A molecular classifier for predicting future graft loss in late kidney transplant biopsies

Gunilla Einecke, Jeff Reeve, Banu Sis, Michael Mengel, Luis Hidalgo, Konrad S. Famulski, Arthur Matas, Bert Kasiske, Bruce Kaplan, Philip F. Halloran

Research output: Contribution to journalArticle

126 Scopus citations

Abstract

Kidney transplant recipients that develop signs of renal dysfunction or proteinuria one or more years after transplantation are at considerable risk for progression to renal failure. To assess the kidney at this time, a "for-cause" biopsy is performed, but this provides little indication as to which recipients will go on to organ failure. In an attempt to identify molecules that could provide this information, we used micorarrays to analyze gene expression in 105 for-cause biopsies taken between 1 and 31 years after transplantation. Using supervised principal components analysis, we derived a molecular classifier to predict graft loss. The genes associated with graft failure were related to tissue injury, epithelial dedifferentiation, matrix remodeling, and TGF-β effects and showed little overlap with rejection-associated genes. We assigned a prognostic molecular risk score to each patient, identifying those at high or low risk for graft loss. The molecular risk score was correlated with interstitial fibrosis, tubular atrophy, tubulitis, interstitial inflammation, proteinuria, and glomerular filtration rate. In multivariate analysis, molecular risk score, peritubular capillary basement membrane multilayering, arteriolar hyalinosis, and proteinuria were independent predictors of graft loss. In an independent validation set, the molecular risk score was the only predictor of graft loss. Thus, the molecular risk score reflects active injury and is superior to either scarring or function in predicting graft failure.

Original languageEnglish (US)
Pages (from-to)1862-1872
Number of pages11
JournalJournal of Clinical Investigation
Volume120
Issue number6
DOIs
StatePublished - Jun 1 2010

ASJC Scopus subject areas

  • Medicine(all)

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    Einecke, G., Reeve, J., Sis, B., Mengel, M., Hidalgo, L., Famulski, K. S., Matas, A., Kasiske, B., Kaplan, B., & Halloran, P. F. (2010). A molecular classifier for predicting future graft loss in late kidney transplant biopsies. Journal of Clinical Investigation, 120(6), 1862-1872. https://doi.org/10.1172/JCI41789