Abstract 19311: Identification of Novel Primary Graft Dysfunction Biomarkers Using Exosome Proteomics

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Background: Primary graft dysfunction (PGD) is defined as severe ventricular dysfunction within 24 hours of heart transplant without discernible etiology. PGD is the leading cause of mortality within the first 30 days after transplant yet the mechanism underlying PGD remains obscure. We hypothesize that there are circulating factors in the recipient prior to transplant that contribute to the development of PGD and that these can be used to identify patients at high risk for developing PGD prior to transplant.

Methods and Results: Sera from 8 patients with PGD and 8 without PGD were prospectively collected at Columbia University Medical Center prior to heat transplant under an approved IRB. Exosomes were purified from serum and analyzed by LC-MS/MS with Orbitrap Fusion Tribrid mass spectrometer. Unsupervised multidimensional scaling analysis of the total exosome proteome demonstrated significant separation of samples based on PGD status alone. Differential analysis identified a signature of 176 proteins at an FDR q<0.01. Pathway analysis showed enrichment of immune and acute phase response such as triggering of the complement system and antibody signal transduction. IL-6 was identified by Ingenuity Pathway Analysis (Qiagen) as a top upstream regulator of this signature. We observed a significant increase in IL-6 in patients who go on to develop PGD compared to those that do not in a separate patient cohort. Prediction of post-graft failure by logistic regression using a leave one out cross validation strategy yielded an AUROC of 1. The presence or absence of proteins were the most predictive features in our model, suggesting a role for exosome protein biomarkers in predicting graft failure after heart transplantation.

Conclusion: Pre-transplant serum exosome analysis showed significant overall protein expression differences with clearly delineated clustering by PGD status. Proteomic analysis revealed an inflammatory phenotype and complement activation in pre-transplant exosomes of patients who had PGD. Logistic regression analysis identified candidate exosome biomarkers whose absence or presence alone was predictive of PGD prior to transplant.

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