Introduction and Aims: Delayed graft function (DGF) is the most common complication affecting kidney allografts in the immediate post-transplant period. Defined as the necessity for dialysis in the first week after surgery, DGF occurs in 20% to 50% of patients receiving a first cadaver graft. DGF is usually the result of ischemic damage to the graft before or during harvesting, and it is further aggravated by the reperfusion syndrome, a multifactorial event in which polymorphonuclear (PMN) cells play a major role. This condition is often associated with an increased risk of premature graft failure and residual graft dysfunction. Factors related to the donor and prerenal, renal, or postrenal transplant factors related to the recipient can contribute to this condition. However, at the state of art, the systemic biological machinery associated to this condition is still not completely known. Methods: Therefore, aims of our study have been to identify, by combining an innovative high-throughput technology (HG-U133A, microarray, Affymetrix) with classical bio-molecular approaches, specific DGF transcriptomic fingerprints (DGF biomarkers). To this purpose, we compared the genomic profile (around 15,000 genes) of 7 patients with DGF with that of 7 patients with early graft function (EGF). This comparison was performed using PMN isolated by whole blood at the time of transplantation (T0) and after one day (T1) post-transplantation. Subsequently, we applied several statistical algorithms and functional analysis by Gene-Set Enrichment Analysis (GSEA), to identify biological processes able to discriminate DGF versus EGF at both T0 and T1. Results: Bioinformatics showed that two pathways: a) NLS BEARING SUBSTRATE IMPORT INTO NUCLEUS (19 annotated genes) and b) PROTEIN IMPORT INTO THE NUCLEUS (32 annotated genes) were significantly up-regulated, at both T0 and T1, in DGF compared to EGF (p<0.009/FDR<30 and p<0.004/FDR<35, respectively). RT-PCR performed on an independent cohort of patients (n:25 with DGF and n:25 with EGF) confirmed microarray results. Both the identified pathways are primary involved in the transport of substrates from cytoplasm to nucleus. Conclusions: Our approach may help researchers to improve the overall biological knowledge of DGF; moreover, it may introduce new potential biomarkers useful to early identify risk patients for DGF and to select new research topics and potential targets for future therapeutic approaches.
IDENTIFICATION OF MOLECULAR BIOMARKERS FOR EARLY DIAGNOSIS OF DELAYED GRAFT FUNCTION IN RENAL TRANSPLANT RECIPIENTS
Zaza, Gianluigi;Granata, Simona;LUPO, Antonio
2012-01-01
Abstract
Introduction and Aims: Delayed graft function (DGF) is the most common complication affecting kidney allografts in the immediate post-transplant period. Defined as the necessity for dialysis in the first week after surgery, DGF occurs in 20% to 50% of patients receiving a first cadaver graft. DGF is usually the result of ischemic damage to the graft before or during harvesting, and it is further aggravated by the reperfusion syndrome, a multifactorial event in which polymorphonuclear (PMN) cells play a major role. This condition is often associated with an increased risk of premature graft failure and residual graft dysfunction. Factors related to the donor and prerenal, renal, or postrenal transplant factors related to the recipient can contribute to this condition. However, at the state of art, the systemic biological machinery associated to this condition is still not completely known. Methods: Therefore, aims of our study have been to identify, by combining an innovative high-throughput technology (HG-U133A, microarray, Affymetrix) with classical bio-molecular approaches, specific DGF transcriptomic fingerprints (DGF biomarkers). To this purpose, we compared the genomic profile (around 15,000 genes) of 7 patients with DGF with that of 7 patients with early graft function (EGF). This comparison was performed using PMN isolated by whole blood at the time of transplantation (T0) and after one day (T1) post-transplantation. Subsequently, we applied several statistical algorithms and functional analysis by Gene-Set Enrichment Analysis (GSEA), to identify biological processes able to discriminate DGF versus EGF at both T0 and T1. Results: Bioinformatics showed that two pathways: a) NLS BEARING SUBSTRATE IMPORT INTO NUCLEUS (19 annotated genes) and b) PROTEIN IMPORT INTO THE NUCLEUS (32 annotated genes) were significantly up-regulated, at both T0 and T1, in DGF compared to EGF (p<0.009/FDR<30 and p<0.004/FDR<35, respectively). RT-PCR performed on an independent cohort of patients (n:25 with DGF and n:25 with EGF) confirmed microarray results. Both the identified pathways are primary involved in the transport of substrates from cytoplasm to nucleus. Conclusions: Our approach may help researchers to improve the overall biological knowledge of DGF; moreover, it may introduce new potential biomarkers useful to early identify risk patients for DGF and to select new research topics and potential targets for future therapeutic approaches.
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