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Novel transcriptomic signatures associated with premature kidney allograft failure

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 retrospec...

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Autores principales: Hruba, Petra, Klema, Jiri, Le, Anh Vu, Girmanova, Eva, Mrazova, Petra, Massart, Annick, Maixnerova, Dita, Voska, Ludek, Piredda, Gian Benedetto, Biancone, Luigi, Puga, Ana Ramirez, Seyahi, Nurhan, Sever, Mehmet Sukru, Weekers, Laurent, Muhfeld, Anja, Budde, Klemens, Watschinger, Bruno, Miglinas, Marius, Zahradka, Ivan, Abramowicz, Marc, Abramowicz, Daniel, Viklicky, Ondrej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480056/
https://www.ncbi.nlm.nih.gov/pubmed/37660534
http://dx.doi.org/10.1016/j.ebiom.2023.104782
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author Hruba, Petra
Klema, Jiri
Le, Anh Vu
Girmanova, Eva
Mrazova, Petra
Massart, Annick
Maixnerova, Dita
Voska, Ludek
Piredda, Gian Benedetto
Biancone, Luigi
Puga, Ana Ramirez
Seyahi, Nurhan
Sever, Mehmet Sukru
Weekers, Laurent
Muhfeld, Anja
Budde, Klemens
Watschinger, Bruno
Miglinas, Marius
Zahradka, Ivan
Abramowicz, Marc
Abramowicz, Daniel
Viklicky, Ondrej
author_facet Hruba, Petra
Klema, Jiri
Le, Anh Vu
Girmanova, Eva
Mrazova, Petra
Massart, Annick
Maixnerova, Dita
Voska, Ludek
Piredda, Gian Benedetto
Biancone, Luigi
Puga, Ana Ramirez
Seyahi, Nurhan
Sever, Mehmet Sukru
Weekers, Laurent
Muhfeld, Anja
Budde, Klemens
Watschinger, Bruno
Miglinas, Marius
Zahradka, Ivan
Abramowicz, Marc
Abramowicz, Daniel
Viklicky, Ondrej
author_sort Hruba, Petra
collection PubMed
description 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 10.13039/501100003243Ministry of Health of the Czech Republic under grant NV19-06-00031.
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spelling pubmed-104800562023-09-06 Novel transcriptomic signatures associated with premature kidney allograft failure Hruba, Petra Klema, Jiri Le, Anh Vu Girmanova, Eva Mrazova, Petra Massart, Annick Maixnerova, Dita Voska, Ludek Piredda, Gian Benedetto Biancone, Luigi Puga, Ana Ramirez Seyahi, Nurhan Sever, Mehmet Sukru Weekers, Laurent Muhfeld, Anja Budde, Klemens Watschinger, Bruno Miglinas, Marius Zahradka, Ivan Abramowicz, Marc Abramowicz, Daniel Viklicky, Ondrej eBioMedicine Articles 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 10.13039/501100003243Ministry of Health of the Czech Republic under grant NV19-06-00031. Elsevier 2023-09-01 /pmc/articles/PMC10480056/ /pubmed/37660534 http://dx.doi.org/10.1016/j.ebiom.2023.104782 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Hruba, Petra
Klema, Jiri
Le, Anh Vu
Girmanova, Eva
Mrazova, Petra
Massart, Annick
Maixnerova, Dita
Voska, Ludek
Piredda, Gian Benedetto
Biancone, Luigi
Puga, Ana Ramirez
Seyahi, Nurhan
Sever, Mehmet Sukru
Weekers, Laurent
Muhfeld, Anja
Budde, Klemens
Watschinger, Bruno
Miglinas, Marius
Zahradka, Ivan
Abramowicz, Marc
Abramowicz, Daniel
Viklicky, Ondrej
Novel transcriptomic signatures associated with premature kidney allograft failure
title Novel transcriptomic signatures associated with premature kidney allograft failure
title_full Novel transcriptomic signatures associated with premature kidney allograft failure
title_fullStr Novel transcriptomic signatures associated with premature kidney allograft failure
title_full_unstemmed Novel transcriptomic signatures associated with premature kidney allograft failure
title_short Novel transcriptomic signatures associated with premature kidney allograft failure
title_sort novel transcriptomic signatures associated with premature kidney allograft failure
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480056/
https://www.ncbi.nlm.nih.gov/pubmed/37660534
http://dx.doi.org/10.1016/j.ebiom.2023.104782
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