Rychkov Dmitry, Sur Swastika, Sirota Marina, Sarwal Minnie M
Division of Multi-Organ Transplantation, Department of Surgery, University of California, San Francisco.
Bakar Computational Health Sciences Institute, University of California, San Francisco.
JAMA Netw Open. 2021 Jan 4;4(1):e2035048. doi: 10.1001/jamanetworkopen.2020.35048.
Clinical decision and immunosuppression dosing in kidney transplantation rely on transplant biopsy tissue histology even though histology has low specificity, sensitivity, and reproducibility for rejection diagnosis. The inclusion of stable allografts in mechanistic and clinical studies is vital to provide a normal, noninjured comparative group for all interrogative studies on understanding allograft injury.
To refine the definition of a stable allograft as one that is clinically, histologically, and molecularly quiescent using publicly available transcriptomics data.
DESIGN, SETTING, AND PARTICIPANTS: In this prognostic study, the National Center for Biotechnology Information Gene Expression Omnibus was used to search for microarray gene expression data from kidney transplant tissues, resulting in 38 studies from January 1, 2017, to December 31, 2018. The diagnostic annotations included 510 acute rejection (AR) samples, 1154 histologically stable (hSTA) samples, and 609 normal samples. Raw fluorescence intensity data were downloaded and preprocessed followed by data set merging and batch correction.
The primary measure was area under the receiver operating characteristics curve from a set of feature selected genes and cell types for distinguishing AR from normal kidney tissue.
Within the 28 data sets, the feature selection procedure identified a set of 6 genes (KLF4, CENPJ, KLF2, PPP1R15A, FOSB, TNFAIP3) (area under the curve [AUC], 0.98) and 5 immune cell types (CD4+ T-cell central memory [Tcm], CD4+ T-cell effector memory [Tem], CD8+ Tem, natural killer [NK] cells, and Type 1 T helper [TH1] cells) (AUC, 0.92) that were combined into 1 composite Instability Score (InstaScore) (AUC, 0.99). The InstaScore was applied to the hSTA samples: 626 of 1154 (54%) were found to be immune quiescent and redefined as histologically and molecularly stable (hSTA/mSTA); 528 of 1154 (46%) were found to have molecular evidence of rejection (hSTA/mAR) and should not have been classified as stable allografts. The validation on an independent cohort of 6 months of protocol biopsy samples in December 2019 showed that hSTA/mAR samples had a significant change in graft function (r = 0.52, P < .001) and graft loss at 5-year follow-up (r = 0.17). A drop by 10 mL/min/1.73m2 in estimated glomerular filtration rate was estimated as a threshold in allograft transitioning from hSTA/mSTA to hSTA/mAR.
The results of this prognostic study suggest that the InstaScore could provide an important adjunct for comprehensive and highly quantitative phenotyping of protocol kidney transplant biopsy samples and could be integrated into clinical care for accurate estimation of subsequent patient clinical outcomes.
肾移植中的临床决策和免疫抑制剂量依赖于移植活检组织的组织学检查,尽管组织学在排斥反应诊断方面特异性、敏感性和可重复性较低。在机制研究和临床研究中纳入稳定的同种异体移植物对于为所有关于理解同种异体移植物损伤的询问性研究提供一个正常、未受损的对照组至关重要。
利用公开可用的转录组学数据,将稳定同种异体移植物的定义细化为临床、组织学和分子水平均静止的移植物。
设计、设置和参与者:在这项预后研究中,利用美国国立生物技术信息中心基因表达综合数据库搜索肾移植组织的微阵列基因表达数据,得到2017年1月1日至2018年12月31日的38项研究。诊断注释包括510个急性排斥反应(AR)样本、1154个组织学稳定(hSTA)样本和609个正常样本。下载原始荧光强度数据并进行预处理,随后进行数据集合并和批次校正。
主要指标是一组选定特征基因和细胞类型的受试者操作特征曲线下面积,用于区分AR与正常肾组织。
在28个数据集中,特征选择程序确定了一组6个基因(KLF4、CENPJ、KLF2、PPP1R15A、FOSB、TNFAIP3)(曲线下面积[AUC]为0.98)和5种免疫细胞类型(CD4 + T细胞中央记忆细胞[Tcm]、CD4 + T细胞效应记忆细胞[Tem]、CD8 + Tem、自然杀伤[NK]细胞和1型辅助性T细胞[TH1]细胞)(AUC为0.92),它们被合并为1个综合不稳定评分(InstaScore)(AUC为0.99)。将InstaScore应用于hSTA样本:1154个样本中有626个(54%)被发现免疫静止,并重新定义为组织学和分子水平稳定(hSTA/mSTA);1154个样本中有528个(46%)被发现有排斥反应的分子证据(hSTA/mAR),不应被归类为稳定的同种异体移植物。对2019年12月6个月方案活检样本的独立队列进行验证,结果显示hSTA/mAR样本的移植功能有显著变化(r = 0.52,P <.001),且在5年随访时有移植丢失(r = 0.17)。估计肾小球滤过率下降10 mL/min/1.73m2被估计为同种异体移植物从hSTA/mSTA转变为hSTA/mAR的阈值。
这项预后研究的结果表明,InstaScore可为方案肾移植活检样本的全面和高度定量表型分析提供重要辅助,并可纳入临床护理以准确估计后续患者的临床结局。