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

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.

Trial registration: ClinicalTrials.gov NCT00724022 . Retrospectively registered July 2008.

Keywords: Acute cellular rejection; Anti-HLA-1 antibodies; Immune signatures; Machine learning; Pre-transplantation risk assessment; Renal transplantation; Single HLA antigen bead assay.

Conflict of interest statement

Authors’ information

The authors are part of the e:KID consortium, an interdisciplinary group which has as its main aim the development and establishment a systems medicine approach to personalized immunosuppressive treatment at an early stage after kidney transplantation. The consortium’s backgrounds areas include expertise in bioinformatics and machine learning (NW, ABN, CB, EL and MO), HLA antibody experimental analysis and immunology (NW, SH, KW, RS, BS, HS and MO), and the clinic of renal transplantation (PR, OT, CH and NB).

Ethics approval and consent to participate

The study was carried out in compliance with the Declaration of Helsinki and Good Clinical Practice. All participants provided written informed consent prior to inclusion into the study. The trial was approved by the Ethics Committee of the Universitätsklinikum Carl Gustav Carus Dresden. The trial is registered with ClinicalTrials.gov, number NCT00724022 (https://ichgcp.net/clinical-trials-registry/NCT00724022). Date of registration was July 2008 (retrospectively registered), date of enrollment was June 2008.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1

Predictive performance of the multiparameter ACR risk assessment classifier based on rank-normalized continuous pre-transplant HLA-1 antibody reactivity profiles. a Output of the classifiers decision function for each patient. The decision threshold is indicated by a dashed horizontal line. Patients with a decision value > 0 are classified as ACR, patients with a decision value < 0 are classified as control. Colors indicate whether patients tested positive (black) or negative (grey) for the presence of serum HLA-1 antibodies during MAB screening. b ROC curve of the multiparameter classifier

Fig. 2

Conventional MFI-thresholded binary MAB screening data do not allow for pre-transplant risk assessment of ACR. Illustrated are the results of the MAB screening data of the cohort (117 graft recipients, 63 ACR + 54 controls; for demographics and clinical characteristics, see Additional file 5: Table S2).). Analyses were carried out on MFI-thresholded binary HLA MAB screening data (conventional approach); according to Fisher’s exact test, differences with respect to the prevalence of HLA antibodies are not significant (p > 0.05)