We prospectively studied kidney transplants that progressed to failure after a biopsy for clinical indications, aiming to assign a cause to every failure. We followed 315 allograft recipients who underwent indication biopsies at 6 days to 32 years posttransplant. Sixty kidneys progressed to failure in the followup period (median 31.4 months). Failure was rare after T-cell-mediated rejection and acute kidney injury and common after antibody-mediated rejection or glomerulonephritis. We developed rules for using biopsy diagnoses, HLA antibody and clinical data to explain each failure. Excluding four with missing information, 56 failures were attributed to four causes: rejection 36 (64%), glomerulonephritis 10 (18%), polyoma virus nephropathy 4 (7%) and intercurrent events 6 (11%). Every rejection loss had evidence of antibodymediated rejection by the time of failure. Among rejection losses, 17 of 36 (47%) had been independently identified as nonadherent by attending clinicians. Nonadherence was more frequent in patients who progressed to failure (32%) versus those who survived (3%). Pure T-cell-mediated rejection, acute kidney injury, drug toxicity and unexplained progressive fibrosis were not causes of loss. This prospective cohort indicates that many actual failures after indication biopsies manifest phenotypic features of antibody-mediated or mixed rejection and also underscores the major role of nonadherence.

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 donorspecific 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.

Histologic diagnosis of T cell-mediated rejection is flawed by subjective assessments, nonspecific lesions and arbitrary rules. This study developed a molecular test for T cell-mediated rejection. We used microarray results from 403 kidney transplant biopsies to derive a classifier assigning T cell-mediated rejection scores to all biopsies, and compared these with histologic assessments. The score correlated with histologic lesions of T cell-mediated rejection (infiltrate, tubulitis). The accuracy of the classifier for the histology diagnoses was 89%. Very high and low molecular scores corresponded with unanimity among three pathologists on the presence or absence of T cell-mediated rejection, respectively. The molecular score had low sensitivity (50%) and positive predictive value (62%) for the histology diagnoses. However, histology showed similar disagreement between pathologists-only 45-56% sensitivity of one pathologist with diagnoses of T cell-mediated rejection by another. Discrepancies between molecular scores and histology were mostly when histology was ambiguous ("borderline") or unreliable, e.g. in cases with scarring or inflammation induced by tissue injury. Vasculitis (isolated v-lesion TCMR) was particularly discrepant, with most cases exhibiting low TCMR scores. We propose new rules to integrate molecular tests and histology into a precision diagnostic system that can reduce errors, ambiguity and interpathologist disagreement.

Calreticulin is a multifunctional protein that acts as a major Ca(2+)-binding (storage) protein in the lumen of the endoplasmic reticulum. It is also found in the nucleus, suggesting that it may have a role in transcription regulation. Calreticulin has been reported to bind to the synthetic peptide KLGFFKR, which is almost identical to an amino-acid sequence in the DNA-binding domain of the superfamily of nuclear receptors. Could calreticulin interact with the DNA-binding domain of these receptors and affect their function? Here we report that the amino terminus of calreticulin interacts with the DNA-binding domain of the glucocorticoid receptor and prevents the receptor from binding to its specific glucocorticoid response element. Overexpression of calreticulin in mouse L fibroblasts inhibits glucocorticoid-response-mediated transcriptional activation of a glucocorticoid-sensitive reporter gene and of the endogenous, glucocorticoid-sensitive gene encoding cytochrome P450. Together these results indicate that calreticulin may be important in gene transcription, regulating the glucocorticoid receptor and perhaps other members of the super-family of nuclear receptors.

Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS).

The prevalent renal transplant population presents an opportunity to observe the adaptive changes in the alloimmune response over time, but such studies have been limited by uncertainties in the conventional biopsy diagnosis of T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR). To circumvent these limitations, we used microarrays and conventional methods to investigate rejection in 703 unselected biopsies taken 3 days to 35 years post-transplant from North American and European centers. Using conventional methods, we diagnosed rejection in 205 biopsy specimens (28%): 67 pure TCMR, 110 pure ABMR, and 28 mixed (89 designated borderline). Using microarrays, we diagnosed rejection in 228 biopsy specimens (32%): 76 pure TCMR, 124 pure ABMR, and 28 mixed (no borderline). Molecular assessment confirmed most conventional diagnoses (agreement was 90% for TCMR and 83% for ABMR) but revealed some errors, particularly in mixed rejection, and improved prediction of failure. ABMR was strongly associated with increased graft loss, but TCMR was not. ABMR became common in biopsy specimens obtained .1 year post-transplant and continued to appear in all subsequent intervals. TCMR was common early but progressively disappeared over time. In 108 biopsy specimens obtained 10.2-35 years post-transplant, TCMR defined by molecular and conventional features was never observed. We conclude that the main cause of kidney transplant failure is ABMR, which can present even decades after transplantation. In contrast, TCMR disappears by 10 years post-transplant, implying that a state of partial adaptive tolerance emerges over time in the kidney transplant population.

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.

Little is known regarding the molecular phenotype of kidneys with AKI because biopsies are performed infrequently. However, all kidney transplants experience acute injury, making early kidney transplants an excellent model of acute injury, provided the absence of rejection, because donor kidneys should not have CKD, post-transplant biopsies occur relatively frequently, and follow-up is excellent typically. Here, we used histopathology and microarrays to compare indication biopsies from 26 transplants with acute injury with 11 pristine protocol biopsies of stable transplants. Kidneys with acute injury showed increased expression of 394 transcripts associated with the repair response to injury, including many epithelium-like injury molecules tissue, remodeling molecules, and inflammation molecules. Many other genes also predicted the phenotype, including the acute injury biomarkers HAVCR1 and IL18. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score in kidneys with acute injury correlated with reduced graft function, future renal recovery, brain death, and need for dialysis, but not with future graft loss. In contrast, histologic features of acute tubular injury did not correlate with function or with the molecular changes. Thus, the transcripts associated with repair of injury suggest a massive coordinated response of the kidney parenchyma to acute injury, providing both an objective measure for assessing the severity of injury in kidney biopsies and validation for many biomarkers of AKI.