Abstract
Background
Ischemia-reperfusion injury (IRI) is an inevitable consequence of liver transplantation, arising during donor organ procurement and reoxygenation. Severe IRI is a leading contributor to early allograft dysfunction (EAD), a post-transplant complication associated with reduced graft survival. Current postoperative biomarkers provide limited time for intervention, highlighting a need to identify preoperative biomarkers of IRI. Meanwhile, tRNA fragments (tRFs) have emerged as novel biomarkers in various diseases, but remain unexplored in the context of liver transplant.
Results
We performed small RNA sequencing on donor liver biopsies to investigate IRI-associated transcript changes. In parallel, donor liver perfusates were analyzed as a non-invasive surrogate for tissue profiling. Across samples, microRNAs (miRNAs) and tRFs were the most abundant small RNAs. Perfusate expression strongly correlated with paired biopsies, supporting its value as a non-invasive source. Comparison of post-reperfusion versus pre-implantation biopsies revealed that IRI reprogrammed tRF expression. Stratification by clinical outcome showed that patients who developed EAD exhibited specific tRNA fragments signature in both biopsy and perfusate. Receiver operating characteristic (ROC) analysis demonstrated that a tRF-based model achieved an AUC of 0.7748, outperforming the donor risk index alone (AUC = 0.6804), representing a 9.4% increase in discriminative capacity.
Conclusions
These results are the first to establish tRFs as IRI-responsive biomolecules abundant in both donor liver tissue and perfusate, a non-invasive biofluid. In particular, various tRF species emerged as promising candidate biomarkers for early detection of EAD. These results lay the foundation to further investigate the diagnostic and prognostic utility of tRF species in clinical liver transplantation.
Full Text Availability
The license terms selected by the author(s) for this preprint version do not permit archiving in PMC. The full text is available from the preprint server.
