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Novel transcriptomic signatures associated with premature kidney allograft failure

ABSTRACT: Prediction power of kidney allograft outcomes based on non-invasive assays is limited. Assessments of operational tolerance (OT) patients allow to identify transcriptomic signatures of true non-responders for construction of predictive models. In the discovery cohort, RNA sequencing was used to identify protective set of transcripts by comparison of 15 OT patients from TOMOGRAM Study (NCT05124444) with 14 chronic active antibody-mediated rejection (CABMR) and 23 stable graft function ≥15 years (STA). Archetypal analysis and classifier performance of RNA sequencing data showed that OT is clearly distinguishable from CABMR, but similar to STA. Selected differentially expressed transcripts between OT and CABMR were used in validation cohort (n=396) to predict 3-year kidney allograft loss at 3 time-points using RT-qPCR. Based on significant transcripts in univariable analysis, 2 multivariable Cox models were created. 3-transcripts (ADGRG3, ATG2A and GNLY) model from POD 7 predicted graft loss with C C-statistics (C) 0.727 (95% CI, 0.638-0.820). Another 3-transcript (IGHM, CD5, GNLY) model from M3 predicted graft loss with C 0.786 (95% CI, 0.785-0.865). Combining 3-transcript model with eGFR at month 3 improved C-statistics to 0.860 (95% CI, 0.778-0.944) and 0.868 (95% CI, 0.790-0.944), respectively. The model based on DGF, acute rejection, HLA mismatch and eGFR reached similar performance (C 0.846). In conclusion, identification of transcripts distinguishing OT from CABMR allowed to construct models predicting premature graft loss. Predictive statistics of these models reach same performance as well known-clinical models. Identified transcripts reflect mechanisms of injury/repair and alloimmune response when assessed at day 7 or with a loss of protective phenotype when assessed at month 3.

ORGANISM(S): Homo sapiens

PROVIDER: GSE222889 | GEO | 2023/01/16

REPOSITORIES: GEO

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Project description:Using meta-analysis of eight independent transplant datasets (236 graft biopsy samples) from four organs, we identified a common rejection module (CRM) consisting of 11 genes that were significantly overexpressed in acute rejection (AR) across all transplanted organs. The CRM genes could diagnose AR with high specificity and sensitivity in three additional independent cohorts (794 samples). In another two independent cohorts (151 renal transplant biopsies), the CRM genes correlated with the extent of graft injury and predicted future injury to a graft using protocol biopsies. Inferred drug mechanisms from the literature suggested that two FDA-approved drugs (atorvastatin and dasatinib), approved for non-transplant indications, could regulate specific CRM genes and reduce the number of graft infiltrating cells during acute rejection. We treated mice with HLA-mismatched murine cardiac transplant with atorvastatin and dasatinib and showed reduction of the CRM genes, significant reduction of graft infiltrating cells, and extended graft survival. We further validated the beneficial effect of atorvastatina on graft survival by retrospective analysis of electronic medical records of a single-center cohort of 2,515 renal transplant patients. In conclusion, we identified a CRM in transplantation that provides new opportunities for diagnosis, drug repositioning and rational drug design. The eight transplant data sets used for discovery include GSE4315, GSE2596, GSE4470, GSE9377, GSE1563, GSE9493, GSE13440, GSE6095. The two additional independent cohorts of 151 transplant biopsies are GSE25902 and GSE1563. Not all samples from all studies were used. Only the samples marked as either AR or STA in each data set were used for analysis. The 101 samples in this study were used as case-control experiment between acute rejection (AR) and stable (STA) in renal transplant. The samples in this series are one of the three independent validation cohorts. The other two cohorts are described in GSE21374 and GSE36059

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Novel transcriptomic signatures associated with premature kidney allograft failure

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