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Circulating proteins to predict adverse COVID-19 outcomes
Chen-Yang Su Mr.; Sirui Zhou; Edgar Gonzalez-Kozlova; Guillaume Butler-Laporte; Elsa Brunet-Ratnasingham; Tomoko Nakanishi; Wonseok Jeon; David Morrison; Laetitia Laurent; Joanthan Afilalo; Marc Afilalo; Danielle Henry; Yiheng Chen; Julia Carrasco-Zanini; Yossi Farjoun; Maik Pietzner; Nofar Kimchi; Zaman Afrasiabi; Nardin Rezk; Meriem Bouab; Louis Petitjean; Charlotte Guzman; Xiaoqing Xue; Chris Tselios; Branka Vulesevic; Olumide Adeleye; Tala Abdullah; Noor Almamlouk; Yara Moussa; Chantal DeLuca; Naomi Duggan; Erwin Schurr; Nathalie Brassard; Madeleine Durand; Diane Marie Del Valle; Ryan Thompson; Mario A. Cedillo; Eric Schadt; Kai Nie; Nicole W Simons; Konstantinos Mouskas; Nicolas Zaki; Manishkumar Patel; Hui Xie; Jocelyn Harris; Robert Marvin; Esther Cheng; Kevin Tuballes; Kimberly Argueta; Ieisha Scott; - The Mount Sinai COVID Biobank Team; Celia M T Greenwood; Clare Paterson; Michael Hinterberg; Claudia Langenberg; Vincenzo Forgetta; Joelle Pineau; Vincent Mooser; Thomas Marron; Noam Beckmann; Ephraim Kenigsberg; Seunghee Kim-schulze; Alexander W. Charney; Sacha Gnjatic; Daniel E. Kaufmann; Miriam Merad; J Brent Richards.
  • Chen-Yang Su Mr.; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Sirui Zhou; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Edgar Gonzalez-Kozlova; Icahn School of Medicine at Mount Sinai
  • Guillaume Butler-Laporte; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Elsa Brunet-Ratnasingham; Centre hospitalier de l'Universite de Montreal
  • Tomoko Nakanishi; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Wonseok Jeon; McGill University
  • David Morrison; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Laetitia Laurent; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Joanthan Afilalo; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Marc Afilalo; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Danielle Henry; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Yiheng Chen; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Julia Carrasco-Zanini; University of Cambridge School of Clinical Medicine
  • Yossi Farjoun; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Maik Pietzner; University of Cambridge School of Clinical Medicine
  • Nofar Kimchi; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Zaman Afrasiabi; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Nardin Rezk; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Meriem Bouab; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Louis Petitjean; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Charlotte Guzman; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Xiaoqing Xue; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Chris Tselios; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Branka Vulesevic; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Olumide Adeleye; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Tala Abdullah; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Noor Almamlouk; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Yara Moussa; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Chantal DeLuca; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Naomi Duggan; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Erwin Schurr; McGill University Health Centre
  • Nathalie Brassard; Centre hospitalier de l'Universite de Montreal
  • Madeleine Durand; Centre hospitalier de l'Universite de Montreal
  • Diane Marie Del Valle; Icahn School of Medicine at Mount Sinai
  • Ryan Thompson; Icahn School of Medicine at Mount Sinai
  • Mario A. Cedillo; Icahn School of Medicine at Mount Sinai
  • Eric Schadt; Icahn School of Medicine at Mount Sinai
  • Kai Nie; Icahn School of Medicine at Mount Sinai
  • Nicole W Simons; Icahn School of Medicine at Mount Sinai
  • Konstantinos Mouskas; Icahn School of Medicine at Mount Sinai
  • Nicolas Zaki; Icahn School of Medicine at Mount Sinai
  • Manishkumar Patel; Icahn School of Medicine at Mount Sinai
  • Hui Xie; Icahn School of Medicine at Mount Sinai
  • Jocelyn Harris; Icahn School of Medicine at Mount Sinai
  • Robert Marvin; Icahn School of Medicine at Mount Sinai
  • Esther Cheng; Icahn School of Medicine at Mount Sinai
  • Kevin Tuballes; Icahn School of Medicine at Mount Sinai
  • Kimberly Argueta; Icahn School of Medicine at Mount Sinai
  • Ieisha Scott; Icahn School of Medicine at Mount Sinai
  • - The Mount Sinai COVID Biobank Team;
  • Celia M T Greenwood; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Clare Paterson; SomaLogic Inc.
  • Michael Hinterberg; SomaLogic Inc.
  • Claudia Langenberg; University of Cambridge School of Clinical Medicine
  • Vincenzo Forgetta; Lady Davis Institute for Medical Research, Jewish General Hospital
  • Joelle Pineau; McGill University
  • Vincent Mooser; McGill University
  • Thomas Marron; Icahn School of Medicine at Mount Sinai
  • Noam Beckmann; Icahn School of Medicine at Mount Sinai
  • Ephraim Kenigsberg; Icahn School of Medicine at Mount Sinai
  • Seunghee Kim-schulze; Icahn School of Medicine at Mount Sinai
  • Alexander W. Charney; Icahn School of Medicine at Mount Sinai
  • Sacha Gnjatic; Icahn School of Medicine at Mount Sinai
  • Daniel E. Kaufmann; Centre hospitalier de l'Universite de Montreal
  • Miriam Merad; Icahn School of Medicine at Mount Sinai
  • J Brent Richards; Lady Davis Institute for Medical Research, Jewish General Hospital
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21264015
ABSTRACT
Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4,701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict adverse COVID-19 outcomes in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4,701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different adverse COVID-19 outcomes were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of adverse COVID-19 outcomes. Further research is needed to understand how to incorporate protein measurement into clinical care.
Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo del documento: Preprint Idioma: Inglés Año: 2021

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Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo del documento: Preprint Idioma: Inglés Año: 2021
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