Journal
TRANSPLANTATION
Volume 101, Issue 6, Pages 1400-1409Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/TP.0000000000001287
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Funding
- Spanish public grant [FIS PI13/01263]
- European Commission grant from the Biomarker-Driven Immunosuppression Minimization (BIODRIM) Consortium (Bio-Drim) [12CEE014]
- Spanish Red de Investigacion Renal (REDinREN) [RD12/0021]
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Background. Subclinical acute rejection (sc-AR) is a main cause for functional decline and kidney graft loss and may only be assessed through surveillance biopsies. Methods. The predictive capacity of 2 novel noninvasive blood biomarkers, the transcriptional kidney Solid Organ Response Test (kSORT), and the IFN-gamma enzyme-linked immunosorbent spot assay (ELISPOT) assay were assessed in the Evaluation of Sub-Clinical Acute rejection PrEdiction (ESCAPE) Study in 75 consecutive kidney transplants who received 6-month protocol biopsies. Both assays were run individually and in combination to optimize the use of these techniques to predict sc-AR risk. Results. Subclinical acute rejection was observed in 22 (29.3%) patients (17 T cell-mediated subclinical rejection [sc-TCMR], 5 antibody-mediated subclinical rejection [sc-ABMR]), whereas 53 (70.7%) showed a noninjured, preserved (stable [STA]) parenchyma. High-risk (HR), low-risk, and indeterminate-risk kSORT scores were observed in 15 (20%), 50 (66.7%), and 10 (13.3%) patients, respectively. The ELISPOT assay was positive in 31 (41%) and negative in 44 (58.7%) patients. The kSORT assay showed high accuracy predicting sc-AR (specificity, 98%; positive predictive value 93%) (all sc-ABMR and 58% sc-TCMR showed HR-kSORT), whereas the ELISPOT showed high precision ruling out sc-TCMR(specificity = 70%, negative predictive value = 92.5%), but could not predict sc-ABMR, unlike kSORT. The predictive probabilities for sc-AR, sc-TCMR, and sc-ABMR were significantly higher when combining both biomarkers (area under the curve > 0.85, P < 0.001) and independently predicted the risk of 6-month sc-AR in a multivariate regression analysis. Conclusions. Combining a molecular and immune cell functional assay may help to identify HR patients for sc-AR, distinguishing between different driving alloimmune effector mechanisms.
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