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
. 2021 Jun:36:100883.
doi: 10.1016/j.eclinm.2021.100883. Epub 2021 May 3.

A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients

Affiliations

A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients

Ralph Wendt et al. EClinicalMedicine. 2021 Jun.

Abstract

Background: COVID-19 prediction models based on clinical characteristics, routine biochemistry and imaging, have been developed, but little is known on proteomic markers reflecting the molecular pathophysiology of disease progression.

Methods: The multicentre (six European study sites) Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection Study (Crit-COV-U) is recruiting consecutive patients (≥ 18 years) with PCR-confirmed SARS-CoV-2 infection. A urinary proteomic biomarker (COV50) developed by capillary-electrophoresis-mass spectrometry (CE-MS) technology, comprising 50 sequenced peptides and identifying the parental proteins, was evaluated in 228 patients (derivation cohort) with replication in 99 patients (validation cohort). Death and progression along the World Health Organization (WHO) Clinical Progression Scale were assessed up to 21 days after the initial PCR test. Statistical methods included logistic regression, receiver operating curve (ROC) analysis and comparison of the area under the curve (AUC).

Findings: In the derivation cohort, 23 patients died, and 48 developed worse WHO scores. The odds ratios (OR) for death per 1 standard deviation (SD) increment in COV50 were 3·52 (95% CI, 2·02-6·13, p <0·0001) unadjusted and 2·73 (1·25-5·95, p = 0·012) adjusted for sex, age, baseline WHO score, body mass index (BMI) and comorbidities. For WHO scale progression, the corresponding OR were 2·63 (1·80-3·85, p<0·0001) and 3·38 (1·85-6·17, p<0·0001), respectively. The area under the curve (AUC) for COV50 as a continuously distributed variable was 0·80 (0·72-0·88) for mortality and 0·74 (0·66-0·81) for worsening WHO score. The optimised COV50 thresholds for mortality and worsening WHO score were 0·47 and 0·04 with sensitivity/specificity of 87·0 (74·6%) and 77·1 (63·9%), respectively. On top of covariates, COV50 improved the AUC, albeit borderline for death, from 0·78 to 0·82 (p = 0·11) and 0·84 (p = 0·052) for mortality and from 0·68 to 0·78 (p = 0·0097) and 0·75 (p = 0·021) for worsening WHO score. The validation cohort findings were confirmatory.

Interpretation: This first CRIT-COV-U report proves the concept that urinary proteomic profiling generates biomarkers indicating adverse COVID-19 outcomes, even at an early disease stage, including WHO stages 1-3. These findings need to be consolidated in an upcoming final dataset.

Funding: The German Federal Ministry of Health funded the study.

Keywords: COVID-19; Disease severity; Risk score; SARS-CoV-2; Urinary proteomics.

PubMed Disclaimer

Conflict of interest statement

AW, BC, BN, HvdL, AN, JB, AM, MM, ACT, BP, KR, CL, RW, SK, ED, JS report payment for study inclusion from the Federal Ministry of Health (Germany) during the conduct of the study; MS reports Scientific Research Activity from Robert Bosch Stiftung during the conduct of the study, grants for clinical trials from Green Cross Wellbeing Co. Ltd. And Gilead Sciences Inc. and grants for research activity from Robert Bosch GmbH, consulting fees as reviewer for Research Impact Fund Hongkong and EU Horizon 2020, honoraria for lectures from CED Service GmbH and ALL Akademie, supporting for meetings from CED Service GmbH and ALL Akademie, participation on advisory board (European PGx Advisory Board) from Agena Bioscience GmbH and other financial interests (Editor) for Phrmacogenetics and Genomics, Drug Research and Genome Medicine; JM, JS and JR are past (JM) or current employees of Mosaiques-Diagnostics, Hanover, Germany, HM is a co-funder and co-owner of Mosaiques-Diagnostics.

Figures

Fig 1
Fig. 1
Performance of COV50 on top of other baseline risk factors in the derivation cohort to discriminate death from survival (panels A-C) and progression from non-progression in the time point 1 WHO score during follow-up (panels D-F) in the derivation cohort The base model included sex, age, body mass index and the presence of comorbidities: hypertension, heart failure, diabetes or cancer. In subsequent steps, the time point 1 WHO score was added and next COV50 as a continuously distributed variable (panels B and E) or as a categorised variable based on an optimised threshold of 0.47 for mortality (panel C) or 0.04 for a worsening WHO score (panel F).

References

    1. Huang C., Wang Y., Li X. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506. - PMC - PubMed
    1. Guan W., Ni Z., Hu Y. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382:1708–1720. - PMC - PubMed
    1. Williamson E.J., Walker A.J., Bhaskaran K. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584:430–436. - PMC - PubMed
    1. Wynants L., Van Calster B., Collins G.S. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. Br Med J. 2020;369:1328. - PMC - PubMed
    1. Montero-Odasso M., Hogan D.B., Lam R. Age alone is not adequate to determine health-care resource allocation during the COVID-19 pandemic. Can Geriatr J. 2020;23:152–154. - PMC - PubMed