All transplanted kidneys are subjected to some degree of injury as a result of the donation-implantation process and various post-transplant stresses such as rejection. Because transplants are frequently biopsied, they present an opportunity to explore the full spectrum of kidney response-to-wounding from all causes. Defining parenchymal damage in transplanted organs is important for clinical management because it determines function and survival. In this study, we classified the scenarios associated with parenchymal injury in genome-wide microarray results from 1,526 kidney transplant indication biopsies collected during the INTERCOMEX study. We defined injury groups by using archetypal analysis (AA) of scores for gene sets and classifiers previously identified in various injury states. Six groups and their characteristics were defined in this population: No injury, minor injury, two classes of acute kidney injury ("AKI," AKI1, and AKI2), chronic kidney disease (CKD), and CKD combined with AKI. We compared the two classes of AKI, namely, AKI1 and AKI2. AKI1 had a poor function and increased parenchymal dedifferentiation but minimal response-to-injury and inflammation, instead having increased expression of PARD3, a gene previously characterized as being related to epithelial polarity and adherens junctions. In contrast, AKI2 had a poor function and increased response-to-injury, significant inflammation, and increased macrophage activity. In random forest analysis, the most important predictors of function (estimated glomerular filtration rate) and graft loss were injury-based molecular scores, not rejection scores. AKI1 and AKI2 differed in 3-year graft survival, with better survival in the AKI2 group. Thus, injury archetype analysis of injury-induced gene expression shows new heterogeneity in kidney response-to-wounding, revealing AKI1, a class of early transplants with a poor function but minimal inflammation or response to injury, a deviant response characterized as PC3, and an increased risk of failure. Given the relationship between parenchymal injury and kidney survival, further characterization of the injury phenotypes in kidney transplants will be important for an improved understanding that could have implications for understanding native kidney diseases (ClinicalTrials.gov #NCT01299168).

Alberta Transplant Applied Genomics Centre Edmonton AB Canada

Department of Clinical Interventions Department of Nephrology and Kidney Transplantation Samodzielny Publiczny Wojewódzki Szpital Zespolony Hospital Pomeranian Medical University Szczecin Poland

Department of Nephrology and Transplant Center Institute for Clinical and Experimental Medicine Prague Czechia

Department of Nephrology Hannover Medical School Hannover Germany

Department of Surgery University of Maryland Baltimore MD United States

Department of Transplantation Medicine Nephrology and Internal Diseases Medical University of Warsaw Warsaw Poland

Division of Nephrology and Dialysis Department of Medicine 3 Medical University of Vienna Vienna Austria

Division of Nephrology and Transplant Immunology Department of Medicine University of Alberta Edmonton AB Canada

Division of Nephrology Virginia Commonwealth University Richmond VA United States

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Halloran PF, Famulski KS, Reeve J. Molecular assessment of disease states in kidney transplant biopsy samples. Nat Rev Nephrol. (2016) 12:534–48. 10.1038/nrneph.2016.85 PubMed DOI

Reeve J, Bohmig GA, Eskandary F, Einecke G, Gupta G, Madill-Thomsen K, et al. . Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers. Am J Transplant. (2019) 19:2719–31. 10.1111/ajt.15351 PubMed DOI

Reeve J, Bohmig GA, Eskandary F, Einecke G, Lefaucheur C, Loupy A, et al. . Assessing rejection-related disease in kidney transplant biopsies based on archetypal analysis of molecular phenotypes. JCI Insight. (2017) 2:e94197. 10.1172/jci.insight.94197 PubMed DOI PMC

Venner JM, Famulski KS, Reeve J, Chang J, Halloran PF. Relationships among injury, fibrosis, and time in human kidney transplants. JCI Insight. (2016) 1:e85323. 10.1172/jci.insight.85323 PubMed DOI PMC

Halloran PF, Reeve J, Akalin E, Aubert O, Bohmig GA, Brennan D, et al. . Real time central assessment of kidney transplant indication biopsies by microarrays: the INTERCOMEX study. Am J Transplant. (2017) 17:2851–62. 10.1111/ajt.14329 PubMed DOI

Halloran PF, Bohmig GA, Bromberg JS, Budde K, Gupta G, Einecke G, et al. . Discovering novel injury features in kidney transplant biopsies associated with TCMR and donor aging. Am J Transplant. (2021) 21:1725–39. 10.1111/ajt.16374 PubMed DOI

R Foundation for Statistical Computing . RCT. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for statistical Computing; (2019) Available online at: http://www.r-project.org/ (accessed November 2, 2021).

Madill-Thomsen KS, Wiggins RC, Eskandary F, Bohmig GA, Halloran PF. The effect of cortex/medulla proportions on molecular diagnoses in kidney transplant biopsies: rejection and injury can be assessed in medulla. Am J Transplant. (2017) 17:2117–28. 10.1111/ajt.14233 PubMed DOI PMC

Loupy A, Haas M, Solez K, Racusen L, Glotz D, Seron D, et al. . The Banff 2015 kidney meeting report: current challenges in rejection classification and prospects for adopting molecular pathology. Am J Transplant. (2017) 17:28–41. 10.1111/ajt.14107 PubMed DOI PMC

Mengel M, Loupy A, Haas M, Roufosse C, Naesens M, Akalin E, et al. . Banff 2019 Meeting Report: molecular diagnostics in solid organ transplantation-Consensus for the Banff Human Organ Transplant (B-HOT) gene panel and open source multicenter validation. Am J Transplant. (2020) 20:2305–17. 10.1111/ajt.16059 PubMed DOI PMC

Halloran PF, Matas A, Kasiske BL, Madill-Thomsen KS, Mackova M, Famulski KS. Molecular phenotype of kidney transplant indication biopsies with inflammation in scarred areas. Am J Transplant. (2019) 19:1356–70. 10.1111/ajt.15178 PubMed DOI

Einecke G, Reeve J, Gupta G, Bohmig GA, Eskandary F, Bromberg JS, et al. . Factors associated with kidney graft survival in pure antibody-mediated rejection at the time of indication biopsy: importance of parenchymal injury but not disease activity. Am J Transplant. (2021) 21:1391–401. 10.1111/ajt.16161 PubMed DOI

Kuhn M. caret: Classification and Regression Training. R package version 6.0-81. (2018). Available online at: https://CRAN.R-project.org/package=caret (accessed November 2, 2021).

Heil M, Land WG. Danger signals - damaged-self recognition across the tree of life. Front Plant Sci. (2014) 5:578. 10.3389/fpls.2014.00578 PubMed DOI PMC

Land WG, Agostinis P, Gasser S, Garg AD, Linkermann A. Transplantation and damage-associated molecular patterns (DAMPs). Am J Transplant. (2016) 16:3338–61. 10.1111/ajt.13963 PubMed DOI

Famulski KS, de Freitas DG, Kreepala C, Chang J, Sellares J, Sis B, et al. . Molecular phenotypes of acute kidney injury in human kidney transplants. J Am Soc Nephrol. (2012) 23:948–58. 10.1681/ASN.2011090887 PubMed DOI PMC

Famulski KS, Broderick G, Einecke G, Hay K, Cruz J, Sis B, et al. . Transcriptome analysis reveals heterogeneity in the injury response of kidney transplants. Am J Transplant. (2007) 7:2483–95. 10.1111/j.1600-6143.2007.01980.x PubMed DOI

Einecke G, Reeve J, Mengel M, Sis B, Bunnag S, Mueller TF, et al. . Expression of B cell and immunoglobulin transcripts is a feature of inflammation in late allografts. Am J Transplant. (2008) 8:1434–43. 10.1111/j.1600-6143.2008.02232.x PubMed DOI

Mengel M, Reeve J, Bunnag S, Einecke G, Sis B, Mueller T, et al. . Molecular correlates of scarring in kidney transplants: the emergence of mast cell transcripts. Am J Transplant. (2009) 9:169–78. 10.1111/j.1600-6143.2008.02462.x PubMed DOI

Einecke G, Kayser D, Vanslambrouck JM, Sis B, Reeve J, Mengel M, et al. . Loss of solute carriers in T cell-mediated rejection in mouse and human kidneys: an active epithelial injury-repair response. Am J Transplant. (2010) 10:2241–51. 10.1111/j.1600-6143.2010.03263.x PubMed DOI

Eugster MJA, Leisch F. From spider-man to hero - archetypal analysis in R. J Stat Softw. (2009) 30:1–23. 10.18637/jss.v030.i08 PubMed DOI

Thogersen JC, Morup M, Damkiaer S, Molin S, Jelsbak L. Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways. BMC Bioinformat. (2013) 14:279. 10.1186/1471-2105-14-279 PubMed DOI PMC

Korem Y, Szekely P, Hart Y, Sheftel H, Hausser J, Mayo A, et al. . Geometry of the gene expression space of individual cells. PLoS Comput Biol. (2015) 11:e1004224. 10.1371/journal.pcbi.1004224 PubMed DOI PMC

Ishwaran H, Kogalur UB. Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC). R package version 3.0.2. (2019). Available online at:https://cran.r-project.org/package=randomForestSRC

Naik AS, Afshinnia F, Cibrik D, Hodgin JB, Wu F, Zhang M, et al. . Quantitative podocyte parameters predict human native kidney and allograft half-lives. JCI Insight. (2016) 1:e86943. 10.1172/jci.insight.86943 PubMed DOI PMC

Ronco C, Bellomo R, Kellum JA. Acute kidney injury. Lancet. (2019) 394:1949–64. 10.1016/S0140-6736(19)32563-2 PubMed DOI

A cross-sectional study of the role of epithelial cell injury in kidney transplant outcomes

Zobrazit více v PubMed

ClinicalTrials.gov
NCT01299168