Transcriptional Changes of Left Ventricle Biopsy During Reperfusion Predict the Outcome of Heart Transplants

Abstract

<h3>Purpose</h3> Ischemia-reperfusion injury may predispose heart transplant to acute rejection and early mortality. Contemporary treatment possibilities are limited. We hypothesize that investigating transcriptomic changes and the underlying biological processes of ischemia-reperfusion injury could yield information on the outcome of the recipient as well as on possible therapeutic targets. <h3>Methods</h3> RNA was extracted and sequenced from 144 left ventricle biopsies that were procured immediately before and 1 hour after reperfusion of the heart transplant. Primary endpoints of the study were acute rejection and graft-related mortality within 1 year after transplantation. <h3>Results</h3> Next-generation sequencing confirmed that a total of 802 genes had significantly changed their expression 1 hour after reperfusion, of which 590 were upregulated and 212 were downregulated. Alteration of certain differentially expressed gene profiles, such as downregulation of C5AR1, GAA, and MEN1 led to a higher probability of graft-related mortality within 1 year, whereas downregulation of FOSB and FOSL1 were associated with a higher risk of acute rejection. Downregulation of MMP19 were shown to predict both mortality as well as acute rejection (Figure 1). Gene ontology pathway analysis showed that these genes are involved in several biological processes, including neutrophil mediated immunity, regulation of protein serine/threonine kinase activity, and response to corticosteroids. <h3>Conclusion</h3> Our study describes the changes in gene expression of the left ventricle biopsies and their related biological processes associated with ischemia-reperfusion injury after heart transplantation. We have confirmed that alterations in certain gene profiles may predict acute rejection and graft-related mortality within 1 year after transplantation. Understanding the biological pathways associated with these gene profiles could be beneficial for identification of possible therapeutic targets.