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10.1172/JCI148635

http://scihub22266oqcxt.onion/10.1172/JCI148635
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34196300!8245177!34196300
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suck abstract from ncbi


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pmid34196300      J+Clin+Invest 2021 ; 131 (13): ä
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  • SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes #MMPMID34196300
  • Li Y; Schneider AM; Mehta A; Sade-Feldman M; Kays KR; Gentili M; Charland NC; Gonye AL; Gushterova I; Khanna HK; LaSalle TJ; Lavin-Parsons KM; Lilley BM; Lodenstein CL; Manakongtreecheep K; Margolin JD; McKaig BN; Parry BA; Rojas-Lopez M; Russo BC; Sharma N; Tantivit J; Thomas MF; Regan J; Flynn JP; Villani AC; Hacohen N; Goldberg MB; Filbin MR; Li JZ
  • J Clin Invest 2021[Jul]; 131 (13): ä PMID34196300show ga
  • BACKGROUNDSARS-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.METHODSWe 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.RESULTSThis 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.CONCLUSIONThese 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.FUNDINGMark 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).
  • |*SARS-CoV-2/pathogenicity/physiology[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Biomarkers/blood[MESH]
  • |COVID-19/*blood/*virology[MESH]
  • |Cohort Studies[MESH]
  • |Female[MESH]
  • |Host Microbial Interactions[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Models, Biological[MESH]
  • |Pandemics[MESH]
  • |Prognosis[MESH]
  • |Proteome/metabolism[MESH]
  • |Proteomics[MESH]
  • |Severity of Illness Index[MESH]
  • |Viremia/*blood/*virology[MESH]


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