Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene expression profiles of human liver biopsies correlate with post-transplant allograft function and are determined by donor type.

ABSTRACT: Ischemia-reperfusion injury during liver transplantation is responsible for early allograft dysfunction (EAD) and failure, both of which are associated with a high risk of morbidity and mortality in the recipient. The purpose of this study was to study major transcriptional alterations in livers procured from different types of human liver donors in order to identify genetic profiles predictive of post-implantation function. We have analyzed samples form living donors (LD), donors after cardiac death (DCD), donors after brain death, with subsequent post-implantation EAD in the recipient (DBD-EAD); and donors after brain death without EAD (DBD). Two samples were obtained from each donor: sample A was taken immediately before cold perfusion (baseline) and sample B 2h after portal reperfusion. We identified clear differences in gene expression patterns according to donor source. Both samples A and B from DBD-EAD and DCD demonstrated over-expression of pro-apoptotic and inflammatory transcripts. However, in DBD and LD, expression of these genes was low at baseline and rose only after reperfusion. DBD and LD demonstrated the greatest increase in overall genetic expression after reperfusion when sample B was contrasted with A, indicating less baseline graft injury in these two groups. Grafts from LD were characterized by activation of transcripts related to anti-ischemic and regenerative processes and fewer pro-inflammatory gene transcripts. This transcriptional events occurring in liver allografts could allow for the prediction of post-transplant function. Pro-inflammatory and ischemic transcriptional changes in the grafts are directly related to donor type and may be useful targets for the development of future therapeutic strategies. The complete database comprised the expression for samples taken from 33 liver grafts. Sample A was taken immediately before cold perfusion (baseline) and sample B 2 h after portal reperfusion. Donors were from one of four groups: living (LD); after cardiac death (DCD); after brain death, with subsequent post-implantation EAD in the recipient (DBD-EAD); and after brain death without EAD (DBD). RNA was extracted from the 66 samples and analyzed using Illumina Beadarray technology. A group of 3 samples from healthy volunteers and 3 samples form LD taken at the start of surgery are included as controls or reference samples. This dataset is part of the TransQST collection.

ORGANISM(S): Homo sapiens

SUBMITTER: Juanjo Lozano

PROVIDER: E-GEOD-23649 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Because of world-wide shortage of renal grafts, kidney transplantation (KTx) from donors after cardiac death (DCD) is an alternative way to KTx from brain-dead donors. Although the prognosis of DCD KTx is gradually improving, the graft often undergoes delayed graft function (DGF) rendering the control of DGF essential for post-KTx patient care. To know the etiology of the DGF, we performed genome-wide gene expression profiling using renal biopsy samples performed at 1 hour after KTx from DCD and compared the data with those of KTx from living donors (LD). A total of 526 genes were differentially expressed between them. Genes involved in acute inflammation were activated, while metabolic pathways were consistently down-regulated in DCD. All of these findings imply inferior performance of the DCD grafts relative to LD grafts. We identified several genes of which expression levels were correlated well with parameters indicating short- and long-term prognosis of the DCD patients. In addition, we identified several genes encoding secretory proteins that might reflect the performance of the graft and be potent non-invasive biomarkers. Our data provide good source for candidates of biomarker that are potentially useful for control of DGF. Experiment Overall Design: This investigation was approved by the Institutional Review Boards of our centers. Written informed consent was obtained from each patient or legal guardian before enrollment. Consecutive patients undergoing either a living (n =15) or DCD KTx (n = 14) at this center were prospectively enrolled. The immunosuppressive regimen was similar in all patients, consisting of basiliximab, tacrolimus or cyclosporine with prednisone and mycophenolate mofetil. All kidney grafts were procured at this canter using in situ regional cooling technique from DCD. All donors after cardiac death from this hospital were classified as type IV in this study. The cause of donor death was cerebrovascular disease in all cases. Although most of those cases required HD (0-22 days) after KTx because of DGF, the function of all of transplanted kidneys eventually recovered. All kidney grafts from LD were procured by open nephrectomy in this study. All graft biopsies were performed one hour after reperfusion during kidney transplant operation using biopsy needles. All biopsy samples were stored immediately in RNA later (Applied Biosytems). Total cellular RNA was extracted from frozen samples using RNeasy (Qiagen, Valencia, CA, USA). For DNA microarray experiments, 200 ng aliquots of total RNA were labeled using the Agilent Low RNA Input Fluorescent Linear Amplification Kit (Agilent Technologies, CA) according to the manufacturerâs instructions. RNA purified from each kidney graft was used for microarray analysis (Cy5-labeled), with pooled RNA derived from normal kidneys (Homan Kidney Total RNA #636529 BD, Franklin Lakes, NJ, USA) as a template control (Cy3-labeled). After checking the labeling efficiency, 1 ïg aliquots of Cy3-labeled normal control RNA and Cy5-labeled RNA from individual grafts were mixed, and then hybridized to Agilent Human 1A (Ver. 2) Microarrays (Product No.G4110B) according to the manufacturerâs hybridization protocol. After washing, the microarray slides were analyzed with an Agilent Microarray scanner and software (scanner model G2565BA). Data analysis was performed using Agilent Feature Extraction software (Ver. A.7.1.1), and Excel 2007 (Microsoft).

Dataset Information

Gene expression profiles of human liver biopsies correlate with post-transplant allograft function and are determined by donor type.

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