Matteo Togninalli1,2, Daisuke Yoneoka1,2, Antonios G A Kolios3, Karsten Borgwardt1,2, Jakob Nilsson4. 1. Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland. 2. SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland; and. 3. Department of Immunology, University Hospital Zurich, Zurich, Switzerland. 4. Department of Immunology, University Hospital Zurich, Zurich, Switzerland jakob.nilsson@usz.ch.
Abstract
BACKGROUND: Patients on organ transplant waiting lists are evaluated for preexisting alloimmunity to minimize episodes of acute and chronic rejection by regularly monitoring for changes in alloimmune status. There are few studies on how alloimmunity changes over time in patients on kidney allograft waiting lists, and an apparent lack of research-based evidence supporting currently used monitoring intervals. METHODS: To investigate the dynamics of alloimmune responses directed at HLA antigens, we retrospectively evaluated data on anti-HLA antibodies measured by the single-antigen bead assay from 627 waitlisted patients who subsequently received a kidney transplant at University Hospital Zurich, Switzerland, between 2008 and 2017. Our analysis focused on a filtered dataset comprising 467 patients who had at least two assay measurements. RESULTS: Within the filtered dataset, we analyzed potential changes in mean fluorescence intensity values (reflecting bound anti-HLA antibodies) between consecutive measurements for individual patients in relation to the time interval between measurements. Using multiple approaches, we found no correlation between these two factors. However, when we stratified the dataset on the basis of documented previous immunizing events (transplant, pregnancy, or transfusion), we found significant differences in the magnitude of change in alloimmune status, especially among patients with a previous transplant versus patients without such a history. Further efforts to cluster patients according to statistical properties related to alloimmune status kinetics were unsuccessful, indicating considerable complexity in individual variability. CONCLUSIONS: Alloimmune kinetics in patients on a kidney transplant waiting list do not appear to be related to the interval between measurements, but are instead associated with alloimmunization history. This suggests that an individualized strategy for alloimmune status monitoring may be preferable to currently used intervals.
BACKGROUND:Patients on organ transplant waiting lists are evaluated for preexisting alloimmunity to minimize episodes of acute and chronic rejection by regularly monitoring for changes in alloimmune status. There are few studies on how alloimmunity changes over time in patients on kidney allograft waiting lists, and an apparent lack of research-based evidence supporting currently used monitoring intervals. METHODS: To investigate the dynamics of alloimmune responses directed at HLA antigens, we retrospectively evaluated data on anti-HLA antibodies measured by the single-antigen bead assay from 627 waitlisted patients who subsequently received a kidney transplant at University Hospital Zurich, Switzerland, between 2008 and 2017. Our analysis focused on a filtered dataset comprising 467 patients who had at least two assay measurements. RESULTS: Within the filtered dataset, we analyzed potential changes in mean fluorescence intensity values (reflecting bound anti-HLA antibodies) between consecutive measurements for individual patients in relation to the time interval between measurements. Using multiple approaches, we found no correlation between these two factors. However, when we stratified the dataset on the basis of documented previous immunizing events (transplant, pregnancy, or transfusion), we found significant differences in the magnitude of change in alloimmune status, especially among patients with a previous transplant versus patients without such a history. Further efforts to cluster patients according to statistical properties related to alloimmune status kinetics were unsuccessful, indicating considerable complexity in individual variability. CONCLUSIONS: Alloimmune kinetics in patients on a kidney transplant waiting list do not appear to be related to the interval between measurements, but are instead associated with alloimmunization history. This suggests that an individualized strategy for alloimmune status monitoring may be preferable to currently used intervals.
Authors: I Katerinis; K Hadaya; R Duquesnoy; S Ferrari-Lacraz; S Meier; C van Delden; P-Y Martin; C-A Siegrist; J Villard Journal: Am J Transplant Date: 2011-06-14 Impact factor: 8.086
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Authors: C Wehmeier; G Hönger; H Cun; P Amico; P Hirt-Minkowski; A Georgalis; H Hopfer; M Dickenmann; J Steiger; S Schaub Journal: Am J Transplant Date: 2017-03-27 Impact factor: 8.086
Authors: J E Locke; A A Zachary; D S Warren; D L Segev; J A Houp; R A Montgomery; M S Leffell Journal: Am J Transplant Date: 2009-07-30 Impact factor: 8.086
Authors: E G Kamburova; B W Wisse; I Joosten; W A Allebes; A van der Meer; L B Hilbrands; M C Baas; E Spierings; C E Hack; F E van Reekum; A D van Zuilen; M C Verhaar; M L Bots; A C A D Drop; L Plaisier; M A J Seelen; J S F Sanders; B G Hepkema; A J A Lambeck; L B Bungener; C Roozendaal; M G J Tilanus; C E Voorter; L Wieten; E M van Duijnhoven; M Gelens; M H L Christiaans; F J van Ittersum; S A Nurmohamed; N M Lardy; W Swelsen; K A van der Pant; N C van der Weerd; I J M Ten Berge; F J Bemelman; A Hoitsma; P J M van der Boog; J W de Fijter; M G H Betjes; S Heidt; D L Roelen; F H Claas; H G Otten Journal: Am J Transplant Date: 2018-04-16 Impact factor: 8.086