Proteomic Signatures Associated with Right Ventricular Failure and Mortality in Pulmonary Arterial Hypertension

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PROJECT SUMMARY/ABSTRACT Pulmonary arterial hypertension (PAH) is a rare but life-threatening disease characterized by vascular remodeling and progressive elevation in pulmonary vascular resistance. These events result in right heart failure, significant morbidity, and a high mortality. The timing of right ventricular (RV) dilation and dysfunction varies from patient to patient, even among individuals with otherwise similar RV afterload; however, the biological basis for this heterogeneity in RV adaptation is not yet known. Identifying and understanding molecular mechanisms of RV maladaptation are important steps for discovering novel right heart targeted therapy. Dr. Pi recently explored plasma metabolomic signatures in a deeply phenotyped cohort of PAH participants using a systems biology approach and found distinct metabolic pathways and profiles associated with metrics of right heart failure and mortality. In particular, polyamine and histidine metabolism were consistently associated with these outcomes. It is important to appreciate that while right heart adaptation is related to right heart failure, it is a distinct condition. Specifically, right heart failure may merely represent the severity of pulmonary hypertension, while right heart adaptation reflects the ability or inability of the right heart to respond to any severity of pulmonary vascular disease. When the metabolomics analyses of right heart failure were adjusted to account for differences in pulmonary vascular resistance, an association between sphingomyelin metabolism and RV adaptation emerged in individuals with otherwise similar right heart afterload. Using the same prospective observational PAH cohort from University of Washington, in this proposal Dr. Pi aims to extend her metabolomics work by (i) identifying proteomic profiles associated with RV maladaptation and mortality in PAH; (ii) integrating the multi-omic (metabolomic and proteomic) signals to find dysregulated pathways and features associated with poor outcomes. Importantly, the scientific aims directly support an ongoing and rigorous training program in systems biology and bioinformatics that will specifically enhance the proteomic analysis and integrative omics approaches. Successful completion of this project will generate novel data and methods that will provide a solid foundation for a K23 proposal focused on RV adaptation and ultimately an independently funded career leveraging “big data” to understand complex cardiopulmonary disease.