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Subclinical and clinical acute kidney injury share similar urinary peptide signatures and prognosis

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Abstract

Purpose

Acute kidney injury (AKI) is a frequent and severe condition in intensive care units (ICUs). In 2020, the Acute Dialysis Quality Initiative (ADQI) group proposed a new stage of AKI, referred to as stage 1S, which represents subclinical disease (sAKI) defined as a positive biomarker but no increase in serum creatinine (sCr). This study aimed to determine and compare the urinary peptide signature of sAKI as defined by biomarkers.

Methods

This is an ancillary analysis of the prospective, observational, multinational FROG-ICU cohort study. AKI was defined according to the Kidney Disease Improving Global Outcome definition (AKIKDIGO). sAKI was defined based on the levels of the following biomarkers, which exceeded the median value: neutrophil gelatinase-associated lipocalin (pNGAL, uNGAL), cystatin C (pCysC, uCysC), proenkephalin A 119–159 (pPENKID) and liver fatty acid binding protein (uLFABP). Urinary peptidomics analysis was performed using capillary electrophoresis-mass spectrometry. Samples were collected at the time of study inclusion.

Results

One thousand eight hundred eighty-five patients had all biomarkers measured at inclusion, which included 1154 patients without AKI (non-AKIKDIGO subgroup). The non-AKIKDIGO subgroup consisted of individuals at a median age of 60 years [48, 71], among whom 321 (27.8%) died. The urinary peptide signatures of sAKI, regardless of the biomarkers used for its definition, were similar to the urinary peptide signatures of AKIKDIGO (inflammation, haemolysis, and endothelial dysfunction). These signatures were also associated with 1-year mortality.

Conclusion

Biomarker-defined sAKI is a common and severe condition observed in patients within intensive care units with a urinary peptide signature that is similar to that of AKI, along with a comparable prognosis.

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Data availability

The data that support the findings of this study are available from the corresponding author (FD) upon reasonable request.

References

  1. Hoste EA, Bagshaw SM, Bellomo R et al (2015) Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med 41(8):1411–1423. https://doi.org/10.1007/s00134-015-3934-7

    Article  PubMed  Google Scholar 

  2. Section 2: AKI Definition. Kidney Int Suppl (2011). 2012 Mar;2(1):19–36. https://doi.org/10.1038/kisup.2011.32

  3. Córdova-Sánchez BM, Herrera-Gómez Á, Ñamendys-Silva SA (2016) Acute Kidney Injury Classified by Serum Creatinine and Urine Output in Critically Ill Cancer Patients. Biomed Res Int 2016:6805169. https://doi.org/10.1155/2016/6805169

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ronco C, Rosner MH (2012) Acute kidney injury and residual renal function. Crit Care 16(4):144. https://doi.org/10.1186/cc11426

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kannapiran M, Nisha D, Madhusudhana RA (2010) Underestimation of impaired kidney function with serum creatinine. Indian J Clin Biochem 25(4):380–384. https://doi.org/10.1007/s12291-010-0080-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Chen YW, Wu MY, Mao CH et al (2022) Severe acute kidney disease is associated with worse kidney outcome among acute kidney injury patients. Sci Rep 12(1):6492. https://doi.org/10.1038/s41598-022-09599-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Noble RA, Lucas BJ, Selby NM (2020) Long-Term Outcomes in Patients with Acute Kidney Injury. Clin J Am Soc Nephrol 15(3):423–429. https://doi.org/10.2215/CJN.10410919

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ostermann M, Zarbock A, Goldstein S et al (2020) Recommendations on acute kidney injury biomarkers from the acute disease quality initiative consensus conference: a consensus statement. JAMA Netw Open 3(10):e2019209. https://doi.org/10.1001/jamanetworkopen.2020.19209

    Article  PubMed  Google Scholar 

  9. Nehomar PG (2020) Biomarkers in Acute Kidney Injury. J Clin Nephrol 4:027–035. https://doi.org/10.29328/journal.jcn.1001056

    Article  Google Scholar 

  10. Mavrogeorgis E, Mischak H, Latosinska A et al (2021) Collagen-Derived Peptides in CKD: a link to fibrosis. Toxins (Basel) 14(1):10. https://doi.org/10.3390/toxins14010010

    Article  CAS  PubMed  Google Scholar 

  11. He T, Mischak M, Clark AL et al (2021) Urinary peptides in heart failure: a link to molecular pathophysiology. Eur J Heart Fail 23(11):1875–1887. https://doi.org/10.1002/ejhf.2195

    Article  CAS  PubMed  Google Scholar 

  12. Piedrafita A, Siwy J, Klein J et al (2022) A universal predictive and mechanistic urinary peptide signature in acute kidney injury. Crit Care 26(1):344. https://doi.org/10.1186/s13054-022-04193-9

    Article  PubMed  PubMed Central  Google Scholar 

  13. Mebazaa A, Casadio MC, Azoulay E et al (2015) Post-ICU discharge and outcome: rationale and methods of the The French and euRopean Outcome egistry in Intensive Care Units (FROG-ICU) observational study. BMC Anesthesiol 15:143. https://doi.org/10.1186/s12871-015-0129-2

    Article  PubMed  PubMed Central  Google Scholar 

  14. Vincent JL, Moreno R, Takala J et al (1996) The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med 22(7):707–710. https://doi.org/10.1007/BF01709751

    Article  CAS  PubMed  Google Scholar 

  15. Le Gall JR, Lemeshow S, Saulnier F (1993) A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA 270(24):2957–2963. https://doi.org/10.1001/jama.270.24.2957

    Article  PubMed  Google Scholar 

  16. Dépret F, Hollinger A, Cariou A et al (2020) Incidence and Outcome of Subclinical Acute Kidney Injury Using penKid in Critically Ill Patients. Am J Respir Crit Care Med 202(6):822–829. https://doi.org/10.1164/rccm.201910-1950OC

    Article  PubMed  Google Scholar 

  17. Mischak H, Vlahou A, Ioannidis JP (2013) Technical aspects and inter-laboratory variability in native peptide profiling: the CE-MS experience. Clin Biochem 46(6):432–443. https://doi.org/10.1016/j.clinbiochem.2012.09.025

    Article  CAS  PubMed  Google Scholar 

  18. Cuschieri S (2019) The STROBE guidelines. Saudi J Anaesth 13(1):S31–S34. https://doi.org/10.4103/sja.SJA_543_18

    Article  PubMed  PubMed Central  Google Scholar 

  19. UniProt Consortium (2023) UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res 51(D1):D523–D531. https://doi.org/10.1093/nar/gkac1052

    Article  CAS  Google Scholar 

  20. Harris MA, Clark J, Ireland A et al (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res 32:D258–D261. https://doi.org/10.1093/nar/gkh036

    Article  CAS  PubMed  Google Scholar 

  21. Haase M, Devarajan P, Haase-Fielitz A et al (2011) The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: a multicenter pooled analysis of prospective studies. J Am Coll Cardiol 57(17):1752–1761. https://doi.org/10.1016/j.jacc.2010.11.051

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Legrand M, Darmon M, Joannidis M (2013) NGAL and AKI: the end of a myth? Intensive Care Med 39(10):1861–1863. https://doi.org/10.1007/s00134-013-3061-2

    Article  PubMed  Google Scholar 

  23. Legrand M, Mari A, Mebazaa A (2013) The elusive task of biomarkers of renal injury. Crit Care 17(2):132. https://doi.org/10.1186/cc12578

    Article  PubMed  PubMed Central  Google Scholar 

  24. Work Group Membership (2011) Kidney Int Suppl 2(4):281. https://doi.org/10.1038/kisup.2012.39

    Article  Google Scholar 

  25. De Vlieger G, Forni L, Schneider A (2022) New diagnostics for AKI in critically ill patients: what to expect in the future. Intensive Care Med 48:1632–1634. https://doi.org/10.1007/s00134-022-06843-6

    Article  PubMed  Google Scholar 

  26. von Groote TC, Ostermann M, Forni LG, Meersch-Dini M, Zarbock A, PrevAKI Investigators (2022) The AKI care bundle: all bundle components are created equal-are they? Intensive Care Med 48(2):242–245. https://doi.org/10.1007/s00134-021-06601-0

    Article  Google Scholar 

  27. Zarbock A, Küllmar M, Ostermann M et al (2021) Prevention of Cardiac Surgery-Associated Acute Kidney Injury by Implementing the KDIGO Guidelines in High-Risk Patients Identified by Biomarkers: The PrevAKI-Multicenter Randomized Controlled Trial. Anesth Analg 133(2):292–302. https://doi.org/10.1213/ANE.0000000000005458

    Article  CAS  PubMed  Google Scholar 

  28. Schrezenmeier EV, Barasch J, Budde K, Westhoff T, Schmidt-Ott KM (2017) Biomarkers in acute kidney injury - pathophysiological basis and clinical performance. Acta Physiol (Oxf) 219(3):554–572. https://doi.org/10.1111/apha.12764

    Article  CAS  PubMed  Google Scholar 

  29. Törnblom S, Nisula S, Petäjä L et al (2020) Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility-data from the observational FINNAKI study. Ann Intensive Care 10(1):51. https://doi.org/10.1186/s13613-020-00667-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Khawaja S, Jafri L, Siddiqui I, Hashmi M, Ghani F (2019) The utility of neutrophil gelatinase-associated Lipocalin (NGAL) as a marker of acute kidney injury (AKI) in critically ill patients. Biomark Res 7:4. https://doi.org/10.1186/s40364-019-0155-1

    Article  PubMed  PubMed Central  Google Scholar 

  31. Shimazui T, Nakada TA, Tateishi Y, Oshima T, Aizimu T, Oda S (2019) Association between serum levels of interleukin-6 on ICU admission and subsequent outcomes in critically ill patients with acute kidney injury. BMC Nephrol 20(1):74. https://doi.org/10.1186/s12882-019-1265-6

    Article  PubMed  PubMed Central  Google Scholar 

  32. Zhang Z, Lu B, Sheng X, Jin N (2011) Cystatin C in prediction of acute kidney injury: a systemic review and meta-analysis. Am J Kidney Dis 58(3):356–365. https://doi.org/10.1053/j.ajkd.2011.02.389

    Article  CAS  PubMed  Google Scholar 

  33. Lagos-Arevalo P, Palijan A, Vertullo L et al (2015) Cystatin C in acute kidney injury diagnosis: early biomarker or alternative to serum creatinine? Pediatr Nephrol 30(4):665–676. https://doi.org/10.1007/s00467-014-2987-0

    Article  PubMed  Google Scholar 

  34. Boutin L, Legrand M, Sadoune M et al (2022) Elevated plasma Galectin-3 is associated with major adverse kidney events and death after ICU admission. Crit Care 26(1):13. https://doi.org/10.1186/s13054-021-03878-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kellum JA, Romagnani P, Ashuntantang G, Ronco C, Zarbock A, Anders HJ (2021) Acute kidney injury. Nat Rev Dis Primers 7(1):52. https://doi.org/10.1038/s41572-021-00284-z

    Article  PubMed  Google Scholar 

  36. Pickkers P, Darmon M, Hoste E et al (2021) Acute kidney injury in the critically ill: an updated review on pathophysiology and management. Intensive Care Med 47(8):835–850. https://doi.org/10.1007/s00134-021-06454-7

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kellum JA, Ronco C, Bellomo R (2021) Conceptual advances and evolving terminology in acute kidney disease. Nat Rev Nephrol 17(7):493–502. https://doi.org/10.1038/s41581-021-00410-w

    Article  CAS  PubMed  Google Scholar 

  38. Forni LG, Joannidis M, Artigas A et al (2022) Characterising acutekidney injury: The complementary roles of biomarkers of renal stress and renal function. J Crit Care 71:154066. https://doi.org/10.1016/j.jcrc.2022.154066

    Article  CAS  PubMed  Google Scholar 

  39. Schmitt J, Aries P, Deserts DD, M. et al (2022) Before AKI renal microcirculation stress may be detected by urine biochemistry. Intensive Care Med 48:1672–1673. https://doi.org/10.1007/s00134-022-06873-0

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors are particularly grateful to CRAs and healthcare providers of all investigating centers. We also thank the “Centre de Recherche Clinique” (CRC) of Lariboisière University Hospital for his support. N. Deye, C. Fauvaux, C. Damoisel, D. Payen, E.Gayat, E. Azoulay, A. S. Moreau, L. Jacob, O. Marie (Hôpital Saint Louis, Paris), M. Wolf, R. Sonneville, R. Bronchard (Hôpital Bichat, Paris), I. Rennuit, C. Paugam (Hôpital Beaujon, Clichy), J. P. Mira, A. Cariou, A. Tesnieres (Hôpital Cochin, Paris), N. Dufour, N. Anguel, L. Guerin, J. Duranteau, C. Ract (Hôpital Bicêtre, Le Kremlin‐Bicêtre), M. Leone, B. Pastene (CHU De Marseille, Marseille), T. Sharshar, A. Fayssoyl (Hôpital Raymond Poincare, Garches), J.‐L. Baudel, B. Guidet (Hôpital Saint‐Antoine), Q. Lu, W. Jie Gu, N. Brechot, A. Combes (Hôpital La Pitie – Salpetriere, Paris), S. Jaber, A. 6 Pradel, Y. Coisel, M. Conseil (CHU St Eloi, Montpellier), A. Veillard‐Baron, L. Bodson (Hôpital Ambroise Pare, Boulogne), Jy. Lefrant, L. Elotmani, A. Ayral, S. Lloret (CHU Caremeau, Nimes), S. Pily‐Flouri, Jb. Pretalli (Hopital Jean Minjoz, Besançon), Pf. Laterre, V. Montiel, Mf. Dujardin, C. Berghe (Clinique Saint‐Luc, Belgium). We thank Nicholas Fong for his revision of the manuscript.

Funding

FROG‐ICU (ClinicalTrials.gov Identifier NCT01367093) was funded by the “Programme Hospitalier de la Recherche Clinique” (AON 10‐216) 5 and by a research grant from the “Société Française d’Anesthésie – Réanimation”. Abbott, Sphingotec, Roche Diagnostics, and Critical Diagnostics provided unrestricted free kits to “Assistance Publique – Hôpitaux de Paris” to conduct biomarker analyses. The original FROG-ICU study was supported by grants from “Assistance Publique‐Hôpitaux de Paris” (AOR01004) and from “Société Française d’Anesthésie–Réanimation”. The study funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

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Authors and Affiliations

  1. Department of Anesthesiology, Critical Care Medicine and Burn Unit, FHU PROMICE AP-HP, Saint Louis and DMU Parabol, AP-HP, Université Paris Cité, 75010, Paris, France

    Louis Boutin, Benjamin Deniau, Etienne Gayat, Alexandre Mebazaa & François Depret

  2. UMR-942, MASCOT, INSERM, Cardiovascular Markers in Stress Condition, Université de Paris, 75010, Paris, France

    Louis Boutin, Benjamin Deniau, Ayu Asakage, Etienne Gayat, Alexandre Mebazaa & François Depret

  3. UMR-S1155, Faculty of Medicine, INSERM Bâtiment Recherche, Tenon Hospital Sorbonne University, 75020, Paris, France

    Louis Boutin & Christos E. Chadjichristos

  4. Mosaiques Diagnostics GmbH, Hannover, Germany

    Agnieszka Latosinska & Harald Mischak

  5. Department of Anesthesiology and Peri-Operative Medicine, Division of Critical Care Medicine, University of California, UCSF Medical Center, 500 Parnassus Ave, San Francisco, CA, 94143, USA

    Matthieu Legrand

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  1. Louis Boutin
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Contributions

FD and LB had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: LB, AL, HM, FD. Acquisition, analysis, or interpretation of data: LB, AL, HM, ML, AM, FD. Drafting of the manuscript: LB, AL, HM, BD, ML, AM, FD. Critical revision of the manuscript for important intellectual content: LB, AL, HM, BD, AA, ML, EG, AM, CEC, FD. Statistical analysis: LB. Obtained funding: ML, EG, AM, FD. Supervision: ML, AM, FD.

Corresponding author

Correspondence to François Depret.

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Conflict of interest

HM is the cofounder and co-owner of Mosaiques Diagnostics (Hannover, Germany) and AL is employee of Mosaiques Diagnostics. EG received a research grant from Sphingotec and consultancy fees from Magnisense and Roche Diagnostics. AM received speaker’s honoraria from Abbott, Novartis, Orion, Roche, and Servier and a fee as a member of the advisory board and/or steering committee from Cardiorentis, Adrenomed, MyCartis, Neurotronik, and Sphingotec. The other authors have no conflicts of interest to declare.

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Boutin, L., Latosinska, A., Mischak, H. et al. Subclinical and clinical acute kidney injury share similar urinary peptide signatures and prognosis. Intensive Care Med 49, 1191–1202 (2023). https://doi.org/10.1007/s00134-023-07198-2

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