Belatacept with time-limited tacrolimus coimmunosuppression modifies the 3-year risk of eplet mismatch in kidney transplantation.

Solid organ transplant donor-recipient eplet mismatch has been correlated with donor-specific antibody (DSA) formation, antibody-mediated rejection, and overall rejection rates. However, studies have been predominantly in patients on tacrolimus-based immunosuppression regimens and have not fully explored differences in ethnically and racially diverse populations. Evidence indicates that patients on belatacept have lower rates of DSA formation, suggesting mediation of the immunogenicity of mismatched human leukocyte antigen polymorphisms. We performed a retrospective, single-center analysis of class II eplet disparity in a cohort of kidney transplant recipients treated using belatacept with tacrolimus induction (Bela/TacTL) or tacrolimus regimens between 2016 and 2019. Bela/TacTL (n = 294) and tacrolimus (n = 294) cohorts were propensity score-matched with standardized difference <0.15. Single-molecule eplet risk level was associated with immune event rates for both groups. In Cox regression analysis stratified by eplet risk level, Bela/TacTL immunosuppression was associated with a decreased rate of DSA (hazard ratio [HR] = 0.4), antibody-mediated rejection (HR = 0.2), and rejection (HR = 0.45). In the low-risk group, cumulative graft failure was lower for patients on Bela/TacTL (P < .02). Analysis of eplet mismatch burden may be a useful adjunct in identifying high-risk populations with increased immunosuppression requirements and should encourage the design of allocation rules to incentivize lower-risk pairings without negatively impacting equity in access.

Incidence of Pediatric Celiac Disease Varies by Region.

INTRODUCTION: The Environmental Determinants of Diabetes in the Young study follows an HLA risk selected birth cohort for celiac disease (CD) development using a uniform protocol. Children under investigation come from 6 different regions within Europe and the United States. Our aim was to identify regional differences in CD autoimmunity and CD cumulative incidence for children born between 2004 and 2010. METHODS: Children (n = 6,628) with DQ2.5 and/or DQ8.1 were enrolled prospectively from birth in Georgia, Washington, Colorado, Finland, Germany, and Sweden. Children underwent periodic study screening for tissue transglutaminase antibodies and then CD evaluation per clinical care. Population-specific estimates were calculated by weighting the study-specific cumulative incidence with the population-specific haplogenotype frequencies obtained from large stem cell registries from each site. RESULTS: Individual haplogenotype risks for CD autoimmunity and CD varied by region and affected the cumulative incidence within that region. The CD incidence by age 10 years was highest in Swedish children at 3%. Within the United States, the incidence by age 10 years in Colorado was 2.4%. In the model adjusted for HLA, sex, and family history, Colorado children had a 2.5-fold higher risk of CD compared to Washington. Likewise, Swedish children had a 1.4-fold and 1.8-fold higher risk of CD compared with those in Finland and Germany, respectively. DISCUSSION: There is high regional variability in cumulative incidence of CD, which suggests differential environmental, genetic, and epigenetic influences even within the United States. The overall high incidence warrants a low threshold for screening and further research on region-specific CD triggers.

HLA amino acid Mismatch-Based risk stratification of kidney allograft failure using a novel Machine learning algorithm.

OBJECTIVE: While associations between HLA antigen-level mismatches (Ag-MM) and kidney allograft failure are well established, HLA amino acid-level mismatches (AA-MM) have been less explored. Ag-MM fails to consider the substantial variability in the number of MMs at polymorphic amino acid (AA) sites within any given Ag-MM category, which may conceal variable impact on allorecognition. In this study we aim to develop a novel Feature Inclusion Bin Evolver for Risk Stratification (FIBERS) and apply it to automatically discover bins of HLA amino acid mismatches that stratify donor-recipient pairs into low versus high graft survival risk groups. METHODS: Using data from the Scientific Registry of Transplant Recipients, we applied FIBERS on a multiethnic population of 166,574 kidney transplants between 2000 and 2017. FIBERS was applied (1) across all HLA-A, B, C, DRB1, and DQB1 locus AA-MMs with comparison to 0-ABDR Ag-MM risk stratification, (2) on AA-MMs within each HLA locus individually, and (3) using cross validation to evaluate FIBERS generalizability. The predictive power of graft failure risk stratification was evaluated while adjusting for donor/recipient characteristics and HLA-A, B, C, DRB1, and DQB1 Ag-MMs as covariates. RESULTS: FIBERS's best-performing bin (on AA-MMs across all loci) added significant predictive power (hazard ratio = 1.10, Bonferroni adj. p < 0.001) in stratifying graft failure risk (where low-risk is defined as zero AA-MMs and high-risk is one or more AA-MMs) even after adjusting for Ag-MMs and donor/recipient covariates. The best bin also categorized more than twice as many patients to the low-risk category, compared to traditional 0-ABDR Ag mismatching (∼24.4% vs âˆ¼ 9.1%). When HLA loci were binned individually, the bin for DRB1 exhibited the strongest risk stratification; relative to zero AA-MM, one or more MMs in the bin yielded HR = 1.11, p < 0.005 in a fully adjusted Cox model. AA-MMs at HLA-DRB1 peptide contact sites contributed most to incremental risk of graft failure. Additionally, FIBERS points to possible risk associated with HLA-DQB1 AA-MMs at positions that determine specificity of peptide anchor residues and HLA-DQ heterodimer stability. CONCLUSION: FIBERS's performance suggests potential for discovery of HLA immunogenetics-based risk stratification of kidney graft failure that outperforms traditional assessment.

ABO-adjusted calculated panel reactive antibody (cPRA): A unified metric for immunologic compatibility in kidney transplantation.

Implementation of the kidney allocation system in 2014 greatly reduced access disparity due to human leukocyte antigen (HLA) sensitization. To address persistent disparity related to candidate ABO blood groups, herein we propose a novel metric termed "ABO-adjusted cPRA," which simultaneously considers the impact of candidate HLA and ABO sensitization on the same scale. An ethnic-weighted ABO-adjusted cPRA value was computed for 190 467 candidates on the kidney waitlist by combining candidate's conventional HLA cPRA with the remaining fraction of HLA-compatible donors that are ABO-incompatible. Consideration of ABO sensitization resulted in higher ABO-adjusted cPRA relative to conventional cPRA by HLA alone, except for AB candidates since they are not ABO-sensitized. Within cPRA Point Group = 99%, 43% of the candidates moved up to ABO-adjusted cPRA Point Group = 100%, though this proportion varied substantially by candidate blood group. Nearly all O and most B candidates would have elevated ABO-adjusted cPRA values above this policy threshold for allocation priority, but relatively few A candidates displayed this shift. Overall, ABO-adjusted cPRA more accurately measures the proportion of immune-compatible donors compared with conventional HLA cPRA, especially for highly sensitized candidates. Implementation of this novel metric could enable the development of allocation policies permitting more ABO-compatible transplants without compromising equity.

Multiplicative fitness, rapid haplotype discovery, and fitness decay explain evolution of human MHC.

The major histocompatibility complex (MHC) is a central component of the vertebrate immune system and hence evolves in the regime of a host-pathogen evolutionary race. The MHC is associated with quantitative traits which directly affect fitness and are subject to selection pressure. The evolution of haplotypes at the MHC HLA (HLA) locus is generally thought to be governed by selection for increased diversity that is manifested in overdominance and/or negative frequency-dependent selection (FDS). However, recently, a model combining purifying selection on haplotypes and balancing selection on alleles has been proposed. We compare the predictions of several population dynamics models of haplotype frequency evolution to the distributions derived from 6.59-million-donor HLA typings from the National Marrow Donor Program registry. We show that models that combine a multiplicative fitness function, extremely high haplotype discovery rates, and exponential fitness decay over time produce the best fit to the data for most of the analyzed populations. In contrast, overdominance is not supported, and population substructure does not explain the observed haplotype frequencies. Furthermore, there is no evidence of negative FDS. Thus, multiplicative fitness, rapid haplotype discovery, and rapid fitness decay appear to be the major factors shaping the HLA haplotype frequency distribution in the human population.

Stem cell donor HLA typing improves CPRA in kidney allocation.

The Organ Procurement and Transplantation Network (OPTN) Kidney Allocation System provides a priority to sensitized candidates based on the calculated panel reactive antibody (CPRA) value. The human leukocyte antigen (HLA) haplotype reference panel used for calculation of the CPRA by the United Network for Organ Sharing (UNOS), the OPTN contractor, has limitations. We derived a novel panel from the National Marrow Donor Program HLA haplotype data set and compared the accuracy of CPRA values generated with this panel (NMDP-CPRA) to those generated from the UNOS panel (UNOS-CPRA), using predicted and actual deceased donor kidney offers for a cohort of 24 282 candidates. The overall accuracy for kidney offers was similar using NMDP-CPRA and UNOS-CPRA. Accuracy was slightly higher for NMDP-CPRA than UNOS-CPRA for candidates in several highly sensitized CPRA categories, with deviations in linkage disequilibrium for Caucasians and the smaller size of the UNOS panel as contributing factors. HLA data derived from stem cell donors yields CPRA values that are comparable to those derived from deceased kidney donors while improving upon several problems with the current reference panel. Consideration should be given to using stem cell donors as the reference panel for calculation of CPRA to improve equity in kidney transplant allocation.

GRIMM: GRaph IMputation and matching for HLA genotypes.

MOTIVATION: For over 10 years allele-level HLA matching for bone marrow registries has been performed in a probabilistic context. HLA typing technologies provide ambiguous results in that they could not distinguish among all known HLA alleles equences; therefore registries have implemented matching algorithms that provide lists of donor and cord blood units ordered in terms of the likelihood of allele-level matching at specific HLA loci. With the growth of registry sizes, current match algorithm implementations are unable to provide match results in real time. RESULTS: We present here a novel computationally-efficient open source implementation of an HLA imputation and match algorithm using a graph database platform. Using graph traversal, the matching algorithm runtime is practically not affected by registry size. This implementation generates results that agree with consensus output on a publicly-available match algorithm cross-validation dataset. AVAILABILITY AND IMPLEMENTATION: The Python, Perl and Neo4j code is available at https://github.com/nmdp-bioinformatics/grimm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Reducing ethnic disparity in access to high-quality HLA-matched cord blood units for transplantation: analysis of the Canadian Blood Services' Cord Blood Bank inventory.

BACKGROUND: Launched in 2013, Canadian Blood Services' Cord Blood Bank (CBS' CBB) has built a high-quality, ethnically diverse cord blood repository that aims to reduce ethnic disparity in accessing suitable units for transplantation. METHODS AND RESULTS: As of December 2016, 2000 units have been banked. The self-reported maternal ethnicity was 58% non-Caucasian. Overall, 26% of units were classified as multi-ethnicity with Caucasian (84%) most frequently observed in combination with Asian, First Nations (predominant indigenous peoples in Canada south of the Arctic Circle), or African ethnicity. Utilization scores that incorporate total nucleated and CD34+ cell counts in the CBS' CBB were associated with greater likelihood of utilization compared with the international inventory of units (p < 0.05). The distribution of utilization scores was similar for Caucasians compared with non-Caucasians (p < 0.05). Using HLA genotypes of cord blood units and their mothers, we determined probable ethnic assignments for each haplotype using HaploStats (National Marrow Donor Program). Significant increases in HLA-match likelihoods are predicted for all ethnicities as the inventory grows to its target of 10,000 units and the gap in HLA-match likelihoods for Caucasian and non-Caucasian patients progressively declines. CONCLUSIONS: The CBS' CBB inventory is predicted to have high HLA-matching likelihoods across a broad spectrum of ethnic groups, improving access to high-quality stem cell products for all patients.

Modeling coverage gaps in haplotype frequencies via Bayesian inference to improve stem cell donor selection.

Regardless of sampling depth, accurate genotype imputation is limited in regions of high polymorphism which often have a heavy-tailed haplotype frequency distribution. Many rare haplotypes are thus unobserved. Statistical methods to improve imputation by extending reference haplotype distributions using linkage disequilibrium patterns that relate allele and haplotype frequencies have not yet been explored. In the field of unrelated stem cell transplantation, imputation of highly polymorphic human leukocyte antigen (HLA) genes has an important application in identifying the best-matched stem cell donor when searching large registries totaling over 28,000,000 donors worldwide. Despite these large registry sizes, a significant proportion of searched patients present novel HLA haplotypes. Supporting this observation, HLA population genetic models have indicated that many extant HLA haplotypes remain unobserved. The absent haplotypes are a significant cause of error in haplotype matching. We have applied a Bayesian inference methodology for extending haplotype frequency distributions, using a model where new haplotypes are created by recombination of observed alleles. Applications of this joint probability model offer significant improvement in frequency distribution estimates over the best existing alternative methods, as we illustrate using five-locus HLA frequency data from the National Marrow Donor Program registry. Transplant matching algorithms and disease association studies involving phasing and imputation of rare variants may benefit from this statistical inference framework.

HLA class I haplotype diversity is consistent with selection for frequent existing haplotypes.

The major histocompatibility complex (MHC) contains the most polymorphic genetic system in humans, the human leukocyte antigen (HLA) genes of the adaptive immune system. High allelic diversity in HLA is argued to be maintained by balancing selection, such as negative frequency-dependent selection or heterozygote advantage. Selective pressure against immune escape by pathogens can maintain appreciable frequencies of many different HLA alleles. The selection pressures operating on combinations of HLA alleles across loci, or haplotypes, have not been extensively evaluated since the high HLA polymorphism necessitates very large sample sizes, which have not been available until recently. We aimed to evaluate the effect of selection operating at the HLA haplotype level by analyzing HLA A~C~B~DRB1~DQB1 haplotype frequencies derived from over six million individuals genotyped by the National Marrow Donor Program registry. In contrast with alleles, HLA haplotype diversity patterns suggest purifying selection, as certain HLA allele combinations co-occur in high linkage disequilibrium. Linkage disequilibrium is positive (Dij'>0) among frequent haplotypes and negative (Dij'<0) among rare haplotypes. Fitting the haplotype frequency distribution to several population dynamics models, we found that the best fit was obtained when significant positive frequency-dependent selection (FDS) was incorporated. Finally, the Ewens-Watterson test of homozygosity showed excess homozygosity for 5-locus haplotypes within 23 US populations studied, with an average Fnd of 28.43. Haplotype diversity is most consistent with purifying selection for HLA Class I haplotypes (HLA-A, -B, -C), and was not inferred for HLA Class II haplotypes (-DRB1 and-DQB1). We discuss our empirical results in the context of evolutionary theory, exploring potential mechanisms of selection that maintain high linkage disequilibrium in MHC haplotype blocks.

HLA match likelihoods for hematopoietic stem-cell grafts in the U.S. registry.

BACKGROUND: Hematopoietic stem-cell transplantation (HSCT) is a potentially lifesaving therapy for several blood cancers and other diseases. For patients without a suitable related HLA-matched donor, unrelated-donor registries of adult volunteers and banked umbilical cord-blood units, such as the Be the Match Registry operated by the National Marrow Donor Program (NMDP), provide potential sources of donors. Our goal in the present study was to measure the likelihood of finding a suitable donor in the U.S. registry. METHODS: Using human HLA data from the NMDP donor and cord-blood-unit registry, we built population-based genetic models for 21 U.S. racial and ethnic groups to predict the likelihood of identifying a suitable donor (either an adult donor or a cord-blood unit) for patients in each group. The models incorporated the degree of HLA matching, adult-donor availability (i.e., ability to donate), and cord-blood-unit cell dose. RESULTS: Our models indicated that most candidates for HSCT will have a suitable (HLA-matched or minimally mismatched) adult donor. However, many patients will not have an optimal adult donor--that is, a donor who is matched at high resolution at HLA-A, HLA-B, HLA-C, and HLA-DRB1. The likelihood of finding an optimal donor varies among racial and ethnic groups, with the highest probability among whites of European descent, at 75%, and the lowest probability among blacks of South or Central American descent, at 16%. Likelihoods for other groups are intermediate. Few patients will have an optimal cord-blood unit--that is, one matched at the antigen level at HLA-A and HLA-B and matched at high resolution at HLA-DRB1. However, cord-blood units mismatched at one or two HLA loci are available for almost all patients younger than 20 years of age and for more than 80% of patients 20 years of age or older, regardless of racial and ethnic background. CONCLUSIONS: Most patients likely to benefit from HSCT will have a donor. Public investment in donor recruitment and cord-blood banks has expanded access to HSCT. (Funded by the Office of Naval Research, Department of the Navy, and the Health Resources and Services Administration, Department of Health and Human Services.).

HapLogic: A Predictive Human Leukocyte Antigen-Matching Algorithm to Enhance Rapid Identification of the Optimal Unrelated Hematopoietic Stem Cell Sources for Transplantation.

The search for a suitable human leukocyte antigen (HLA)-matched unrelated adult stem cell donor (URD) or umbilical cord blood unit (UCB) is a complex process. The National Marrow Donor Program (NMDP) developed a search algorithm known as HapLogic, which is currently provided within the NMDP Traxis application. The HapLogic algorithm has been in use since 2006 and has advanced URD/UCB HLA-matching technology. The algorithm has been shown to have high predictive accuracy, which can streamline URD/UCB selection and drive efficiencies in the search process to the benefit of the stem cell transplantation community. Here, we describe the fundamental components of the NMDP matching algorithm, output, validation, and future directions.

Fine-mapping of HLA associations with chronic lymphocytic leukemia in US populations.

Chronic lymphocytic leukemia (CLL) displays remarkable ethnic predisposition for whites, with relative sparing of African-American and Asian populations. In addition, CLL displays among the highest familial predispositions of all hematologic malignancies, yet the genetic basis for these differences is not clearly defined. The highly polymorphic HLA genes of the major histocompatibility complex play a central role in immune surveillance and confer risk for autoimmune and infectious diseases and several different cancers, the role for which in the development of CLL has not been extensively investigated. The National Marrow Donor Program/Be The Match has collected HLA typing from CLL patients in need of allogeneic hematopoietic stem cell transplant and has recruited millions of volunteers to potentially donate hematopoietic stem cells. HLA genotypes for 3491 US white, 397 African-American, and 90 Hispanic CLL patients were compared with 50 000 controls per population from the donor registry. We identified several HLA alleles associated with CLL susceptibility in each population, reconfirming predisposing roles of HLA-A*02:01 and HLA-DRB4*01:01 in whites. Associations for haplotype DRB4*01:01∼DRB1*07:01∼DQB1*03:03 were replicated across all 3 populations. These findings provide a comprehensive assessment of the role of HLA in the development of severe CLL.

Power laws for heavy-tailed distributions: modeling allele and haplotype diversity for the national marrow donor program.

Measures of allele and haplotype diversity, which are fundamental properties in population genetics, often follow heavy tailed distributions. These measures are of particular interest in the field of hematopoietic stem cell transplant (HSCT). Donor/Recipient suitability for HSCT is determined by Human Leukocyte Antigen (HLA) similarity. Match predictions rely upon a precise description of HLA diversity, yet classical estimates are inaccurate given the heavy-tailed nature of the distribution. This directly affects HSCT matching and diversity measures in broader fields such as species richness. We, therefore, have developed a power-law based estimator to measure allele and haplotype diversity that accommodates heavy tails using the concepts of regular variation and occupancy distributions. Application of our estimator to 6.59 million donors in the Be The Match Registry revealed that haplotypes follow a heavy tail distribution across all ethnicities: for example, 44.65% of the European American haplotypes are represented by only 1 individual. Indeed, our discovery rate of all U.S. European American haplotypes is estimated at 23.45% based upon sampling 3.97% of the population, leaving a large number of unobserved haplotypes. Population coverage, however, is much higher at 99.4% given that 90% of European Americans carry one of the 4.5% most frequent haplotypes. Alleles were found to be less diverse suggesting the current registry represents most alleles in the population. Thus, for HSCT registries, haplotype discovery will remain high with continued recruitment to a very deep level of sampling, but population coverage will not. Finally, we compared the convergence of our power-law versus classical diversity estimators such as Capture recapture, Chao, ACE and Jackknife methods. When fit to the haplotype data, our estimator displayed favorable properties in terms of convergence (with respect to sampling depth) and accuracy (with respect to diversity estimates). This suggests that power-law based estimators offer a valid alternative to classical diversity estimators and may have broad applicability in the field of population genetics.

High-resolution HLA genotyping improves PIRCHE-II assessment of molecular mismatching in kidney transplantation.

HLA matching in solid organ transplant is performed with the aim of assessing immunologic compatibility in order to avoid hyperacute rejection and assess the risk of future rejection events. Molecular mismatch algorithms are intended to improve granularity in histocompatibility assessment and risk stratification. PIRCHE-II uses HLA genotyping to predict indirectly presented mismatched donor HLA peptides, though most clinical validation studies rely on imputing high resolution (HR) genotypes from low resolution (LR) typing data. We hypothesized that use of bona fide HR typing could overcome limitations in imputation, improving accuracy and predictive ability for donor-specific antibody development and acute rejection. We performed a retrospective analysis of adult and pediatric kidney transplant donor/recipient pairs (N = 419) with HR typing and compared the use of imputed LR genotyping verses HR genotyping for PIRCHE-II analysis and outcomes. Imputation success was highly dependent on the reference population used, as using historic Caucasian reference populations resulted in 10 % of pairs with unsuccessful imputation while multiethnic reference populations improved successful imputation with only 1 % unable to be imputed. Comparing PIRCHE-II analysis with HR and LR genotyping produced notably different results, with 20 % of patients discrepantly classified to immunologic risk groups. These data emphasize the importance of using multiethnic reference panels when performing imputation and indicate HR HLA genotyping has clinically meaningful benefit for PIRCHE-II analysis compared to imputed LR typing.

Balancing Equity and HLA Matching in Deceased-Donor Kidney Allocation with Eplet Mismatch.

Background: Prioritization of HLA antigen-level matching in the US kidney allocation system intends to improve post-transplant survival but causes racial disparities and thus has been substantially de-emphasized. Recently, molecular matching based on eplets has been found to improve risk stratification compared to antigen matching. Methods: To assign eplets unambiguously, we utilized a cohort of 5193 individuals with high resolution allele-level HLA genotypes from the National Kidney Registry. Using repeated random sampling to simulate donor-recipient genotype pairings based on the ethnic composition of the historical US deceased donor pool, we profiled the percentage of well-matched donors for candidates by ethnicity. Results: The percentage of well-matched donors with zero-DR/DQ eplet mismatch was 3-fold less racially disparate for Black and Asian candidates than percentage of donors with zero-ABDR antigen mismatches, and 2-fold less racially disparate for Latino candidates. For other HLA antigen and eplet mismatch thresholds, the percentage of well-matched donors was more similar across candidate ethnic groups. Conclusions: Compared to the current zero-ABDR antigen mismatch, prioritizing a zero-DR/DQ eplet mismatch in allocation would decrease racial disparities and increase the percentage of well-matched donors. High resolution HLA deceased donor genotyping would enable unambiguous assignment of eplets to operationalize molecular mismatch metrics in allocation. Key Points: Question: What is the impact of prioritizing low molecular mismatch transplants on racial and ethnic disparities in US deceased-donor kidney allocation, compared to the current prioritization of antigen-level matching?Findings: The lowest-risk eplet mismatch approach decreases racial disparities up to 3-fold compared to lowest-risk antigen mismatch and identifies a larger number of the lowest allo-immune risk donors.Meaning: Prioritizing eplet matching in kidney transplant allocation could both improve outcomes and reduce racial disparities compared to the current antigen matching.

IgM marks persistent IgG anti-human leukocyte antigen antibodies in highly sensitized heart transplant patients.

BACKGROUND: Sensitization to human leukocyte antigens (HLA) is a persistent problem in heart transplant (HT) candidates. We sought to characterize the anti-HLA antibody and circulating B cell repertoire in a cohort of highly sensitized HT candidates. METHODS: We assessed immunoglobulin G (IgG) and immunoglobulin M (IgM) anti-HLA antibodies using Luminex single antigen bead assays in a cohort of 11 highly sensitized (HS; calculated panel reactive antibody ≥ 90%) and 3 mildly sensitized (MS) candidates. We also performed B cell receptor repertoire sequencing (BCRseq) in HS candidates and 33 non-candidate controls. HLA antibody strength was measured by mean fluorescence intensity (MFI). RESULTS: We found that IgM anti-HLA antibodies were present in all HS candidates, but with a lower breadth and strength as compared to IgG. When anti-HLA IgG specificities intersected with IgM, binding strength was higher. In contrast, there were IgM but no intersecting IgG specificities for the MS group. In four candidates in the HS group, IgG anti-HLA antibodies decreased in both breadth and strength after HT, but the decrease in strength was smaller if the IgG possessed a specificity that intersected with pre-transplant IgM. BCRseq revealed larger B cell clonotypes in HS candidates but similar diversity as compared to controls. CONCLUSIONS: IgM marks IgG anti-HLA antibodies with higher strength before HT and persistence after HT. The presence of IgM intersecting IgG for an anti-HLA specificity may be a useful approach to determine which donor HLA should be avoided for a sensitized candidate.

HLA sensitization is associated with an increased risk of primary graft dysfunction after heart transplantation.

Primary graft dysfunction (PGD) is a leading cause of early morbidity and mortality following heart transplantation (HT). We sought to determine the association between pretransplant human leukocyte antigen (HLA) sensitization, as measured using the calculated panel reactive antibody (cPRA) value, and the risk of PGD. METHODS: Consecutive adult HT recipients (n = 596) from 1/2015 to 12/2019 at 2 US centers were included. Severity of PGD was based on the 2014 International Society for Heart and Lung Transplantation consensus statement. For each recipient, unacceptable HLA antigens were obtained and locus-specific cPRA (cPRA-LS) and pre-HT donor-specific antibodies (DSA) were assessed. RESULTS: Univariable logistic modeling showed that peak cPRA-LS for all loci and HLA-A was associated with increased severity of PGD as an ordinal variable (all loci: OR 1.78, 95% CI: 1.01-1.14, p = 0.025, HLA-A: OR 1.14, 95% CI: 1.03-1.26, p = 0.011). Multivariable analysis showed peak cPRA-LS for HLA-A, recipient beta-blocker use, total ischemic time, donor age, prior cardiac surgery, and United Network for Organ Sharing status 1 or 2 were associated with increased severity of PGD. The presence of DSA to HLA-B was associated with trend toward increased risk of mild-to-moderate PGD (OR 2.56, 95% CI: 0.99-6.63, p = 0.053), but DSA to other HLA loci was not associated with PGD. CONCLUSIONS: Sensitization for all HLA loci, and specifically HLA-A, is associated with an increased severity of PGD. These factors should be included in pre-HT risk stratification to minimize the risk of PGD.

Exploration of potential immune mechanisms in cervical dystonia.

BACKGROUND: Although there are many possible causes for cervical dystonia (CD), a specific etiology cannot be identified in most cases. Prior studies have suggested a relationship between autoimmune disease and some cases of CD, pointing to possible immunological mechanisms. OBJECTIVE: The goal was to explore the potential role of multiple different immunological mechanisms in CD. METHODS: First, a broad screening test compared neuronal antibodies in controls and CD. Second, unbiased blood plasma proteomics provided a broad screen for potential biologic differences between controls and CD. Third, a multiplex immunoassay compared 37 markers associated with immunological processes in controls and CD. Fourth, relative immune cell frequencies were investigated in blood samples of controls and CD. Finally, sequencing studies investigated the association of HLA DQB1 and DRB1 alleles in controls versus CD. RESULTS: Screens for anti-neuronal antibodies did not reveal any obvious abnormalities. Plasma proteomics pointed towards certain abnormalities of immune mechanisms, and the multiplex assay pointed more specifically towards abnormalities in T lymphocytes. Abnormal immune cell frequencies were identified for some CD cases, and these cases clustered together as a potential subgroup. Studies of HLA alleles indicated a possible association between CD and DRB1*15:03, which is reported to mediate the penetrance of autoimmune disorders. CONCLUSIONS: Altogether, the association of CD with multiple different blood-based immune measures point to abnormalities in cell-mediated immunity that may play a pathogenic role for a subgroup of individuals with CD.