Individuals afflicted with cystic fibrosis (CF) typically succumb to pulmonary complications of their disease, but CF involves all of the major organ systems. Survival of CF patients correlates strongly with body mass index, and mouse models indicate that body size in CF is due to a complex interaction of neuroendocrine function, adipose metabolism and intestinal function. We will continue to utilize mouse models to elucidate the pathways involved and their interactions, and here we propose a plan that will invoke bioinformatics to extract pathway information from literature and databases and sort out those that are concordant with our empiric data. From those pathways, we will develop computational models that will predict outcomes of these pathways when perturbed in specific ways. Using genetic and pharmacologic methods, we will perturb those pathways and assess how well they predict outcomes. Data from these manipulations will be entered back into the bioinformatics processing and new or revised models will be generated and tested until truly predictive models are generated. Concurrently, a whole-genome association study is being carried out and genes showing association with pulmonary disease or body mass index will be examined to determine if they can be placed on the pathway maps generated by the mouse studies. By this iterative process, we hope to identify new pathways contributing to CF pathophysiology and/or clarify the role of pathways known to influence CF severity.

Public Health Relevance

The work described in this proposal has fundamental importance to human disease. It describes a plan that takes advantage of multiple disciplines and cutting-edge technologies to better understand a complex disease, cystic fibrosis. The plan utilizes the power of mouse genetics and molecular biology, human genetics and high throughput genetic screening, bioinformatics and computational modeling to elucidate fundamental, but complex, changes in a simple mendelian disease. The results should be applicable to many other human conditions that are much less tractable due their complex origins, including obesity diabetes and other metabolic conditions.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
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Special Emphasis Panel (ZGM1-GDB-2 (CP))
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Krasnewich, Donna M
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Case Western Reserve University
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