KIR Genotyping Data of More Than 3 Million Individuals Are Available for Global Unrelated Stem Cell Donor Searches (Comment to: Weisdorf D, Cooley S, Wang T, et al. KIR donor selection: feasibility in identifying better donors. Biol Blood Marrow Transplant. 2018; doi: 10.1016/j.bbmt.2018.08.022.)

Schmidt, Alexander H.; Lange, Vinzenz; Hofmann, Jan A.; Schetelig, Johannes; Pingel, Julia

doi:10.1016/j.bbmt.2018.09.020

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…In a joined study, several groups combined their expertise for the in-depth characterization of a cohort of 512 samples (49). However, only the application of NGS enabled the comprehensive characterization of the complete KIR family of genes at allelic level in one assay (29). In contrast to our approach which is based on PCR for target selection, the study by Norman et al (31)relies on capture technology.…”

Section: Discussionmentioning

confidence: 99%

“…Owing to the fact that KIR and HLA genes reside on different chromosomes, unrelated donors and recipients who are HLA -matched rarely share identical KIR genes. Genotyping the KIR genes of potential stem cell donors at high resolution upon registration and providing this information in addition to the HLA genotypes would thus be beneficial for optimizing the unrelated donor selection process (28, 29).…”

Section: Introductionmentioning

confidence: 99%

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Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations

et al. 2018

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The killer-cell immunoglobulin-like receptor (KIR) genes regulate natural killer cell activity, influencing predisposition to immune mediated disease, and affecting hematopoietic stem cell transplantation (HSCT) outcome. Owing to the complexity of the KIR locus, with extensive gene copy number variation (CNV) and allelic diversity, high-resolution characterization of KIR has so far been applied only to relatively small cohorts. Here, we present a comprehensive high-throughput KIR genotyping approach based on next generation sequencing. Through PCR amplification of specific exons, our approach delivers both copy numbers of the individual genes and allelic information for every KIR gene. Ten-fold replicate analysis of a set of 190 samples revealed a precision of 99.9%. Genotyping of an independent set of 360 samples resulted in an accuracy of more than 99% taking into account consistent copy number prediction. We applied the workflow to genotype 1.8 million stem cell donor registry samples. We report on the observed KIR allele diversity and relative abundance of alleles based on a subset of more than 300,000 samples. Furthermore, we identified more than 2,000 previously unreported KIR variants repeatedly in independent samples, underscoring the large diversity of the KIR region that awaits discovery. This cost-efficient high-resolution KIR genotyping approach is now applied to samples of volunteers registering as potential donors for HSCT. This will facilitate the utilization of KIR as additional selection criterion to improve unrelated donor stem cell transplantation outcome. In addition, the approach may serve studies requiring high-resolution KIR genotyping, like population genetics and disease association studies.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations

et al. 2018

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“…In our study, we extended the method to limit haplotype structure to pre-established patterns in order to make it applicable to our data obtained by high-throughput KIR genotyping in the context of unrelated HSCT donor registration (53,54). We applied a three-step approach to estimate population-specific KIR haplotype frequencies at allele group resolution.…”

Section: Introductionmentioning

confidence: 99%

Estimation of German KIR Allele Group Haplotype Frequencies

et al. 2020

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The impact of the highly polymorphic Killer-cell immunoglobulin-like receptor (KIR) gene cluster on the outcome of hematopoietic stem cell transplantation (HCST) is subject of current research. To further understand the involvement of this gene family into Natural Killer (NK) cell-mediated graft-versus-leukemia reactions, knowledge of haplotype structures, and allelic linkage is of importance. In this analysis, we estimate population-specific KIR haplotype frequencies at allele group resolution in a cohort of n = 458 German families. We addressed the polymorphism of the KIR gene complex and phasing ambiguities by a combined approach. Haplotype inference within first-degree family relations allowed us to limit the number of possible diplotypes. Structural restriction to a pattern set of 92 previously described KIR copy number haplotypes further reduced ambiguities. KIR haplotype frequency estimation was finally accomplished by means of an expectation-maximization algorithm. Applying a resolution threshold of ½ n, we were able to identify a set of 551 KIR allele group haplotypes, representing 21 KIR copy number haplotypes. The haplotype frequencies allow studying linkage disequilibrium in two-locus as well as in multi-locus analyses. Our study reveals associations between KIR haplotype structures and allele group frequencies, thereby broadening our understanding of the KIR gene complex.

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“…Massive cost reductions resulting from next‐generation sequencing (NGS)‐based HLA typing (Schmidt et al, ) enabled a substantial extension of the DKMS standard typing profile of new donors beyond HLA. This standard typing profile currently includes the following parameters beyond the six “classical” HLA loci (A, B, C, DRB1, DQB1, DPB1): ABO and Rh blood groups (Lang et al, ), Cytomegalovirus (CMV) Immunoglobulin G (IgG) serostatus (Behrens et al, ; full publication submitted), 16 KIR genes (Schmidt, Lange, Hofmann, Schetelig, & Pingel, ; Wagner et al, ), MICA/MICB (publication submitted), HLA‐E (Hofmann et al, ; full publication in preparation), HLA‐DRB3/4/5, HLA‐DQA1, and HLA‐DPA1 (since October 2019) and the C‐C motif chemokine receptor 5 Delta32 (CCR5∆32) deletion (Solloch et al, ). …”

Section: Donor Typing: Beyond the Classical Hla Locimentioning

confidence: 99%

Immunogenetics in stem cell donor registry work: The DKMS example (Part 2)

Schmidt

Sauter

Baier

et al. 2020

Int J Immunogenetics

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DKMS is a leading stem cell donor registry with more than 9 million donors. Donor registry activities share many touch points with topics from immunogenetics or population genetics. In this two‐part review article, we deal with these aspects of donor registry work by using the example of DKMS. In the second part of the review, we focus on donor typing of non‐HLA genes, the impact of donor age, gender and CMV serostatus on donation probabilities, the identification of novel HLA, KIR and MIC alleles by high‐throughput donor typing, the activities of the Collaborative Biobank and pharmacogenetics in the donor registry context.

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KIR Genotyping Data of More Than 3 Million Individuals Are Available for Global Unrelated Stem Cell Donor Searches (Comment to: Weisdorf D, Cooley S, Wang T, et al. KIR donor selection: feasibility in identifying better donors. Biol Blood Marrow Transplant. 2018; doi: 10.1016/j.bbmt.2018.08.022.)

Cited by 5 publications

References 8 publications

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations

Estimation of German KIR Allele Group Haplotype Frequencies

Immunogenetics in stem cell donor registry work: The DKMS example (Part 2)

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