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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10480056 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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