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Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and...

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Autores principales: Wang, Lihua, Western, Dan, Timsina, Jigyasha, Repaci, Charlie, Song, Won-Min, Norton, Joanne, Kohlfeld, Pat, Budde, John, Climer, Sharlee, Butt, Omar H., Jacobson, Daniel, Garvin, Michael, Templeton, Alan R, Campagna, Shawn, O’Halloran, Jane, Presti, Rachel, Goss, Charles W., Mudd, Philip A., Ances, Beau M., Zhang, Bin, Sung, Yun Ju, Cruchaga, Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347279/
https://www.ncbi.nlm.nih.gov/pubmed/35923315
http://dx.doi.org/10.1101/2022.07.25.22278025
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author Wang, Lihua
Western, Dan
Timsina, Jigyasha
Repaci, Charlie
Song, Won-Min
Norton, Joanne
Kohlfeld, Pat
Budde, John
Climer, Sharlee
Butt, Omar H.
Jacobson, Daniel
Garvin, Michael
Templeton, Alan R
Campagna, Shawn
O’Halloran, Jane
Presti, Rachel
Goss, Charles W.
Mudd, Philip A.
Ances, Beau M.
Zhang, Bin
Sung, Yun Ju
Cruchaga, Carlos
author_facet Wang, Lihua
Western, Dan
Timsina, Jigyasha
Repaci, Charlie
Song, Won-Min
Norton, Joanne
Kohlfeld, Pat
Budde, John
Climer, Sharlee
Butt, Omar H.
Jacobson, Daniel
Garvin, Michael
Templeton, Alan R
Campagna, Shawn
O’Halloran, Jane
Presti, Rachel
Goss, Charles W.
Mudd, Philip A.
Ances, Beau M.
Zhang, Bin
Sung, Yun Ju
Cruchaga, Carlos
author_sort Wang, Lihua
collection PubMed
description Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal (https://covid.proteomics.wustl.edu/). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10(−14)), Alzheimer’s disease (FDR ≤ 5.46×10(−10)) and coronary artery disease (FDR ≤ 4.64×10(−2)). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer’s disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
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spelling pubmed-93472792022-08-04 Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways Wang, Lihua Western, Dan Timsina, Jigyasha Repaci, Charlie Song, Won-Min Norton, Joanne Kohlfeld, Pat Budde, John Climer, Sharlee Butt, Omar H. Jacobson, Daniel Garvin, Michael Templeton, Alan R Campagna, Shawn O’Halloran, Jane Presti, Rachel Goss, Charles W. Mudd, Philip A. Ances, Beau M. Zhang, Bin Sung, Yun Ju Cruchaga, Carlos medRxiv Article Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal (https://covid.proteomics.wustl.edu/). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10(−14)), Alzheimer’s disease (FDR ≤ 5.46×10(−10)) and coronary artery disease (FDR ≤ 4.64×10(−2)). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer’s disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes. Cold Spring Harbor Laboratory 2022-07-25 /pmc/articles/PMC9347279/ /pubmed/35923315 http://dx.doi.org/10.1101/2022.07.25.22278025 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Wang, Lihua
Western, Dan
Timsina, Jigyasha
Repaci, Charlie
Song, Won-Min
Norton, Joanne
Kohlfeld, Pat
Budde, John
Climer, Sharlee
Butt, Omar H.
Jacobson, Daniel
Garvin, Michael
Templeton, Alan R
Campagna, Shawn
O’Halloran, Jane
Presti, Rachel
Goss, Charles W.
Mudd, Philip A.
Ances, Beau M.
Zhang, Bin
Sung, Yun Ju
Cruchaga, Carlos
Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title_full Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title_fullStr Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title_full_unstemmed Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title_short Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
title_sort plasma proteomics of sars-cov-2 infection and severity reveals impact on alzheimer and coronary disease pathways
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347279/
https://www.ncbi.nlm.nih.gov/pubmed/35923315
http://dx.doi.org/10.1101/2022.07.25.22278025
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