Six-locus high resolution HLA haplotype frequencies derived from mixed-resolution DNA typing for the entire US donor registry

AbstractWe have calculated six-locus high resolution HLA A∼C∼B∼DRB3/4/5∼DRB1∼DQB1 haplotype frequencies using all Be The Match® Registry volunteer donors typed by DNA methods at recruitment. Mixed resolution HLA typing data was inputted to a modified expectation–maximization (EM) algorithm in the form of genotype lists generated by interpretation of primary genomic typing data to the IMGT/HLA v3.4.0 allele list. The full cohort consists of 6.59million subjects categorized at a broad race level. Overall 25.8% of the individuals were typed at the C locus, and 5.2% typed at the DQB1 locus, while all individuals were typed for A, B, DRB1. We also present a subset of 2.90million subjects with detailed race/ethnic information mapped to 21 population subgroups, 64.1% of which have primary DNA typing data across at least A, B, and DRB1 loci. Sample sizes at the detailed race level range from 1,242,890 for European Caucasian to 1,376 Alaskan Native or Aleut. Genetic distance measurements show high levels of HLA genetic divergence among the 21 detailed race categories, especially among the eight Asian–American populations. These haplotype frequencies will be used to improve match predictions for donor selection algorithms for hematopoietic stem cell transplantation and improve the accuracy in modeling registry match rates

The Impact of Amino Acid Variability on Alloreactivity Defines a Functional Distance Predictive of Permissive HLA-DPB1 Mismatches in Hematopoietic Stem Cell Transplantation

AbstractA major challenge in unrelated hematopoietic stem cell transplantation (HSCT) is the prediction of permissive HLA mismatches, ie, those associated with lower clinical risks compared to their nonpermissive counterparts. For HLA-DPB1, a clinically prognostic model has been shown to be matching for T cell epitope (TCE) groups assigned by cross reactivity of T cells alloreactive to HLA-DPB1∗09:01; however, the molecular basis of this observation is not fully understood. Here, we have mutated amino acids (aa) in 10 positions of HLA-DPB1∗09:01 to other naturally occurring variants, expressed them by lentiviral vectors in B cell lines, and quantitatively measured allorecognition by 17 CD4+ T cell effectors from 6 unrelated individuals. A significant impact on the median alloresponse was observed for peptide contact positions 9, 11, 35, 55, 69, 76, and 84, but not for positions 8, 56, and 57 pointing away from the groove. A score for the “functional distance” (FD) from HLA-DPB1∗09:01 was defined as the sum of the median impact of polymorphic aa in a given HLA-DPB1 allele on T cell alloreactivity. Established TCE group assignment of 23 alleles correlated with FD scores of ≤0.5, 0.6 to 1.9 and ≥2 for TCE groups 1, 2, and 3, respectively. Based on this, prediction of TCE group assignment will be possible for any given HLA-DPB1 allele, including currently 367 alleles encoding distinct proteins for which T cell cross reactivity patterns are unknown. Experimental confirmation of the in silico TCE group classification was successfully performed for 7 of 7 of these alleles. Our findings have practical implications for the applicability of TCE group matching in unrelated HSCT and provide new insights into the molecular mechanisms underlying this model. The innovative concept of FD opens new potential avenues for risk prediction in unrelated HSCT

A Detailed View of KIR Haplotype Structures and Gene Families as Provided by a New Motif-Based Multiple Sequence Alignment

Human chromosome 19q13.4 contains genes encoding killer-cell immunoglobulin-like receptors (KIR). Reported haplotype lengths range from 67 to 269 kb and contain 4 to 18 genes. The region has certain properties such as single nucleotide variation, structural variation, homology, and repetitive elements that make it hard to align accurately beyond single gene alleles. To the best of our knowledge, a multiple sequence alignment of KIR haplotypes has never been published or presented. Such an alignment would be useful to precisely define KIR haplotypes and loci, provide context for assigning alleles (especially fusion alleles) to genes, infer evolutionary history, impute alleles, interpret and predict co-expression, and generate markers. In order to extend the framework of KIR haplotype sequences in the human genome reference, 27 new sequences were generated including 24 haplotypes from 12 individuals of African American ancestry that were selected for genotypic diversity and novelty to the reference, to bring the total to 68 full length genomic KIR haplotype sequences. We leveraged these data and tools from our long-read KIR haplotype assembly algorithm to define and align KIR haplotypes at <5 kb resolution on average. We then used a standard alignment algorithm to refine that alignment down to single base resolution. This processing demonstrated that the high-level alignment recapitulates human-curated annotation of the human haplotypes as well as a chimpanzee haplotype. Further, assignments and alignments of gene alleles were consistent with their human curation in haplotype and allele databases. These results define KIR haplotypes as 14 loci containing 9 genes. The multiple sequence alignments have been applied in two software packages as probes to capture and annotate KIR haplotypes and as markers to genotype KIR from WGS

World Marrow Donor Association guidelines for the reporting of novel HLA alleles

The guidelines for the implementation and reporting of HLA nomenclature for the World Marrow Donor Association have served as a reliable standard for communication of HLA data in the hematopoietic cell transplantation process. Wider use of next-generation sequencing made a special provision of the guidelines increasingly pertinent: how to communicate novel HLA alleles. Novel alleles need to be recognized by the WHO Nomenclature Committee for Factors of the HLA system to obtain official allele designations. Until then they have to be handled according to the specific rules. Leaving the actual rules basically unchanged we give some advice on how to communicate novel alleles to best facilitate the search process for cases where novel alleles are identified on donor or patient side.Scopu

Tight junctions: from simple barriers to multifunctional molecular gates

Epithelia and endothelia separate different tissue compartments and protect multicellular organisms from the outside world. This requires the formation of tight junctions, selective gates that control paracellular diffusion of ions and solutes. Tight junctions also form the border between the apical and basolateral plasma-membrane domains and are linked to the machinery that controls apicobasal polarization. Additionally, signalling networks that guide diverse cell behaviours and functions are connected to tight junctions, transmitting information to and from the cytoskeleton, nucleus and different cell adhesion complexes. Recent advances have broadened our understanding of the molecular architecture and cellular functions of tight junctions

Trans-population graph-based coverage optimization of allogeneic cellular therapy

BackgroundPre-clinical development and in-human trials of ‘off-the-shelf’ immune effector cell therapy (IECT) are burgeoning. IECT offers many potential advantages over autologous products. The relevant HLA matching criteria vary from product to product and depend on the strategies employed to reduce the risk of GvHD or to improve allo-IEC persistence, as warranted by different clinical indications, disease kinetics, on-target/off-tumor effects, and therapeutic cell type (T cell subtype, NK, etc.).ObjectiveThe optimal choice of candidate donors to maximize target patient population coverage and minimize cost and redundant effort in creating off-the-shelf IECT product banks is still an open problem. We propose here a solution to this problem, and test whether it would be more expensive to recruit additional donors or to prevent class I or class II HLA expression through gene editing.Study designWe developed an optimal coverage problem, combined with a graph-based algorithm to solve the donor selection problem under different, clinically plausible scenarios (having different HLA matching priorities). We then compared the efficiency of different optimization algorithms – a greedy solution, a linear programming (LP) solution, and integer linear programming (ILP) -- as well as random donor selection (average of 5 random trials) to show that an optimization can be performed at the entire population level.ResultsThe average additional population coverage per donor decrease with the number of donors, and varies with the scenario. The Greedy, LP and ILP algorithms consistently achieve the optimal coverage with far fewer donors than the random choice. In all cases, the number of randomly-selected donors required to achieve a desired coverage increases with increasing population. However, when optimal donors are selected, the number of donors required may counter-intuitively decrease with increasing population size. When comparing recruiting more donors vs gene editing, the latter was generally more expensive. When choosing donors and patients from different populations, the number of random donors required drastically increases, while the number of optimal donors does not change. Random donors fail to cover populations different from their original populations, while a small number of optimal donors from one population can cover a different population.DiscussionGraph-based coverage optimization algorithms can flexibly handle various HLA matching criteria and accommodate additional information such as KIR genotype, when such information becomes routinely available. These algorithms offer a more efficient way to develop off-the-shelf IECT product banks compared to random donor selection and offer some possibility of improved transparency and standardization in product design