Abstract
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. 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.
Highlights
Breakthroughs in surgical approaches and development of newer generations of immunosuppressive drugs have resulted in reduction of clinical allograft acute rejection (AR) and improvements in life expectancy and quality of life for kidney transplant recipients.[1]
Within the 28 data sets, the feature selection procedure identified a set of 6 genes (KLF4, CENPJ, KLF2, PPP1R15A, FOSB, TNFAIP3) 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)
From the total 28 data sets, the feature selection procedure identified a set of 6 genes (KLF4, CENPJ, KLF2, PPP1R15A, FOSB, and TNFAIP3) (AUC, 0.98) and 5 immune cell types (CD4+ Tcm, CD4+ Tem, CD8+ Tem, NK cells, and TH1 cells) (AUC, 0.92) that were combined into 1 composite InstaScore (AUC, 0.99)
Summary
Breakthroughs in surgical approaches and development of newer generations of immunosuppressive drugs have resulted in reduction of clinical allograft acute rejection (AR) and improvements in life expectancy and quality of life for kidney transplant recipients.[1]. There is a failure to uncover the molecular biologic diversity in the histologic definition of a stable allograft. This bias is further amplified during interrogation of kidney transplant biopsy samples across different pathologists and investigators in public data sets. We have aggregated, to our knowledge, the largest public data set for human kidney transplantation to date: 2273 kidney tissue microarray samples from 28 publicly available normal and transplant kidney tissue data sets[14] in Gene Expression Omnibus,[15] a public genomics data repository, to investigate the molecular diversity of stable allografts.[16,17,18,19] We proposed that for accurate definition of a stable allograft, the sample must be associated with (1) stable clinical function, (2) normal kidney histology with AR (histologically stable [hSTA]), and (3) absence of a transcriptional signature of AR (molecularly stable [mSTA]). Our prognostic study proposes an approach to recognize immunologic heterogeneity in hSTA kidney allografts
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