Haplotype analyses of classical HLA genes from families
K. Osoegawa (Palo Alto, CA, US)
HLA alleles are observed in specific haplotypes because of linkage disequilibrium between particular alleles. Haplotype frequencies for alleles have been established for specific ethnic groups and racial categories from population studies. HLA typing using Next Generation Sequencing (NGS) platforms allows generation of nearly full-length gene sequences, obtaining four-field HLA types and detecting novel alleles. NGS technologies also permit high-throughput HLA typing for large numbers of samples in a cost effective manner. To establish HLA haplotypes with four-field resolution, we built family-based haplotypes. We selected families, which include both parents and two children, and may contain extended family members, from our clinical database. DNA was processed using MIA FORA NGS kits, and sequenced on either MiSeq or NextSeq platforms. HLA types were obtained using MIA FORA software. We developed software that compares offspring and parents’ HLA types and build haplotypes in an automated fashion. The software reports HLA haplotypes according to the order of genes along the chromosome to facilitate identifying potential meiotic recombination, and also compares to the previously established haplotypes. Of 250 selected families, we sequenced 150 families and built 450 unique haplotypes. Typing of DPB1 locus by NGS-shotgun sequencing and Sanger often results in ambiguous genotypes because of lack of phasing between exons 2 and 3. In the present study virtually all ambiguities were resolved through the analyses of segregation of sequences. Understanding haplotype structures allows delineating evolutionary pathways of the HLA region that include both divergent and consequent evolution. The haplotypes generated from this study provide valuable resources for hematopoietic stem cell donor match prediction and play a role as reference haplotypes for expanding a collection of HLA haplotypes.
Chimerism monitoring with NGS: a feasibility study
E. Rozemuller (Utrecht, NL)
Accurate monitoring of patients after stem cell transplantation is essential to detect rejection or relapse. The technique mostly used is STR fragment length analysis. The major disadvantages of this technique are the low sensitivity and the laborious data analysis. Currently qPCR-based techniques are getting more and more attention for micro-chimerism monitoring, as it offers high sensitivity (0.05%), enabling prediction of relapse, rather than confirmation. However, the drawback of qPCR is that it requires a pre-transplant sample at each monitoring time point, and multiple markers need to be analysed to be able to select suitable markers for monitoring. As more and more HLA-typing labs have access to NGS, it is efficient to use NGS for transplantation monitoring. We hypothesize that NGS chimerism monitoring will have a similar sensitivity as qPCR methods, and have a wide dynamic range, also including the dynamic range of STR technology. In addition, NGS chimerism monitoring does not need a pre-transplant sample with every time point. Here, we present the results of a feasibility study of applying NGS for chimerism monitoring. The amplification approach for a set of indel systems of our current qPCR chimerism KMRtype and AlleleSEQR kits have been redesigned to cover the full indel region. The amplification results were analysed by customized analysis tools that determine the good-quality reads, the short/long allele counts and calculate their ratio.
Here we will show preliminary results that already clearly demonstrates that NGS chimerism monitoring is feasible, with a high sensitivity and wide dynamic range.
Recipients’ CD86 gene polymorphism affects overall survival after allogeneic hematopoietic stem cell transplantation
L. Karabon (Wroclaw, PL)
The balance of alloimmune T cells reactions is important for successful outcome after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Donor T-cells eliminate malignant residual host T-cells (graft versus leukemia effect), and on the other hand play a crucial role in the development of graft versus host disease, the main complication after allo- HSCT. The full T-cell activation requires signals provided by interaction between co-stimulatory molecule CD28 on T-cell and CD86 or CD80 on the antigen presenting cell. The aim of this study was to evaluate association between recipients’ CD86 gene single nucleotide polymorphisms (SNPs) and complications after allo-HSCT. Altogether 295 adult patients (pts) undergoing related donor matched HSCT (105 pts) and unrelated donor matched HSCT (190pts) were typed for rs1129055, rs9831894 and rs2715267 SNPs in the CD86 gene using the TaqMan SNP Genotyping Assays. In univariate and multivariate analysis we found that none of investigated recipients’ CD86 polymorphisms were associated with susceptibility to aGvHD and rate of relapse. However, the Cox regression analysis showed that recipients with the rs2715267GG genotype have an increased risk of death (HR=1.93; CI95% 1.14- 3.08, p=0.0092) as compared to recipients possessing T allele (GT or TT genotypes). The presence of rs2715267GG genotype resulted in worse overall survival (OS) during 24 months observation than did the presence of the TT or GT, for which the OS were similar (48.4% vs.68.2% and 72.4%, log-rank p=0.0092). On the basis of the present study, we conclude that the recipients’ rs2715267 polymorphism in CD86 gene influences the outcome after allo-HSCT, especially overall survival of HSCT recipients.
Killer-cell Immunoglobulin-like Receptor (KIR) allele typing using Single Molecule Real-Time (SMRT) DNA sequencing from full length PCR amplicons
W. Bultitude (London, GB)
The Killer-cell Immunoglobulin-like Receptor (KIR) genes are a complex, highly polymorphic family of genes involved in regulating natural killer (NK) cells. Allelic polymorphism at the KIR loci is known to affect factors such as ligand avidity and cell surface expression. Furthermore, previous studies have demonstrated the importance of certain KIR presence/absence combinations in a wide variety of malignancies, as well as pregnancy and Haematopoietic Stem Cell Transplantation (HSCT) outcomes. To better understand the role of KIR in these scenarios, we have developed a third generation sequencing method with multiplexing capacity to determine complete Coding Domain Sequence (CDS) for fully phased allele typing of the KIR2DL1, KIR2DL2, KIR2DL3, KIR2DL4, KIR2DS2, KIR3DL1, KIR3DL2, KIR3DL3 and KIR3DS1 genes. To validate the technique, we applied it to a panel of IHW cell lines with previous KIR typing and compared allele designations. Mean average read depth and quality value per allele were 265 reads and >92.99, respectively. Overall, allele concordance against previous KIR typing was 92% (86/93 alleles) and CDS concordance to existing KIR alleles was 99.99% of nucleotides (107002/107006), demonstrating the legitimacy of our technique. The discordant alleles (8%, 7/93 alleles) include three with novel polymorphisms (3%) and five completely discrepant types (5%), four of which form examples of allele combinations that require full-length, isolated sequencing to determine polymorphism phase, thereby highlighting the advantage that SMRT DNA sequencing has over other KIR allele typing methods. Sanger sequencing is being performed to confirm all other polymorphisms. We have been able to specifically target and simultaneously sequence multiple full-length KIR alleles to definitively assign KIR types. By increasing the resolution at which we study KIR, we aim to better understand their clinical importance as NK cell receptors.
OptiMaS: a matching service for the new BMDW search & match service
H. Eberhard (Ulm, DE)
In 2006, the German National Bone Marrow Donor Registry (ZKRD) introduced the OptiMatch® search engine for the probabilistic matching of volunteer unrelated stem cell donors to patients in need of a transplant. In subsequent years, the core parts of OptiMatch® were isolated into a deployable stand-alone matching service called OptiMaS (OptiMatch® as a Service). OptiMaS has been used in the production environments of the Canadian OneMatch registry since 2012 and of the Australian Bone Marrow Donor Registry since 2013 and has meanwhile demonstrated to be a sound option for registries to benefit from the advantages of the OptiMatch® matching service locally. In 2016 OptiMatch® was selected as a matching algorithm for the new Bone Marrow Donors Worldwide (BMDW) Search & Match Service. In addition to the OptiMatch® search engine, the OptiMaS framework uses solely open-source software. Altogether, OptiMaS is a black box computer giving access to the capabilities of OptiMatch® via a small set of high-level web service functions. It fully supports the European Marrow Donor Information System (EMDIS) matching preferences and is compliant with the World Marrow Donor Association (WMDA) HLA Nomenclature Guidelines.
For this study, we have investigated the live system’s performance for 60 consecutive days as well as for a complete recalculation of the search report for all patients. The analysis is based on over 29 million donors and cord blood units and on over 4000 for the daily and over 3000 patients for the complete calculation. We have focused on average matching times for typical search settings and highlighted special constellations leading to extreme (low and high) system burden. We have also studied the effects of input parameters on parallel processing. Daily average match time is 2 minutes with 50% of the searches returning within 25 seconds on a machine with 4 dedicated matching processes. In conclusion, OptiMaS has shown for two representative scenarios to provide an appropriate matching service for BMDW’s global patient and donor load.
Validation of amplicon based next generation sequencing of human leukocyte antigens by more than 17,000 confirmatory typing results
D. Baier (Tuebingen, DE)
Since 2013, typing of DKMS donors at recruitment level has been performed by an in-house developed amplicon based NGS approach. Since this release, over 1.8 million potential unrelated stem cell donors have been typed at recruitment for HLA-A,-B,-C,-DRB1,-DQB1 and -DPB1 with over 98% high-resolution results by DKMS Germany. For these donors, more than 95,000 HLA loci have been re-typed in the context of over 17,000 CT requests. In total we found 129 discrepant typing reports of which 115 (89%) were due to genotyping errors during confirmatory typing. Only for 11% (n=14) the typing at recruitment turned out to be erroneous. 11 of these cases referred to HLA-DPB1, 2 cases to HLA-DQB1 and one to HLA-B. Issues with homozygosity handling were responsible for most DPB1 discrepancies. We observed this effect in a preliminary analysis in 2015 and optimized our software neXtype to cope with homozygosity by adjusting the detection parameters for hetero- and homozygosity. Since this optimization, no additional errors due to false detection of homozygosity have been observed. Out of 115 errors in CT, 98 (85%) comprised HLA class II loci. About half (60) of these 115 discrepancies were outside the transplantation relevant antigen recognition domain and might be due to inadequate usage of multi-allele codes for reporting typing results. 34 of the 39 DRB1 errors were related to DRB1*14:01 vs. DRB1*14:54 that could be distinguished by typing exon 3 to recognize the relevant SNP. If exon 3 is not typed, the result should be reported as DRB1*14:01:01G (or DRB1*14:BCAD). One error was related to ambiguities remaining in Sanger sequencing which are resolved by next generation sequencing. In conclusion, we were able to show that using an NGS based typing strategy is of exceptional high quality. We observed an error rate below 0.15 ‰ (14 out of 95,876) with the maximum error rate per locus not exceeding 1.6 ‰ for DPB1 (11 out of 6,921).