*Purpose: Recent molecular studies have highlighted the unrecognized burden of sub-clinical graft rejection of a histologically stable allograft, defined as transplants with absence of clinical acute rejection (AR) and histological inflammation. However, some of them might not have stable immune quiescence, as they may be molecularly similar to AR. Thus, refining the definition of a stable allograft as one that is clinically, histologically and molecularly quiescent is critical, as the inclusion of stable allografts in mechanistic and clinical studies are vital to provide a normal, non-injured comparative group for all interrogative studies on understanding allograft injury.

*Methods: In this meta-analysis study, we analyzed publicly available transcriptional data across 4,845 human kidney tissue samples from 38 GEO datasets, inclusive of 510 AR, 1,154 histological stable (hSTA), and 609 normal kidney (donor) samples.

*Results: By leveraging gene expression measures in AR and donor biopsies and applying machine learning techniques, we identified of a subset of 6 genes (KLF4, CENPJ, KLF2, PPP1R15A, FOSB, TNFAIP3) with the highest predictive value in separating AR from normal donor kidneys. Additionally, we found a specific subset of 5 immune cell types (CD4+ Tcm, CD4+ Tem, CD8+ Tem, NK cells, and Th1 cells) that together with 6 selected genes were combined into one composite score, the Instability Score (InstaScore). We found that about a half (54%) of the histologically defined STA (hSTA) had immune quiescence and molecular similarities to the healthy donor kidneys and have been redefined as histologically and molecularly stable (hSTA/mSTA). Another part of the hSTA (46%) had molecular evidence of rejection (hSTA/mAR) and should not have been classified as stable allografts. We conducted an independent validation of the InstaScore and identified subgroups of hSTA phenotypes on 6 months protocol biopsies where hSTA/mAR samples had a significant change in graft function and graft loss at 5-year follow-ups. Consequently, we also identified a drop by 10 in eGFR as a threshold in allograft transitioning from hSTA/mSTA to hSTA/mAR states that could have an important clinical utility.

*Conclusions: This is the first development and application of a combined gene and cell type score in tissue that can rapidly reclassify samples into molecularly and functionally relevant groups. Thus, this tool could provide an important adjunct for comprehensive and highly quantitative phenotyping of protocol kidney transplant biopsy and be integrated into clinical care for accurate prediction of subsequent patient clinical outcomes.

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