Back to Search Start Over

Novel transcriptomic signatures associated with premature kidney allograft failureResearch in context

Authors :
Petra Hruba
Jiri Klema
Anh Vu Le
Eva Girmanova
Petra Mrazova
Annick Massart
Dita Maixnerova
Ludek Voska
Gian Benedetto Piredda
Luigi Biancone
Ana Ramirez Puga
Nurhan Seyahi
Mehmet Sukru Sever
Laurent Weekers
Anja Muhfeld
Klemens Budde
Bruno Watschinger
Marius Miglinas
Ivan Zahradka
Marc Abramowicz
Daniel Abramowicz
Ondrej Viklicky
Source :
EBioMedicine, Vol 96, Iss , Pp 104782- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: Background: The power to predict kidney allograft outcomes based on non-invasive assays is limited. Assessment of operational tolerance (OT) patients allows us to identify transcriptomic signatures of true non-responders for construction of predictive models. Methods: In this observational retrospective study, RNA sequencing of peripheral blood was used in a derivation cohort to identify a protective set of transcripts by comparing 15 OT patients (40% females), from the TOMOGRAM Study (NCT05124444), 14 chronic active antibody-mediated rejection (CABMR) and 23 stable graft function patients ≥15 years (STA). The selected differentially expressed transcripts between OT and CABMR were used in a validation cohort (n = 396) to predict 3-year kidney allograft loss at 3 time-points using RT-qPCR. Findings: Archetypal analysis and classifier performance of RNA sequencing data showed that OT is clearly distinguishable from CABMR, but similar to STA. Based on significant transcripts from the validation cohort in univariable analysis, 2 multivariable Cox models were created. A 3-transcript (ADGRG3, ATG2A, and GNLY) model from POD 7 predicted graft loss with 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-transcripts models with eGFR at POD 7 and M3 improved C-statistics to 0.860 (95% CI, 0.778–0.944) and 0.868 (95% CI, 0.790–0.944), respectively. Interpretation: Identification of transcripts distinguishing OT from CABMR allowed us to construct models predicting premature graft loss. 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. Funding: Supported by the Ministry of Health of the Czech Republic under grant NV19-06-00031.

Details

Language :
English
ISSN :
23523964
Volume :
96
Issue :
104782-
Database :
Directory of Open Access Journals
Journal :
EBioMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.6f8b0114d8394fbaba4fde90f52363e0
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ebiom.2023.104782