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

Lihua Wang; Daniel Western; Jigyasha Timsina; Charlie Repaci; Won Min Song; Joanne Norton; Pat Kohlfeld; John Budde; Sharlee Climer; Omar H. Butt; Daniel Jacobson; Michael Garvin; Alan R. Templeton; Shawn Campagna; Jane O'Halloran; Rachel Presti; Charles W. Goss; Philip A. Mudd; Beau M. Ances; Bin Zhang; Yun Ju Sung; Carlos Cruchaga

doi:10.1016/j.isci.2023.106408

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

Lihua Wang, Daniel Western, Jigyasha Timsina, Charlie Repaci, Won Min Song, Joanne Norton, Pat Kohlfeld, John Budde, Sharlee Climer, Omar H. Butt, Daniel Jacobson, Michael Garvin, Alan R. Templeton, Shawn Campagna, Jane O'Halloran, Rachel Presti, Charles W. Goss, Philip A. Mudd, Beau M. Ances, Bin ZhangYun Ju Sung, Carlos Cruchaga

Computational and Predictive Biology

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Original language	English
Article number	106408
Journal	iScience
Volume	26
Issue number	4
DOIs	https://doi.org/10.1016/j.isci.2023.106408
State	Published - Apr 21 2023

Funding

This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/ ) and the Departments of Neurology and Psychiatry at Washington University School of Medicine. The recruitment and clinical characterization of research participants at Washington University were supported by NIH P30AG066444 (JCM), P01AG03991 (JCM), and P01AG026276 (JCM). This study utilized samples obtained from the Washington University School of Medicine’s COVID-19 biorepository, which is supported by: the Barnes-Jewish Hospital Foundation ; the Siteman Cancer Center grant P30 CA091842 from the National Cancer Institute of the National Institutes of Health ; and the Washington UniversityInstitute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences of the National Institutes of Health . The content is solely the responsibility of the authors and does not necessarily represent the view of the NIH. This work was supported by grants from the National Institutes of Health ( RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC, JCM), RF1AG053303 (CC, SC), RF1AG058501 (CC), and U01AG058922 (CC), Alzheimer's Association Research Grant 925002 (SC), the Chan Zuckerberg Initiative (CZI), and the Alzheimer's Association Zenith Fellows Award ( ZEN-22-848604 , awarded to CC). C.C. has received research support from: Biogen, EISAI, Alector, GSK, an anonymous foundation and Parabon. The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. C.C. is a member of the advisory board of Vivid Genomics, and Circular Genomics and own stocks.

Funders	Funder number
Departments of Neurology and Psychiatry at Washington University School of Medicine
Neurogenomics and Informatics Center
Washington UniversityInstitute of Clinical and Translational Sciences
National Institutes of Health	U01AG058922, RF1AG058501, RF1AG074007, R01AG044546, P30AG066444, RF1AG053303, P01AG026276
National Institute on Aging	P01AG003991
National Cancer Institute
Alzheimer's Association	925002
GlaxoSmithKline
Biogen
National Center for Advancing Translational Sciences	UL1TR002345
Foundation for Barnes-Jewish Hospital
Washington University School of Medicine in St. Louis
Alvin J. Siteman Cancer Center	P30 CA091842
Hope Center for Neurological Disorders
Chan Zuckerberg Initiative	ZEN-22-848604

Keywords

Biochemistry
Biological sciences
Disease
Protein

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.isci.2023.106408

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Wang, L., Western, D., Timsina, J., Repaci, C., Song, W. M., Norton, J., Kohlfeld, P., Budde, J., Climer, S., Butt, O. H., Jacobson, D., Garvin, M., Templeton, A. R., Campagna, S., O'Halloran, J., Presti, R., Goss, C. W., Mudd, P. A., Ances, B. M., ... Cruchaga, C. (2023). Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways. iScience, 26(4), Article 106408. https://doi.org/10.1016/j.isci.2023.106408

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title = "Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways",

abstract = "Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.",

keywords = "Biochemistry, Biological sciences, Disease, Protein",

author = "Lihua Wang and Daniel Western and Jigyasha Timsina and Charlie Repaci and Song, {Won Min} and Joanne Norton and Pat Kohlfeld and John Budde and Sharlee Climer and Butt, {Omar H.} and Daniel Jacobson and Michael Garvin and Templeton, {Alan R.} and Shawn Campagna and Jane O'Halloran and Rachel Presti and Goss, {Charles W.} and Mudd, {Philip A.} and Ances, {Beau M.} and Bin Zhang and Sung, {Yun Ju} and Carlos Cruchaga",

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year = "2023",

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Wang, L, Western, D, Timsina, J, Repaci, C, Song, WM, Norton, J, Kohlfeld, P, Budde, J, Climer, S, Butt, OH, Jacobson, D , Garvin, M, Templeton, AR, Campagna, S, O'Halloran, J, Presti, R, Goss, CW, Mudd, PA, Ances, BM, Zhang, B, Sung, YJ & Cruchaga, C 2023, 'Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways', iScience, vol. 26, no. 4, 106408. https://doi.org/10.1016/j.isci.2023.106408

TY - JOUR

T1 - Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

AU - Wang, Lihua

AU - Western, Daniel

AU - Timsina, Jigyasha

AU - Repaci, Charlie

AU - Song, Won Min

AU - Norton, Joanne

AU - Kohlfeld, Pat

AU - Budde, John

AU - Climer, Sharlee

AU - Butt, Omar H.

AU - Jacobson, Daniel

AU - Garvin, Michael

AU - Templeton, Alan R.

AU - Campagna, Shawn

AU - O'Halloran, Jane

AU - Presti, Rachel

AU - Goss, Charles W.

AU - Mudd, Philip A.

AU - Ances, Beau M.

AU - Zhang, Bin

AU - Sung, Yun Ju

AU - Cruchaga, Carlos

PY - 2023/4/21

Y1 - 2023/4/21

N2 - Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

AB - Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

KW - Biochemistry

KW - Biological sciences

KW - Disease

KW - Protein

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VL - 26

JO - iScience

JF - iScience

IS - 4

M1 - 106408

ER -

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

Abstract

Funding

Keywords

UN SDGs

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