Research and Development, PIRCHE AG, Berlin, Germany.
Center for Tumor Medicine, H&I Laboratory, Charité University Medicine Berlin, Berlin, Germany.
Front Immunol. 2022 Oct 28;13:1005601. doi: 10.3389/fimmu.2022.1005601. eCollection 2022.
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.
供者特异性人类白细胞抗原（HLA）抗体（DSA）的产生仍然是器官移植后移植物丢失的一个主要危险因素，其中 DSA 针对各自器官供体 HLA 蛋白三维结构上的斑块。基于 HLA 表位匹配供者和受者似乎有利于避免 DSA。然而，定义表面表位仍然具有挑战性，并且其特征背后的概念尚未完全理解。基于我们最近实施的用于定义 HLA I 类蛋白特异性表面残基的计算深度学习管道，我们假设 HLA 蛋白特异性溶剂可及的基因间氨基酸错配（任意称为雪花）数量与 DSA 的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 名在移植前没有 DSA 的肾移植患者。在随访期间，定期进行 HLA 抗体筛查以识别 DSA。妊娠队列（PC）考虑了 231 名在妊娠前没有重大致敏事件的女性，她们分娩了活产儿。产后血清筛查针对针对儿童遗传父系单体型（CSA）的 HLA 抗体。基于所涉及个体的 HLA 分型，计算了基因间错配抗体验证表位（AbvEPS）、T 细胞表位 PIRCHE-II 模型和雪花的数量，进行了基因座特异性（HLA-A、-B 和 -C）归一化和汇总。在两个队列中，发生 DSA/CSA 的受者/母亲的雪花数量显着升高。单变量回归显示 DSA/CSA 与 AbvEPS、PIRCHE-II 和 Snowflake 之间存在显著正相关。与 PIRCHE-II 相比，Snowflake 数量与 AbvEPS 数量的相关性更强。我们的数据显示雪花分数与同种免疫后 DSA 的发生率之间存在相关性。鉴于 AbvEPS 和 Snowflake 都是 B 细胞表位模型，与 PIRCHE-II 和 Snowflake 相比，它们之间的相关性更强是合理的。我们的数据证实，探索溶剂可及性是一种用于改进 B 细胞表位定义的有价值的方法。
