4.7 Article

WARS1, TYMP and GBP1 display a distinctive microcirculation pattern by immunohistochemistry during antibody-mediated rejection in kidney transplantation

Journal

SCIENTIFIC REPORTS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-022-23078-z

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Funding

  1. France Rein Aquitaine

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This study utilized three interferon-related proteins in immunohistochemical analysis of kidney allograft biopsies, supplemented by a deep learning framework, to assist in the diagnosis of antibody-mediated rejection. The results showed promising diagnostic performance and reproducibility of these proteins with deep learning technology, effectively addressing the diagnostic challenges of ABMR.
Antibody-mediated rejection (ABMR) is the leading cause of allograft failure in kidney transplantation. Defined by the Banff classification, its gold standard diagnosis remains a challenge, with limited inter-observer reproducibility of the histological scores and efficient immunomarker availability. We performed an immunohistochemical analysis of 3 interferon-related proteins, WARS1, TYMP and GBP1 in a cohort of kidney allograft biopsies including 17 ABMR cases and 37 other common graft injuries. Slides were interpreted, for an ABMR diagnosis, by four blinded nephropathologists and by a deep learning framework using convolutional neural networks. Pathologists identified a distinctive microcirculation staining pattern in ABMR with all three antibodies, displaying promising diagnostic performances and a substantial reproducibility. The deep learning analysis supported the microcirculation staining pattern and achieved similar diagnostic performance from internal validation, with a mean area under the receiver operating characteristic curve of 0.89 (+/- 0.02) for WARS1, 0.80 (+/- 0.04) for TYMP and 0.89 (+/- 0.04) for GBP1. The glomerulitis and peritubular capillaritis scores, the hallmarks of histological ABMR, were the most highly correlated Banff scores with the deep learning output, whatever the C4d status. These novel immunomarkers combined with a CNN framework could help mitigate current challenges in ABMR diagnosis and should be assessed in larger cohorts.

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