Molecular diagnosis of antibody-mediated rejection in human kidney transplants.

Antibody-mediated rejection is the major cause of kidney transplant failure, but the histology-based diagnostic system misses most cases due to its requirement for C4d positivity. We hypothesized that gene expression data could be used to test biopsies for the presence of antibody-mediated rejection. To develop a molecular test, we prospectively assigned diagnoses, including C4d-negative antibody-mediated rejection, to 403 indication biopsies from 315 patients, based on histology (microcirculation lesions) and donor-specific HLA antibody. We then used microarray data to develop classifiers that assigned antibody-mediated rejection scores to each biopsy. The transcripts distinguishing antibody-mediated rejection from other conditions were mostly expressed in endothelial cells or NK cells, or were IFNG-inducible. The scores correlated with the presence of microcirculation lesions and donor-specific antibody. Of 45 biopsies with scores>0.5, 39 had been diagnosed as antibody-mediated rejection on the basis of histology and donor-specific antibody. High scores were also associated with unanimity among pathologists that antibody-mediated rejection was present. The molecular score also strongly predicted future graft loss in Cox regression analysis. We conclude that microarray assessment of gene expression can assign a probability of ABMR to transplant biopsies without knowledge of HLA antibody status, histology, or C4d staining, and predicts future failure.

Comparing molecular assessment of implantation biopsies with histologic and demographic risk assessment.

We hypothesized that measurement of previously defined acute kidney injury-induced transcripts at the time of implantation would add a new dimension to existing methods based on donor factors, histology and recipient factors. We analyzed microarray results from implantation biopsies taken after reperfusion from 70 kidneys from 53 deceased donors. We used two definitions of early dysfunction: serum creatinine > 265 umol/L at day 7 posttransplant; and dialysis in the first week. The strongest correlate with early dysfunction was the mean expression of 30 injury transcripts. Older donor and recipient age were associated with early dysfunction, but histologic lesions were not. Prediction was best when the injury transcript expression was combined with donor or recipient age, particularly in standard criteria donors. In contrast, although extended criteria donor kidneys had a high risk of early dysfunction, no variables tested, including injury transcripts, predicted risk significantly, probably because these kidneys were allocated preferentially to old, high risk recipients. The injury transcripts did not predict late function, which was mainly associated with donor age. Thus, measurement of injury-induced transcripts at the time of implantation improves the prediction of early kidney dysfunction, but risk prediction may fail when old kidneys are transplanted into old recipients.