A prospective clinical trial of immunosuppression reduction in recipients of low eplet mismatched renal allografts: the kidney for life initiative

项目总结 肾移植是终末期肾病最有效的治疗方法，因为它可以提高两种疾病的存活率 和生活质量，而且比透析更具成本效益。然而，移植肾脏的寿命是 由于慢性免疫驱动的损伤和免疫抑制药物的直接肾毒性而缩短。 过早的移植物丢失和再次移植的需要加剧了本已严重的器官短缺。延长 移植物的存活可能取决于优化供者和受者的免疫匹配，以最大限度地减少 免疫攻击，减少对侵袭性免疫抑制的需求。从历史上看，人类白细胞抗原匹配 依赖于通过血清学分析或两种方法确定的供者和接受者的人类白细胞抗原基因型别的比较。 空间基因序列。随着新的高分辨率基因分型，人类白细胞抗原的物理结构 可以预测，从而能够在分子水平上比较供者/受者的人类白细胞抗原基因型别。简而言之，与 高分辨率的基因数据，一种名为HLAMatchaker的计算机算法可以将基因序列提取到 位于人类白细胞抗原分子表面的多态氨基酸串，称为eplet，因此 可被宿主免疫系统访问。当供者和受者的人类白细胞抗原基因型别转化为 相应的Eplet，我们可以将它们之间的免疫识别差异归结为 电子邮件不匹配的情况。回顾数据表明，偶然接受死亡的供体或肾脏的患者 低Eplet失配(MM)负荷具有较低的从头供体特异性抗体(DnDSA)形成率， 移植物存活率高，可能需要较少的免疫抑制。有了活体捐赠，就有机会 评估给定接受者的多个潜在捐赠者，并在选择之前比较他们的Eplet MM程度 选择哪位捐赠者进行移植。因此，活体供肾移植(LKDT)的接受者是最理想的 在患者群体中测试优化EPLET配型是否确实会产生较低的移植比例 同种异体免疫风险。与最大的配对肾脏交易所国家肾脏注册中心(NKR)合作， 我们已经开始将Eplet MM分析与其现有的捐赠者-接受者匹配算法相结合，以便 产生大量低Eplet MM活体供肾移植。这些移植现在正在被 作为这一试点计划的一部分，在全国各地的中心演出。初步数据表明，dnDSA 在这些受者中形成是罕见的，然而低Eplet MM LDKT允许的程度 免疫抑制的减少尚不清楚。这笔R34拨款将使我们能够设计一种多中心随机 前瞻性测试低Eplet MM LDKT受者的免疫抑制减少的试验，以及 比较低Eplet MM LKDT和高Eplet MM LDKT的安全性和有效性。如果我们的假设是正确的，我们 将建立一种途径，通过它可以优化供者/接受者匹配，以最大限度地延长移植物寿命和 最终提高患者的存活率和生活质量。

PROJECT SUMMARY Kidney transplantation is the best available treatment for end stage renal disease as it improves both survival and quality of life and is more cost effective than dialysis. However, the lifespan of transplanted kidneys is shortened due to chronic immune-driven injury and the direct nephrotoxicity of immunosuppressive drugs. Premature graft loss and the need for re-transplantation worsens an already dire organ shortage. Prolonging graft survival may hinge on optimizing immunologic matching of donors with recipients, to minimize targets of immunologic attack and decrease the need for aggressive immunosuppression. HLA matching has historically relied upon comparison of donor and recipient HLA genotypes determined either by serologic analysis or two- dimensional gene sequences. With newer high-resolution genotyping, the physical structures of HLA antigens can be predicted, enabling comparisons of donor/recipient HLA genotypes at the molecular level. In brief, with high-resolution genotype data, a computer algorithm called HLAMatchmaker can distill gene sequences into strings of polymorphic amino acids termed ‘eplets’ that are located on the HLA molecule surface and are thus accessible to the host immune system. When donor and recipient HLA genotypes are translated into their corresponding eplets, we can tally the immunologically recognizable differences between them as the number of eplet mismatches. Retrospective data indicate that patients who, by chance, received deceaseddonorkidneys with a low eplet mismatch (MM) load have lower rates of de novo donor specific antibody (dnDSA) formation, superior graft survival, and may require less immunosuppression. With living donation, there is opportunity to evaluate multiple potential donors for a given recipient and compare their degree of eplet MM before choosing which donor to proceed with to transplant. Thus, living donor kidney transplant (LKDT) recipients are the optimal patient population in which to test whether optimizing eplet matching indeed yields transplants that are at lower alloimmune risk. In collaboration with the largest paired kidney exchange, the National Kidney Registry (NKR), we have begun combining eplet MM analysis with its existing donor-recipient matching algorithms in order to generate high volumes of low eplet MM living donor kidney transplants. These transplants are now being performed at centers across the country as part of this pilot program. Preliminary data indicate that dnDSA formation is rare occurred in these recipients, however the degree to which low eplet MM LDKT permits immunosuppression reduction is not known. This R34 grant will enable us to design a multi-center randomized trial to prospectively test immunosuppression reduction in recipients of low eplet MM LDKT, as well as to compare the safety and efficacy of low eplet MM LKDT to high eplet MM LDKT. If our hypothesis is correct, we will establish a pathway by which donor/recipient matching can be optimized to maximize graft longevity and ultimately improve both patient survival and quality of life.