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We determined peripheral blood (PB) and biopsy (Bx) RNA expression signatures in a Brazilian and US cohort of kidney transplant patients. Phenotypes assigned by precise histology were: acute rejection (AR), interstitial fibrosis/tubular atrophy/chronic rejection (CR), excellent functioning transplants (TX), and glomerulonephritis recurrence (GN). Samples were analyzed on microarrays and profiles from each cohort were cross-validated on the other cohort with similar phenotypes. We discovered signatures for each tissue: (1) AR vs TX, (2) CR vs TX, and (3) GN vs TX using the Random Forests algorithm. We validated biopsies signatures of AR vs TX (area under the curve [AUC] 0.97) and CR vs TX (AUC 0.87). We also validated both PB and Bx signatures of AR vs TX and CR vs TX with varying degrees of accuracy. Several biological pathways were shared between AR and CR, suggesting similar rejection mechanisms in these 2 clinical phenotypes. Thus, we identified gene expression signatures for AR and CR in transplant patients and validated them in independent cohorts of significantly different racial/ethnic backgrounds. These results reveal that there are strong unifying immune mechanisms driving transplant diseases and identified in the signatures discovered in each cohort, suggesting that molecular diagnostics across populations are feasible despite ethnic and environmental differences., (© 2019 The American Society of Transplantation and the American Society of Transplant Surgeons.)

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm-driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA-seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation., (© 2017 The American Society of Transplantation and the American Society of Transplant Surgeons.)

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction., (© Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.)