Validating a Proteomic Signature of Severe COVID-19
OBJECTIVES:. COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN:. Prospective obs...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer
2022-12-01
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| Series: | Critical Care Explorations |
| Online Access: | http://journals.lww.com/10.1097/CCE.0000000000000800 |
| _version_ | 1797976936522186752 |
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| author | Christopher V. Cosgriff, MD, MPH Todd A. Miano, PhD, PharmD Divij Mathew, PhD Alexander C. Huang, MD, PhD Heather M. Giannini, MD, MS Leticia Kuri-Cervantes, PhD M. Betina Pampena, PhD Caroline A. G. Ittner, PhD Ariel R. Weisman, MS Roseline S. Agyekum, BS Thomas G. Dunn, BS Oluwatosin Oniyide, BS Alexandra P. Turner, BS Kurt D’Andrea, BS Sharon Adamski, BS Allison R. Greenplate, PhD Brian J. Anderson, MD, MSCE Michael O. Harhay, PhD Tiffanie K. Jones, MD, MPH, MSCE John P. Reilly, MD, MSCE Nilam S. Mangalmurti, MD Michael G. S. Shashaty, MD, MSCE Michael R. Betts, PhD E. John Wherry, PhD Nuala J. Meyer, MD, MS |
| author_facet | Christopher V. Cosgriff, MD, MPH Todd A. Miano, PhD, PharmD Divij Mathew, PhD Alexander C. Huang, MD, PhD Heather M. Giannini, MD, MS Leticia Kuri-Cervantes, PhD M. Betina Pampena, PhD Caroline A. G. Ittner, PhD Ariel R. Weisman, MS Roseline S. Agyekum, BS Thomas G. Dunn, BS Oluwatosin Oniyide, BS Alexandra P. Turner, BS Kurt D’Andrea, BS Sharon Adamski, BS Allison R. Greenplate, PhD Brian J. Anderson, MD, MSCE Michael O. Harhay, PhD Tiffanie K. Jones, MD, MPH, MSCE John P. Reilly, MD, MSCE Nilam S. Mangalmurti, MD Michael G. S. Shashaty, MD, MSCE Michael R. Betts, PhD E. John Wherry, PhD Nuala J. Meyer, MD, MS |
| author_sort | Christopher V. Cosgriff, MD, MPH |
| collection | DOAJ |
| description | OBJECTIVES:. COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19.
DESIGN:. Prospective observational cohort study.
SETTING:. Two hospitals in the United States.
PATIENTS:. One hundred sixty-seven hospitalized adults with COVID-19.
INTERVENTION:. None.
MEASUREMENTS AND MAIN RESULTS:. We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88–0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006).
CONCLUSIONS:. Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia. |
| first_indexed | 2024-04-11T04:58:57Z |
| format | Article |
| id | doaj.art-987a6075e22c4b8b8c873ee3a0bd699e |
| institution | Directory Open Access Journal |
| issn | 2639-8028 |
| language | English |
| last_indexed | 2024-04-11T04:58:57Z |
| publishDate | 2022-12-01 |
| publisher | Wolters Kluwer |
| record_format | Article |
| series | Critical Care Explorations |
| spelling | doaj.art-987a6075e22c4b8b8c873ee3a0bd699e2022-12-26T06:01:07ZengWolters KluwerCritical Care Explorations2639-80282022-12-01412e080010.1097/CCE.0000000000000800202212000-00006Validating a Proteomic Signature of Severe COVID-19Christopher V. Cosgriff, MD, MPH0Todd A. Miano, PhD, PharmD1Divij Mathew, PhD2Alexander C. Huang, MD, PhD3Heather M. Giannini, MD, MS4Leticia Kuri-Cervantes, PhD5M. Betina Pampena, PhD6Caroline A. G. Ittner, PhD7Ariel R. Weisman, MS8Roseline S. Agyekum, BS9Thomas G. Dunn, BS10Oluwatosin Oniyide, BS11Alexandra P. Turner, BS12Kurt D’Andrea, BS13Sharon Adamski, BS14Allison R. Greenplate, PhD15Brian J. Anderson, MD, MSCE16Michael O. Harhay, PhD17Tiffanie K. Jones, MD, MPH, MSCE18John P. Reilly, MD, MSCE19Nilam S. Mangalmurti, MD20Michael G. S. Shashaty, MD, MSCE21Michael R. Betts, PhD22E. John Wherry, PhD23Nuala J. Meyer, MD, MS241 Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.2 Department of Epidemiology, Biostatistics, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.11 Immune Health Project, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.2 Department of Epidemiology, Biostatistics, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.2 Department of Epidemiology, Biostatistics, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.3 Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.8 Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.OBJECTIVES:. COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN:. Prospective observational cohort study. SETTING:. Two hospitals in the United States. PATIENTS:. One hundred sixty-seven hospitalized adults with COVID-19. INTERVENTION:. None. MEASUREMENTS AND MAIN RESULTS:. We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88–0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006). CONCLUSIONS:. Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.http://journals.lww.com/10.1097/CCE.0000000000000800 |
| spellingShingle | Christopher V. Cosgriff, MD, MPH Todd A. Miano, PhD, PharmD Divij Mathew, PhD Alexander C. Huang, MD, PhD Heather M. Giannini, MD, MS Leticia Kuri-Cervantes, PhD M. Betina Pampena, PhD Caroline A. G. Ittner, PhD Ariel R. Weisman, MS Roseline S. Agyekum, BS Thomas G. Dunn, BS Oluwatosin Oniyide, BS Alexandra P. Turner, BS Kurt D’Andrea, BS Sharon Adamski, BS Allison R. Greenplate, PhD Brian J. Anderson, MD, MSCE Michael O. Harhay, PhD Tiffanie K. Jones, MD, MPH, MSCE John P. Reilly, MD, MSCE Nilam S. Mangalmurti, MD Michael G. S. Shashaty, MD, MSCE Michael R. Betts, PhD E. John Wherry, PhD Nuala J. Meyer, MD, MS Validating a Proteomic Signature of Severe COVID-19 Critical Care Explorations |
| title | Validating a Proteomic Signature of Severe COVID-19 |
| title_full | Validating a Proteomic Signature of Severe COVID-19 |
| title_fullStr | Validating a Proteomic Signature of Severe COVID-19 |
| title_full_unstemmed | Validating a Proteomic Signature of Severe COVID-19 |
| title_short | Validating a Proteomic Signature of Severe COVID-19 |
| title_sort | validating a proteomic signature of severe covid 19 |
| url | http://journals.lww.com/10.1097/CCE.0000000000000800 |
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