BACKGROUND: Clinical- and histopathology-based scores are limited predictors of allograft outcome. In addition, more objective markers of early transplant function are needed to identify and validate biomarkers and predictive scores. We evaluated existing scores and transcriptome biomarkers of kidney injury as predictors of early transplant function measured by renal scan. METHODS: Clinical, histopathologic and transcriptome data were collected in 143 consecutive kidney transplant recipients. A post-operative renal scan was performed within 48 h. Prediction scores for early outcomes were calculated. RESULTS: Patients were stratified into three groups by renal scan: normal, mild-to-moderate or severe dysfunction. Kidneys with severe dysfunction were more often from deceased donors (P < 0.001), had greater HLA antigen mismatches (P < 0.001), were transplanted into older recipients (P = 0.040), had lower urine output during the first 8 h (P < 0.001), higher Day 7 serum creatinine (P < 0.001) and higher incidence of delayed graft function (P < 0.001). Clinical- and pathology-based scores did not discriminate between scan groups. In contrast, the overall transcriptome (P < 0.001) and transcripts of preselected acute kidney injury (AKI) genes were significantly different between the groups, with kidney injury molecule 1 (P = 0.001) and neutrophil gelatinase-associated lipocalin (P = 0.002) being most highly expressed and genes associated with glutathione metabolism (GSTA1, 3 and 4) most down-regulated in kidneys with subsequent severe dysfunction. CONCLUSIONS: Renal scans reflect early transplant function and allow for a more objective assessment of scores predicting early outcome and for identification of biomarkers. The study shows that transcript levels of AKI genes correlate better with renal scans than clinical- or histopathology-based scores.
BACKGROUND: Clinical- and histopathology-based scores are limited predictors of allograft outcome. In addition, more objective markers of early transplant function are needed to identify and validate biomarkers and predictive scores. We evaluated existing scores and transcriptome biomarkers of kidney injury as predictors of early transplant function measured by renal scan. METHODS: Clinical, histopathologic and transcriptome data were collected in 143 consecutive kidney transplant recipients. A post-operative renal scan was performed within 48 h. Prediction scores for early outcomes were calculated. RESULTS:Patients were stratified into three groups by renal scan: normal, mild-to-moderate or severe dysfunction. Kidneys with severe dysfunction were more often from deceased donors (P < 0.001), had greater HLA antigen mismatches (P < 0.001), were transplanted into older recipients (P = 0.040), had lower urine output during the first 8 h (P < 0.001), higher Day 7 serum creatinine (P < 0.001) and higher incidence of delayed graft function (P < 0.001). Clinical- and pathology-based scores did not discriminate between scan groups. In contrast, the overall transcriptome (P < 0.001) and transcripts of preselected acute kidney injury (AKI) genes were significantly different between the groups, with kidney injury molecule 1 (P = 0.001) and neutrophil gelatinase-associated lipocalin (P = 0.002) being most highly expressed and genes associated with glutathione metabolism (GSTA1, 3 and 4) most down-regulated in kidneys with subsequent severe dysfunction. CONCLUSIONS: Renal scans reflect early transplant function and allow for a more objective assessment of scores predicting early outcome and for identification of biomarkers. The study shows that transcript levels of AKI genes correlate better with renal scans than clinical- or histopathology-based scores.
Authors: Stan Benjamens; Robert A Pol; Stefan P Berger; Andor W J M Glaudemans; Petra Dibbets-Schneider; Riemer H J A Slart; Lioe-Fee de Geus-Oei Journal: Eur Radiol Date: 2019-07-23 Impact factor: 5.315