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SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes
Yijia Li, … , Michael R. Filbin, Jonathan Z. Li
Yijia Li, … , Michael R. Filbin, Jonathan Z. Li
Published July 1, 2021
Citation Information: J Clin Invest. 2021;131(13):e148635. https://doi.org/10.1172/JCI148635.
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Clinical Research and Public Health Infectious disease

SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes

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Abstract

BACKGROUND SARS-CoV-2 plasma viremia has been associated with severe disease and death in COVID-19 in small-scale cohort studies. The mechanisms behind this association remain elusive.METHODS We evaluated the relationship between SARS-CoV-2 viremia, disease outcome, and inflammatory and proteomic profiles in a cohort of COVID-19 emergency department participants. SARS-CoV-2 viral load was measured using a quantitative reverse transcription PCR–based platform. Proteomic data were generated with Proximity Extension Assay using the Olink platform.RESULTS This study included 300 participants with nucleic acid test–confirmed COVID-19. Plasma SARS-CoV-2 viremia levels at the time of presentation predicted adverse disease outcomes, with an adjusted OR of 10.6 (95% CI 4.4–25.5, P < 0.001) for severe disease (mechanical ventilation and/or 28-day mortality) and 3.9 (95% CI 1.5–10.1, P = 0.006) for 28-day mortality. Proteomic analyses revealed prominent proteomic pathways associated with SARS-CoV-2 viremia, including upregulation of SARS-CoV-2 entry factors (ACE2, CTSL, FURIN), heightened markers of tissue damage to the lungs, gastrointestinal tract, and endothelium/vasculature, and alterations in coagulation pathways.CONCLUSION These results highlight the cascade of vascular and tissue damage associated with SARS-CoV-2 plasma viremia that underlies its ability to predict COVID-19 disease outcomes.FUNDING Mark and Lisa Schwartz; the National Institutes of Health (U19AI082630); the American Lung Association; the Executive Committee on Research at Massachusetts General Hospital; the Chan Zuckerberg Initiative; Arthur, Sandra, and Sarah Irving for the David P. Ryan, MD, Endowed Chair in Cancer Research; an EMBO Long-Term Fellowship (ALTF 486-2018); a Cancer Research Institute/Bristol Myers Squibb Fellowship (CRI2993); the Harvard Catalyst/Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, NIH awards UL1TR001102 and UL1TR002541-01); and by the Harvard University Center for AIDS Research (National Institute of Allergy and Infectious Diseases, 5P30AI060354).

Authors

Yijia Li, Alexis M. Schneider, Arnav Mehta, Moshe Sade-Feldman, Kyle R. Kays, Matteo Gentili, Nicole C. Charland, Anna L.K. Gonye, Irena Gushterova, Hargun K. Khanna, Thomas J. LaSalle, Kendall M. Lavin-Parsons, Brendan M. Lilley, Carl L. Lodenstein, Kasidet Manakongtreecheep, Justin D. Margolin, Brenna N. McKaig, Blair A. Parry, Maricarmen Rojas-Lopez, Brian C. Russo, Nihaarika Sharma, Jessica Tantivit, Molly F. Thomas, James Regan, James P. Flynn, Alexandra-Chloé Villani, Nir Hacohen, Marcia B. Goldberg, Michael R. Filbin, Jonathan Z. Li

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Figure 6

Neutralization level and viremia.

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Neutralization level and viremia.
(A) Violin plot of neutralization leve...
(A) Violin plot of neutralization levels stratified by viremia status. Mann-Whitney U test was used to evaluate the difference between 2 groups. (B) Neutralization rate between viremic and aviremic groups. LOWESS (locally weighted scatterplot smoothing) smooth regression was performed to depict the trajectory of neutralizing rates between 2 groups. (C) Correlation between SDC1/CD138 (a marker for plasmablasts) NPX and neutralizing rate at day 0. Linear regression (solid line) with 95% CIs (dotted lines) is shown. Spearmann’s correlation was used to evaluate the correlation between SDC1/CD138 NPX and neutralizing rates. n = 175.

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