TY - JOUR
T1 - Prediction of Liver Transplant Rejection with a Biologically Relevant Gene Expression Signature
AU - Levitsky, Josh
AU - Kandpal, Manoj
AU - Guo, Kexin
AU - Zhao, Lihui
AU - Kurian, Sunil
AU - Whisenant, Thomas
AU - Abecassis, Michael Messod
N1 - Funding Information:
J.L. and S.K. provided consultancy to Transplant Genomics Incorporated (Eurofins/Viracor). M.A. is a cofounder of Transplant Genomics Incorporated (Eurofins/Viracor). J.L. received research funding from Novartis. The other authors declare no conflicts of interest.
Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/5/1
Y1 - 2022/5/1
N2 - Background. Noninvasive biomarkers distinguishing early immune activation before acute rejection (AR) could more objectively inform immunosuppression management in liver transplant recipients (LTRs). We previously reported a genomic profile distinguishing LTR with AR versus stable graft function. This current study includes key phenotypes with other causes of graft dysfunction and uses a novel random forest approach to augment the specificity of predicting and diagnosing AR. Methods. Gene expression results in LTRs with AR versus non-AR (combination of other causes of graft dysfunction and normal function) were analyzed from single and multicenter cohorts. A 70:30 approach (61 ARs; 162 non-ARs) was used for training and testing sets. Microarray data were normalized using a LT-specific vector. Results. Random forest modeling on the training set generated a 59-probe classifier distinguishing AR versus non-AR (area under the curve 0.83; accuracy 0.78, sensitivity 0.70, specificity 0.81, positive predictive value 0.54, negative predictive value [NPV] 0.89; F-score 0.61). Using a locked threshold, the classifier performed well on the testing set (accuracy 0.72, sensitivity 0.67, specificity 0.73, positive predictive value 0.48, NPV 0.86; F-score 0.56). Probability scores increased in samples preceding AR versus non-AR, when liver function tests were normal, and decreased following AR treatment (P < 0.001). Ingenuity pathway analysis of the genes revealed a high percentage related to immune responses and liver injury. Conclusions. We have developed a blood-based biologically relevant biomarker that can be detected before AR-associated graft injury distinct from LTR never developing AR. Given its high NPV ("rule out AR"), the biomarker has the potential to inform precision-guided immunosuppression minimization in LTRs.
AB - Background. Noninvasive biomarkers distinguishing early immune activation before acute rejection (AR) could more objectively inform immunosuppression management in liver transplant recipients (LTRs). We previously reported a genomic profile distinguishing LTR with AR versus stable graft function. This current study includes key phenotypes with other causes of graft dysfunction and uses a novel random forest approach to augment the specificity of predicting and diagnosing AR. Methods. Gene expression results in LTRs with AR versus non-AR (combination of other causes of graft dysfunction and normal function) were analyzed from single and multicenter cohorts. A 70:30 approach (61 ARs; 162 non-ARs) was used for training and testing sets. Microarray data were normalized using a LT-specific vector. Results. Random forest modeling on the training set generated a 59-probe classifier distinguishing AR versus non-AR (area under the curve 0.83; accuracy 0.78, sensitivity 0.70, specificity 0.81, positive predictive value 0.54, negative predictive value [NPV] 0.89; F-score 0.61). Using a locked threshold, the classifier performed well on the testing set (accuracy 0.72, sensitivity 0.67, specificity 0.73, positive predictive value 0.48, NPV 0.86; F-score 0.56). Probability scores increased in samples preceding AR versus non-AR, when liver function tests were normal, and decreased following AR treatment (P < 0.001). Ingenuity pathway analysis of the genes revealed a high percentage related to immune responses and liver injury. Conclusions. We have developed a blood-based biologically relevant biomarker that can be detected before AR-associated graft injury distinct from LTR never developing AR. Given its high NPV ("rule out AR"), the biomarker has the potential to inform precision-guided immunosuppression minimization in LTRs.
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U2 - 10.1097/TP.0000000000003895
DO - 10.1097/TP.0000000000003895
M3 - Article
C2 - 34342962
AN - SCOPUS:85129778292
SN - 0041-1337
VL - 106
SP - 1004
EP - 1011
JO - Transplantation
JF - Transplantation
IS - 5
ER -