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Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways
Carlos Cruchaga; Lihua Wang; Yun Ju Sung; Dan Western; Jigyasha Timsina; Charlie Repaci; Won-Min Song; Joanne Norton; Pat Kohlfeld; John Budde; Sharlee Climer; Omar H. Bbut; Daniel A Jacobson; Michael R Garvin; Alan R. Templeton; Shawn Campagna; Jane O'Halloran; Rachel Presti; Charles William Goss; Philip A Mudd; Beau M. Ances; Bin Zhang.
  • Carlos Cruchaga; Washington University School of Medicine, St Louis, MO, USA
  • Lihua Wang; Washington University School of Medicine, St Louis, MO, USA
  • Yun Ju Sung; Washington University School of Medicine, St Louis, MO, USA
  • Dan Western; Washington University School of Medicine, St Louis, MO, USA
  • Jigyasha Timsina; Washington University School of Medicine, St Louis, MO, USA
  • Charlie Repaci; Washington University School of Medicine, St Louis, MO, USA
  • Won-Min Song; Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  • Joanne Norton; Washington University School of Medicine, St Louis, MO, USA
  • Pat Kohlfeld; Washington University School of Medicine, St Louis, MO, USA
  • John Budde; Washington University School of Medicine, St Louis, MO, USA
  • Sharlee Climer; University of Missouri-St. Louis, St. Louis, MO, USA
  • Omar H. Bbut; Washington University School of Medicine, St Louis, MO, USA
  • Daniel A Jacobson; Oak Ridge National Laboratory
  • Michael R Garvin; UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB
  • Alan R. Templeton; Washington University School of Medicine, St Louis, MO, USA
  • Shawn Campagna; University of Tennessee, Knoxville, TN, USA
  • Jane O'Halloran; Washington University in St. Louis School of Medicine
  • Rachel Presti; Washington University School of Medicine, St Louis, MO, USA
  • Charles William Goss; Washington University in St. Louis School of Medicine
  • Philip A Mudd; Washington University School of Medicine
  • Beau M. Ances; Washington University School of Medicine, St Louis, MO, USA
  • Bin Zhang; Icahn School of Medicine at Mount Sinai, New York, New York, USA
Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-22278025
ABSTRACT
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 [≤] 3.72x10-14), Alzheimers disease (FDR [≤] 5.46x10-10) and coronary artery disease (FDR [≤] 4.64x10-2). 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 Alzheimers disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Type d'étude: Étude de cohorte / Études expérimentales / Étude observationnelle / Étude pronostique Les sujets: Variantes langue: Anglais Année: 2022 Type de document: Preprint

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Texte intégral: Disponible Collection: Preprints Base de données: medRxiv Type d'étude: Étude de cohorte / Études expérimentales / Étude observationnelle / Étude pronostique Les sujets: Variantes langue: Anglais Année: 2022 Type de document: Preprint