Literature DB >> 27190362

Deceased donor kidney transplantation across donor-specific antibody barriers: predictors of antibody-mediated rejection.

Elisabeth Schwaiger1, Farsad Eskandary2, Nicolas Kozakowski3, Gregor Bond1, Željko Kikić1, Daniel Yoo4, Susanne Rasoul-Rockenschaub5, Rainer Oberbauer1, Georg A Böhmig1.   

Abstract

BACKGROUND: Apheresis-based desensitization allows for successful transplantation across major immunological barriers. For donor-specific antibody (DSA)- and/or crossmatch-positive transplantation, however, it has been shown that even intense immunomodulation may not completely prevent antibody-mediated rejection (ABMR).
METHODS: In this study, we evaluated transplant outcomes in 101 DSA+ deceased donor kidney transplant recipients (transplantation between 2009 and 2013; median follow-up: 24 months) who were subjected to immunoadsorption (IA)-based desensitization. Treatment included a single pre-transplant IA session, followed by anti-lymphocyte antibody and serial post-transplant IA. In 27 cases, a positive complement-dependent cytotoxicity crossmatch (CDCXM) was rendered negative immediately before transplantation. Seventy-four of the DSA+ recipients had a negative CDCXM already before IA.
RESULTS: Three-year death-censored graft survival in DSA+ patients was significantly worse than in 513 DSA- recipients transplanted during the same period (79 versus 88%, P = 0.008). Thirty-three DSA+ recipients (33%) had ABMR. While a positive baseline CDCXM showed only a trend towards higher ABMR rates (41 versus 30% in CDCXM- recipients, P = 0.2), DSA mean fluorescence intensity (MFI) in single bead assays significantly associated with rejection, showing 20 versus 71% ABMR rates at <5000 versus >15 000 peak DSA MFI. The predictive value of MFI was moderate, with the highest accuracy at a median of 13 300 MFI (after cross-validation: 0.72). Other baseline variables, including CDC assay results, human leukocyte antigen mismatch, prior transplantation or type of induction treatment, did not add independent predictive information.
CONCLUSIONS: IA-based desensitization failed to prevent ABMR in a considerable number of DSA+ recipients. Assessing DSA MFI may help stratify risk of rejection, supporting its use as a guide to organ allocation and individualized treatment.
© The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Entities:  

Keywords:  antibody-mediated rejection; crossmatch; donor-specific antibodies; immunoadsorption; kidney transplantation

Mesh:

Substances:

Year:  2016        PMID: 27190362     DOI: 10.1093/ndt/gfw027

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


  19 in total

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Authors:  Joshua M Thurman; Sarah E Panzer; Moglie Le Quintrec
Journal:  Mol Immunol       Date:  2019-06-10       Impact factor: 4.407

Review 3.  Follicular T-cell regulation of alloantibody formation.

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4.  A Randomized Trial of Bortezomib in Late Antibody-Mediated Kidney Transplant Rejection.

Authors:  Farsad Eskandary; Heinz Regele; Lukas Baumann; Gregor Bond; Nicolas Kozakowski; Markus Wahrmann; Luis G Hidalgo; Helmuth Haslacher; Christopher C Kaltenecker; Marie-Bernadette Aretin; Rainer Oberbauer; Martin Posch; Anton Staudenherz; Ammon Handisurya; Jeff Reeve; Philip F Halloran; Georg A Böhmig
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7.  Follicular T cells mediate donor-specific antibody and rejection after solid organ transplantation.

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Journal:  Transplantation       Date:  2017-10       Impact factor: 4.939

9.  Torque Teno Virus Load-Inverse Association With Antibody-Mediated Rejection After Kidney Transplantation.

Authors:  Martin Schiemann; Elisabeth Puchhammer-Stöckl; Farsad Eskandary; Philip Kohlbeck; Susanne Rasoul-Rockenschaub; Andreas Heilos; Nicolas Kozakowski; Irene Görzer; Željko Kikić; Harald Herkner; Georg A Böhmig; Gregor Bond
Journal:  Transplantation       Date:  2017-02       Impact factor: 4.939

10.  Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs.

Authors:  Mohammadreza Nemati; Haonan Zhang; Michael Sloma; Dulat Bekbolsynov; Hong Wang; Stanislaw Stepkowski; Kevin S Xu
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