The impact of different pathophysiologic mechanisms on outcome is unknown. Graft dysfunction (GD) after heart transplantation (HTx) is a major cause of morbidity and mortality. This paper exemplifies that in patients presenting with unexplained graft dysfunction, GEP test score and QTc-interval correlate with the changes in the graft function. The molecular expression test score showed gradual increase and QTc-interval showed gradual prolongation with the gradual decline in graft function.
Patient presented with graft failure with negative findings on all known criteria of rejection including acute cellular rejection, antibody mediated rejection and cardiac allograft vasculopathy. In this paper we present for the first time, longitudinal pattern of changes in this novel diagnostic test score along with QTc-interval in a patient who was admitted with unexplained graft dysfunction. A noninvasive molecular expression diagnostic test was developed and validated to rule out histological acute cellular rejection. In the current era of immunosuppressive medications there is increased observed incidence of graft dysfunction in the absence of known histological criteria of rejection after heart transplantation. Larger prospectively designed studies are needed to corroborate our hypothesis. Our pilot data suggest that GEP of PBMC may become a valuable tool in the evaluation of patients at risk of CAV. Out of 8 transcripts available for RT-PCR analysis, we confirmed 6 transcripts (75.0%) including FPRL1, S100A9, CXCL10, PRO1073, and MMP9 (P <.
Over 300 genes were differentially expressed (FDR < 5%), and 18 GO-categories including "macrophage activation", "Interleukin-6 pathway", "NF-KappaB cascade", and "response to virus" were enriched by these genes (FDR < 5%). We corroborated our findings by retrospective analysis of PBMC real-time PCR data from 33 patients. We used significance analysis of microarrays to identify differentially expressed genes and High-Throughput GoMiner to assess gene ontology (GO) categories. We retrospectively analyzed a limited set of whole-genome PBMC microarrays from 10 post-transplant patients who did (n = 3) or did not (n = 7) develop advanced grade CAV during their long-term follow-up. We hypothesized that PBMC gene expression profiles (GEP) can identify patients at risk of CAV. Currently, no diagnostic methods are available during the early post-transplant period to accurately identify patients at risk of CAV. Cardiac allograft vasculopathy (CAV) is a major cause of graft loss and death after heart transplantation.
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