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A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation

 
: Wittenbrink, N.; Herrmann, S.; Blazquez-Navarro, A.; Bauer, C.; Lindberg, E.; Wolk, K.; Sabat, R.; Reinke, P.; Sawitzki, B.; Thomusch, O.; Hugo, C.; Babel, N.; Seitz, H.; Or-Guil, M.

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Volltext ()

BMC immunology 20 (2019), Art. 11, 10 S.
ISSN: 1471-2172
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IZI ()

Abstract
Background: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach.
Results: The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%).
Conclusions: The resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information.

: http://publica.fraunhofer.de/dokumente/N-558703.html