Novel transcriptomic signatures associated with premature kidney allograft failure
Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved..
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.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:96 |
---|---|
Enthalten in: |
EBioMedicine - 96(2023) vom: 01. Okt., Seite 104782 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Hruba, Petra [VerfasserIn] |
---|
Links: |
---|
Themen: |
Chronic antibody-mediated rejection |
---|
Anmerkungen: |
Date Revised 13.10.2023 published: Print-Electronic Citation Status Publisher |
---|
doi: |
10.1016/j.ebiom.2023.104782 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM361582579 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM361582579 | ||
003 | DE-627 | ||
005 | 20231226085440.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.ebiom.2023.104782 |2 doi | |
028 | 5 | 2 | |a pubmed24n1205.xml |
035 | |a (DE-627)NLM361582579 | ||
035 | |a (NLM)37660534 | ||
035 | |a (PII)S2352-3964(23)00348-1 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Hruba, Petra |e verfasserin |4 aut | |
245 | 1 | 0 | |a Novel transcriptomic signatures associated with premature kidney allograft failure |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Revised 13.10.2023 | ||
500 | |a published: Print-Electronic | ||
500 | |a Citation Status Publisher | ||
520 | |a Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved. | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a FUNDING: Supported by the Ministry of Health of the Czech Republic under grant NV19-06-00031 | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Chronic antibody-mediated rejection | |
650 | 4 | |a Kidney graft failure | |
650 | 4 | |a Operational tolerance | |
650 | 4 | |a Peripheral blood transcripts | |
650 | 4 | |a RNA sequencing | |
700 | 1 | |a Klema, Jiri |e verfasserin |4 aut | |
700 | 1 | |a Le, Anh Vu |e verfasserin |4 aut | |
700 | 1 | |a Girmanova, Eva |e verfasserin |4 aut | |
700 | 1 | |a Mrazova, Petra |e verfasserin |4 aut | |
700 | 1 | |a Massart, Annick |e verfasserin |4 aut | |
700 | 1 | |a Maixnerova, Dita |e verfasserin |4 aut | |
700 | 1 | |a Voska, Ludek |e verfasserin |4 aut | |
700 | 1 | |a Piredda, Gian Benedetto |e verfasserin |4 aut | |
700 | 1 | |a Biancone, Luigi |e verfasserin |4 aut | |
700 | 1 | |a Puga, Ana Ramirez |e verfasserin |4 aut | |
700 | 1 | |a Seyahi, Nurhan |e verfasserin |4 aut | |
700 | 1 | |a Sever, Mehmet Sukru |e verfasserin |4 aut | |
700 | 1 | |a Weekers, Laurent |e verfasserin |4 aut | |
700 | 1 | |a Muhfeld, Anja |e verfasserin |4 aut | |
700 | 1 | |a Budde, Klemens |e verfasserin |4 aut | |
700 | 1 | |a Watschinger, Bruno |e verfasserin |4 aut | |
700 | 1 | |a Miglinas, Marius |e verfasserin |4 aut | |
700 | 1 | |a Zahradka, Ivan |e verfasserin |4 aut | |
700 | 1 | |a Abramowicz, Marc |e verfasserin |4 aut | |
700 | 1 | |a Abramowicz, Daniel |e verfasserin |4 aut | |
700 | 1 | |a Viklicky, Ondrej |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t EBioMedicine |d 2014 |g 96(2023) vom: 01. Okt., Seite 104782 |w (DE-627)NLM244581355 |x 2352-3964 |7 nnns |
773 | 1 | 8 | |g volume:96 |g year:2023 |g day:01 |g month:10 |g pages:104782 |
856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.ebiom.2023.104782 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 96 |j 2023 |b 01 |c 10 |h 104782 |