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Hruba P, Klema J, Le AV, Girmanova E, Mrazova P, Massart A, Maixnerova D, Voska L, Piredda GB, Biancone L, Puga AR, Seyahi N, Sever MS, Weekers L, Muhfeld A, Budde K, Watschinger B, Miglinas M, Zahradka I, Abramowicz M, Abramowicz D, Viklicky O. Novel transcriptomic signatures associated with premature kidney allograft failure. EBioMedicine 2023; 96:104782. [PMID: 37660534 PMCID: PMC10480056 DOI: 10.1016/j.ebiom.2023.104782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/18/2023] [Accepted: 08/18/2023] [Indexed: 09/05/2023] Open
Abstract
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.
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Affiliation(s)
- Petra Hruba
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jiri Klema
- Department of Computer Science, Czech Technical University, Prague, Czech Republic
| | - Anh Vu Le
- Department of Computer Science, Czech Technical University, Prague, Czech Republic
| | - Eva Girmanova
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Petra Mrazova
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Annick Massart
- Antwerp University Hospital and Antwerp University, Antwerp, Belgium
| | - Dita Maixnerova
- Department of Nephrology, 1st Faculty of Medicine and General Faculty Hospital, Prague, Czech Republic
| | - Ludek Voska
- Department of Clinical and Transplant Pathology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Gian Benedetto Piredda
- Department of Kidney Disease Medicine of Renal Transplantation, G.Brotzu Hospital Cagliari, Italy
| | - Luigi Biancone
- Department of Medical Sciences, University of Torino, Torino, Italy
| | - Ana Ramirez Puga
- Hospital Universitario Insular de Gran Canaria, Servicio de nefrología, Spain
| | - Nurhan Seyahi
- Istanbul University, Cerrahpasa Medical Faculty, Nephrology, Istanbul, Turkey
| | - Mehmet Sukru Sever
- Istanbul University, Istanbul School of Medicine, Internal Medicine, Nephrology, Istanbul, Turkey
| | | | - Anja Muhfeld
- Department of Nephrology, Uniklinik RWTH Aachen, Aachen, Germany
| | - Klemens Budde
- Charité - Universitätsmedizin Berlin, Medizinische Klinik mit Schwerpunkt Nephrologie und Internistische Intensivmedizin, Berlin, Germany
| | - Bruno Watschinger
- Department of Internal Medicine III, Nephrology, Medical University Vienna / AKH Wien, Vienna, Austria
| | - Marius Miglinas
- Faculty of Medicine, Nephrology Center, Vilnius University Hospital Santaros Klinikos, Vilnius University, Vilnius, Lithuania
| | - Ivan Zahradka
- Department of Nephrology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Marc Abramowicz
- Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Rue Michel Servet 1, 1206 Geneva, Switzerland
| | - Daniel Abramowicz
- Antwerp University Hospital and Antwerp University, Antwerp, Belgium
| | - Ondrej Viklicky
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic; Department of Nephrology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
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