Implementation of Eplet Mismatch Analysis in Pediatric Kidney Transplantation

Eplet 错配分析在小儿肾移植中的实施

基本信息

  • 批准号:
    10739126
  • 负责人:
  • 金额:
    $ 17.52万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-08-01 至 2027-05-31
  • 项目状态:
    未结题

项目摘要

Kidney transplant (KT) offers a significant survival and morbidity benefit over dialysis, making it the preferred treatment modality for end-stage kidney disease. While late allograft failure has a multifactorial etiology, one of the largest contributors is the development of donor specific HLA antibodies (dnDSA), leading to allograft loss at a median 3-5 years post detection of antibodies. Donor specific HLA antibodies develop against short amino acid sequences within the HLA antigen. Each HLA antigen has multiple epitopes that can interact with the recipient immune system, and antibody-verified epitopes are termed “eplets”. Mismatched epitopes can be identified and enumerated using various molecular mismatch software packages. However, not all epitopes are equally likely to induce an antibody response in the recipient, as specific “high-risk” eplet mismatches were found to be disproportionally associated with dnDSA formation. Avoidance of high-risk mismatches between donor and recipient at the time of organ allocation is one way to improve long-term allograft survival because it would reduce the number of potential dnDSA targets. Variable immunogenicity is an accepted concept however details about which mismatches are high risk has not been well established. I propose to establish a multi-site pediatric kidney transplant (KT) cohort with full HLA genotyping on recipients and donors to perform such an analysis. This will inform the development of an adaptive allocation model, that can better account for the entangled and dynamic nature of allocation systems. The Organ Procurement and Transplant Network (OPTN) has mandated the development of a new allocation model, to develop a composite allocation scoring system that can account for dynamic changes in multiple recipient and donor characteristics. There is insufficient data to inform such a model on how to handle HLA mismatch on an epitope-level. My work with the multi-site cohort will inform how to best inform incorporate molecular mismatch analysis and high-resolution tissue typing data into an adaptive allocation model. My career goal is to become an independent clinical researcher focused on improving outcomes for KT recipients by studying the adaptive and humoral immune response to the allograft and conducting clinical trials to test interventions to reduce the burden of disease. By completion of the proposed research and didactic training at the Johns Hopkins School of Public Health, I will obtain a PhD in Clinical Research Methodology and develop a unique skillset that will allow me to establish an independent research career in transplant immunology. Specifically, I will gain expertise in multi-site study design and execution, large data management and analysis, advanced computational modeling, and application of immunogenetics to clinical practice.
与透析相比,肾移植(KT)提供了显著的生存和发病率优势,使其成为最佳的治疗方案

项目成果

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Olga Charnaya其他文献

Olga Charnaya的其他文献

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