Dataset Information

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

ABSTRACT:

Background

The delayed diagnosis of acute kidney injury (AKI) episodes and the lack of specificity of current single AKI biomarkers hamper its management. Urinary peptidome analysis may help to identify early molecular changes in AKI and grasp its complexity to identify potential targetable molecular pathways.

Methods

In derivation and validation cohorts totalizing 1170 major cardiac bypass surgery patients and in an external cohort of 1569 intensive care unit (ICU) patients, a peptide-based score predictive of AKI (7-day KDIGO classification) was developed, validated, and compared to the reference biomarker urinary NGAL and NephroCheck and clinical scores.

Results

A set of 204 urinary peptides derived from 48 proteins related to hemolysis, inflammation, immune cells trafficking, innate immunity, and cell growth and survival was identified and validated for the early discrimination (< 4 h) of patients according to their risk to develop AKI (OR 6.13 [3.96-9.59], p < 0.001) outperforming reference biomarkers (urinary NGAL and [IGFBP7].[TIMP2] product) and clinical scores. In an external cohort of 1569 ICU patients, performances of the signature were similar (OR 5.92 [4.73-7.45], p < 0.001), and it was also associated with the in-hospital mortality (OR 2.62 [2.05-3.38], p < 0.001).

Conclusions

An overarching AKI physiopathology-driven urinary peptide signature shows significant promise for identifying, at an early stage, patients who will progress to AKI and thus to develop tailored treatments for this frequent and life-threatening condition. Performance of the urine peptide signature is as high as or higher than that of single biomarkers but adds mechanistic information that may help to discriminate sub-phenotypes of AKI offering new therapeutic avenues.

SUBMITTER: Piedrafita A

PROVIDER: S-EPMC9640896 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

Piedrafita Alexis A Siwy Justyna J Klein Julie J Akkari Amal A Amaya-Garrido Ana A Mebazaa Alexandre A Sanz Anna Belen AB Breuil Benjamin B Montero Herrero Laura L Marcheix Bertrand B Depret François F Fernandez Lucie L Tardif Elsa E Minville Vincent V Alves Melinda M Metzger Jochen J Grossac Julia J Mischak Harald H Ortiz Alberto A Gazut Stéphane S Schanstra Joost P JP Faguer Stanislas S

Critical care (London, England) 20221107 1

<h4>Background</h4>The delayed diagnosis of acute kidney injury (AKI) episodes and the lack of specificity of current single AKI biomarkers hamper its management. Urinary peptidome analysis may help to identify early molecular changes in AKI and grasp its complexity to identify potential targetable molecular pathways.<h4>Methods</h4>In derivation and validation cohorts totalizing 1170 major cardiac bypass surgery patients and in an external cohort of 1569 intensive care unit (ICU) patients, a pe ...[more]

PMID: 36345008

Similar Datasets

Project description:ObjectivesWe investigated the temporal pattern and predictive value (alone and in combination) of 4 urinary biomarkers (neutrophil gelatinase-associated lipocalin [NGAL], interleukin [IL]-18, liver fatty acid-binding protein [L-FABP], and kidney injury molecule [KIM]-1) for cardiac surgery-associated acute kidney injury (AKI).BackgroundSerum creatinine (S(Cr)) is a delayed marker for AKI after cardiopulmonary bypass (CPB). Rapidly detectable AKI biomarkers could allow early intervention and improve outcomes.MethodsData from 220 pediatric patients were analyzed. Urine samples were obtained before and at intervals after CPB initiation. AKI was defined as a ≥50% increase in S(Cr) from baseline within 48 h after CPB. The temporal pattern of biomarker elevation was established, and biomarker elevations were correlated with AKI severity and clinical outcomes. Biomarker predictive abilities were evaluated by area under the curve (AUC), net reclassification improvement, and integrated discrimination improvement.ResultsAKI occurred in 27% of patients. Urine NGAL significantly increased in AKI patients at 2 h after CPB initiation. IL-18 and L-FABP increased at 6 h, and KIM-1 increased at 12 h. Biomarker elevations were correlated with AKI severity and clinical outcomes and improved AKI prediction above a clinical model. At 2 h, addition of NGAL increased the AUC from 0.74 to 0.85 (p < 0.0001). At 6 h, NGAL, IL-18, and L-FABP each improved the AUC from 0.72 to 0.91, 0.84, and 0.77, respectively (all p < 0.05). The added predictive ability of the biomarkers was supported by net reclassification improvement and integrated discrimination improvement. Biomarker combinations further improved AKI prediction.ConclusionsUrine NGAL, IL-18, L-FABP, and KIM-1 are sequential predictive biomarkers for AKI and are correlated with disease severity and clinical outcomes after pediatric CPB. These biomarkers, particularly in combination, may help establish the timing of injury and allow earlier intervention in AKI.

Dataset Information

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

Background

Methods

Results

Conclusions

Publications

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets