Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

UNLABELLED: The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities. METHODS: We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m(2), whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m(2). RESULTS: Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P<0.01, false discovery rate <0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and P value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function after transplantation. CONCLUSIONS: Inclusion of pretransplantation molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pretransplantation time.

Pretransplant transcriptome profiles identify among kidneys with delayed graft function those with poorer quality and outcome.

Robust biomarkers are needed to identify donor kidneys with poor quality associated with inferior early and longer-term outcome. The occurrence of delayed graft function (DGF) is most often used as a clinical outcome marker to capture poor kidney quality. Gene expression profiles of 92 preimplantation biopsies were evaluated in relation to DGF and estimated glomerular filtration rate (eGFR) to identify preoperative gene transcript changes associated with short-term function. Patients were stratified into those who required dialysis during the first week (DGF group) versus those without (noDGF group) and subclassified according to 1-month eGFR of >45 mL/min (eGFR(hi)) versus eGFR of ≤45 mL/min (eGFR(lo)). The groups and subgroups were compared in relation to clinical donor and recipient variables and transcriptome-associated biological pathways. A validation set was used to confirm target genes. Donor and recipient characteristics were similar between the DGF versus noDGF groups. A total of 206 probe sets were significant between groups (P < 0.01), but the gene functional analyses failed to identify any significantly affected pathways. However, the subclassification of the DGF and noDGF groups identified 283 probe sets to be significant among groups and associated with biological pathways. Kidneys that developed postoperative DGF and sustained an impaired 1-month function (DGF(lo) group) showed a transcriptome profile of significant immune activation already preimplant. In addition, these kidneys maintained a poorer transplant function throughout the first-year posttransplant. In conclusion, DGF is a poor marker for organ quality and transplant outcome. In contrast, preimplant gene expression profiles identify "poor quality" grafts and may eventually improve organ allocation.