Abstract
Renal transplantation from hepatitis C (HCV) nucleic acid amplification test-positive (NAAT-positive) donors to uninfected recipients has greatly increased the organ donation pool. However, there is concern for adverse outcomes in these recipients due to dysregulated immunologic activation secondary to active inflammation from acute viremia at the time of transplantation. This includes increased rates of cytomegalovirus (CMV) DNAemia and allograft rejection. In this study, we evaluate transcriptional responses in circulating leukocytes to define the character, timing, and resolution of this immune dysregulation and assess for biomarkers of adverse outcomes in transplant patients. We enrolled 67 renal transplant recipients (30 controls, 37 HCV recipients) and performed RNA sequencing on serial samples from one, 3-, and 6-months post-transplant. CMV DNAemia and allograft rejection outcomes were measured. Least absolute shrinkage and selection operator was utilized to develop gene expression classifiers predictive of clinical outcomes. Acute HCV incited a marked transcriptomic response in circulating leukocytes of renal transplant recipients in the acute post-transplant setting, despite the presence of immunosuppression, with 109 genes significantly differentially expressed compared to controls. These HCV infection-associated genes were reflective of antiviral immune pathways and generally resolved by the 3-month timepoint after sustained viral response (SVR) for HCV. Differential gene expression was also noted from patients who developed CMV DNAemia or allograft rejection compared to those who did not, although transcriptomic classifiers could not accurately predict these outcomes, likely due to sample size and variable time-to-event. Acute HCV infection incites evidence of immune activation and canonical antiviral responses in the human host even in the presence of systemic immunosuppression. After treatment of HCV with antiviral therapy and subsequent aviremia, this immune activation resolves. Changes in gene expression patterns in circulating leukocytes are associated with some clinical outcomes, although larger studies are needed to develop accurate predictive classifiers of these events.