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B cells play a central role in antibody-mediated rejection and certain autoimmune diseases. However, B cell-targeted therapy such as anti-CD20 B cell-depleting antibody (aCD20) has yielded mixed results in improving outcomes. In this study, we investigated whether an accelerated B cell reconstitution leading to aCD20 depletion resistance could account for these discrepancies. Using a transplantation model, we found that antigen-independent inflammation, likely through toll-like receptor (TLR) signaling, was sufficient to mitigate B cell depletion. Secondary lymphoid organs had a quicker recovery of B cells when compared to peripheral blood. Inflammation altered the pharmacokinetics (PK) and pharmacodynamics (PD) of aCD20 therapy by shortening drug half-life and accelerating the reconstitution of the peripheral B cell pool by bone marrow-derived B cell precursors. IVIG (intravenous immunoglobulin) coadministration also shortened aCD20 drug half-life and led to accelerated B cell recovery. Repeated aCD20 dosing restored B cell depletion and delayed allograft rejection, especially B cell-dependent, antibody-independent allograft rejection. These data demonstrate the importance of further clinical studies of the PK/PD of monoclonal antibody treatment in inflammatory conditions. The data also highlight the disconnect between B cell depletion on peripheral blood compared to secondary lymphoid organs, the deleterious effect of IVIG when given with aCD20 and the relevance of redosing of aCD20 for effective B cell depletion in alloimmunity.

Background: A number of studies have demonstrated the role of CX3CR1 in regulating the migration of monocytes into peripheral tissue and their transformation into DC. No data are yet available on the importance of chemokine pathways in regulating homeostasis of dendritic cell (DC) in heart transplants. Recently, we showed that recipients of heart allografts from CXC3R1-/- donors show longer survival. To dissect the role of CX3CR1 signaling in the homeostasis of heart dDC, we have developed and tested a novel in vivo imaging tool in CX3CR1GFP/+ DC (B6 background) heart graft into BALB/c recipient model. Results: Majority of GFP positive cells located in the middle of cardiac myocyte and their shapes were stretching and still roundish in the early phase of post transplant (3 and 24hours). However, images from 72hours at cardiac graft showed many of GFP positive cells move to vessel areas. In addition, significant immunological events such as GFP positive cell exiting from cardiac myocyte and changes of GFP positive cell motility and shape were detected. GFP positive cells were detected in the vasculature and lymph nodes. Only 1 GFP positive cell was observed in three lymph nodes (2 mesenteric, 1 inguinal) (72hours). Conclusions: Current data will define the function of dDC in regulating alloimmune responses in vivo and provide information to develop novel strategies designed to achieve durable tolerance and prevent chronic rejection.

Background We have previously found that CD4+CD25+ regulatory T cells (Tregs) can adoptively transfer tolerance after its induction with costimulatory blockade in a mouse model of murine cardiac allograft transplantation. In these experiments, we tested an hypothesis with three components: (1) the Tregs that transfer tolerance have the capacity for linked suppression, (2) the determinants that stimulate the Tregs are expressed by the indirect pathway, and (3) the donor peptides contributing to these indirect determinants are derived from donor major histocompatibility complex (MHC) antigens (Ags). Methods First heart transplants were performed from the indicated donor strain to B10.D2 recipients along with costimulatory blockade treatment (250 μg i.p. injection of MR1 on day 0 and 250 μg i.p. injection of CTLA-4 Ig on day 2). At least 8 weeks later, a second heart transplant was performed to a new B10.D2 recipient who had been irradiated with 450 cGy. This recipient was given 40 × 106 naive B10.D2 spleen cells + 40 × 106 B10.D2 spleen cells from the first (tolerant) recipient. We performed three different types of heart transplants using various donors. Results (1) Tregs suppress the graft rejection in an Ag-specific manner. (2) Tregs generated in the face of MHC disparities suppress the rejection of grafts expressing third party MHC along with tolerant MHC. Conclusion The limits of linkage appear to be quantitative and not universally determined by either the indirect pathway or by peptides of donor MHC Ags.

Ligands of the B7 family provide both positive and negative costimulatory signals to the CD28 family of receptors on T lymphocytes, the balance of which determines the immune response. B7-H3 is a member of the B7 family whose function in T-cell activation has been the subject of some controversy: in autoimmunity and tumor immunity, it has been described as both costimulatory and coinhibitory, while in transplantation, B7-H3 signaling is thought to contribute to graft rejection. However, we now demonstrate results to the contrary. Signaling through a putative B7-H3 receptor prolonged allograft survival in a fully MHC-mismatched cardiac model and promoted a shift toward a Th2 milieu; conversely, B7-H3 blockade, achieved by use of a blocking antibody, resulted in accelerated rejection, an effect associated with enhanced IFN-γ production. Finally, graft prolongation achieved by CTLA4 Ig was shortened both by B7-H3 blockade and the absence of recipient B7-H3. These findings suggest a coinhibitory role for B7-H3. However, experience with other CD28/B7 family members suggests that immune redundancy plays a crucial role in determining the functions of various pathways. Given the abundance of conflicting data, it is plausible that, under differing conditions, B7-H3 may have both positive and negative costimulatory functions.

Aim Mandatory HLA-DPB and DQA typing has recently been instituted for deceased organ donors. While these loci are not routinely used for organ allocation or listed as unacceptable antigens, if they are in the future, consistent typings will be important. We sought to determine the current state of compliance with the mandatory typing as well as to analyze repeat typings for discrepant results. Methods We examined 162,598 HLA typings submitted to UNOS on deceased donors from 10/1/87 through 12/31/17. Data was obtained with permission from UNOS as a SAS “STAR” file and analyzed with JMP® (SAS Institute). Results Prior to January, 2016, just fewer than ten percent of the 146,896 donors were typed for DPB, DPA, DQA while typing results were submitted for DPB and DQA for virtually all donors subsequently and in 76% DPA was also submitted. In the era prior to 1/1/16, less than 3% of typings were repeated. This increased to 30–36% in the current era (Table 1). The total number of discrepancies for DPB typings was 152 out of 5,495 typings that were repeated (2.8%). The most common discrepancies in DPB typing were between DPB*104:01 and 03:01 (N = 47), DPB*04:02 and 105:01(N = 29), and DPB*04:02 with 04:01 (N = 13). A number of other discrepancies were observed involving DPB*03:01, 04:02, 104:01, 105:01 and 04:01, which accounted for 71% of the DPB discrepancies. Download : Download high-res image (223KB) Download : Download full-size image Conclusions HLA-DPB and DQA typing of deceased donors is now mandatory. There has been excellent compliance with submission of typing results. Over three quarters of typings also include DPA results. The large proportion of repeat typings has permitted an analysis of both the rate of discrepancies and which antigens account for most of them. If these loci are to be considered for allocation, further analysis of the nature and reasons for these discrepancies will be needed to reduce the error rate.

Aim Currently, there are two different approaches to calculating cPRA. The first, used in USA since 2009, is the expectation maximization (EM) algorithm. The second, utilized in Europe/Canada, is to simply observe the percentage of donors with a particular antigen (“count method”). Recently, the UNOS/OPTN Histocompatibility Committee has been re-evaluating the optimal method for determining cPRA. This has been driven by the need to consider incorporating DP (and other) locus antibodies. The benefit of the EM method, based on haplotype frequencies, is to estimate population frequencies that would include unobserved, rare phenotypes. However, because DP is not in linkage disequilibrium, it may no longer be feasible to use. Here, we evaluate the use of the count method in comparison with the EM approach for determining HLA antigen frequencies in the U.S. donor population. Methods Using the UNOS/OPTN data, we evaluated HLA typings from 39,568 deceased donors from 1/2015–1/2018. We then compared the observed antigen frequencies (count method) with those derived from the UNet cPRA calculator (EM method). Results See table. Download : Download high-res image (81KB) Download : Download full-size image Conclusions There was high concordance between the two methods of calculating cPRA in antigen frequencies within the A, B, and DR loci. Instances where there were large discrepancies were primarily due to parent antigens that were subsequently split; the UNet cPRA was based upon a pool of donors from 2007–9. This suggests, at the very least, that updates to the cPRA calculator are needed. Since DPB is not in linkage disequilibrium with the other loci, thereby negating our ability to use the EM algorithm, we suggest a new updated cPRA calculator be based upon the count method of calculating antigen frequencies.

Aim Single antigen bead (SAB) assay is used to test the presence of antibodies against HLA antigens including HLA-DQ. Each SAB DQ bead is comprised of an alpha and a beta chain representative of an HLA-DQ antigen. A positive result represents reactivity to either or both chains. The aim of this report is to evaluate the frequency of HLA-DQ alpha antibodies in transplant candidates known to have Class II antibody. Methods Class II SAB data (One Lambda Inc.) was collected from 2346 transplant candidates at Brigham and Women’s Hospital from 6/9/2012 to 1/15/2014. The reactivity to HLA-DQ alpha was considered positive (MFI >3000) if all the beads containing a specific HLA-DQ alpha were reactive but the beads with corresponding HLA-DQ beta chain were negative. For example, the sera which were considered positive for HLA DQA1*03:02, had positive reaction with two beads containing DQA1*03:02, [DQA1*03:02, DQB1*03:02] and [DQA1*03:02, DQB1*03:03], but negative reaction with five beads positive for either DQB1*03:02 or DQB1*03:03 combined with DQA1 chains other than DQA1*03:02. Results Of the 29 HLA-DQ assay beads, 12 different HLA-DQ alpha chains were combined with different HLA-DQ beta chains. Sixteen (16/2346, 0.69%) sera reacted with beads specific for DQA1*03:02. These sera reacted with the alpha chain in combination with either DQB1*03:02 or DQB1*03:03. A similar pattern could be observed with sera (17/2346, 0.72%) that had specific reactivity to DQA1*02:01. Interestingly, none of the sera appeared to react selectively with DQA1*01:01, DQA1*01:02, DQA1*03:01, or DQA1*05:01. Although reactions with beads coated with DQA1*01:03, DQA1*03:03, DQA1*04:01, DQA1*05:03, DQA1*05:05, or DQA1*06:01 were present, they could not be attributed to DQA1 as the number of reactions or beads were not sufficient to rule out reactivity to DQB1. Out of the 33 patients who showed reactivity to either DQA1*03:02 or DQA1*02:01, only three (9.1%) had reactivity exclusively to the HLA-DQ alpha chain with no reactivity to any other HLA class II antigen. Conclusions The frequency of antibodies which appear to have HLA-DQ alpha specificity in transplant candidates is low (1.4%). Our results imply that a large number of sensitized patients will have to be studied in order to determine the clinical significance of antibodies to DQAlpha.

B7 ligands deliver both costimulatory and coinhibitory signals to the CD28 family of receptors on T lymphocytes, the balance between which determines the ultimate immune response. Although B7-H4, a recently discovered member of the B7 family, is known to negatively regulate T cell immunity in autoimmunity and cancer, its role in solid organ allograft rejection and tolerance has not been established. Targeting the B7-H4 molecule by a blocking antibody or use of B7-H4(-/-) mice as recipients of fully MHC-mismatched cardiac allografts did not affect graft survival. However, B7-H4 blockade resulted in accelerated allograft rejection in CD28-deficient recipients. B7-1/B7-2-double-deficient recipients are truly independent of CD28/CTLA-4:B7 signals and usually accept MHC-mismatched heart allografts. Blockade of B7-H4 in these mice also precipitated rejection, demonstrating regulatory function of this molecule independent of an intact CD28/CTLA-4:B7 costimulatory pathway. Accelerated allograft rejection was always accompanied by increased frequencies of alloreactive IFN-γ-, IL-4- and Granzyme B-producing splenocytes. Finally, intact recipient, but not donor, B7-H4 is essential for prolongation of allograft survival by blocking CD28/CTLA4:B7 pathway using CTLA4-Ig. These data are the first to provide evidence of the regulatory effects of B7-H4 in alloimmune responses in a murine model of solid organ transplantation.

Apart from their role in humoral immunity, B cells can exhibit IL-10-dependent regulatory activity (Bregs). These regulatory subpopulations have been shown to inhibit inflammation and allograft rejection. However, our understanding of Bregs has been hampered by their rarity, lack of a specific marker, and poor insight into their induction and maintenance. We previously demonstrated that T cell immunoglobulin mucin domain-1 (TIM-1) identifies over 70% of IL-10-producing B cells, irrespective of other markers. We now show that TIM-1 is the primary receptor responsible for Breg induction by apoptotic cells (ACs). However, B cells that express a mutant form of TIM-1 lacking the mucin domain (TIM-1(Δmucin) ) exhibit decreased phosphatidylserine binding and are unable to produce IL-10 in response to ACs or by specific ligation with anti-TIM-1. TIM-1(Δmucin) mice also exhibit accelerated allograft rejection, which appears to be due in part to their defect in both baseline and induced IL-10(+) Bregs, since a single transfer of WT TIM-1(+) B cells can restore long-term graft survival. These data suggest that TIM-1 signaling plays a direct role in Breg maintenance and induction both under physiological conditions (in response to ACs) and in response to therapy through TIM-1 ligation. Moreover, they directly demonstrate that the mucin domain regulates TIM-1 signaling.

Aim DNA library preparation for next generation sequencing (NGS) consists of several hundred material transfer and wash steps, which are time consuming, labor intensive, and increase the risk of repetitive strain injury. Robotic liquid handlers can automate and standardize library preparation, but few HLA laboratories have experience with high-complexity robotic platforms. We sought to evaluate the use of robotics for library preparation in conjunction with a NGS based HLA typing assay. Methods A Beckman Coulter Biomek NXp Span-8 robotic liquid handler was acquired along with the vendor supplied robotics method for the Illumina TruSight HLA v2 sequencing panel. The robotics method was first optimized with a series of runs using water, 50% glycerol, 85% ethanol, and AMPure beads. Next, DNA and reagents were run to identify sample viscosity and reagent issues. After each run, issues were communicated to the vendor for method improvement. The finalized method was run on 78 DNA samples over seven runs to assess the quality of normalization, pooling, sequencing, and reproducibility of results. Results Robotic issues were encountered with pipette calibration, labware definitions, proper labware selection, and efficiency. To add complexity, these issues had subtle compounding effects on the overall success of the method, which required that each be addressed individually and in detail. Eleven versions of the method were subsequently produced and tested to ensure robustness and consistency. The finalized method produced consistent high quality sequencing metrics on the NGS typing platform which agreed with the known HLA typing results. Conclusions Detailed documentation of issues by lab staff and clear communication with the vendor allowed for a rapid and iterative improvement of the robotics method. The lessons learned during the implementation process formed a roadmap that allowed for successful implementation of a robotics platform for NGS based HLA typing.

Aim Chimerism testing is a valuable tool for determining the proportion of donor vs. recipient DNA in a sample. The commonly used polymerase chain reaction amplifications of short tandem repeats assay (Promega, Madison, WI) produces results for 21 loci, but only 9 loci are used in manual calculations. We sought to improve the tedious and time consuming process of manually calculating a patient’s percent chimerism by developing an automated chimerism calculator for rapid and accurate chimerism calculations based off of all 21 loci. Methods The calculator was developed using Microsoft Excel Macros and is able to report the percent donor chimerism +/− the margin of error. To determine whether precision is improved by using 21 loci, the results of a 21 loci analysis and a 9 loci analysis were compared in 111 patient samples. Additionally, each of the 21 loci was evaluated for its average deviation from the mean. Finally, 298 patient samples were analyzed by the program in order to determine if precision is equal at all chimerism percentages. Results When the same loci are analyzed, the chimerism calculator results are identical to the manual calculations, but completed in 10% of the time. The analysis of patient samples using 21 and 9 loci yielded, on average, chimerism percentages within 2.0% of each other. The average margin of error using 9 loci for analysis is 2.41% compared to 0.8% using all 21 loci. Among the 21 loci, the average deviation from the mean was found to range from 8.9% and 5.9%. Finally, we found that the average margin of error for patients between 90 and 100 percent donor chimerism is 0.19% while patients between 30 and 40 percent donor chimerism have 10.1% margin of error. Conclusions The chimerism calculator allows for routine use of all 21 STR loci with significantly reduced analysis time, 30% less margin of error, and an informative statistical analysis. In various laboratory settings, similar methods of computer assisted chimerism analysis can be easily implemented.

Aim Accurate classification of serologically-distinct antigens (Ag) is critical in organ allocation, and nowadays it is possible to define anti-HLA antibody specificity to the allelic level. We examined class I antibodies (Ab) for allelic specificities that may be serologically distinct and evaluated its impact on crossmatch (XM) results and organ allocation. Methods 6726 sera were tested for anti-HLA Ab using LABScreen Single Ag assay (One Lambda), in which 17 class I HLA Ag are represented by more than one allele. Discordance in MFI values between the two allelic beads was examined as a categorical variable to mimic clinical practice, and as a continuous variable (MFI value) to better reflect biological plausibility. To evaluate the significance of an allele-specific Ab on XM results, we examined an unbiased cohort of deceased donor-candidate testing (125,828 CDC XMs between 2014 and 2017). In our lab, all candidates within a blood group have a CDC XM performed, regardless of whether they have donor-specific antibody (DSA). This uniquely allows us to examine whether a candidate with an allele-specific DSA, who has already been excluded from the match run, would indeed have a positive XM against a donor who has a different allele. Statistical analyses were performed using JMP12Pro (SAS Institute). Results 1. The incidence of discordance between the two allelic beads varied depending on whether MFI values were considered as continuous vs categorical variables. 2. The presence of allele-specific Ab for rare alleles was out of proportion to their frequencies in the population. 3. The presence of Ab against only the rare allele was a poor predictor of a positive CDC XM, with a positive predictive value of 0–7% compared with 52.5% if the candidate had DSA against an A or B locus Ag. Conclusions 9 out of 17 Class I HLA antigens had potential allele-specific reactivity, meaning that candidates with antibody selectivity against rare alleles may be unnecessarily excluded from many organ offers based on definition of unacceptable antigens by serological equivalence. Conversely, for centers relying on virtual-XM, prematurely defining alleles as new serological splits could unfortunately allow transplants for which the recipient has DSA. Further testing is needed to rigorously confirm these allele-specific reactivity patterns.

The proinflammatory cytokine IL-6 plays an important role in controlling T-cell differentiation, especially the development of Th17 and regulatory T cells. To determine the function of IL-6 in regulating allograft rejection and tolerance, BALB/c cardiac grafts were transplanted into wild-type or IL-6-deficient C57BL/6 mice. We observed that production of IL-6 and IFN-γ was upregulated during allograft rejection in untreated wild-type mice. In IL-6-deficient mice, IFN-γ production was greater than that observed in wild-type controls, suggesting that IL-6 production affects Th1/Th2 balance during allograft rejection. CD28-B7 blockade by CTLA4-Ig inhibited IFN-γ production in C57BL/6 recipients, but had no effect on the production of IL-6. Although wild-type C57BL/6 recipients treated with CTLA4-Ig rejected fully MHC-mismatched BALB/c heart transplants, treatment of IL-6-deficient mice with CTLA4-Ig resulted in graft acceptance. Allograft acceptance appeared to result from the combined effect of costimulatory molecule blockade and IL-6-deficiency, which limited the differentiation of effector cells and promoted the migration of regulatory T cells into the grafts. These data suggest that the blockade of IL-6, or its signaling pathway, when combined with strategies that inhibit Th1 responses, has a synergistic effect on the promotion of allograft acceptance. Thus, targeting the effects of IL-6 production may represent an important part of costimulation blockade-based strategies to promote allograft acceptance and tolerance.

Fetomaternal tolerance has been shown to depend both on regulatory T cells (Tregs) and negative signals from the PD1–PDL1 costimulatory pathway. More recently, IL-17–producing T cells (Th17) have been recognized as a barrier in inducing tolerance in transplantation. In this study, we investigate the mechanisms of PDL1-mediated regulation of fetomaternal tolerance using an alloantigen-specific CD4+ TCR transgenic mouse model system (ABM-tg mouse). PDL1 blockade led to an increase in embryo resorption and a reduction in litter size. This was associated with a decrease in Tregs, leading to a lower Treg/effector T cell ratio. Moreover, PDL1 blockade inhibited Ag-specific alloreactive T cell apoptosis and induced apoptosis of Tregs and a shift toward higher frequency of Th17 cells, breaking fetomaternal tolerance. These Th17 cells arose predominantly from CD4+Foxp3− cells, rather than from conversion of Tregs. Locally in the placenta, similar decrease in regulatory and apoptotic markers was observed by real-time PCR. Neutralization of IL-17 abrogated the anti-PDL1 effect on fetal survival rate and restored Treg numbers. Finally, the adoptive transfer of Tregs was also able to improve fetal survival in the setting of PDL1 blockade. This is to our knowledge the first report using an alloantigen-specific model that establishes a link between PDL1, Th17 cells, and fetomaternal tolerance.

Since their discovery in 2001, the T-cell immunoglobulin mucin (TIM) family members have been shown to play important roles in the regulation of immune responses. The TIM family comprises of eight genes in the mouse, three of which are conserved in humans (TIM-1, TIM-3 and TIM-4). Initially, TIM-1 and TIM-3 were thought to be expressed solely on T cells. However, emerging data suggest a much broader expression pattern where their presence on APCs confers differing functions, including the ability to mediate phagocytosis. In contrast, TIM-4 is exclusively expressed on APCs. Together, the TIM molecules provide a functional repertoire for determining the fate of T-cell activation and differentiation. To date, much of the knowledge about the TIM family members has been garnered from the models of asthma, allergy and autoimmunity. More recently, data from experimental models of transplantation demonstrate that TIM family members also have a key role in alloimmunity. This review will serve to highlight the emerging data regarding this unique family of molecules and to identify their potential in transplantation tolerance.

The PD1:PDL1 pathway is an essential negative costimulatory pathway that plays a key role in regulating the alloimune response. PDL1 is expressed not only on antigen-presenting cells (APCs) but also cardiac endothelium. In this study, we investigated the importance of PDL1 expression on donor cardiac allograft in acquired transplantation tolerance in a fully MHC-mismatched model. We generated PDL1 chimeric mice on B6 background that expressed PDL1 on either hematopoietic cells or nonhematopoietic cells of the heart. Sham animals were used as controls. These hearts were then transplanted into BALB/c recipients and treated with CTLA4-Ig to induce tolerance. Cardiac endothelium showed significant expression of PDL1, which was upregulated upon transplantation. While the absence of PDL1 on hematopoietic cells of the heart resulted in delayed rejection and prevented long-term tolerance in most but not all recipients, we observed an accelerated and early graft rejection of all donor allografts that lacked PDL1 on the endothelium. Moreover, PDL1-deficient endothelium hearts had significant higher frequency of IFN-γ-producing alloreactive cells as well as higher frequency of CD8(+) effector T cells. These findings demonstrate that PDL1 expression mainly on donor endothelium is functionally important in a fully allogeneic mismatched model for the induction of cardiac allograft tolerance.