HLA最新文献

{"title":"ESMpHLA: Evolutionary Scale Model-Based Deep Learning Prediction of HLA Class I Binding Peptides","authors":"Xiaorui Cheng,&nbsp;Hu Mei,&nbsp;Pengji Chen,&nbsp;Haixia Wu,&nbsp;Rui Liu,&nbsp;Yuanyuan Lei,&nbsp;Pingqing Wang","doi":"10.1111/tan.70263","DOIUrl":"https://doi.org/10.1111/tan.70263","url":null,"abstract":"<div>\u0000 \u0000 <p>The recognition of endogenous peptides by HLA class I plays a crucial role in CD8+ T cell immune responses and human adaptive cell immune. Thus, the prediction of HLA class I-peptide binding affinities is always the core issue for the research of immune recognition and vaccine development. In this study, an evolutionary scale model (ESM) combined with parallel CNN blocks and a cross attention mechanism was used to construct a novel ESMpHLA model for predicting HLA class I binding peptides. Based on the 91,560 binding peptides of 41 HLA-A alleles, 56,731 of 50 HLA-B alleles and 2444 of 10 HLA-C alleles, the ESMpHLA model was successfully established and achieved satisfying prediction performances with the overall accuracy and AUC values of 0.874 and 0.938 for the test dataset. The results indicate that the ESMpHLA model performs well in dealing with different HLA class I 2-field alleles as well as the peptides with different lengths. Then, the generalisation ability of the ESMpHLA model was validated by an independent test dataset compiled from recent IEDB weekly benchmark datasets. The results showed that the ESMpHLA model achieved the highest ROC-AUC and PR-AUC values when compared with the latest BVMHC, CapsNet-MHC, STMHCpan and BVLSTM models. In addition, two ensemble models were also established by integrating the above 5 deep learning models using soft-voting and hard-voting strategies.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Registry of Unmet Need: A World Marrow Donor Association Analysis of Patients Without an HLA Match","authors":"Martin Maiers,&nbsp;Valerie Greco-Stewart,&nbsp;Abeer Madbouly,&nbsp;James Robinson,&nbsp;Hans-Peter Eberhard,&nbsp;Jürgen Sauter,&nbsp;Yoram Louzoun,&nbsp;Sapir Israeli,&nbsp;Yung-Tsi Bolon,&nbsp;Julia Pingel,&nbsp;Alexander H. Schmidt,&nbsp;Eric Spierings,&nbsp;Christina Leonhard-Melief,&nbsp;Lydia Foeken,&nbsp;Martine Schuit,&nbsp;Alicia Venter,&nbsp;Steven G. E. Marsh","doi":"10.1111/tan.70255","DOIUrl":"https://doi.org/10.1111/tan.70255","url":null,"abstract":"<p>While the World Marrow Donor Association global database currently offers approximately 42.7 million potential donors and cord blood units to patients in need of haematopoietic cell transplant, lack of eight HLA-matched donors remains a significant barrier. The Registry of Unmet Need (RUN) Project seeks to address disparities in transplant access for patients with rare HLA genotypes, particularly those from populations that have been historically underrepresented and underserved by global donor registries. Patients eligible for this study searched for an unrelated donor for transplant between 2015 and 2017 and, at that time, lacked a potential eight-of-eight HLA-matched unrelated donor (MUD). Sixteen donor registries contributed data from 3654 patients using standardised data-collection project templates. To address this unmet need, pooled data were analysed to identify trends and inform global recruitment strategies. Patient genotypes were queried against the global inventory at later timepoints in 2018 and 2023 to determine whether potential matches had been recruited within the years since the initial search. Patient haplotypes were imputed using an open-source method referencing US population frequencies. The imputation process used five continental reference populations and 21 detailed populations derived from the NMDP database. The method provided a Bayesian inference of population membership. A control group consisting of US patients that yielded 1000 or more potential matches was used for comparison. RUN patient haplotype and genotype frequencies were substantially lower compared with controls; both the more frequent and less frequent haplotypes in RUN patients were found to be approximately 100 times less common than those in the control group. We identified 782 potential cases in which a potential MUD was recruited after the initial RUN patient search was performed; while this result is being further investigated, clear patterns of where these new matches can be found have emerged; typically, new matches are found outside the country where the patient search was initiated. Our findings demonstrate that rare haplotypes are the primary barrier to identifying a MUD; the presence of rare alleles or haplotype combinations, as with multi-race ancestry, is rarely the cause. Although strategic donor recruitment efforts will help improve MUD access, patient transplants should not be delayed in pursuit of a MUD when viable alternative options are available.</p>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/tan.70255","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frequency and Distribution of KIR Genotypes of Donors-Recipient Pairs in the Haploidentical Haematopoietic Stem Cell Transplantation Setting: Collaborative Study by the Spanish Working Group in Histocompatibility and Transplant Immunology (GETHIT) and the Spanish Haematopoietic Transplantation and Cell Therapy Group (GETH-TC)","authors":"Mar Luis-Hidalgo,&nbsp;Dolores Planelles,&nbsp;José Luis Piñana,&nbsp;Juan Carbonell,&nbsp;Paula Amat,&nbsp;Inés Gómez-Seguí,&nbsp;Manuel Guerreiro,&nbsp;Abelardo Caballero,&nbsp;Alberto Torío,&nbsp;Mª. Jesús Pascual-Cascón,&nbsp;Francisco Boix,&nbsp;Luis Marín Rubio,&nbsp;Lourdes Vázquez,&nbsp;Natalia Martínez-Pomar,&nbsp;Vanesa Cunill,&nbsp;Antonia Sampol,&nbsp;Julio Ochoa,&nbsp;Cristina Arbona,&nbsp;Carlos Solano","doi":"10.1111/tan.70248","DOIUrl":"https://doi.org/10.1111/tan.70248","url":null,"abstract":"<div>\u0000 \u0000 <p>There is limited information regarding the influence of <i>KIR</i> genotype, compared to the HLA system, in haploidentical haematopoietic stem cell transplantation (haplo-HSCT). This study aimed to determine the frequencies of <i>KIR</i> genotypes in Spanish haematologic patients undergoing haplo-HSCT. A study was conducted on 113 oncohaematological patients and their donors, treated across five centres that are members of the Spanish Working Group in Histocompatibility and Transplant Immunology (GETHIT) and the Spanish Haematopoietic Transplantation and Cell Therapy Group (GETH-TC). <i>KIR</i> typing was performed using PCR-rSSO or PCR-SSP. <i>KIR</i> genotypes were identified using the KIR Allele Frequency Net Database. Among donors, the most frequent <i>KIR</i> genotypes were Type 1 (28.3%), Type 2 (12.4%) and Type 4 (10.6%). In patients, Genotypes 1 (23.9%), 4 (23%) and 2 (14.2%) were most prevalent. Donors exhibited AA centromeric (46%) and telomeric (59.3%) types, while patients had a higher AB centromeric frequency (52.2%). Differences were observed in the BB centromeric type (3.5% patients; 16.8% donors, <i>p</i> = 0.002). The AB <i>KIR</i> genotype was the most common (70.8% donors; 75.2% patients). Most were classified as ‘neutral’ (61.9% donors; 73.5% patients). B-content score1 was the most common (48.7% patients; 33.6% donors). Notably, classification as best was rare (2.7% patients; 16.8% donors, <i>p</i> = 0.002). The study highlights the distribution of KIR genotypes in haplo-HSCT patients and donors, with Genotypes 1, 2 and 4 being the most prevalent. AB <i>KIR</i> genotypes and B-content score 1 were dominant. Moreover, <i>KIR</i> genotypes ID may serve as criteria for future investigation about the immunogenetic predisposition to malignant haematological diseases.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterisation of the Novel HLA-C*08:272 Allele by Next-Generation Sequencing in a Chinese Donor","authors":"Nanying Chen,&nbsp;Fang Wang,&nbsp;Lina Dong,&nbsp;Wei Zhang,&nbsp;Faming Zhu","doi":"10.1111/tan.70259","DOIUrl":"https://doi.org/10.1111/tan.70259","url":null,"abstract":"<div>\u0000 \u0000 <p><i>HLA-C</i>*08:272 differs from <i>HLA-C</i>*08:01:01:01 by one single nucleotide substitution at position 7 G&gt;T in exon 1.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Missense Substitution in Exon 2 Generates the First HLA-DQB1*04 Allele With Glutamine at Residue 52, DQB1*04:108","authors":"Juan López-Pérez,&nbsp;Francisco Javier Gil-Etayo,&nbsp;Ariadna Vicente Parra,&nbsp;Isabel Jiménez Hernaz,&nbsp;Amalia Tejeda Velarde","doi":"10.1111/tan.70265","DOIUrl":"https://doi.org/10.1111/tan.70265","url":null,"abstract":"<div>\u0000 \u0000 <p><i>HLA-DQB1*04:108</i>, the first <i>HLA-DQB1*04</i> allele with Glutamine at residue 52 in the peptide-binding domain.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144091679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of the Novel HLA-B*55:141 Allele in a Chinese Individual","authors":"Wenjing Yuan,&nbsp;Fang Wang,&nbsp;Nanying Chen,&nbsp;Wei Zhang,&nbsp;Faming Zhu","doi":"10.1111/tan.70246","DOIUrl":"https://doi.org/10.1111/tan.70246","url":null,"abstract":"<div>\u0000 \u0000 <p><i>HLA-B*55:141</i> differs from <i>HLA-B*55:08</i> by a single nucleotide substitution at position 363 G&gt;C in exon 3.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144091673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of the Novel HLA-DQB1*04:95 Allele Using Next-Generation Sequencing in a Chinese Cord Blood Donor","authors":"Nanying Chen,&nbsp;Lina Dong,&nbsp;Fang Wang,&nbsp;Wei Zhang,&nbsp;Faming Zhu","doi":"10.1111/tan.70260","DOIUrl":"https://doi.org/10.1111/tan.70260","url":null,"abstract":"<div>\u0000 \u0000 <p><i>HLA-DQB1</i>*04:95 shows one single-nucleotide substitution at position 431 A&gt;G in Exon 3 compared with <i>HLA-DQB1</i>*04:01:01:01.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of the Novel MICA*002:01:30 Allele in a Haematopoietic Stem Cell Donor From India","authors":"Gaurav Sharma,&nbsp;Disha Agarwal,&nbsp;Alka Khadwal,&nbsp;Pankaj Malhotra","doi":"10.1111/tan.70237","DOIUrl":"https://doi.org/10.1111/tan.70237","url":null,"abstract":"<div>\u0000 \u0000 <p>MICA*002:01:30 differs from MICA*002:01:03 by a transition of C &gt; T at position 3678 in intron 1.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterisation of the Novel HLA-C*04:538 Allele by Third-Generation Sequencing","authors":"Chiara Biagini,&nbsp;Silvia Fornaciari,&nbsp;Roberta Lamanna,&nbsp;Veronica De Gregorio,&nbsp;Michele Curcio","doi":"10.1111/tan.70256","DOIUrl":"https://doi.org/10.1111/tan.70256","url":null,"abstract":"<div>\u0000 \u0000 <p>HLA-C*04:538 differs from HLA-C*04:01:01:01 by a single nucleotide polymorphism in exon 1, codon −13.</p>\u0000 </div>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repeated HLA-DRB1 and HLA-DQB1 Mismatches Without Preformed DSA Affect Graft Survival, Rejection and DSA Development: A Multicenter Analysis","authors":"D. A. J. van den Broek,&nbsp;S. Meziyerh,&nbsp;D. van der Helm,&nbsp;J. C. van den Born,&nbsp;J. S. F. Sanders,&nbsp;B. G. Hepkema,&nbsp;J. van de Wetering,&nbsp;J. A. Kal van Gestel,&nbsp;J. Kers,&nbsp;C. van Kooten,&nbsp;J. I. Rotmans,&nbsp;A. P. J. de Vries,&nbsp;D. L. Roelen","doi":"10.1111/tan.70264","DOIUrl":"https://doi.org/10.1111/tan.70264","url":null,"abstract":"<p>Repeat transplantations represent up to 20% of all kidney transplants. Whereas repeat transplantations in the presence of circulating donor-specific HLA-antibodies are generally avoided, the risk of repeated HLA-mismatches (RMM) without detectable antibodies remains debated. This multicenter study evaluated the hazard of RMM, stratified by HLA-class, on transplant outcomes in the absence of preformed donor-specific antibodies. We included repeat kidney transplant recipients from January 2009 onward with available HLA typing for HLA-A, -B, -C, -DRB1, -DRB3/4/5 and -DQB1 from current and previous donors. RMM were defined at the split serological antigen level, excluding patients with only HLA-DP or HLA-DRB3/4/5 RMM. Patients were included if: (a) preformed donor-specific HLA-antibodies (DSA) had never been detected and (b) this was confirmed by Luminex assays within 6 months pre-transplantation. A competing risk model, adjusting for demographic factors and total HLA-mismatch load while accounting for death as a competing risk, showed that HLA-DRB1 and/or HLA-DQB1 RMM significantly increased the risk of graft loss within 1 year post-transplant (HR 3.75 [95% CI 1.51–9.34], <i>p</i> = 0.004). Cox proportional hazard models further linked these HLA-class II RMM to higher risks of biopsy-proven rejection (HR 1.98 [95% CI 1.04–3.76], <i>p</i> = 0.037) and DSA development (HR 9.89 [95% CI 1.92–50.99], <i>p</i> = 0.006), while no significant risks were observed for HLA-class I RMM. Sensitivity analyses in patients screened for pretransplant DSA via single antigen bead assays, those with similar immunosuppression, and those with allelic RMM further confirmed these findings. These results suggest that avoiding HLA-DRB1 and HLA-DQB1 RMM, when feasible, may improve transplant outcomes.</p>","PeriodicalId":13172,"journal":{"name":"HLA","volume":"105 5","pages":""},"PeriodicalIF":5.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/tan.70264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}