Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions
Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasm...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/131124 |
| _version_ | 1811097253895471104 |
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| author | Filbin, Michael R. Mehta, Arnav Schneider, Alexis M. Kays, Kyle R. Guess, Jamey R. Gentili, Matteo Fenyves, Bánk G. Charland, Nicole C. Gonye, Anna L.K. Gushterova, Irena Khanna, Hargun K. LaSalle, Thomas J. Lavin-Parsons, Kendall M. Lilley, Brendan M. Lodenstein, Carl L. Manakongtreecheep, Kasidet Margolin, Justin D. McKaig, Brenna N. Rojas-Lopez, Maricarmen Russo, Brian C. Sharma, Nihaarika Tantivit, Jessica Thomas, Molly F. Gerszten, Robert E. Heimberg, Graham S. Hoover, Paul J. Lieb, David J. Lin, Brian Ngo, Debby Pelka, Karin Reyes, Miguel Smillie, Chris S Waghray, Avinash Wood, Thomas E. Zajac, Amanda S. Jennings, Lori L. Grundberg, Ida Bhattacharyya, Roby P. Parry, Blair Alden Villani, Alexandra-Chloé Sade-Feldman, Moshe Hacohen, Nir Goldberg, Marcia B. |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Filbin, Michael R. Mehta, Arnav Schneider, Alexis M. Kays, Kyle R. Guess, Jamey R. Gentili, Matteo Fenyves, Bánk G. Charland, Nicole C. Gonye, Anna L.K. Gushterova, Irena Khanna, Hargun K. LaSalle, Thomas J. Lavin-Parsons, Kendall M. Lilley, Brendan M. Lodenstein, Carl L. Manakongtreecheep, Kasidet Margolin, Justin D. McKaig, Brenna N. Rojas-Lopez, Maricarmen Russo, Brian C. Sharma, Nihaarika Tantivit, Jessica Thomas, Molly F. Gerszten, Robert E. Heimberg, Graham S. Hoover, Paul J. Lieb, David J. Lin, Brian Ngo, Debby Pelka, Karin Reyes, Miguel Smillie, Chris S Waghray, Avinash Wood, Thomas E. Zajac, Amanda S. Jennings, Lori L. Grundberg, Ida Bhattacharyya, Roby P. Parry, Blair Alden Villani, Alexandra-Chloé Sade-Feldman, Moshe Hacohen, Nir Goldberg, Marcia B. |
| author_sort | Filbin, Michael R. |
| collection | MIT |
| description | Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease. |
| first_indexed | 2024-09-23T16:56:45Z |
| format | Article |
| id | mit-1721.1/131124 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:56:45Z |
| publishDate | 2021 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1311242022-10-03T09:19:12Z Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions Filbin, Michael R. Mehta, Arnav Schneider, Alexis M. Kays, Kyle R. Guess, Jamey R. Gentili, Matteo Fenyves, Bánk G. Charland, Nicole C. Gonye, Anna L.K. Gushterova, Irena Khanna, Hargun K. LaSalle, Thomas J. Lavin-Parsons, Kendall M. Lilley, Brendan M. Lodenstein, Carl L. Manakongtreecheep, Kasidet Margolin, Justin D. McKaig, Brenna N. Rojas-Lopez, Maricarmen Russo, Brian C. Sharma, Nihaarika Tantivit, Jessica Thomas, Molly F. Gerszten, Robert E. Heimberg, Graham S. Hoover, Paul J. Lieb, David J. Lin, Brian Ngo, Debby Pelka, Karin Reyes, Miguel Smillie, Chris S Waghray, Avinash Wood, Thomas E. Zajac, Amanda S. Jennings, Lori L. Grundberg, Ida Bhattacharyya, Roby P. Parry, Blair Alden Villani, Alexandra-Chloé Sade-Feldman, Moshe Hacohen, Nir Goldberg, Marcia B. Massachusetts Institute of Technology. Department of Biological Engineering Broad Institute of MIT and Harvard Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease. NIH/NIAID (Grant U19 AI082630) 2021-07-21T21:51:47Z 2021-07-21T21:51:47Z 2021-05 2021-03 2021-07-21T11:55:30Z Article http://purl.org/eprint/type/JournalArticle 2666-3791 https://hdl.handle.net/1721.1/131124 Filbin, Michael R. et al. "Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions." Cell Reports Medicine 2, 5 (May 2021): 100287 © 2021 The Authors en http://dx.doi.org/10.1016/j.xcrm.2021.100287 Cell Reports Medicine Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Elsevier |
| spellingShingle | Filbin, Michael R. Mehta, Arnav Schneider, Alexis M. Kays, Kyle R. Guess, Jamey R. Gentili, Matteo Fenyves, Bánk G. Charland, Nicole C. Gonye, Anna L.K. Gushterova, Irena Khanna, Hargun K. LaSalle, Thomas J. Lavin-Parsons, Kendall M. Lilley, Brendan M. Lodenstein, Carl L. Manakongtreecheep, Kasidet Margolin, Justin D. McKaig, Brenna N. Rojas-Lopez, Maricarmen Russo, Brian C. Sharma, Nihaarika Tantivit, Jessica Thomas, Molly F. Gerszten, Robert E. Heimberg, Graham S. Hoover, Paul J. Lieb, David J. Lin, Brian Ngo, Debby Pelka, Karin Reyes, Miguel Smillie, Chris S Waghray, Avinash Wood, Thomas E. Zajac, Amanda S. Jennings, Lori L. Grundberg, Ida Bhattacharyya, Roby P. Parry, Blair Alden Villani, Alexandra-Chloé Sade-Feldman, Moshe Hacohen, Nir Goldberg, Marcia B. Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title | Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title_full | Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title_fullStr | Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title_full_unstemmed | Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title_short | Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions |
| title_sort | longitudinal proteomic analysis of severe covid 19 reveals survival associated signatures tissue specific cell death and cell cell interactions |
| url | https://hdl.handle.net/1721.1/131124 |
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