Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments
Summary: Prognostic biomarkers have been widely studied in COVID-19, but their levels may be influenced by treatment strategies. This study examined plasma biomarkers and proteomic survival prediction in two unvaccinated hospitalized COVID-19 cohorts receiving different treatments. In a derivation c...
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Elsevier
2025-03-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004225003062 |
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| author | Cecilie Bo Hansen Maria Elizabeth Engel Møller Laura Pérez-Alós Simone Bastrup Israelsen Lylia Drici Maud Eline Ottenheijm Annelaura Bach Nielsen Nicolai J. Wewer Albrechtsen Thomas Benfield Peter Garred |
| author_facet | Cecilie Bo Hansen Maria Elizabeth Engel Møller Laura Pérez-Alós Simone Bastrup Israelsen Lylia Drici Maud Eline Ottenheijm Annelaura Bach Nielsen Nicolai J. Wewer Albrechtsen Thomas Benfield Peter Garred |
| author_sort | Cecilie Bo Hansen |
| collection | DOAJ |
| description | Summary: Prognostic biomarkers have been widely studied in COVID-19, but their levels may be influenced by treatment strategies. This study examined plasma biomarkers and proteomic survival prediction in two unvaccinated hospitalized COVID-19 cohorts receiving different treatments. In a derivation cohort (n = 126) from early 2020, we performed plasma proteomic profiling and evaluated innate and complement system immune markers. A proteomic model based on differentially expressed proteins predicted 30-day mortality with an area under the curve (AUC) of 0.81. The model was tested in a validation cohort (n = 80) from late 2020, where patients received remdesivir and dexamethasone, and performed with an AUC of 0.75. Biomarker levels varied considerably between cohorts, sometimes in opposite directions, highlighting the impact of treatment regimens on biomarker expression. These findings underscore the need to account for treatment effects when developing prognostic models, as treatment differences may limit their generalizability across populations. |
| format | Article |
| id | doaj-art-c76b23e89b4c49f29e5a107d5ca99e49 |
| institution | DOAJ |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-c76b23e89b4c49f29e5a107d5ca99e492025-08-20T03:16:34ZengElsevieriScience2589-00422025-03-0128311204610.1016/j.isci.2025.112046Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatmentsCecilie Bo Hansen0Maria Elizabeth Engel Møller1Laura Pérez-Alós2Simone Bastrup Israelsen3Lylia Drici4Maud Eline Ottenheijm5Annelaura Bach Nielsen6Nicolai J. Wewer Albrechtsen7Thomas Benfield8Peter Garred9Laboratory of Molecular Medicine, Department of Clinical Immunology, Section 7631, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark; Corresponding authorDepartment of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, DenmarkLaboratory of Molecular Medicine, Department of Clinical Immunology, Section 7631, Copenhagen University Hospital - Rigshospitalet, Copenhagen, DenmarkDepartment of Infectious Diseases, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, DenmarkNNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Bispebjerg Hospital, Copenhagen, DenmarkNNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Bispebjerg Hospital, Copenhagen, DenmarkNNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Bispebjerg Hospital, Copenhagen, DenmarkNNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital - Bispebjerg Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkDepartment of Infectious Diseases, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkLaboratory of Molecular Medicine, Department of Clinical Immunology, Section 7631, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DenmarkSummary: Prognostic biomarkers have been widely studied in COVID-19, but their levels may be influenced by treatment strategies. This study examined plasma biomarkers and proteomic survival prediction in two unvaccinated hospitalized COVID-19 cohorts receiving different treatments. In a derivation cohort (n = 126) from early 2020, we performed plasma proteomic profiling and evaluated innate and complement system immune markers. A proteomic model based on differentially expressed proteins predicted 30-day mortality with an area under the curve (AUC) of 0.81. The model was tested in a validation cohort (n = 80) from late 2020, where patients received remdesivir and dexamethasone, and performed with an AUC of 0.75. Biomarker levels varied considerably between cohorts, sometimes in opposite directions, highlighting the impact of treatment regimens on biomarker expression. These findings underscore the need to account for treatment effects when developing prognostic models, as treatment differences may limit their generalizability across populations.http://www.sciencedirect.com/science/article/pii/S2589004225003062ImmunologyProteomics |
| spellingShingle | Cecilie Bo Hansen Maria Elizabeth Engel Møller Laura Pérez-Alós Simone Bastrup Israelsen Lylia Drici Maud Eline Ottenheijm Annelaura Bach Nielsen Nicolai J. Wewer Albrechtsen Thomas Benfield Peter Garred Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments iScience Immunology Proteomics |
| title | Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments |
| title_full | Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments |
| title_fullStr | Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments |
| title_full_unstemmed | Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments |
| title_short | Differences in biomarker levels and proteomic survival prediction across two COVID-19 cohorts with distinct treatments |
| title_sort | differences in biomarker levels and proteomic survival prediction across two covid 19 cohorts with distinct treatments |
| topic | Immunology Proteomics |
| url | http://www.sciencedirect.com/science/article/pii/S2589004225003062 |
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