This application is in response to PA-07-043 Right Heart Function in Health and Chronic Lung Diseases. There are approximately 100,000 new pulmonary hypertension (PH) patients annually in the U.S., and 50,000- 300,000 new cases of interstitial and chronic obstructive lung diseases (COPD) respectively. It is widely recognized that right ventricular dysfunction plays a pivotal role in heart failure in patients with pulmonary arterial hypertension (PAH), interstitial lung diseases and COPD. Right heart failure is the leading cause of mortality in PAH and contributes significantly to mortality in interstitial and obstructive lung diseases. A better understanding of right heart dysfunction in these diseases will likely enable new therapies to prevent or treat right heart failure, resulting in reduced morbidity and mortality in these patients. In spite of this, our understanding of the pathogenesis of right ventricular dysfunction in these diseases is very limited and even less is known about genes that influence the susceptibility for right ventricular hypertrophy (RVH) and elevated pulmonary artery pressure (PAP). We hypothesize that genetic differences between individuals and/or within populations play a major role in determining the susceptibility to RVH and/or elevated right ventricular systolic pressure (RVSP) in chronic lung disease such as PAH. Employing a well-established mouse model of PH induced by exposure to chronic hypoxia, we will identify strain specific differences in right ventricular dysfunction. Our preliminary data already clearly indicates that major differences exist between different strains. The primary objective of this application is to identify specific regions of the mouse genome containing genes contributing to increased susceptibility to chronic hypoxia-induced PH. To achieve this, the following specific aims are proposed: 1) Survey inbred strains to determine appropriate mouse models for genetic analysis of chronic hypoxia-induced pulmonary hypertension;2) Perform conventional mapping to identify quantitative trait loci (QTLs) contributing to chronic hypoxia-induced PH. Strains demonstrating the largest differences in RVH and RVSP after chronic hypoxia will be selected as models for QTL analysis;3) Identify candidate and positional candidate genes associated with susceptibility to chronic hypoxia-induced pulmonary hypertension for each mouse model within identified QTL regions. Fine mapping with additional single nucleotide polymorphisms in the QTL regions, recently developed haplotype association mapping methods of the QTL regions, and microarray analysis of parental and F2 animals for each model will be performed to refine the regions and identify any genes in the QTL regions demonstrating changes in gene expression. These genes can be prioritized as potential quantitative trait candidate genes (QTGs).
There are approximately 100,000 new pulmonary hypertension patients annually in the U.S., and 50,000- 300,000 new cases of interstitial and chronic obstructive lung diseases respectively. It is widely recognized that right ventricular (RV) dysfunction plays a pivotal role in heart failure in patients with pulmonary arterial hypertension (PAH), interstitial lung diseases and chronic obstructive pulmonary disease (COPD). Right heart failure is the leading cause of mortality in PAH and significantly contributes to mortality in interstitial and obstructive lung diseases. Employing a well-established mouse model of pulmonary hypertension induced by exposure to chronic hypoxia, we will identify strain specific differences in right ventricular dysfunction. The primary objective of this application is identify specific regions of the mouse genome containing genes contributing to increased susceptibility to chronic hypoxia-induced right ventricular hypertrophy and/or increased right ventricular systolic pressure. A better understanding of the genetics of right heart dysfunction in these diseases will likely enable new therapies to prevent and/or to treat right heart failure, resulting in reduced morbidity and mortality.
