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人类白细胞抗原氨基酸多态性与肾移植存活率

HLA Amino Acid Polymorphisms and Kidney Allograft Survival.

作者信息

Kamoun Malek, McCullough Keith P, Maiers Martin, Fernandez Vina Marcelo A, Li Hongzhe, Teal Valerie, Leichtman Alan B, Merion Robert M

机构信息

1 Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA. 2 Arbor Research Collaborative for Health, Ann Arbor, MI. 3 National Marrow Donor Program, Minneapolis, MN. 4 Department of Pathology, Stanford University, Palo Alto, CA. 5 Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA.

出版信息

Transplantation. 2017 May;101(5):e170-e177. doi: 10.1097/TP.0000000000001670.

DOI:10.1097/TP.0000000000001670
PMID:28221244
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5642346/
Abstract

BACKGROUND

The association of HLA mismatching with kidney allograft survival has been well established. We examined whether amino acid (AA) mismatches (MMs) at the antigen recognition site of HLA molecules represent independent and incremental risk factors for kidney graft failure (GF) beyond those MMs assessed at the antigenic (2-digit) specificity.

METHODS

Data on 240 024 kidney transplants performed between 1987 and 2009 were obtained from the Scientific Registry of Transplant Recipients. We imputed HLA-A, -B, and -DRB1 alleles and corresponding AA polymorphisms from antigenic specificity through the application of statistical and population genetics inferences. GF risk was evaluated using Cox proportional-hazards regression models adjusted for covariates including patient and donor risk factors and HLA antigen MMs.

RESULTS

We show that estimated AA MMs at particular positions in the peptide-binding pockets of HLA-DRB1 molecule account for a significant incremental risk that was independent of the well-known association of HLA antigen MMs with graft survival. A statistically significant linear relationship between the estimated number of AA MMs and risk of GF was observed for HLA-DRB1 in deceased donor and living donor transplants. This relationship was strongest during the first 12 months after transplantation (hazard ratio, 1.30 per 15 DRB1 AA MM; P < 0.0001).

CONCLUSIONS

This study shows that independent of the well-known association of HLA antigen (2-digit specificity) MMs with kidney graft survival, estimated AA MMs at peptide-binding sites of the HLA-DRB1 molecule account for an important incremental risk of GF.

摘要

背景

HLA错配与肾移植存活率之间的关联已得到充分证实。我们研究了HLA分子抗原识别位点的氨基酸(AA)错配是否代表肾移植失败(GF)的独立且递增的风险因素,这些因素超出了在抗原性(2位数字)特异性水平评估的错配。

方法

从移植受者科学登记处获取了1987年至2009年间进行的240024例肾移植的数据。通过应用统计和群体遗传学推断,从抗原特异性中推算出HLA-A、-B和-DRB1等位基因以及相应的AA多态性。使用Cox比例风险回归模型评估GF风险,并对包括患者和供体风险因素以及HLA抗原错配在内的协变量进行调整。

结果

我们发现,HLA-DRB1分子肽结合口袋中特定位置的估计AA错配占显著的递增风险,这与HLA抗原错配与移植物存活的已知关联无关。在 deceased donor和 living donor移植中,观察到HLA-DRB1的AA错配估计数与GF风险之间存在统计学上显著的线性关系。这种关系在移植后的前12个月最强(风险比,每15个DRB1 AA错配为1.30;P < 0.0001)。

结论

本研究表明,独立于HLA抗原(2位数字特异性)错配与肾移植存活的已知关联,HLA-DRB1分子肽结合位点的估计AA错配占GF的重要递增风险。

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本文引用的文献

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The eplet load concept in clinical transplantation.临床移植中的表位负荷概念。
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HapLogic: A Predictive Human Leukocyte Antigen-Matching Algorithm to Enhance Rapid Identification of the Optimal Unrelated Hematopoietic Stem Cell Sources for Transplantation.HapLogic:一种预测性人类白细胞抗原匹配算法,用于加强对移植最佳无关造血干细胞来源的快速识别。
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A comparative reference study for the validation of HLA-matching algorithms in the search for allogeneic hematopoietic stem cell donors and cord blood units.
基于 HLA 氨基酸错配的新型机器学习算法对肾移植失败的风险分层。
J Biomed Inform. 2023 Jun;142:104374. doi: 10.1016/j.jbi.2023.104374. Epub 2023 Apr 27.
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Fine mapping of the HLA locus in Parkinson's disease in Europeans.欧洲人群中帕金森病HLA基因座的精细定位
NPJ Parkinsons Dis. 2021 Sep 21;7(1):84. doi: 10.1038/s41531-021-00231-5.
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Unique Pathogen Peptidomes Facilitate Pathogen-Specific Selection and Specialization of MHC Alleles.独特病原体肽组学促进 MHC 等位基因的病原体特异性选择和特化。
Mol Biol Evol. 2021 Sep 27;38(10):4376-4387. doi: 10.1093/molbev/msab176.
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Common, intermediate and well-documented HLA alleles in world populations: CIWD version 3.0.0.世界人群中常见、中等频率且记录完善的HLA等位基因:CIWD版本3.0.0
HLA. 2020 Jun;95(6):516-531. doi: 10.1111/tan.13811. Epub 2020 Jan 31.
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HLA. 2019 Sep;94(3):296-306. doi: 10.1111/tan.13619. Epub 2019 Jul 15.
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