j ourna l homepage: www.e lsev ie r .com/ locate / t r im
The PROCARE consortium: Toward an improved allocation strategy forkidney allografts
H.G. Otten a,⁎, I. Joosten b, W.A. Allebes b, A. van der Meer b, L.B. Hilbrands c, M. Baas c, E. Spierings a, C.E. Hack a,F. van Reekum d, A.D. van Zuilen d, M.C. Verhaar d, M.L. Bots e, M.A.J. Seelen f, J.S.F. Sanders f, B.G. Hepkema g,A.J. Lambeck g, L.B. Bungener g, C. Roozendaal g, M.G.J. Tilanus h, J. Vanderlocht h, C.E. Voorter h, L. Wieten h,E. van Duijnhoven i, M. Gelens i, M. Christiaans i, F. van Ittersum j, A. Nurmohamed j, N.M. Lardy k,W.T. Swelsen k, K.A.M.I. van Donselaar-van der Pant l, N.C. van der Weerd l, I.J.M. ten Berge l, F.J. Bemelman l,A.J. Hoitsma m, J.W. de Fijter n, M.G.H. Betjes o, D.L. Roelen p, F.H.J. Claas p
a UMC Utrecht, Laboratory for Translational Immunology, The Netherlandsb Radboudumc, Dept. of Laboratory Medicine, The Netherlandsc Radboudumc, Dept. of Nephrology, The Netherlandsd UMC Utrecht, Dept. of Nephrology and Hypertension, The Netherlandse UMC Utrecht, Julius Center for Health Sciences and Primary Care, The Netherlandsf UMCG, Dept. of Nephrology, The Netherlandsg UMCG, Dept. of Laboratory Medicine, The Netherlandsh Maastricht UMC, Transplantation Immunology, The Netherlandsi Maastricht UMC, Dept. of Nephrology, The Netherlandsj VUmc, Dept. of Nephrology, The Netherlandsk Sanquin, Dept. of Immunogenetics, The Netherlandsl AMC Renal Transplant Unit, Dept. of Nephrology, The Netherlandsm NOTR/NTS Leiden, The Netherlandsn LUMC, Dept. of Nephrology, The Netherlandso Erasmus MC, Dept. of Nephrology, The Netherlandsp LUMC, Immunohematology and Blood Transfusion, The Netherlands
Please cite this article as: Otten HG, et al, TImmunol (2014), http://dx.doi.org/10.1016/
a b s t r a c t
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Keywords:Kidney transplantationHLA antibodiesAutoantibodiesGene polymorphismsT and B cell epitopes
Kidney transplantation is the best treatment option for patients with end-stage renal failure. At present, approxi-mately 800 Dutch patients are registered on the active waiting list of Eurotransplant. The waiting time in theNetherlands for a kidney from a deceased donor is on average between 3 and 4 years. During this period, patientsare fully dependent on dialysis, which replaces only partly the renal function, whereas the quality of life is limited.Mortality among patients on the waiting list is high. In order to increase the number of kidney donors, several ini-tiatives have been undertaken by the Dutch Kidney Foundation including national calls for donor registration andproviding information on organ donation and kidney transplantation. The aim of the national PROCARE consortiumis to develop improvedmatching algorithms thatwill lead to a prolonged survival of transplanteddonor kidneys anda reduced HLA immunization. The latter will positively affect the waiting time for a retransplantation.The present algorithm for allocation is among others based onmatching for HLA antigens,whichwere originally de-fined by antibodies using serological typing techniques. However, several studies suggest that this algorithm needsadaptation and that other immune parameters which are currently not included may assist in improving graft sur-vival rates. We will employ a multicenter-based evaluation on 5429 patients transplanted between 1995 and 2005in the Netherlands. The association between key clinical endpoints and selected laboratory defined parameters willbe examined, including Luminex-defined HLA antibody specificities, T and B cell epitopes recognized on the mis-matched HLA antigens, non-HLA antibodies, and also polymorphisms in complement and Fc receptors functionallyassociatedwith effector functions of anti-graft antibodies. From these data, key parameters determining the successof kidney transplantation will be identified which will lead to the identification of additional parameters to be in-cluded in futurematching algorithms aiming to extend survival of transplanted kidneys and to diminishHLA immu-nization. Computer simulation studies will reveal the number of patients having a direct benefit from improvedmatching, the effect on shortening of the waiting list, and the decrease in waiting time.
Rejection by the innate and adaptive immune system is an importantparameter determining survival of kidney grafts. To prevent rejection ofgrafts, matching algorithms have been developed to select optimaldonor–recipient combinations. Immune and biologic parameters classi-cally included in these algorithms are the ABO blood group system, thepresence and specificity of HLA antibodies in sera from patients, as wellas HLA-typing of donor and recipient. Recent insight has shown thatinclusion of other immunological parameters in matching algorithms islikely to improve the short and long-term results of kidney transplanta-tion. The presence of complement fixing HLA antibodies against potentialkidney donors prior to transplantation is considered a contraindicationfor transplantation [1]. Although complement dependent crossmatching(CDC) is a widely used technique to detect these antibodies, it ishampered by interference from immune complexes and autoantibodies,and it is by definition incapable of detecting non-complement fixingHLA antibodies such as IgG2 and IgG4 [2,3]. HLA antibody detection bysolid phase assays including those based on luminex technology ismuch more sensitive than CDC and yields a higher resolution ofantibody specificity [4–9]. In addition, in multiple studies autoantibodiesagainst non-HLA antigens have been found in sera from patients on thewaiting list for kidney transplantation. Depending on their specificitythe presence of these antibodies has been associated with chronic trans-plant glomerulopathy, a higher number of acute rejection episodes,acute vascular rejection, refractory acute vascular rejection andmalignanthypertension [10–19]. These data indicate that detection of preformednon-HLA antibodies may be useful in identifying patients at risk forgraft loss. Furthermore, IgG antibodies binding to antigens exposed bycells of the kidney graft (HLA and/or non-HLA antibodies), in particularendotheliall cells, can provoke damage by complement activation orinduction of antibody dependent cellular cytotoxicity [20]. The efficiencyof these effector mechanisms of IgG is influenced by several functionalpolymorphisms [21–27]. Although these polymorphisms have beenlinked to clinical prognosis in different clinical settings, such as chronicrejection after lung transplantation, they have not been systematicallystudied in kidney transplantation. Finally, more recent insights haveindicated that epitope matching between donor and recipient can alsobe used to prevent HLA-immunization [28–32]. However, is not clearwhich B or T cell epitope mismatches are associated with an increasedrisk for renal allograft rejection and whether the same ones are relevantin unimmunized versus highly-immunized patients.
Recently, the Dutch tissue typing laboratories and Nephrologydepartments involved in kidney transplantation in the associatedacademic hospitals have formed a consortium to collaborate in a nationalstudy funded by the Dutch Kidney Foundation. All research teamsinvolved in this study participate in Eurotransplant, either as heads/representatives of tissue typing laboratories or as nephrologists involvedin kidney transplantation. The central hypothesis is that the combinationof class-I and -II luminex-defined donor specific antibodies (DSA)present prior to transplantation, a set of non-HLA antibodies, B and Tcell epitopes recognized on donor HLA, and specific polymorphisms ineffector mechanisms of IgG provide information to better predict therisk for kidney allograft graft failure. We aim to define the impact ofthese parameters in kidney transplantation and provide matching algo-rithms used for allocation of kidney grafts resulting in extended half-lifesof transplanted kidneys and less HLA immunization. As a consequencehereof we expect less transplantations thereby shortening waiting listsand waiting time until kidney transplantation. To this end, a cohortconsisting of all Dutch kidney transplantations (N5400) performedbetween 1995 and 2005 will be examined in which we will: A) definethe clinical relevance of luminex-defined DSA against class-I and -IIHLA antigens in a multicenter and multivariate analysis, and establish auniform policy to apply luminex-defined DSA in the donor selectionprocess; B) investigate the extent to which matching of specific HLA-epitopes recognized by B and/or T cells will decrease the rate of HLA-
Please cite this article as: Otten HG, et al, The PROCARE consortium: ToImmunol (2014), http://dx.doi.org/10.1016/j.trim.2014.09.008
immunization and will significantly improve graft survival rates; C)identify patients with circulating antibodies reactive with non-HLAantigens and assess the impact of these antibodies on the risk for rejectionand/or graft loss; and D) assess the relation between clinical key-parameters defining successful kidney transplantation and genepolymorphisms encoding proteins involved in effector function of IgGanti-graft antibodies.
The primary clinical endpoint of this nation-wide study will be graftfailure. In addition, a set of secondary endpoints are included in thestudy. The impact of these algorithms within Eurotransplant will beevaluated in computer simulation studies with the aim to determinethe number of patients having a direct benefit from this improvedmatching algorithm, and to determine the effect on length of thewaiting lists and probable decrease in waiting time of end stage renalfailure (ESRF) patients needing a kidney transplantation.
2. Background and specific aims
2.1. Luminex-defined HLA antibodies
The exact clinical significance of luminex-defined donor-specificantibodies (DSA) that do not cause a positive CDC crossmatch is notclear [6]. In a number of studies a relation was found between graftloss and the pretransplant levels of luminex-defined DSA, whereas inother studies the presence of HLA antibodies in pre- or post transplantsera did not result in a significant increase in graft loss. A limitednumber of studies have demonstrated the pre- and post transplantpresence of antibodies against HLA-DQA, -DQB and -DP. The clinicalsignificance of these antibodies is, however, unknown [7,8]. In addition,there is no consensus on the definition of HLA-antibody positivity byluminex-based techniques. For these reasons, there is no uniform policybetween centers to establish whether and how luminex-defined DSAshould be included in clinical decision making both with respect todonor acceptance, as well as concerning immunosuppressive treatmentafter transplantation.
Recently, a cohort of 837 patients was studied in the UniversityMedical Center Utrecht (NL), treated by kidney transplantation between1990 and 2008 [9]. All transplants were performed after a negative CDCcrossmatch and the presence of DSA was determined in pretransplantsera using the luminex. The results showed that the presence of bothHLA class-I and-II DSA led to a significant increase in graft loss (70%)after 10 year as compared to graft loss in absence or presence of eitherclass-I or -II DSA (31–35%). The half-life of kidney grafts in patients withclass-I and-II DSA was 5 years versus more than 20 years in the otherpatients, indicating that allocation based on luminex-defined DSA mighthave prevented earlier readmission on the waiting list. In a separateanalysis, the impact of pretransplant HLA antibodies was comparedbetween patients having received a kidney from living donors, versuspatients that were transplanted with donors after brain death orcardiac death. In both groups, graft survival rates are significantlylower in patients positive for class-I and -II DSA according Kaplan–Meier analysis (data not shown). This indicates that patients withclass-I and -II DSA against a potential donor are at increased riskfor graft failure, independent whether a kidney is from a living ordeceased donor. Translated into practice, inclusion of luminex-defined DSA would not only affect allocation of kidneys derivedfrom deceased donors, but may also help to decide about transplan-tation with a kidney from a living donor. Notably though a relativelylarge cohort of patients was included, it was a single center study.Therefore, the conclusions should be confirmated in a multicenterstudy. Furthermore, additional information on the antibody titer,immunoglobulin subclass and other physicochemical propertiesrelevant for effector function is essential in order to draw any conclu-sions on the relevance in an individual patient rather than a populationof patients.
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2.2. non-HLA antibodies
Although the presence of complement-fixing donor-specific HLAantibodies is widely acknowledged as a contraindication for transplan-tation, antibodies have also been found against non-HLA antigens andtheir contribution to graft dysfunction is still under investigation. In alarge study among 3001 HLA-identical sibling kidney transplantation,it was shown that the grade of HLA-immunization—expressed aspercentage of panel reactive antibodies prior to transplantation—isassociated with chronic graft loss [11]. The patient group without HLAantibodies showed a graft survival rate of 82% after 10 years versus63% in those having N50% PRA. As graft loss in this study could not bethe result of anti-HLA alloreactivity, these data suggest an importantrole for immunity against antigens other thanHLA in kidney transplanta-tion. A substantial number of non-HLA antigens have been identified astargets of autoantibodies in kidney transplantation including vimentin,tubulin, myosin, collagen V, angiotensin type 1 receptor (AT1r), agrin,and LG3 [12–19]. The presence of antibodies against the glomerularbasement membrane protein agrin was found in 11 of 16 patients withchronic transplant glomerulopathy and 3 of 6 controls with chronicallograft nephropathy in absence of chronic transplant glomerulopathy.The presence of these antibodies was associated with a higher numberof prior acute rejection episodes in kidney transplant recipients [14].Fifteen patients who experienced acute vascular rejection had elevatedanti-LG3 titers pre and post transplantation compared to 15 subjectswith tubulo-interstitial rejection or stable graft function (n = 30) [15].Elevated pretransplant levels of anti-LG3 antibodies were associatedwith acute vascular rejection with and odds-ratio of 4.6 independentlyfrom DSA. Agonistic antibodies for AT1R were identified as a risk factorin kidney transplant recipients for acute rejection and graft loss [13],and also in DSA negative patients with antibody-mediated rejection.Autoantibodies against vimentin—an intermediate filament expressedat the surface different cell types—identified patients at risk of developingcoronary artery disease but also chronic rejection after kidney transplan-tation [12,16]. In addition, variable numbers of patients waiting for renaltransplant were shown to have antibodies against tubulin beta chain,vimentin, lamin-B1, andRhoGDP-dissociation inhibitor 2 [17]. Antibodiesagainst nucleolin were found in 25.5% of the patients after irreversiblerejection of a kidney allograft compared to 2% in healthy persons [18].Finally, anti-endothelial cell antibodies of the IgG2 and IgG4 subclassesoccurred more frequently in recipients with rejection compared tothose without rejection [19], indicating that discrimination of IgGautoantibodies into subclasses may show an improved relation withclinical parameters associated with graft loss.
Although the above studies do not provide definite proof thatautoantibodies contribute to the pathogenesis of graft dysfunction,the data indicate that detection of preformed antibodies directedagainst determinants other than HLA (non-HLA antibodies) mayhelp to identify patients at risk for graft loss. Establishing the relationbetween clinical key-parameters and non-HLA antibodies in a largecohort of patients receiving a kidney graft will define the clinical rele-vance of these graft reactive non-HLA antibodies.
2.2.1. Effector mechanisms of HLA and non-HLA antibodiesThe pathogenesis of endothelial damage from the transplanted
kidney, caused by binding of HLA- or non-HLA antibodies to the cellsurface, may involve complement activation, antibody dependentcellular cytotoxicity (ADCC), or intracellular signaling by clusteringof target (e.g. HLA) molecules. In this study we will examine therelation between IgG effector function and clinical endpoints.
2.2.1.1. Polymorphisms of complement and their regulators. C4ddepositionin peritubular capillaries of a graft from a patient with deterioratingkidney function is often considered to be the diagnostic hallmark forantibody mediated rejection. Complement activation mediated byantibodies binding to the cell surface can result in cellular activation
Please cite this article as: Otten HG, et al, The PROCARE consortium: ToImmunol (2014), http://dx.doi.org/10.1016/j.trim.2014.09.008
or cell lysis. The extent of complement activation on cells is regulated byfluid phase and membrane bound complement regulatory proteins(mCRP), CD59, CD55 and CD46, which protect against uncontrolledcomplement-mediated damage. Several functional polymorphisms ofcomplement proteins have been described affecting the efficacy ofcomplement control, and which are related to complement associateddiseases [21].
A number of polymorphisms in fluid phase regulators are related tothe regulation of formation of the C3 convertase C3bBb. Factor B formstogether with C3b the alternative C3 convertase which by itself cleavesmore C3 to C3b, capturing factor B and buildingmore C3bBb convertase(designated as the alternative pathway amplification loop). Factor Bwith an Arginine at position 32 binds more efficiently to C3b than thevariant with Glutamine at that position, generating more C3bBb andresulting in higher levels of alternative pathway activation. Factor H isa fluid phase protein acting as the central negative regulator of thealternative pathway [21]. However, this protein also limits thecommon complement pathway by hindering amplification by C3b,which explains the link found between a polymorphism in the encodinggene and effectiveness of Rituximab [22]. FactorHbinds to and inactivatesthe C3bBb convertase by displacing Bb. C3b with Glycine at position 102binds factor H less strongly compared to the variant with Arginine atthat position, causing less efficient C3b inactivation leading to moreactivation of the alternative pathway. Both, factor BR32q and C3bR102gare associated with age-related macular degeneration, but also densedeposit disease and atypical hemolytic uremic syndrome. These 2 variantsare examples of complement polymorphisms known to be associatedwith disease, and display a difference in levels of functional control ofcomplement regulation.
HLA antibodies can induce sublytic quantities of C5b–C9 mem-brane attack complex on endothelial cells and kidney tubular epi-thelial cells. This induces cellular activation and the release ofproinflammatory cytokines including interleukin6 and tumor necrosisfactor [20]. By this mechanism, continuous exposure to HLA antibodiesmay lead to chronic rejection. CD59 regulates complement activationbeyond C4 activation, which provides an explanation for the findingthat C4d deposition is not always indicative of a poor prognosis.Interestingly, the role of CD59 was also described in ABO-incompatiblekidney transplantation where endothelial cells develop resistance tocomplement fixing blood group antibodies; a process designated asaccommodation [26].
Part of the project will focus on the intrinsic ability of the graftedkidney to defend itself from undesired complement mediated damage.SNPs in promotor/enhancer regions are known to be associated withprotein expression levels and we will include sequence analysis of theregulatory sequences of all 3 mCRPs (CD59, CD46 and CD55) on DNAderived from patients and kidney donors and relate this in the contextof donor-specific antibodies to the primary and secondary clinicalendpoints.
2.2.1.2. FcRγ polymorphisms.During complement activation the cleavagefragments C3a and C5a are generated which recruit effector cells to thesite of activation. During antibody-mediated rejection infiltration ofmononuclear cells and neutrophils can be observed in the glomerularor peritubular capillaries, strongly suggesting that infiltrating cellscould mediate the endothelial injury through their Fc receptors and/or complement receptors [27]. Antibody-dependent cell-mediatedcytotoxicity (ADCC) can be mediated by NK cells and to some extentmonocytes and neutrophils. In this process, IgG bound to the cell surfaceis recognized via FcRγ receptors of which polymorphisms are knowninfluencing the affinity for IgG. CD16a/FcγR3a has a SNP definingwhether Valine (V) or Phenylalanine (F) is present at amino acidposition 158. In a number of studies, patients with the CD16a/FcγR3ain configuration with higher affinity for IgG (homozygous VV) showedimproved responses to Rituximab therapy compared to those with VFor FF at that position [23,24]. Another FcRγ receptor CD32/FcγR2a has
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a SNP defining whether an Arginine (R) or Histidine (H) is present atamino acid position 131. The CD32/FcγR2a variant with 131H can bindIgG2 whereas 131R cannot [25]. These SNPs co-determine the effective-ness of FcRγ bearing mononuclear cells to respond to IgG bound totarget cells, and although there is no evidence, it can be envisionedthat the configurations of these SNP are related to the incidence orseverity of graft rejection.
2.2.2. Definition of HLA-mismatches not inducing antibody formationImmunological contact with foreign HLA molecules does not by
definition lead to formation of specific HLA antibodies. Several studieshave shown that the HLA-background of the recipient determineswhich HLA mismatches are recognized leading to antibody formation,or not. This selective HLA-immunization has been demonstrated afterkidney transplantation and pregnancy (22–26). The lack of antibodyproduction againstHLAmismatcheshas been shown tobemechanisticallycaused by A) failure of antibody production by B cells due to the presenceof tolerance against the aggregate of self-epitopes present on foreign HLAor B) lack of T hell help due to the inability of the recipients' class-IImolecule to present the relevant allogeneic donor class-I peptides.Although implementation of this knowledge could be used to select forHLA-mismatched donors not leading to HLA antibody formation, currentalgorithms for patient-donor allocation usually do not take this optioninto account.
2.2.2.1. B cell recognition of donor HLA class-I epitopes. After the introduc-tion of molecular typing techniques, including sequence based typing,themolecular nature of the targets of HLAalloantibodies became clearer.In the meantime more than 5000 different HLA class I alleles have beendescribed but the polymorphism of these HLA alleles with respect toantibody reactivity is based on approximately 180 crucial amino acidvariations (epitopes). HLA molecules can be considered as patchworkmolecules consisting of a number of epitopes. Furthermore, epitopesare often shared between different HLA molecules, which is the reasonwhy the immunogenicity of a HLA mismatch is dependent on the ownHLA antigens of the recipient. A particular HLA mismatch may havemany potential antibody epitopes in one patient and no foreign epitopesin another patient. The HLAMatchmaker algorithm developed by ReneDuquesnoy in Pittsburgh in close collaboration with the group in Leidenhas been instrumental for the identification of the most importantantibody epitopes [28–31]. Preliminary data show that donor kidneyswith mismatched HLA antigens in the absence of foreign epitopes forthe recipient will not induce antibodies and have a similar graft survivalas fully HLA matched grafts. These data need to be confirmed andextended in the current proposal. Furthermore, the current largemulticenter studywill enable us to determine the relative immunogenic-ity of the individual epitopes. It is already clear that not everymismatchedepitope leads to an antibody response, either because these epitopes areless likely to be recognized by the B cells or due to the differential helpof T cells [28–30].
2.2.2.2. T cell recognition of donor HLA class-I epitopes. Cognate T-cell helpis required for proliferation and differentiation of antigen-specific naiveB cells into IgG producing cells. In case of production of IgG anti-HLAantibodies, mismatched HLA molecules have to be recognized byrecipient T cells. Binding of peptides to HLA molecules is predictable.We have applied HLA binding algorithms to define kidney donor HLAclass-I epitopes derived that can be presented in HLA class-II moleculesfrom the patient. We used this information to determine whether thelack of antibodyproduction against certainHLAmismatches after allegraftnephrectomy can be predicted [32]. In a cohort of 21 non-immunizedindividuals grafted with a kidney containing 1 or more HLA class-I mis-matches, post-nephrectomy sera were analyzed. HLA class-I mismatcheswhich induced donor-specific antibodies were found to contain a largernumber of HLA class-II restricted predicted indirectly recognizable HLAepitopes (PIRCHE-II) than mismatches which did not induce donor
Please cite this article as: Otten HG, et al, The PROCARE consortium: ToImmunol (2014), http://dx.doi.org/10.1016/j.trim.2014.09.008
specific HLA antibodies. Most PIRCHE-II (68%) were not part of an epletas defined by HLAMatchmaker. Although the use of this concept maylead to a better definition of permissible HLAmismatches in organ trans-plantation, it is clear that large clinical studies must be performed toevaluate the effect of this mechanism on graft survival and antibodyresponses after graft failure.
T cells may also directly harm the transplanted kidney afterrecognition. In this process, indirect recognition of HLA may alsoplay a role. We will therefore analyze whether indirect recognition ofHLA epitopes presented on the kidney leads to lower graft survival. Tothis end, we will focus on the Predicted Indirectly Recognizable HLAEpitopes presented on either HLA class I or HLA class II.
3. Execution of the study
3.1. Collection and analysis of sera
The basis for this study is the central, consortium-based, collection ofa large cohort of pretransplant sera from patients. We will analyze allkidney transplants performed in the period between 1995 and 2005,which would result in N5400 cases with adequate clinical follow-up.This approach enables multicenter evaluation and validation of resultsacquired. According to the Eurotransplant kidney transplant program,negative crossmatch results were required for all kidney transplantationsin the presence of dithiothreitol by the classical complement-dependentcytotoxicity method, carried out without the use of anti-human globulin.In that period, DSAwere rarely analyzed by solid phase assays and resultsknown prior to transplantation did not influence the initial and/ormaintenance immunosuppression. Pretransplant sera were drawn fromall patients for crossmatching (in case of a deceased donor at themomentof admission; in case of a living donor 1 or 2 weeks before the plannedprocedure) and routinely stored at −80 °C. 0.5 ml of those patient serastored locally in participating centers will be taken and pipetted intotubes with predefined positions (according to the database setupdescribed below) set in 8 × 12 arrays suitable for multichannel analysis.Preferentially, sera are taken which were used for crossmatching (themost recent serum prior to transplantation) but if that leaves insufficientmaterial present for future crossmatching, then samples will be takenfrom an earlier stage. All sera will be assessed for the presence of donorspecific class-I or -II antibodies and autoantibodies potentially relevantfor prediction of kidney graft function. To define the clinical relevanceof luminex-based assays measuring the complement fixing abilityof HLA antibodies, we will perform a nested case-control studywith sufficient number of patients according power analysis. Twohundred patients with HLA class-I and -II antibodies will be selectedhaving lost their graft within 5 years and as control 200 patientsmatched not only for the specificity and titer of HLA antibodies, butalso for relevant clinical parameters such as the type of organ donor(living or deceased).
3.2. Building of the ICT infrastructure
An ICT infrastructure will be built to address all research questionsinvestigated in this project. The central database will be establishedusing data included in the Dutch National Organ Transplant Registry(NOTR) and Eurotransplant Network Information system (ENIS).Patients and donors will be pseudo-anonymized based on theirEurotransplant number and the combination of these numbers willprovide an anonymous transplant number. Pretransplant sera will beassigned with a unique code linked with a position in the 8 × 12 arrayscontaining frozen sera. One part of the project will be the assignmentof donor-specific HLA antibodies, based on HLA typing of the donorsand luminex-based HLA-antibody profile of patients. Upon analysis forHLA-antibodies we will use the dedicated programs supplied by thecompanies and store the output directly into the central database. Tothis end, scripts will be built for importing these data from the dedicated
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- Graft failure - the number of rejections- time to 1st rejection- time to 1st biopsy- creatinine levels (at 3 months,1 and 5 years)- proteinuria (at 3 months, 1 and5 years)- incidence of delayed graft function
Recipient covariates Donor covariates- age at transplant - age at death, age at donation- sex - sex- nr. of transplants - type of donor (living, (non-)heart
beating)- date and cause of death - cause of death- % HLA immunization - HLA mismatches incl. PIRCHE-II- use of induction therapy - cold ischemia time- the type (or change) ofimmunosuppression.
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programs. This data flow prevents any manual entries in the databaseassociated with errors (Fig. 1).
Molecular typing techniques (SSP or SSO) were used between 1995and 2005 and these ENIS-derived data will be imported in the database.Based on these typing data, the central databasewill assign thepresenceof DSA for the HLA-A, -B, -C, -DR and -DQ antigens. HLA-DP typing wasnot included in that era and DQA/DQBwere not typed separately. Uponassessment of class-II antibodies, the database will identify the patientswith anti-DQ and/or Dp antibodies, generating lists used for furtherselection of donor DNA. The database structurewill allow establishmentof relations between all covariates and clinical endpoints described inthe next paragraph, DSA defined by different cut-off values and alsodifferent combinations of DSA (e.g. HLA-A and -DP, HLA-B, -C andDQA etc.). In addition, all other serological and molecular data such asSNPs involved in IgG effector functions) will be included and madeready for query. The database will allow multicenter-based evaluationand web-based access for all participants allowing local statistical dataanalysis.
3.3. Completion of the clinical database
Clinical data present in the Dutch National Organ Transplant Registry(NOTR) must be completed for all transplants investigated to an extentensuring that the majority of data is filled-in prior to statistical analysislinking laboratorywith clinical data. TheDutch collective ofNephrologistshas defined a set of clinical and secondary endpoints for this study, anddefined covariates to be included (see Table 1). Death censoredgraft failure will be used as primary endpoint. Three categories of graftfailures are classified: immunological, non-immunological (recurrentprimary renal disease, vascular or ureteric operative problems, notsurgical- or rejection-related vascular problems, infection of graft, infec-tion not graft related, nonviable kidney, technical problems, thrombosis/infarction) and multifactorial (the rest).
As secondary endpoint we will include the histological classificationof rejection. A retrospective analysis of historic conclusions drawn fromhistological analysiswill not suffice as the definition of antibodymediatedrejection (AMR) has been subject to change in the last decades. Forinstance, the presence of vascular rejection once was thought to be anexclusive indicator of antibody mediated rejection but is no longer
Database SeraDispen
predefined
Tes�Data analysis
Fig. 1. Sample and d
Please cite this article as: Otten HG, et al, The PROCARE consortium: ToImmunol (2014), http://dx.doi.org/10.1016/j.trim.2014.09.008
regarded as such. Also the technique for C4d staining as well as theaccuracy of its detection has gone through several phases. It is nowclear that a proportion of antibody-mediated rejection is C4d-negative.In addition, the presence of peritubular capillaritis and glomerulitis hasonly recently received its full appreciation as a sign of antibodymediatedrejection. It is possible that slides have been fixed and stained withtechniques that preclude additional assays.
3.4. Statistical data analysis and delivery of improved algorithms for kidneyallocation
All data will be collected followed by a detailed multicenter, multi-variate analysis to address all research questions listed, includingrelations between clinical data included and luminex results of HLAantibodies, autoantibodies, polymorphisms of antibody effectormechanisms etc. State-of-the-art study design and statistical modelswill applied targeted to addressing the research question, being etiologi-cal or prognostic. For prognosticmodelingwe closely follow the approach
se at positions
1.2um filtra�on
Storage at -800C
ng
ata processing.
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described [33]. Below, several examples are expressed in general terms.We will use a death-censored definition of graft failure, i.e., graft failuredefinitionwill not include patient deathwith a functioning graft. Analysisof DSA will include the use of different cutoffs for defining class-I and -IIDSA in order to examine their influence on graft loss and secondaryclinical endpoints. We expect that the presence rather than strengthof HLA-antibodies is related to graft loss. The relation between thepretransplant presence and titers of individual autoantibodies and clinicalendpoints will be examined, and also whether co-existence of specificautoantibodies is related to clinical endpoints. In order to examine theeffect of specific complement/FcRγ SNP configurations, individuals thatare homozygous at a distinct position will be compared to both theheterozygous and the homozygous variant with the different nucleotide.We will also examine whether combinations of specific SNP configura-tions involved in coding of different antigens (e.g. R32Q in factor B plusV62I in factor H) are related to clinical endpoints. In order to performPIRCHE-II analysis, all HLA typing data will be recoded to the mostfrequently encoding alleles according to the data set defined by the“common and well defined antigens” (Cano, Human Immunology2007). Furthermore, the algorithmwill include prediction of absenceof antibody formation using pretransplant sera from the 2ndtransplantation and compare the antibodies present/absent with theHLA-mismatches from the 1st kidney transplant. In the previous study[9], 71 retransplantationswere performedwithin the total of 837 kidneytransplantations. In the current consortium study, that number isincreased by about a factor of 7 yielding sufficient data to identify non-immunogenic HLA epitopes.
In order to analyze the clinical impact and advantage of B cellepitope matching in comparison to classical HLA antigen matching,the HLA phenotypes of both patients and donors will be transferredinto epitopes i.e. triplets and/or eplets according to theHLAMatchmakeralgorithm. The effect of epitope matching and mismatching on graftoutcome (incidence of rejection, graft function and a graft loss) will beanalyzed and compared to classical HLA antigen (mis)matching.Similarly, the induction of de novo DSA after transplantation willbe analyzed. Special focus will be on donor–recipient combinations,which are HLA antigen mismatched but epitope matched.Patientswith early graft loss defined as within 1 year and those with late graftloss (defined as N5 years) after transplantation will be compared topatients with functioning grafts at that time as it may well be that aspecific set of investigated parameters is related with early graft failureand another set with late graft failure. Graft-survival rates willbe computed using the Kaplan–Meier method and groups will becompared by the log-rank test. In all circumstances death-censoredgraft survival will be reported defined according to the Eurotransplantgraft failure system as irreversible end-stage renal failure, necessitatingrenal replacement therapy for patient survival. Continuous variableswill be analyzed by Student's t-test and categorical data with theFisher's exact test. Graft survival will be compared between patientswithout HLA-antibodies, with HLA antibodies but not against thegrafted kidney, and those with DSA (using different MFI cutoff values)using log-rank analysis. Multivariable Cox proportional hazards modelwill be applied to examine adjust for potential confounders in analysis 1and 5 years after transplantation. Results will be shown as adjustedhazard ratios including 95% confidence intervals. With regard to a roughsample size estimation; we will study 7 events (clinical endpoints) andat least 19 variables analyzed in the study (HLA antibodies, non-HLAand others). According to the previous study (Otten-2012) the primaryendpoint of graft survival differs between patients with class-I plus -IIDSA in the range of 20% after 1 year. In a multivariable analysesapproximately 10 events are needed per explanatory variable,resulting in 1/0.2 × 7 × 19=665 cases. Furthermore, we needmulticen-ter validation indicating that approximately 665 patients are needed percenter resulting in the total number of ±4000 patients. In further studiestheir data will be used as training set, and the data from other patientsincluded as validation set needed to study algorithm improvements.
Please cite this article as: Otten HG, et al, The PROCARE consortium: ToImmunol (2014), http://dx.doi.org/10.1016/j.trim.2014.09.008
Between 1995 and 2005, 5429 kidney transplantations wereperformed in the Netherlands. Grafts from deceased donors originatedfrom 826 persons after cardiac death and 3103 donors after braindeath, and 1500 grafts were donated by living donors. These patientswill be included for analysis. Because prediction models derived withmultivariable regression analysis are known for overestimated regres-sion coefficients, which results in too extreme predictions when appliedinnewpatients,we also internally validate ourmodelwith bootstrappingtechniques where in each bootstrap sample the entire modeling processwas repeated. This resulted in a shrinkage factor for the regressioncoefficients. The bootstrap procedure was also used to estimate a valueof the AUC that was corrected for overoptimism to provide an estimateof discriminative ability that is expected in future similar patients.Bootstrapping is the recommended approach for internal validation, asthe data of all patients is used for model development.
To facilitate practical application of the model based on all patientdata, the regression coefficients of the predictors in the model will beconverted into points on a score chart. Also regular parameters suchas age of donor and recipient, blood group, waiting time etc. will beincluded. The total points (sum scores) are linked to the risk of failure.Finally, various cut-off values will be introduced in the predicted proba-bilities, categorizing patients as having a very low risk, low risk,moderaterisk and high risk to failure. The sensitivities, specificities and negativepredictive values of these thresholds will be calculated.
4. Future prospects
Collaboration on the scale described in this consortium is essential toestablish a uniform policy within the Netherlands in determining howthe above described parameters should be included in clinical decisionmaking both with respect to donor acceptance as well as to immuno-suppressive treatment after transplantation. The present algorithm forHLA-based allocation uses HLAmatching defined by antibodies classicallyused for HLA typing.We intend tomodernize thesematching algorithms.To this end, we will use a multicenter-based evaluation of parametersknown to be associated with clinical endpoints. All data will be evaluatedby multicenter and multivariate analysis, leading to proposition of newmatching algorithms aimed to extend half-lifes of transplanted kidneysand less HLA immunization. Implementation of these algorithms withinEurotransplant will be evaluated in simulation studies not only to deter-mine the number of patients having a direct benefit from an improvedmatching, but also to determine the effect on shortening of waiting listsand the decrease in waiting time till kidney transplant.
New insights on relevant non-HLA targets, SNPs relevant in effectorfunctions, HLAMatchmaker and the PIRCHE algorithm will be includedwhen obtained during the project. The current project is focused onassessment of pretransplant immunological parameters associatedwith graft function. A forthcoming project may be the evaluation ofparameters of the innate or adaptive immune system associated withgraft function after transplantation. During the project we will seekfurther cooperation with partners outside of the Netherlands, such asother Eurotransplant affiliated centers, in order to expand opportunitiesfor research and validation of proposed new matching algorithms.
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