UNIVERSITY OF WASHINGTON

This application responds to NHLBI Participation in Research and Research Infrastructure "Grand Opportunities" (RC2) (RFA-OD-09-004) for Large-scale DNA Sequencing and Molecular Profiling of Well-Phenotyped NHLBI Cohorts. The major goal of this proposal is to apply second generation resequencing technology to identify disease-causing variants influencing pediatric and adult lung diseases in a collection of seven population cohorts that have been well-characterized for a comprehensive set of clinical traits. The technology we are applying to receive involves the array-based capture and massively parallel resequencing of all protein coding sequences in the human genome (the "exome"). In the initial discovery stage we will work with the selected sequencing center(s) to generate a catalogue of rare and common variants for a key set of lung diseases which are third leading cause of death in the United States. Our exome variant catalogue will be generated from each of 50-200 individuals in the tails of the distribution of the major clinical phenotype assessed for key lung diseases in the US population. Our phenotypes include: severity of lung disease in cystic fibrosis, time to acquisition of Pseudomonas aeruginosa (Pa) in cystic fibrosis, severity of lung disease in asthma, rate of decline of lung function in chronic obstructive pulmonary disease, and severity of pulmonary hypertension and severity of acute lung injury. The variant catalogues from each tail will be subjected mined by novel bioinformatics approaches to identify high-priority disease-modifying genes and/or causal variants. This genome-wide resequencing approach presents one of the most important challenges and opportunities in modern genetics. As we show for other diseases, exome sequencing can uncover low frequency alleles not currently typed or detectable by genome-wide association studies. In a second stage, we propose each high priority candidate gene or variant will be evaluated in all individuals in each cohort using conventional methods. Discovery of the genetic variants influencing these overlapping pulmonary phenotypes will substantially expand our understanding of biology of lung diseases, the third leading cause of death in the United States and will facilitate accurate diagnosis and improved management of a group of diseases that impact the very youngest and oldest in our country. Our findings may well provide insights for novel therapeutics to prevent lung disease in the U.S. and globally.

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