Mortality Risk and Urinary Proteome Changes in Acute COVID-19 Survivors in the Multinational CRIT-COV-U Study
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND/OBJECTIVES: Survival prospects following SARS-CoV-2 infection may extend beyond the acute phase, influenced by various factors including age, health conditions, and infection severity; however, this topic has not been studied in detail. Therefore, within this study, the mortality risk post-acute COVID-19 in the CRIT-COV-U cohort was investigated. METHODS: Survival data from 651 patients that survived an acute phase of COVID-19 were retrieved and the association between urinary peptides and future death was assessed. Data spanning until December 2023 were collected from six countries, comparing mortality trends with age- and sex-matched COVID-19-negative controls. A death prediction classifier was developed and validated using pre-existing urinary peptidomic datasets. RESULTS: Notably, 13.98% of post-COVID-19 patients succumbed during the follow-up, with mortality rates significantly higher than COVID-19-negative controls, particularly evident in younger individuals (<65 years). These data for the first time demonstrate that SARS-CoV-2 infection highly significantly increases the risk of mortality not only during the acute phase of the disease but also beyond for a period of about one year. In our study, we were further able to identify 201 urinary peptides linked to mortality. These peptides are fragments of albumin, alpha-2-HS-glycoprotein, apolipoprotein A-I, beta-2-microglobulin, CD99 antigen, various collagens, fibrinogen alpha, polymeric immunoglobulin receptor, sodium/potassium-transporting ATPase, and uromodulin and were integrated these into a predictive classifier (DP201). Higher DP201 scores, alongside age and BMI, significantly predicted death. CONCLUSIONS: The peptide-based classifier demonstrated significant predictive value for mortality in post-acute COVID-19 patients, highlighting the utility of urinary peptides in prognosticating post-acute COVID-19 mortality, offering insights for targeted interventions. By utilizing these defined biomarkers in the clinic, risk stratification, monitoring, and personalized interventions can be significantly improved. Our data also suggest that mortality should be considered as one possible symptom or a consequence of post-acute sequelae of SARS-CoV-2 infection, a fact that is currently overlooked.
Source: Biomedicines
Authors: Justyna Siwy, Felix Keller, Mirosław Banasik, Björn Peters, Emmanuel Dudoignon, Alexandre Mebazaa, Dilara Gülmez, Goce Spasovski, Mercedes Salgueira Lazo, Marek W. Rajzer, Łukasz Fuławka, Magdalena Dzitkowska-Zabielska, Harald Mischak, Manfred Hecking, Joachim Beige, Ralph Wendt, UriCoV Working Group
Institutions: Mosaiques Diagnostics and Therapeutics (Germany), Innsbruck Medical University, Universität Innsbruck, University of Wrocław, Wroclaw Medical University, Skaraborg Hospital, University of Gothenburg, Assistance Publique – Hôpitaux de Paris, Hôpital Lariboisière, Medical University of Vienna, Ss. Cyril and Methodius University in Skopje, Hospital Universitario Virgen Macarena, Universidad de Sevilla, Jagiellonian University, Molecular Pathology Centre Cellgen, Gdansk University of Physical Education and Sport, Gdańsk Medical University, Klinikum St. Georg, Martin Luther University Halle-Wittenberg
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,955
Funders: Västra Götalandsregionen, Universidad de Sevilla, Uniwersytet Jagielloński Collegium Medicum, Agence Nationale de la Recherche, Institut National de la Santé et de la Recherche Médicale, VINNOVA, Bundesministerium für Bildung und Forschung, Austrian Science Fund, Universität Wien, Bundesministerium für Gesundheit, Göteborgs Universitet, Medizinische Universität Wien, Assistance publique-Hôpitaux de Paris, Śląski Uniwersytet Medyczny w Katowicach, Uniwersytet Śląski w Katowicach, Sorbonne Université, Narodowe Centrum Badań i Rozwoju, Sahlgrenska Akademin
Awards: G1190643235, G1429210840, URInary peptidomic patterns of Long-COVID syndrom, G1720065626, G1841313488, G1844800759, G2012367807, G2054381315, G2065891390, G2455050838, G2788552355, G33095994, G343429224, Urinary peptidomic patterns of longCoVID syndrome (UriCoV), G4023994298, G4082499701, G4313100455, G4371762634, G4495373907, G4568159235, Urinary peptidomic patterns of Long-COVID syndrome, G4690222332, G4753025026, G4942035999, UriCoV - Urin-peptidomische Muster als Biomarker des Long-COVID Syndroms, G5384092168, G5418141630, G5496075972, G5637409084, G6021309638, G6166306422, G6734062441, G7197900497, G7238891561, G7435269324, G759645546, G7673201846, Body fluid proteome SIGnatures for personNALised interventio (SIGNAL), URInary peptidomic patterns of Long-COVID syndrome, G8208325170, G8243742226, G8264134133, G8401070593, G8483752417, G8590477180, G978281865, G993847510
OpenAlex ID: W4402523478