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

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.

Molecular Phenotypes of Acute Kidney Injury in Kidney Transplants

“…33 The IRRATs show considerable similarity to the transcripts induced in late kidneys with diseases that predict progression to renal failure in such kidneys and that can be used to define a risk score (e.g., ITGB6, VCAN, NNMT). 34 Thus, 11 of the top 30 IRRATs were previously reported by us as frequently used by the molecular risk score classifier for predicting a graft loss in late kidney transplant biopsies. 34 Although the significance of this observation is the subject of a separate study, it seems likely that the IRRATs are an important signal in a variety of renal diseases other than AKI, but their significance will reflect whether that disease is treatable or self-limited or untreatable and relentlessly progressive.…”

Renal Allograft Fibrosis: Biology and Therapeutic Targets

“…Additional analyses might further improve the predictive value of allograft biopsies such as the immunohistochemical detection of CD44 and vimentin (366), activation markers of parietal epithelial cells as markers of FSGS in the renal transplant (367), or immunohistochemistry aided analyses of peritubular capillaries to detect their early and progressive rarefaction in allografts (368). Renal biopsy tissue can also be used for unbiased approaches such as microarray analyses, which may yield diagnostic molecular signatures (213,(369)(370)(371)(372)(373)(374). This ''molecular microscope'' has been shown to improve the diagnosis of rejection but also to reflect molecular alterations in fibrosis (375)(376)(377)(378).…”

Comparing Molecular Assessment of Implantation Biopsies With Histologic and Demographic Risk Assessment

“…Microarray data files (GSE37838) for 70 implantation biopsies and 8 nephrectomies were preprocessed using Robust Multiarray Analysis in Bioconductor (36). The molecular characteristics of implant biopsies used previously identified pathogenesis-based transcript sets (PBT) that reflect biological processes of known relevance for the pathogenesis of renal inflammation and injury in transplants.…”