Non-Additive Ah Receptor Ligand Interactions

点击翻译按钮获取中文摘要

Although human exposure to toxicants occurs as a complex mixture, risk assessments are typically based on single chemical studies conducted in rodent models. Limitations associated with current approaches are increasingly being questioned due to the potential for significant health, societal and economic consequences. In order to improve the quantitative risk assessment of chronic and subchronic exposure to synthetic and natural chemicals and their complex mixtures, uncertainties within the source-to-outcome continuum must be minimized in the context of the whole organisms, and its genome. In this proposal, 2,3,7,8-tetrachlrodibenzo-p-dioxin (TCDD), 3,3',4,4',5-pentachlorobiphenyl (PCB126), and 2,2',4,4',5,5'- hexachlorobiphenyl (PCB153) as well as a reconstituted mixture that reflects environmental levels of these contaminants will be systematically examined to elucidate the mechanisms of action of additive, antagonistic and synergistic interactions that occur at molecular and physiological levels. Ray designs and modeling approaches will be used to minimize full factorial studies in order to investigate the hypothesis that a mixture of TCDD, PCB126 and PCB153 at environmentally relevant levels elicit non-additive hepatotoxic effects. Dose- and time-dependent hepatic gene expression and fatty liver effects will be assessed using a mouse cDNA array enriched with dioxin responsive genes and complementary histopathology approaches. Microarray data will be computationally integrated with histopathology and clinical chemistry to identify associations between changes in gene expression and physiological/toxic outcomes that facilitates the elucidation the mechanisms of action of dioxin-mediated fatty liver toxicity. The mixture will then be examined to detect and characterize the additive, synergistic and antagonistic interactions that affect the fatty liver response using response surface models for genes associated with fatty liver. This proposal will not only develop innovative and credible statistical strategies to rigorously assess interactions induced by mixtures containing chemicals that use a common mechanism of action, but will also further elucidate mechanisms of toxicity associated with TCDD-induced fatty.