Identification of biomarkers to assess organ quality and predict posttransplantation outcomes

Transplantation. 2012 Oct 27;94(8):851-8. doi: 10.1097/TP.0b013e318263702b.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Biomarkers
  • Glomerular Filtration Rate
  • Humans
  • Kidney Transplantation*
  • Oligonucleotide Array Sequence Analysis
  • Proportional Hazards Models
  • Signal Transduction
  • Tissue Donors*
  • Transcriptome*
  • Transplantation, Homologous

Substances

  • Biomarkers