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

项目摘要 肾移植是终末期肾病的最佳治疗方法，因为它可以提高生存率和降低死亡率。 和生活质量，并且比透析更具成本效益。然而，移植肾脏的寿命是 由于慢性免疫驱动损伤和免疫抑制药物的直接肾毒性， 过早的移植物丢失和再次移植的需要使本已严重的器官短缺雪上加霜。延长 移植物存活可能取决于供体与受体的最佳免疫匹配， 免疫攻击和减少侵略性免疫抑制的需要。HLA配型历来 依赖于通过血清学分析或两种方法确定的供体和受体HLA基因型的比较， 三维基因序列随着新的高分辨率基因分型，HLA抗原的物理结构 可以预测，从而能够在分子水平上比较供体/受体HLA基因型。简而言之，随着 高分辨率的基因型数据，一种名为HLAMatchmaker的计算机算法可以将基因序列提取为 被称为“eplets”的多态性氨基酸串位于HLA分子表面， 进入宿主免疫系统当供体和受体的HLA基因型被翻译成他们的 对应的小片段，我们可以将它们之间的免疫学可识别的差异记为 eplet不匹配。回顾性数据表明，那些偶然接受死亡供体肾脏的患者 具有低eplet错配（MM）负荷的人具有较低的从头供体特异性抗体（dnDSA）形成率， 上级移植物存活，并且可能需要较少的免疫抑制。有了活体捐赠， 评估给定受体的多个潜在供体，并在选择前比较他们的eplet MM程度 选择哪个捐赠者进行移植因此，活体供肾移植（LKDT）受体是最佳的 患者群体，在其中测试优化eplet匹配是否确实产生在较低水平下的移植。 同种免疫风险在与最大的配对肾脏交换，国家肾脏登记（NKR）， 我们已经开始将epletMM分析与其现有的供体-受体匹配算法相结合， 产生大量低eplet MM活体供肾移植。这些移植手术 在全国各地的中心进行，作为该试点计划的一部分。初步数据显示，dnDSA 形成是罕见的发生在这些受体，但在何种程度上低eplet MM LDKT允许 免疫抑制减少是未知的。这项R34补助金将使我们能够设计一个多中心的随机 一项前瞻性试验，旨在检测低eplet MM LDKT接受者的免疫抑制减少，以及 比较低eplet MM LKDT与高eplet MM LDKT的安全性和有效性。如果我们的假设是正确的， 将建立一种途径，通过该途径可以优化供体/受体匹配，以最大限度地延长移植物寿命， 最终提高患者生存率和生活质量。

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.