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

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 V...

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Autores principales: Wendt, Ralph, Thijs, Lutgarde, Kalbitz, Sven, Mischak, Harald, Siwy, Justyna, Raad, Julia, Metzger, Jochen, Neuhaus, Barbara, Leyen, Heiko von der, Dudoignon, Emmanuel, Mebazaa, Alexandre, Spasovski, Goce, Milenkova, Mimoza, Canevska-Talevska, Aleksandra, Czerwieńska, Beata, Wiecek, Andrzej, Peters, Björn, Nilsson, Åsa, Schwab, Matthias, Rothfuss, Katja, Lübbert, Christoph, Staessen, Jan A., Beige, Joachim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8092440/
https://www.ncbi.nlm.nih.gov/pubmed/33969282
http://dx.doi.org/10.1016/j.eclinm.2021.100883
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author Wendt, Ralph
Thijs, Lutgarde
Kalbitz, Sven
Mischak, Harald
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Leyen, Heiko von der
Dudoignon, Emmanuel
Mebazaa, Alexandre
Spasovski, Goce
Milenkova, Mimoza
Canevska-Talevska, Aleksandra
Czerwieńska, Beata
Wiecek, Andrzej
Peters, Björn
Nilsson, Åsa
Schwab, Matthias
Rothfuss, Katja
Lübbert, Christoph
Staessen, Jan A.
Beige, Joachim
author_facet Wendt, Ralph
Thijs, Lutgarde
Kalbitz, Sven
Mischak, Harald
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Leyen, Heiko von der
Dudoignon, Emmanuel
Mebazaa, Alexandre
Spasovski, Goce
Milenkova, Mimoza
Canevska-Talevska, Aleksandra
Czerwieńska, Beata
Wiecek, Andrzej
Peters, Björn
Nilsson, Åsa
Schwab, Matthias
Rothfuss, Katja
Lübbert, Christoph
Staessen, Jan A.
Beige, Joachim
author_sort Wendt, Ralph
collection PubMed
description 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.
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spelling pubmed-80924402021-05-03 A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients Wendt, Ralph Thijs, Lutgarde Kalbitz, Sven Mischak, Harald Siwy, Justyna Raad, Julia Metzger, Jochen Neuhaus, Barbara Leyen, Heiko von der Dudoignon, Emmanuel Mebazaa, Alexandre Spasovski, Goce Milenkova, Mimoza Canevska-Talevska, Aleksandra Czerwieńska, Beata Wiecek, Andrzej Peters, Björn Nilsson, Åsa Schwab, Matthias Rothfuss, Katja Lübbert, Christoph Staessen, Jan A. Beige, Joachim EClinicalMedicine Research Paper 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. Elsevier 2021-05-03 /pmc/articles/PMC8092440/ /pubmed/33969282 http://dx.doi.org/10.1016/j.eclinm.2021.100883 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Wendt, Ralph
Thijs, Lutgarde
Kalbitz, Sven
Mischak, Harald
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Leyen, Heiko von der
Dudoignon, Emmanuel
Mebazaa, Alexandre
Spasovski, Goce
Milenkova, Mimoza
Canevska-Talevska, Aleksandra
Czerwieńska, Beata
Wiecek, Andrzej
Peters, Björn
Nilsson, Åsa
Schwab, Matthias
Rothfuss, Katja
Lübbert, Christoph
Staessen, Jan A.
Beige, Joachim
A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title_full A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title_fullStr A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title_full_unstemmed A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title_short A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients
title_sort urinary peptidomic profile predicts outcome in sars-cov-2-infected patients
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8092440/
https://www.ncbi.nlm.nih.gov/pubmed/33969282
http://dx.doi.org/10.1016/j.eclinm.2021.100883
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