nevirapine is widely prescribed for HIV-1 infection. We characterized relationships between nevirapine-associated cutaneous and hepatic adverse events and genetic variants among HIV-infected adults. DESIGN We retrospectively identified cases and controls. Cases experienced symptomatic nevirapine-associated severe (grade III/IV) cutaneous and/or hepatic adverse events within 8 weeks of initiating nevirapine. Controls did not experience adverse events during more than 18 weeks of nevirapine therapy. METHODS Cases and controls were matched 1: 2 on baseline CD4 T-cell count, sex, and race. Individuals with 150 or less CD4 T cells/μl at baseline were excluded. We characterized 123 human leukocyte antigen (HLA) alleles and 2744 single-nucleotide polymorphisms in major histocompatibility complex (MHC) and drug metabolism and transport genes. RESULTS We studied 276 evaluable cases (175 cutaneous adverse events, 101 hepatic adverse events) and 587 controls. Cutaneous adverse events were associated with CYP2B6 516G→T (OR 1.66, all), HLA-Cw*04 (OR 2.51, all), and HLA-B*35 (OR 3.47, Asians; 5.65, Thais). Risk for cutaneous adverse events was particularly high among Blacks with CYP2B6 516TT and HLA-Cw*04 (OR 18.90) and Asians with HLA-B*35 and HLA-Cw*04 (OR 18.34). Hepatic adverse events were associated with HLA-DRB*01 (OR 3.02, Whites), but not CYP2B6 genotypes. Associations differed by population, at least in part reflecting allele frequencies. CONCLUSION Among patients with at least 150 CD4 T cells/μl, polymorphisms in drug metabolism and immune response pathways were associated with greater likelihood of risk for nevirapine-related adverse events. Results suggest fundamentally different mechanisms of adverse events: cutaneous, most likely MHC class I-mediated, influenced by nevirapine CYP2B6 metabolism; hepatic, most likely MHC class II-mediated and unaffected by such metabolism. These risk variants are insensitive for routine clinical screening