PDF(Pubmed)
Abstract：
Development of donor-specific human leukocyte antigen (HLA) antibodies (DSA) remains a major risk factor for graft loss following organ transplantation, where DSA are directed towards patches on the three-dimensional structure of the respective organ donor\'s HLA proteins. Matching donors and recipients based on HLA epitopes appears beneficial for the avoidance of DSA. Defining surface epitopes however remains challenging and the concepts underlying their characterization are not fully understood. Based on our recently implemented computational deep learning pipeline to define HLA Class I protein-specific surface residues, we hypothesized a correlation between the number of HLA protein-specific solvent-accessible interlocus amino acid mismatches (arbitrarily called Snowflake) and the incidence of DSA. To validate our hypothesis, we considered two cohorts simultaneously. The kidney transplant cohort (KTC) considers 305 kidney-transplanted patients without DSA prior to transplantation. During the follow-up, HLA antibody screening was performed regularly to identify DSA. The pregnancy cohort (PC) considers 231 women without major sensitization events prior to pregnancy who gave live birth. Post-delivery serum was screened for HLA antibodies directed against the child\'s inherited paternal haplotype (CSA). Based on the involved individuals\' HLA typings, the numbers of interlocus-mismatched antibody-verified eplets (AbvEPS), the T cell epitope PIRCHE-II model and Snowflake were calculated locus-specific (HLA-A, -B and -C), normalized and pooled. In both cohorts, Snowflake numbers were significantly elevated in recipients/mothers that developed DSA/CSA. Univariable regression revealed significant positive correlation between DSA/CSA and AbvEPS, PIRCHE-II and Snowflake. Snowflake numbers showed stronger correlation with numbers of AbvEPS compared to Snowflake numbers with PIRCHE-II. Our data shows correlation between Snowflake scores and the incidence of DSA after allo-immunization. Given both AbvEPS and Snowflake are B cell epitope models, their stronger correlation compared to PIRCHE-II and Snowflake appears plausible. Our data confirms that exploring solvent accessibility is a valuable approach for refining B cell epitope definitions.
摘要：
供体特异性人类白细胞抗原（HLA）抗体（DSA）的发展仍然是器官移植后移植物丢失的主要危险因素，其中DSA指向相应器官供体HLA蛋白的三维结构上的斑块。基于HLA表位的匹配供体和受体似乎有利于避免DSA。然而，定义表面表位仍然具有挑战性，并且其表征的概念尚未完全理解。基于我们最近实施的计算深度学习管道来定义HLAI类蛋白质特异性表面残基，我们假设HLA蛋白特异性溶剂可及位点间氨基酸错配(任意称为雪花)的数量与DSA发生率之间存在相关性.为了验证我们的假设，我们同时考虑了两个队列。肾移植队列（KTC）考虑了305例移植前没有DSA的肾移植患者。在后续行动中,定期进行HLA抗体筛选以鉴定DSA。怀孕队列（PC）考虑了231名在怀孕前没有重大致敏事件的妇女，他们分娩了活产。分娩后血清筛选针对儿童遗传父系单倍型(CSA)的HLA抗体。根据涉及的个人HLA分型，基因座间错配抗体验证小片(AbvEPS)的数量，计算T细胞表位PIRCHE-II模型和雪花的基因座特异性(HLA-A，-B和-C)，标准化和汇集。在这两个队列中，患有DSA/CSA的接受者/母亲的雪花数量显着增加。单变量回归分析显示DSA/CSA与AbvEPS呈显著正相关,PIRCHE-II和雪花。与PIRCHE-II的雪花数相比，雪花数与AbvEPS数的相关性更强。我们的数据显示了雪花评分与同种免疫后DSA发生率之间的相关性。鉴于AbvEPS和雪花都是B细胞表位模型，与PIRCHE-II和雪花相比，它们的相关性更强似乎是合理的。我们的数据证实，探索溶剂可及性是完善B细胞表位定义的有价值的方法。
