TY - JOUR
T1 - Data-driven kidney transplant phenotyping as a histology- independent framework for biomarker discovery
AU - Buscher, Konrad
AU - Heitplatz, Barbara
AU - van Marck, Veerle
AU - Song, Jian
AU - Loismann, Sophie
AU - Rixen, Rebecca
AU - Huchtmann, Birte
AU - Kurian, Sunil
AU - Ehinger, Erik
AU - Wolf, Dennis
AU - Ley, Klaus
AU - Pavenstadt, Hermann
AU - Reuter, Stefan
N1 - Publisher Copyright:
© 2021 American Society of Nephrology. All rights reserved.
PY - 2021/8
Y1 - 2021/8
N2 - Background In transplant medicine, clinical decision making largely relies on histology of biopsy specimens. However, histology suffers from low specificity, sensitivity, and reproducibility, leading to suboptimal stratification of patients. We developed a histology-independent immune framework of kidney graft homeostasis and rejection. Methods We applied tailored RNA deconvolution for leukocyte enumeration and coregulated gene network analysis to published bulk human kidney transplant RNA transcriptomes as input for unsupervised, high-dimensional phenotype clustering. We used framework-based graft survival analysis to identify a biomarker that was subsequently characterized in independent transplant biopsy specimens. Results We found seven immune phenotypes that confirm known rejection types and uncovered novel signatures. The molecular phenotypes allow for improved graft survival analysis compared with histology, and identify a high-risk group in nonrejecting transplants. Two fibrosis-related phenotypes with distinct immune features emerged with reduced graft survival. We identified lysyl oxidase-like 2 (LOXL2)-expressing peritubular CD681 macrophages as a framework-derived biomarker of impaired allograft function. These cells precede graft fibrosis, as demonstrated in longitudinal biopsy specimens, and may be clinically useful as a biomarker for early fibrogenesis. Conclusions This study provides a comprehensive, data-driven atlas of human kidney transplant phenotypes and demonstrates its utility to identify novel clinical biomarkers.
AB - Background In transplant medicine, clinical decision making largely relies on histology of biopsy specimens. However, histology suffers from low specificity, sensitivity, and reproducibility, leading to suboptimal stratification of patients. We developed a histology-independent immune framework of kidney graft homeostasis and rejection. Methods We applied tailored RNA deconvolution for leukocyte enumeration and coregulated gene network analysis to published bulk human kidney transplant RNA transcriptomes as input for unsupervised, high-dimensional phenotype clustering. We used framework-based graft survival analysis to identify a biomarker that was subsequently characterized in independent transplant biopsy specimens. Results We found seven immune phenotypes that confirm known rejection types and uncovered novel signatures. The molecular phenotypes allow for improved graft survival analysis compared with histology, and identify a high-risk group in nonrejecting transplants. Two fibrosis-related phenotypes with distinct immune features emerged with reduced graft survival. We identified lysyl oxidase-like 2 (LOXL2)-expressing peritubular CD681 macrophages as a framework-derived biomarker of impaired allograft function. These cells precede graft fibrosis, as demonstrated in longitudinal biopsy specimens, and may be clinically useful as a biomarker for early fibrogenesis. Conclusions This study provides a comprehensive, data-driven atlas of human kidney transplant phenotypes and demonstrates its utility to identify novel clinical biomarkers.
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U2 - 10.1681/ASN.2020121685
DO - 10.1681/ASN.2020121685
M3 - Article
C2 - 34078665
AN - SCOPUS:85112014543
SN - 1046-6673
VL - 32
SP - 1933
EP - 1945
JO - Journal of the American Society of Nephrology
JF - Journal of the American Society of Nephrology
IS - 8
ER -