TYPE Original Research PUBLISHED 29 September 2022 DOI 10.3389/fimmu.2022.924825 On the clinical relevance OPEN ACCESS of using complete high- EDITED BY Brian Duncan Tait, The University of Melbourne, Australia resolution HLA typing for an REVIEWED BY Dulat Bekbolsynov, accurate interpretation of University of Toledo, United States Michelle Willicombe, Imperial College London, posttransplant immune- United Kingdom *CORRESPONDENCE mediated graft outcomes Oriol Bestard obestard@vhebron.net † Maria Meneghini 1,2, Anna Perona 3†, Elena Crespo 2†, These authors have contributed equally to this work. Frederike Bemelman 4, Petra Reinke 5, Ondrej Viklicky 6,7, SPECIALTY SECTION Magali Giral 8, Eduard Palou 9, Alba Torija 2, Laura Donadeu 2, This article was submitted to Alloimmunity and Transplantation, Edoardo Melilli 10, Jose Zuñiga 1, Anett Sefrin 5, a section of the journal Nils Lachmann 11, Liu Hu 4, Petra Hruba 6,7, Frontiers in Immunology Cécile Guillot-Gueguen 8, Sophie Brouard 8, RECEIVED 20 April 2022 ACCEPTED 30 August 2022 Josep Grinyo 3 and Oriol Bestard 1,2* PUBLISHED 29 September 2022 1 Kidney Transplant Unit, Nephrology Department. Vall d’Hebron University Hospital, Barcelona, CITATION Spain, 2 Vall d’Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Meneghini M, Perona A, Crespo E, Spain, 3 Department of Medicine, Barcelona University, Barcelona, Spain, 4 Renal Transplant Unit, Bemelman F, Reinke P, Viklicky O, Department of Internal Medicine, Amsterdam University Medical Centers, Academic Medical Center Giral M, Palou E, Torija A, Donadeu L, - University of Amsterdam, Amsterdam, Netherlands, 5 Berlin Center for Advanced Therapies Melilli E, Zuñiga J, Sefrin A, (BeCAT), Berlin Institute of Health Center for Regenerative Therapies (BCRT) and Department of Lachmann N, Hu L, Hruba P, Nephrology and Intensive Care, Charité Universitätsmedizin Berlin, Berlin Institute of Health, Berlin, Guillot-Gueguen C, Brouard S, Germany, 6 Transplant Laboratory, Institute for Clinical and Experimental Medicine (IKEM), Prague, Grinyo J and Bestard O (2022) On the Czechia, 7 Department of Nephrology, Institute for Clinical and Experimental Medicine (IKEM), clinical relevance of using complete Prague, Czechia, 8 Nantes Université, Inserm, Centre Hospitalier Universitaire (CHU) Nantes, Centre high-resolution HLA typing for an de Recherche en Transplantation et Immunologie UMR1064, Institut de Transplantation Urologie- accurate interpretation of Néphrologie (ITUN), Nantes, France, 9 Histocompatibility Laboratory, Immunology Department. posttransplant immune-mediated graft Hospital Clinic, Barcelona, Spain, 10 Kidney Transplant Unit, Nephrology Department, Bellvitge outcomes. University Hospital, Barcelona, Spain, 11 HLA- Laboratory, Charité- Universitätsmedizin Berlin, Front. Immunol. 13:924825. Berlin, Germany doi: 10.3389/fimmu.2022.924825 COPYRIGHT © 2022 Meneghini, Perona, Crespo, Bemelman, Reinke, Viklicky, Giral, Palou, Complete and high-resolution (HR) HLA typing improves the accurate assessment Torija, Donadeu, Melilli, Zuñiga, Sefrin, Lachmann, Hu, Hruba, Guillot-Gueguen, of donor–recipient compatibility and pre-transplant donor-specific antibodies Brouard, Grinyo and Bestard. This is an (DSA). However, the value of this information to identify de novo immune- open-access article distributed under the terms of the Creative Commons mediated graft events and its impact on outcomes has not been assessed. In Attribution License (CC BY). The use, 241 donor/recipient kidney transplant pairs, DNA samples were re-evaluated for distribution or reproduction in other six-locus (A/B/C/DRB1/DQB1+A1/DPB1) HR HLA typing. De novo anti-HLA forums is permitted, provided the original author(s) and the copyright antibodies were assessed using solid-phase assays, and dnDSA were classified owner(s) are credited and that the either (1) as per current clinical practice according to three-locus (A/B/DRB1) low- original publication in this journal is cited, in accordance with accepted resolution (LR) typing, estimating donor HLA-C/DQ typing with frequency tables, academic practice. No use, or (2) according to complete six-locus HR typing. The impact on graft outcomes distribution or reproduction is was compared between groups. According to LR HLA typing, 36 (15%) patients permitted which does not comply with these terms. developed dnDSA (LR_dnDSA+). Twenty-nine out of 36 (80%) were confirmed to have dnDSA by HR typing (LR_dnDSA+/HR_dnDSA+), whereas 7 (20%) did not Frontiers in Immunology 01 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 (LR_dnDSA+/HR_dnDSA−). Out of 49 LR_dnDSA specificities, 34 (69%) were confirmed by HR typing whereas 15 (31%) LR specificities were not confirmed. LR_dnDSA+/HR_dnDSA+ patients were at higher risk of ABMR as compared to dnDSA− and LR_dnDSA+/HR_dnDSA− (logRank < 0.001), and higher risk of death- censored graft loss (logRank = 0.001). Both LR_dnDSA+ (HR: 3.51, 95% CI = 1.25– 9.85) and LR_dnDSA+/HR_dnDSA+ (HR: 4.09, 95% CI = 1.45–11.54), but not LR_dnDSA+/HR_dnDSA− independently predicted graft loss. The implementation of HR HLA typing improves the characterization of biologically relevant de novo anti-HLA DSA and discriminates patients with poorer graft outcomes. KEYWORDS kidney transplantation, HLA typing, donor-specific antibodies, allograft rejection, precision medicine Introduction patients developing dnDSA, allograft biopsies to rule out ongoing immune-mediated lesions and enhancement of the The development of de novo donor-specific anti-HLA immunosuppression burden are frequently performed (10–12). antibodies (dnDSA) after kidney transplantation has a Therefore, the precise identification that such de novo anti-HLA deleterious impact on graft outcomes favoring the advent of antibodies are indeed directed against donor (HLA)-specific chronic antibody-mediated rejection (ABMR) and premature antigens is highly warranted to avoid invasive procedures and graft loss (1, 2). Therefore, most transplant programs have unnecessary rescue immunosuppressive therapies and, implemented routine screening of these antibodies during furthermore, to recognize those patients with true dnDSA to posttransplant follow-up (3). establish guided therapeutic strategies. While the implementation of solid-phase assays has In this study, we investigated in a large cohort of kidney revolutionized the assessment of antibodies with precise HLA- transplant recipients without preformed DSA participating in antigen specificities prior to and after transplantation, these two prospective randomized trials whether complete two-field advances have not paralleled the characterization of HLA typing HR HLA typing as compared to the commonly used A-B-DRB1 in clinical practice. Indeed, the most frequent donor–recipient one-field LR HLA typing would have an impact on the HLA genotyping worldwide still relies on one-field (two digits) identification of posttransplant immunological events such as low-resolution (LR) typing by sequence-specific primer PCR dnDSA formation, development of ABMR, and risk of graft loss. (SSP) or sequence-specific oligonucleotide probes (PCR-SSOP) of HLA-A, B, and DRB1 loci. However, an important body of evidence has shown that advanced high-resolution (HR) HLA Methods genotyping based on next-generation sequencing technologies (NGS) by moving from one field to two fields (four digits) and Study population a more complete HLA antigen assessment of up to nine distinct HLA loci (A, B, C, DRB1-3-4-5, DQ, and DP) significantly Two hundred forty-one adult kidney transplant recipients improves the accurate characterization of the degree of donor/ from five European transplant centers (Bellvitge University recipient HLA matching (4). All previous studies underscored the Hospital, Barcelona, Spain; Amsterdam University Medical value of such refined donor/recipient HLA typing not only to Center, Amsterdam, the Netherlands; Charités Universitätsmedizin better characterize donor/recipient compatibility and to uncover Berlin, Germany; Institute for Clinical and Experimental Medicine- all pretransplant circulating anti-HLA antibodies with donor IKEM, Prague, Czech Republic; and Inserm CHU, Nantes, France), (HLA)-antigen specificity, but also to enable to assess the degree participating in two prospective randomized clinical trials (NCT of donor/recipient HLA disparity at the molecular level (5–9). 02540395 and NCT 02550639) between 2014 until 2018 and in However, while complete HR HLA typing has shown its whom donor and recipient DNA was available to perform HR HLA clinical value in the pretransplant setting, the impact of this typing, were retrospectively investigated. All participants were ABO biological information in the management of patients after compatible and had a negative complement-dependent cytotoxicity transplantation has not been assessed yet. Notably, while there crossmatch and no preformed DSA by solid-phase assay at is still no clear evidence on how to manage transplant transplantation. The absence of preformed DSA was confirmed by Frontiers in Immunology 02 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 complete HR HLA donor typing. HLA-identical patients were Donor/recipient molecular excluded from the study (Figure 1). This study was approved by the mismatch assessment review board of each center. Main demographic, clinical, and immunological variables Donor/recipient HLA eplet mismatches (EpMM) were were recorded. Biopsy-proven acute rejection (BPAR) was determined by the last versions of the HLAMatchmaker diagnosed according to the Banff 2019 classification (13). software (v3.0, available at http://www.epitopes.net/downloads. Estimated glomerular filtration rate (eGFR) was calculated by html). Since two-field HLA typing is necessary to calculate CKD-EPI formula and allograft loss was defined as either return EpMM, either it was predicted according to haplotype to chronic dialysis or re-transplantation. All clinical and frequencies (HaploStats) from the available LR HLA typing immunological events were considered during the study (LR_EpMM) or using directly typed HR HLA typing was follow-up, which was of 55 ± 15.6 months. introduced in the software (HR_EpMM). Results of those two eplet MM calculations were compared. HLA typing Detection of circulating First, recipients’ and donors’ one-field LR HLA class I (A, B) anti-HLA antibodies and class II (DRB1) typing were obtained using DNA-based sequence-specific primers (SSP for donors and SSOP for Circulating anti-HLA antibodies were assessed at baseline, at recipients), according to current clinical practice. As usually 6 and 12 months after transplantation, and yearly thereafter as done in clinical practice, in case of anti-HLA antibodies against well as when graft biopsies showed BPAR lesions. A single- HLA-DQ and -C, donor typing at these loci was estimated using antigen class I and class II flow beads-assay kit was used the web application of the National Marrow Donor Program (Lifecodes, Immucor, Stanford, CA). All beads showing a (NMDP) HaploStat (http://www.haplostats.org). normalized mean fluorescence intensity (MFI) > 500 were In all included patients, two-field HR typing was performed considered positive if (MFI/MFI lowest bead) > 5. using the NGS HLA typing kit on the Illumina MiSeq platform at six loci: HLA-A, -B, -C, -DRB1, -DQB1/A1, and -DPB1. Two- field donor typing at HLA-DPA1 and -DRB3/4/5 loci was performed in all cases with the presence of anti-HLA Statistical analyses antibodies against these loci to confirm anti-donor specificity. All data were expressed as mean ± SD or as median and interquartile range for continuous variables, and as frequencies for categorical variables. Groups were compared using the Student’s t-test for normally distributed quantitative variables, and non-parametric Mann–Whitney U-test for non-normally distributed variables. Bivariate correlation analyses were performed using Spearman test for non-normally distributed variables. Univariate and multivariate logistic and Cox regression models were performed to examine the factors associated with rejection and graft survival. Kaplan–Meier probabilities of graft survival and rejection- free survival were plotted and compared using log-rank tests. The statistical significance level was defined as two-tailed p < 0.05. Statistical analyses were performed with IBM SPSS Statistics (SPSS Inc., Chicago, IL) version 26.0 and GraphPad Prism version 6.0 (GraphPad, Software, La Jolla, CA). Results FIGURE 1 Study population Flow chart of the study. HR, high-resolution; HLA, Human Leukocyte Antigens; DSA, donor-specific antibodies; SAB, single antigen bead assay. The main demographic and clinical characteristics of the study population are depicted in Table 1. Most patients were Frontiers in Immunology 03 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 men and received a first kidney transplant, and the majority glomerular disease (2, 12.5%), infectious complications (1, received induction treatment with anti-IL2R monoclonal 6%), and unspecific fibrosis (5, 31%). Eighteen (7%) patients antibody basiliximab. died, mainly due to cancer (7, 39%), cardiovascular (4, 22%), and Biopsy-proven acute rejection (BPAR) was diagnosed in 51/ infectious complications (3, 17%). 241 (21%) patients, 34 (67%) T-cell-mediated (TCMR) and 17 (33%) antibody-mediated (ABMR), with 8 of these ABMR (47%) showing a mixed component with concomitant TCMR lesions. Donor/recipient HLA antigen and Sixteen out of 241 (7%) patients lost their graft during molecular matching follow-up due to rejection (8, 50%), recurrence of primary Mean number of HLA mismatches (MM) using either LR or complete HR HLA typing is depicted in Table 2. According to TABLE 1 Demographic and clinical characteristics of patients included in the study. LR HLA typing, class I (A, B) MM were 2.68 ± 0.98, class II (DRB1) MM were 1.09 ± 0.62, and the global three-locus MM Demographic and clinical characteristics n = 241 were 3.78 ± 1.28. With complete and HR HLA typing, class I (A, B, and C) MM were 4.12 ± 1.42, class II (DRB1, DQA1/B1, and Recipient age (years) 52.53 ± 13.79 DPB1) MM were 3.71 ± 1.36, and the global six-locus MM were Recipient gender (male) 164 (68) 7.79 ± 2.41. As shown in Figure 2, correlations between LR allelic Ethnicity (Caucasian) 228 (95) MM and complete HR HLA MM were as follows: r = 0.76, p < ESRD cause 0.00 for total HLA MM; r = 0.84, p < 0.001 for class I; and r = Vascular disease 27 (11) 0.52, p < 0.001 for class II HLA MM. Diabetes mellitus 33 (14) Donor/recipient molecular mismatches at the eplet level Glomerular disease 65 (27) (EpMM) were also assessed and calculated by introducing Polycystic kidney disease 47 (19) either haplotype frequency imputation of one-field LR HLA Interstitial diseases 16 (7) typing (LR_EpMM) to simulate the information available in Others/unknown 53 (22) Time on renal replacement therapy (months) 25.88 ± 40.50 standard clinical practice or the complete HR HLA genotyping Donor age (years) 53.33 ± 13.71 (HR_EpMM) (Supplementary Table 1). The correlation between Donor gender (male) 119 (49) LR_EpMM and HR_EpMM for class I and class II was r = 0.96, p Type of transplantation (deceased donor) 134 (56) < 0.001 and r = 0.89, p < 0.001, respectively, and significantly Kidney transplant index (first) 230 (95) lower r = 0.79, p < 0.001 when DQ and DPB1 loci are considered Induction immunosuppression (Supplementary Figure 1). rATG/anti-IL2R mAb (basiliximab) 33 (14)/208 (86) Maintenance immunosuppression 241 (100) CNI-based 40 (16) dnDSA identification according to CNI monotherapy different HLA typing DGF 50 (21) Biopsy-proven acute rejection (BPAR) 51 (21) As shown in Figure 3, according to LR HLA typing, 36 (15%) TCMR 34 (67) patients displayed any detectable dnDSA (LR_dnDSA+). In 29/ ABMR 17 (33) 36 (80%) patients, antibodies were confirmed to be DSA by eGFR (ml/min/1.73 m2) complete HR HLA typing (LR_dnDSA+/HR_dnDSA+), 12 months 52.97 ± 19.27 whereas in 7 (20%) patients, these antibodies were revealed 24 months 51.84 ± 19.03 not to show anti-donor specificity using complete HR HLA 36 months 49.688 ± 19.81 typing (LR_dnDSA+/HR_dnDSA−). Furthermore, by using 60 months 50.79 ± 19.15 complete HR HLA typing, three new patients were identified Proteinuria (g/L) 12 months 0.16 ± 0.35 TABLE 2 Mean number of HLA mismatches according to LR HLA 24 months 0.19 ± 0.32 typing (A, B, and DRB1) and HR complete HLA typing (A, B, C, DRB1, 36 months 0.31 ± 0.53 DQA/B, and DPB1). 60 months 0.32 ± 0.49 HLA mismatches LR HLA typing HR HLA typing Death censored graft loss 16 (7) Patient death 18 (7) Class I 2.68 ± 0.98 4.12 ± 1.42 Class II 1.09 ± 0.62 3.71 ± 1.36 ESRD, end-stage renal disease; rATG, rabbit anti-thymoglobulin; IL2R mAb, anti- interleukin 2 receptor monoclonal antibody; CNI, calcineurin inhibitors; DGF, delayed Global 3.78 ± 1.28 7.79 ± 2.41 graft function; TCMR, T-cell-mediated rejection; ABMR, antibody-mediated rejection; eGFR, estimated glomerular filtration rate. LR, low resolution; HR, high resolution. Frontiers in Immunology 04 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 A B C FIGURE 2 Correlation between high resolution and low resolution HLA Typing (A) global; (B) Class I and (C) class II. HR, high resolution; LR, low resolution. to show dnDSA (LR_dnDSA−/HR_dnDSA+), anti-DP, and Patients developing any confirmed dnDSA (LR_dnDSA +/ anti-DQ. Thus, 32/241 (13%) patients were deemed to show HR_dnDSA+) had a trend towards higher total number of LR true HR_dnDSA. and HR HLA MM (LR: 4.25 ± 1.16 vs. 3.70 ± 1.28, p = 0.09; HR: Ten out of 32 (31%) patients with HR_dnDSA+ displayed 8.31 ± 2.02 vs. 7.71 ± 2.46, p = 0.06 in dnDSA+ and dnDSA−, anti-class I dnDSA only, 20/32 (62.5%) anti-class II only, and 2 respectively) and patients developing anti-class II dnDSA (6.5%) patients both anti-class I and II dnDSA. showed a higher mean number of both LR and HR class II When considering the number of detected dnDSA, while 49 HLA MM (LR: 1.45 ± 0.51 vs. 1.05 ± 0.62, p = 0.004; HR: 4.45 ± distinct dnDSA were detected with LR HLA typing, 34/49 (69%) 1.14 vs. 3.63 ± 1.36, p = 0.009). No statistically significant were confirmed by both LR and HR HLA typing while 15 (31%) difference was observed for anti-class I dnDSA and class I dnDSA detected by LR were not confirmed by HR HLA typing. HLA MM (LR: 3.0 ± 1.05 vs. 2.67 ± 0.97, p = 0.81; HR: 4.17 ± Conversely, seven circulating anti-HLA antibodies were 1.27 vs. 4.12 ± 1.43, p = 0.94). identified to be dnDSA only by HR HLA typing (Table 3). Most HR-confirmed anti-class II dnDSA were anti-DQ (17, 41%) dnDSA, 4 (10%) anti-DRB1, and 5 (12%) anti-DP dnDSA. Eplet mismatch and dnDSA formation The main causes of discrepancy were different allele according to different HLA typing specificities at two-field resolution using HR typing or allele estimation (three anti-A, one anti-B, one anti-DRB1, and three Patients developing anti-class I dnDSA (LR_dnDSA +/ anti-DQ). In other cases, discrepancies were due to absence of HR_dnDSA+) displayed higher class I eplet MM as compared DQA1 (two cases) and DP (five cases) typing and missing to negative patients according to LR typing (A, B) (14.83 ± 5.29 representation of donor antigen specificities on single-antigen vs. 11.71 ± 5.36, in dnDSA+ and dnDSA−, respectively, p = bead (SAB) assays in six cases (four anti-B, one anti-DRB1, and 0.059) but not when considering HR A-B-C typing (14.50 ± 5.78 two anti-DQ) (Table 3). vs. 13.16 ± 5.95, p = 0.43). FIGURE 3 Proportion of patients with dnDSA according to LR or complete HR HLA typing. dnDSA, de novo donor -specific antibody; HR, high resolution; LR, low resolution. Frontiers in Immunology 05 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 TABLE 3 All dnDSA specificities detected by LR HLA typing and if confirmed or not by HR donor HLA typing. Patient Anti-HLA antibody MFI LR donor HLA typing HR HLA donor typing Non-shared eplets no. specificity range LR_dnDSA+/ 1 DR*11:03 1,462 Donor DRB1*11 Donor DRB1*11:04 (negative) DRB1*11:03: Not AbV 71E HR_dnDSA− 2 A*11:01 9,897 Donor A*11 Donor A*11:02 (negative) A*11:01: Not AbV:19K 3 DQB1*03:03/DQA1*04:01 786 Estimated donor typing Donor DQB1*03:03/ DQB1*03:03/DQA1*04:01: AbV: DQB1*03:03 DQA1*03:02 (negative) 40GR; Not AbV: 69T 76L 4 B*35:01; 35:08 2,425 Donor B*35 Donor B*35:02 (not available on SAB) 5 DQB1*03:01/DQA1*03:01; 1,291– Estimated donor typing Donor DQB1*03:01/ 03:02; 05:01; 06:01 2,322 DQB1*03:01 DQA1*05:05 (not available on SAB) 6 DQB1*03:01/DQA1*05:01; 18,143– Estimated donor typing Donor DQB1*03:01/ 06:01 14,722 DQB1*03:01 DQA1*05:05 (not available on SAB) 7 B*27:03; 27:05 1,150– Donor B*27 Donor B*27:02 (not available on 1,200 SAB) LR_dnDSA+/ 8 B*51:01 792 Donor B*51 Donor B*51:01 HR_dnDSA+ 9 DQB1*03:02/DQA1*02:01; 14,825– Estimated donor typing Donor DQB1*03:02/ 03:01; 03:02 15,601 DQB1*03:02 DQA1*02:01 10 DQB1*03:01/DQA1*03:01; 16,816– Estimated donor Donor DQB1*03:01/ 03:02; 05:01; 06:01 18,520 DQB1*03:01, DQB1*06:03 DQA1*05:01 DQB1*06:03/DQA1*01:03 1,964 Donor DQB1*06:03/ DQA1*01:03 11 DQB1*03:02/DQA1*02:01 1,958 Estimated donor typing Donor DQB1*03:02/ DQB1*03:02 DQA1*02:01 12 DQB1*03:01/DQA1*03:02; 3,672– Estimated donor typing Donor DQB1*03:01/ 05:01; 06:01 6,355 DQB1*03:01 DQA1*03:02 13 DQB1*02:01/DQA1*05:01 6,603 Estimated donor typing Donor DQB1*02:01/ DQB1*02:01 DQA1*05:01 14 C*05:01 4,303 Estimated donor typing Donor C*05:01 C*05:01 15 A*29:01; 29:02 2,494– Donor A*29, estimated Donor A*29:02 DQB1*03:01/DQA1*03:01; 3,990 donor typing DQB1*03:01 Donor DQB1*03:01/ 03:02; 05:01; 06:01 7,019– DQA1*05:01 13,441 16 DQB1*03:02/DQA1*02:01; 7,005– Estimated donor typing Donor DQB1*03:02/ 03:01; 03:02 7,752 DQB1*03:02 DQA1*03:01 17 DQB1*05:01/DQA1*01:01 5,186 Estimated donor typing Donor DQB1*05:01/ DQB1*05:01 DQA1*01:01 18 DRB1*13:01 1,966 Donor DRB1*13 Donor DRB1*13:01 19 DQB1*06:02/DQA1*01:02 18,641 Estimated donor typing Donor DQB1*06:02/ DQB1*06:02 DQA1*01:02 20 B*08:01 1,871 Donor B*08 Donor B*08:01 21 A*02:01; 02:02; 02:03 1,171– Donor A*02 Donor A*02:01 2,342 22 DRB1*15:01; 15:02; 15:03 1,616– Donor DRB1*15 Donor DRB1*15:01 6,493 23 DQB1*05:01/DQA1*01:01; 1,123– Estimated donor typing Donor DQB1*05:01/ 01:02 1,375 DQB1*05:01 DQA1*01:01 24 B*52:01 1,050 Donor B*52 Donor B*52:01 DQ*05:01/DQA1*01:01; 1,990– Estimated donor typing Donor DQB1*05:01/ 01:02 2,300 DQB1*05:01 DQA1*01:01 25 A*01:01 7,900 Donor A*01 Donor A*01:01 26 C*04:01 1,182 Estimated donor typing Donor C*04:01 C*06:02 1,159 C*04:01, C*06:02 Donor C*06:02 27 B*44:03 2,000 Donor B*44 Donor B*44:03 (Continued) Frontiers in Immunology 06 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 TABLE 3 Continued Patient Anti-HLA antibody MFI LR donor HLA typing HR HLA donor typing Non-shared eplets no. specificity range LR_dnDSA−/ 28 DQB1*03:01/DQA1*03:02; 1,150– Estimated donor typing Donor DQB1*03:01/ HR_dnDSA+ 05:01; 06:01 1,907 DQB1*04:02, DQB1*06:03 DQA1*06:01 29 DPB1*04:02/DPA1*01:03; 816– Not available DP typing Donor DPB1*04:02 03:01 4,008 30 DPB1*04:01/DPA1*04:01 4,347 Not available DP typing Donor DPB1*04:01 Patients with more than one possible DSA and potential misclassification 31 DQB1*04:02/DQA1*03:01 2,514 Estimated donor typing Donor DQB1*04:02/ DQB1*03:01/DQA1*03:02 2,621 DQB1*04:02, DQB1*03:02 DQA1*03:01 DQB1*03:02/DQA1*02:01; 6,809 Donor DQB1*03:01/ 03:01; 03:02 DQA1*03:02 32 DQB1*02:02/DQA1*02:01; 12,406– Estimated donor typing Donor DQB1*02:02/ 03:02; 05:01 13,055 DQB1*02:02, DQB1*03:01 DQA1*02:01 DQB1*03:02/DQA1*02:01; 13,991– Donor DQB1*03:02/ 03:01; 03:02 1,512 DQA1*03:01 33 B*35:08 1,989 Donor B*35, B*51 Donor B*35:01 (negative) B*35:08: none B*51:01 1,401 Donor B*51:01 34 A*02:05 2,685 Donor A*02 Donor A*02:01(negative); A*02:05: Not AbV 43R DQB1*05:01/DQA1*01:01; 2,694– Estimated donor typing A*02:13 (not available on SAB) 01:02 7,438 DQB1*05:01 DQB1*05:01/DQA1*01:01 DPB1*02:01/DPA1*01:03 8,846 DP typing not available DPB1*02:01 DPB1*04:02/DPA1*01:03; 13,513– DPB1*04:02 03:01 14,085 35 DRB1*11:01 4,241 Donor DRB1*11 Donor DRB1*11:02 (not DPB1*04:01/DPA1*01:03; 4,315– DP typing not available available on SAB) 02:01 6,814 Donor DPB1*04:01 36 A*24:02; 24:03 4,646– Donor A*24, A*29, B*44 Donor A*24:02 A*29*02: none A*29:01 10,894 Donor A*29:02 (negative) B*44:02; 44:03 2,464 Donor B*44:03 5,661– 5,647 37 DRB1*03:01; 03:02 1,159– Donor DRB1*03 Donor DRB1*03:01 DQB1*02:01/DQA1*02:01: AbV: DQB1*02:01/DQA1*02:01 1,256 Estimated donor typing Donor DQB1*02:01/ 47KHL DQB1*03:03/DQA1*03:02; 1,611 DQB1*02:01, DQB1*03:03 DQA1*05:01 (negative) 04:01; 06:01 1,278– Donor DQB1*03:03/ 1,689 DQA1*03:02 38 B*57:01 9,606 Donor B*57, DRB1*15 Donor B*57:03 (not available on DRB1*15:01; 15:02 2,380– Estimated donor typing SAB) DQB1*03:01/DQA1*03:01; 3,074 DQB1*03:01 Donor DRB1*15:01 03:02; 05:01; 06:01 21,875– Donor DQB1*03:01/ 22,402 DQA1*05:01 39 A*01:01 2,000 Donor A*01, B*15 Donor A*01:01 B*15:12: Not AbV: 156WA B*15:12 Donor B*15:17 (negative) LR, low resolution; HR, high resolution; DSA, donor-specific antibody; AbV, antibody verified; SAB, single antigen bead. In case of misclassified DSA, eplets only present on non-donor-specific HLA molecule (LR_dnDSA+) but not in the actual donor HLA molecule (HR_dnDSA−) are listed. In red colour, misclassified dnDSA specificities not confirmed by HR HLA typing; in green, dnDSA specificities confirmed by HR HLA typing. Patients developing anti-class II dnDSA (LR_dnDSA +/ (DQB1) and direct HR HLA typing (DQA1/B1) were significantly HR_dnDSA+) showed higher class II (especially antibody- higher in anti-DQ dnDSA+ patients (LR_EpMM: 9.82 ± 3.5 vs. verified) eplet MM, both calculated introducing LR typing and 6.10 ± 5.29 p = 0.003; HR_EpMM: 12.94 ± 5.09 vs. 8.49 ± 6.24 p = haplotype frequency imputation of DQB1 (DRB1/DQB1 0.002, in anti-DQ dnDSA+ and anti-DQ dnDSA−, respectively). LR_EpMM: 19.32 ± 7.70 vs. 14.15 ± 10.04, p = 0.025; antibody- DRB1 EpMM were not different between patients developing and verified: 7.17 ± 3.43 vs. 5.33 ± 3.98, p = 0.04, in dnDSA+ and not developing anti-DRB1 dnDSA. dnDSA−, respectively) and complete HR typing (DRB1/DQ/DPB1 As shown in Table 3, in most of the cases of LR_dnDSA HR_EpMM: 25.41 ± 8.89 vs. 20.49 ± 12.68, p = 0.019; antibody- +/HR_dnDSA−, only few eplets were different between the HLA verified: 11.09 ± 4.28 vs. 8.02 ± 5.15, p = 0.003) (Supplementary molecule targeted by the circulating antibody (LR_dnDSA+) and Figure 2). Similarly, DQ EpMM by haplotype frequency imputation not represented on the actual donor HLA molecules Frontiers in Immunology 07 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 (HR_dnDSA−). In two cases, no eplets were different between the two molecules; therefore, we cannot rule out the possibility of unspecific binding, or that the antibody is targeting other parts of the molecule not defined by the HLAMatchmaker algorithm. Interestingly, in two other cases, the number of eplet MM was higher in the HLA molecule NOT targeted by the antibody (HR_dnDSA−) as compared to the specific one against which the antibody was directed (LR_dnDSA+), highlighting the importance of the type of molecular antigens more than their number, as hypothesized in previous studies (14). Impact of dnDSA on subsequent BPAR FIGURE 4 according to different HLA typing Kaplan Meyer Survival curves for ABMR according to different dnDSA identification. dnDSA, de novo donor -specific antibody; Fifty-one patients (21%) developed BPAR, 35/51 (69%) TCMR HR, high resolution; LR, low resolution; ABMR, antibody- mediated rejection. and 17/51 (33%) ABMR. Twelve out of 17 (70.5%) patients with ABMR showed dnDSA, while five showed Banff compatible histological lesions with ABMR without detectable dnDSA neither than all other groups (Log Rank < 0.001 global, Log Rank < 0.001 with LR nor with complete HR HLA typing. Conversely, while no as compared to dnDSA−, Log Rank = 0.23 as compared to TCMR patients showed dnDSA at the time of rejection, 8 (35%) of LR_dnDSA+/HR_dnDSA−, Log Rank = 0.39 as compared to them subsequently developed dnDSA over time. LR_dnDSA−/HR_dnDSA+) (Figure 5). The same results were When comparing the incidence of ABMR, LR_dnDSA +/ observed when breaking down dnDSA into class I and class II HR_dnDSA+ patients displayed significantly higher cumulative (data not shown). rates as compared to dnDSA− patients and those only detected At multivariate Cox regression analysis, transplant number by LR HLA typing (LR_dnDSA+/HR_dnDSA−) (Log Rank < (HR: 0.24, 95% CI = 0.07–0.84, p = 0.03), 12-month eGFR (HR: 0.001 global, Log Rank < 0.001 as compared to dnDSA−, Log 0.94, 95% CI = 0.89–0.98, p = 0.004), previous BPAR (HR: 4.08, Rank = 0.12 as compared to LR_dnDSA+/HR_dnDSA−) 95% CI = 1.23–13.52, p = 0.02), and both LR_dnDSA+ (HR: 3.51, (Figure 4). Similarly, LR_dnDSA−/HR_dnDSA+ displayed 95% CI = 1.25–9.85, p = 0.017) and LR_dnDSA+/HR_dnDSA+ higher risk as compared to LR_dnDSA+/HR_dnDSA− (Log (HR: 4.09, 95% CI = 1.45–11.54, p = 0.008) independently predicted Rank = 0.038). LR_dnDSA+/HR_dnDSA+ and LR_dnDSA-/ graft loss (Table 5). None of the patients with either LR_dnDSA +/ HR_dnDSA+HR_dnDSA− displayed a higher risk of ABMR HR_dnDSA− or LR_dnDSA−/HR_dnDSA+ lost their graft until also when stratifying in class I and class II dnDSA (class I Log last follow-up. Rank < 0.001 for LR_dnDSA+/HR_dnDSA+ vs. dnDSA− and 0.21 vs. LR_dnDSA-/HR_dnDSA−, Log rank 0.66 for LR_dnDSA +/HR _dnDSA− vs. dnDSA−. There were no cases of LR_dnDSA −/HR_dnDSA+. class II Log Rank < 0.001 Discussion for LR_dnDSA +/HR_dnDSA+ vs. dnDSA− and 0.21 vs. LR_dnDSA +/HR_dnDSA− and 0.48 vs. LR_dnDSA −/ The use of complete HR HLA genotyping of donor/recipient HR_dnDSA+; Log rank 0.72 for LR_dnDSA+/HR_dnDSA− vs. pairs in kidney transplantation has been shown to have relevant dnDSA−; Log Rank < 0.001 for LR_dnDSA−/HR_dnDSA+ vs. implications in the pretransplant setting on the one hand to dnDSA−). better define the degree of HLA matching and, on the other, to At univariate logistic regression analysis including main clinical, identify biologically impactful preformed DSA, especially those demographic, and immunological variables, dnDSA defined as with anti-DQ specificity and when these antibodies are directed LR_dnDSA+, LR_dnDSA+/HR_dnDSA+ and LR_dnDSA −/ against HLA alleles not assessed by standard SSP/SSOP typing HR_dnDSA+ were significant correlates of ABMR (Table 4). (6, 8, 15). In this study, we rather focused on the impact of using complete two-field HR HLA genotyping on the identification of Impact of dnDSA on the risk of graft loss posttransplant immunologic events as compared to according to different HLA typing conventional one-field LR typing. Here, we show that those de novo anti-HLA antibodies that were confirmed to be specific Patients with LR_dnDSA+/HR_dnDSA+ showed against donor antigens by complete HR genotyping (LR_dnDSA significantly higher cumulative death-censored graft loss rates +/HR_dnDSA+) displayed a deleterious effect on main allograft Frontiers in Immunology 08 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 TABLE 4 Univariate logistic regression analysis of main clinical, demographic, and immunological variables associated with ABMR. Variables OR (95% CI) p Recipient age (years) 0.98 (0.94–1.01) 0.20 Recipient gender (F) 0.31 (0.07–1.41) 0.13 ESRD cause (diabetes) 0.58 (0.05–6.73) 0.66 Recipient ethnicity (Caucasian) 0.78 (0.09–6.48) 0.82 Donor age (years) 0.99 (0.95–1.03) 0.53 Donor gender (F) 0.89 (0.31–2.54) 0.83 Transplant number (1) 0.65 (0.08–5.43) 0.69 Time on dialysis (months) 0.99 (0.98–1.01) 0.68 Type of transplantation 1.21 (0.42–3.52) 0.72 (deceased donor) FIGURE 5 Induction (rATG) 0.71 (0.19–2.64) 0.61 Kaplan Meyer Survival curves for death-censored graft loss Maintenance CNI monotherapy 1.25 (0.38–4.09) 0.71 according to different dnDSA identification. dnDSA, de novo donor -specific antibody; HR, high resolution; LR, low resolution. DGF 0.95 (0.26–3.51) 0.94 LR Typing HLA MM (1–6) 1.34 (0.86–2.08) 0.19 HR Typing HLA MM (1–12) 1.09 (0.87–1.38) 0.43 representation in the SAB platform explained some incongruity, LR_dnDSA+ 15.38 (4.88–48.52) <0.001 which highlights the limitation of using distinct SAB assays LR_dnDSA+/HR_dnDSA+ 21.79 (6.75–70.33) <0.001 showing, albeit low (17), distinct sensitivity to detect DSA. These LR_dnDSA+/HR_dnDSA− NA differences may have relevant clinical implication since, on the LR_dnDSA−/HR_dnDSA+ 29.73 (2.55–346.89) 0.007 one hand, patients with a false-positive dnDSA determination F, female; ESRD, end-stage renal disease; rATG, rabbit anti-thymoglobulin; CNI, may be exposed to invasive procedures such as protocol biopsies calcineurin inhibitors; DGF, delayed graft function; LR, low resolution; HR, high resolution; MM, mismatch; dnDSA, de novo donor-specific antibody. Bold values and even to antibody-depletion rescue therapies to eliminate highlights all p values <0.05. NA, Not applicable. alloantibodies and, on the other, patients with non-recognized circulating dnDSA with HR genotyping may undergo outcomes such as ABMR and poorer graft survival, whereas minimization strategies over time and be at higher risk of patients with anti-HLA antibodies that were not confirmed to be accelerated immune-mediated graft lesions and subsequent donor-specific (LR_dnDSA+/HR_dnDSA−) (20% of patients) premature graft loss. Indeed, this was confirmed when the risk did not show any significant risk of developing either ABMR or of ABMR and/or graft loss was shown to be only significant for premature graft loss. Our study is the first report to show the those patients with confirmed dnDSA by complete HR clinical impact of using two-field resolution of HLA typing for a HLA genotyping. more accurate diagnosis of dnDSA arising after transplantation. Correlation between HLA LR and HR MM was rather high It supports the recommendations made by distinct international but lacking important relevant alleles that may affect the working groups focusing on the pretransplant immune-risk generation of de novo alloimmune responses. Likewise, the stratification (3, 16), in which assessing donor/recipient with degree of concordance of EpMM assessed by LR HLA typing complete HLA typing at HR level seems to be highly warranted introducing haplotype frequency imputation as compared to also for the posttransplant clinical follow-up and immunological two-field complete HR was high. However, when assessing their risk stratification. predictive capacity of generating primary alloimmune Notably, the most impactful difference between the two HLA activation, while patients developing dnDSA showed typing approaches was the identification of patients developing significantly higher EpMM, assessed by both technologies, dnDSA and the number of dnDSA specificities. Indeed, only 29/ especially class II molecules, a significantly higher association 36 (80%) patients diagnosed to display dnDSA were confirmed was clearly observed when using HR HLA genotyping. These when applying HR genotyping, and furthermore, three other data confirm previous observations on the importance of a patients were found to show dnDSA not identified by LR HLA correct imputation in the algorithm (7, 18). The fact that also typing. More importantly, when the number of dnDSA EpMM calculated by LR typing and inferred two-field resolution specificities was evaluated, these differences were even more associate to dnDSA appearance might be justified by high relevant, since 49 dnDSA detected with LR changed to be only 34 concordance at eplet level and is in accordance with the results (69%) with HR and 7 additional dnDSA were identified only by that have been generated in the last decade using this HR HLA typing. The main reasons for these discrepancies were methodology (19, 20). However, at the single-patient level, the the two-field resolution allele typing and the absence of DQA1 estimation of the second field of resolution to calculate and DP typing using LR. Also, the absence of some HLA antigen compatibility at the allele and eplet level, as well as to diagnose Frontiers in Immunology 09 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 TABLE 5 Univariate and multivariate Cox regression analysis for death-censored graft loss. Univariate Multivariate Variables HR (95% CI) p HR (95% CI) p Recipient age (years) 1.01 (0.97–1.05) 0.45 Recipient gender (F) 0.63 (0.20–1.95) 0.42 ESRD cause (diabetes) 1.08 (0.21–5.47) 0.92 Donor age (years) 1. 04 (1.002–1.08) 0.04 1.04 (0.99–1.09) 0.09 Donor gender (F) 0.61 (0.22–1.73) 0.36 Transplant number (1) 0.17 (0.05–0.54) 0.003 0.24 (0.07–0.84) 0.03 Time on dialysis (months) 1.01 (1.002–1.02) 0.009 1.003 (0.99–1.01) 0.49 Type of transplantation 1.41 (0.79–2.49) 0.24 (deceased donor) Induction (rATG) 1.31 (0.36–4.78) 0.68 Maintenance CNI monotherapy 1.82 (0.41–8.10) 0.43 LR Typing HLA MM (1–6) 1.08 (0.71–1.65) 0.72 HR Typing HLA MM (1–12) 1.02 (0.82–1.27) 0.88 DGF 3.32 (1.20–9.16) 0.02 1.97 (0.66–5.92) 0.23 12 months eGFR (ml/m/1.73 m2) 0.91 (0.88–0.95) <0.001 0.94 (0.89–0.98) 0.004 BPAR 6.31 (2.33–17.11) <0.001 4.08 (1.23–13.52) 0.02 *LR_dnDSA+ 4.90 (1.82–13.19) 0.002 3.51 (1.25–9.85) 0.017 *LR_dnDSA+/HR_dnDSA+ 4.90 (1.82–13.19) 0.002 4.09 (1.45–11.54) 0.008 LR_dnDSA+/HR_dnDSA− NA LR_dnDSA−/HR_dnDSA+ NA *Independent models due to collinearity. F, female; ESRD, end-stage renal disease; rATG, rabbit anti-thymoglobulin; CNI, calcineurin inhibitors; DGF, delayed graft function; LR, low resolution; HR, high resolution; MM, mismatch; eGFR, estimated glomerular filtration rate; BPAR, biopsy-proven acute rejection; dnDSA, de novo donor-specific antibody. Bold values highlights all p values <0.05. NA, Not applicable. dnDSA, seems to run into some relevant pitfalls and must be transplantation to precisely rule out the presence of preformed discouraged especially if EpMM are used to classify patients in and de novo serological anti-donor immunity, respectively, clinical trials or for clinical decision-making. which may ultimately affect graft outcomes. Importantly, NGS technology for HLA genotyping provides HLA data up to the four‐field level (including information on synonymous substitutions and changes in non-coding regions). Data availability statement In our study, similar to most recent reports in this field, we focused on the accurate characterization of two-field (four digits) The raw data supporting the conclusions of this article will typing giving information on the complete protein elements of be made available by the authors, without undue reservation. the HLA molecule. Nonetheless, the clinical application of the knowledge of the third/fourth field needs to be further explored in solid-organ transplantation (21). Ethics statement In the era of modern medicine, the individualization of immunosuppressive treatment and diagnostic procedures is This study was reviewed and approved by Bellvitge highly recommended and different consortia are performing University Hospital. The patients/participants provided their clinical interventional trials in this direction (EUtrain: written informed consent to participate in this study. NCT03652402; Outsmart: EudraCT 2012–004308-36; BIOIMMUN: EudraCT 2017-002293-39). However, any implementation in clinical practice of biomarkers used to Author contributions guide medical decisions should rely on the highest technological standards with the best accuracy when defining OB designed the study. MM, FB, PR, OV, MG, EM, AS, LH, high- or low-risk patients. According to our results, the use of PH, CG-G, SB, JG and OB had enrolled patients in the study. HR complete HLA genotyping significantly improves the correct MM, AP, FB, PR, OV, MG, EP, EM, JZ, AS, NL, LH, PH, CGG identification of DSA, both prior to and after kidney and SB collected clinical and immunological data. MM, AP, EC, Frontiers in Immunology 10 frontiersin.org Meneghini et al. 10.3389/fimmu.2022.924825 EP, AT, LD, JG and OB participated in data analysis. MM, AP, standard operating procedures with the appropriate approval of EC and OB wrote the manuscript. All authors contributed to the the Ethics and Scientific Committees. article and approved the submitted version. Conflict of interest Funding The authors declare that the research was conducted in the This work was supported by the Biomarker-Driven absence of any commercial or financial relationships that could Immunosuppression Minimization (BIO-DRIM) Consortium be construed as a potential conflict of interest. (EU FP7-health, grant agreement number 305147; FP7/2012- 2017) and by the Instituto de Salud Carlos III (ISCIII) (grant numbers ICI14/00242, PI16/01321, and PI19/01710), co-funded Publisher’s note by European Regional Development Fund (ERDF), a way to build Europe. Also, this work was partly supported by the All claims expressed in this article are solely those of the SLT002/16/00183 grant, from the Department of Health of the authors and do not necessarily represent those of their affiliated Generalitat de Catalunya by the call “Acció instrumental de organizations, or those of the publisher, the editors and the programes de recerca orientats en l’àmbit de la recerca i la reviewers. Any product that may be evaluated in this article, or innovació en salut”. claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Acknowledgments We acknowledge the assistance of our lab technicians for Supplementary material careful management of all biological samples. Samples from patients included in this study were provided by the Biobank The Supplementary Material for this article can be found HUB-ICO-IDIBELL (PT17/0015/0024), integrated in the online at: https://www.frontiersin.org/articles/10.3389/ Spanish Biobank Network, and they were processed following fimmu.2022.924825/full#supplementary-material References 1. Nickerson PW. What have we learned about how to prevent and treat rejection, and graft failure after kidney transplantation: An observational cohort antibody-mediated rejection in kidney transplantation? Am J Transplant (2020) 20 study. J Am Soc Nephrol (2020) 31(9):2193–204. doi: 10.1681/ASN.2020010019 Suppl 4(S4):12–22. doi: 10.1111/AJT.15859 10. Kiberd BA, Miller A, Martin S, Tennankore KK. De novo donor-specific 2. McCaughan JA, Tinckam KJ. 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