Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jan 9;24(1):10.
doi: 10.1186/s13054-019-2686-0.

A novel urinary biomarker predicts 1-year mortality after discharge from intensive care

Esther Nkuipou-Kenfack  1 , Agnieszka Latosinska  1 , Wen-Yi Yang  2   3 , Marie-Céline Fournier  4 , Alice Blet  4   5 , Blerim Mujaj  2 , Lutgarde Thijs  2 , Elodie Feliot  4 , Etienne Gayat  4   5   6 , Harald Mischak  1 , Jan A Staessen  2   7 , Alexandre Mebazaa  4   5   6 , Zhen-Yu Zhang  8 ; French and European Outcome Registry in Intensive Care Unit Investigators
Collaborators, Affiliations

A novel urinary biomarker predicts 1-year mortality after discharge from intensive care

Esther Nkuipou-Kenfack et al. Crit Care. .

Abstract

Rationale: The urinary proteome reflects molecular drivers of disease.

Objectives: To construct a urinary proteomic biomarker predicting 1-year post-ICU mortality.

Methods: In 1243 patients, the urinary proteome was measured on ICU admission, using capillary electrophoresis coupled with mass spectrometry along with clinical variables, circulating biomarkers (BNP, hsTnT, active ADM, and NGAL), and urinary albumin. Methods included support vector modeling to construct the classifier, Cox regression, the integrated discrimination (IDI), and net reclassification (NRI) improvement, and area under the curve (AUC) to assess predictive accuracy, and Proteasix and protein-proteome interactome analyses.

Measurements and main results: In the discovery (deaths/survivors, 70/299) and test (175/699) datasets, the new classifier ACM128, mainly consisting of collagen fragments, yielding AUCs of 0.755 (95% CI, 0.708-0.798) and 0.688 (0.656-0.719), respectively. While accounting for study site and clinical risk factors, hazard ratios in 1243 patients were 2.41 (2.00-2.91) for ACM128 (+ 1 SD), 1.24 (1.16-1.32) for the Charlson Comorbidity Index (+ 1 point), and ≥ 1.19 (P ≤ 0.022) for other biomarkers (+ 1 SD). ACM128 improved (P ≤ 0.0001) IDI (≥ + 0.50), NRI (≥ + 53.7), and AUC (≥ + 0.037) over and beyond clinical risk indicators and other biomarkers. Interactome mapping, using parental proteins derived from sequenced peptides included in ACM128 and in silico predicted proteases, including/excluding urinary collagen fragments (63/35 peptides), revealed as top molecular pathways protein digestion and absorption, lysosomal activity, and apoptosis.

Conclusions: The urinary proteomic classifier ACM128 predicts the 1-year post-ICU mortality over and beyond clinical risk factors and other biomarkers and revealed molecular pathways potentially contributing to a fatal outcome.

Keywords: Biomarker; Heart failure; Intensive care medicine; Mortality; Urinary proteomics.

PubMed Disclaimer

Conflict of interest statement

H.M. is the co-owner of Mosaiques Diagnostics. E.N-K and A.L. are employed by Mosaiques Diagnostics. All other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Cumulative incidence of mortality over 1 year in 1243 study participants by thirds of the ACM128 distribution, unadjusted (a), adjusted for sex and age (b), and additionally adjusted for Charlson Comorbidity Index (c). P values denote the significance of the difference between the low (≤ − 0.662) and top (> − 0.091) thirds of the ACM128 distribution. The numbers along the horizontal axis denote the number of patients at risk at 60-day intervals
See this image and copyright information in PMC

References

    1. Wunsch H, Guerra C, Barnato AE, Angus DC, Li G, Linde-Zwirble WT. Three-year outcomes for Medicare beneficiaries who survive intensive care. J Am Med Assoc. 2010;303:849–856. doi: 10.1001/jama.2010.216. - DOI - PubMed
    1. Keenan SP, Dodek P, Chan K, Hogg RS, Craib KJP, Anis AH, Spinelli JJ. Intensive care unit admission has minimal impact on long-term mortality. Crit Care Med. 2002;30:501–507. doi: 10.1097/00003246-200203000-00002. - DOI - PubMed
    1. Williams TA, Dobb GJ, Finn JC, Knuiman MW, Geelhoed E, Li K, Webb SAR. Determinants of long-term survival after intensive care. Crit Care Med. 2008;36:1523–1530. doi: 10.1097/CCM.0b013e318170a405. - DOI - PubMed
    1. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Amann M, Anderson HR, Andrews KG, Aryee M, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010 : a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–2260. doi: 10.1016/S0140-6736(12)61766-8. - DOI - PMC - PubMed
    1. Angus DC, Carlet J, on behalf of the Brussels Roundtable Participants: surviving intensive care: a report from the 2002 Brussels Roundtable. Intensive Care Med. 2002;2002(29):368–377. - PubMed

Publication types

LinkOut - more resources