Sickle cell disease (SCD) affects approximately 100,000 patients in the United States, with approximately 250,000 new cases born each year world-wide. Despite advances in the care of SCD patients, the annual mortality still approaches 4% and the median age of death is in the 5th decade. An elevated tricuspid regurgitant jet velocity (TRV), suggestive of pulmonary hypertension (PH) occurs in up to 1/3 of adults with sickle cell anemia (HbSS) and carries with it a 6-10-fold increased mortality risk. One explanation for increased mortality is that an elevated TRV is reflective of a more diffuse systemic vasculopathy, the pathogenesis of which is multi-factorial. Current diagnosis is by right heart catheterization (RHC) as echocardiography is frequently inaccurate and may be falsely positive. At least 50% of SCD patients with PH have some degree of pulmonary venous hypertension (PVH), usually related to diastolic dysfunction, another independent risk factor for mortality. The remainder of patients has pulmonary arterial hypertension (PAH) similar pathologically to idiopathic PAH, often with milder hemodynamics. As PH of SCD is frequently asymptomatic early in the course of disease, developing a screening test to identify a higher risk population is essential and thus significant interest is focused in refining the TRV via the use of serum biomarkers. This is especially true for the pediatric SCD population where an elevated TRV occurs in up to 22% with unclear long-term prognostic implications. Clinical proteomics states that alterations in the abundance of plasma proteins reflect systemic changes associated with disease and may serve as biomarkers. Furthermore, nonspecific changes occurring within plasma proteins may act as global indicators of inflammation and altered redox biology in the systemic state. Alteration of redox biology is known to be an important disease modifier in SCD and leads to oxidative post- translational modifications (OPTMs). OPTMs lead to changes in protein function, rates of turnover and in modulation of interactions with other proteins, biopolymers and ligands. Our hypothesis is that the specificity of detecting markers related to PH of SCD will be greatly enhanced by a targeted proteomic approach to identify both specific protein and OPTM changes. The goals of this proposal are to 1) Utilize proteomics technology to identify a plasma protein and OPTM signature profile reflective of PH and pulmonary vasculopathy related to SCD. 2) Confirm and validate plasma protein and OPTM profiles associated with PH of SCD and determine expression of selected target proteins in a limited cohort of SCD patients with PAH and PVH. The overall goal of this proposal is to develop a clinical-proteomics signature profile that is associated with PAH and PVH in SCD in order to create models and identify cellular pathways and putative biomarkers to predict the risk in SCD patients and to identify future targets for further functional studies. We will use the data generated by this proposal to form the framework to test the hypothesis that PH in SCD is a heritable trait with the plan to create a network of clinical, genetic and proteomic factors that can be used to predict disease and risk.
SCD affects approximately 100,000 patients in the United States, with approximately 250,000 new cases born each year world-wide. Pulmonary hypertension is a major risk factor for mortality, which often occurs prior to the 5th decade. The goal of this proposal is to use a combination of clinical and proteomic data to create models and identify cellular pathways and putative biomarkers to predict the risk of pulmonary hypertension in SCD patients and to identify potential future targets for treatment.
|Ataga, Kenneth I; Klings, Elizabeth S (2014) Pulmonary hypertension in sickle cell disease: diagnosis and management. Hematology Am Soc Hematol Educ Program 2014:425-31|
|Spencer, Jean L; Bhatia, Vivek N; Whelan, Stephen A et al. (2013) STRAP PTM: Software Tool for Rapid Annotation and Differential Comparison of Protein Post-Translational Modifications. Curr Protoc Bioinformatics 44:13.22.1-36|