Authors

Dorien Feyaerts, Stanford University School of Medicine
Julien Hedou, Stanford University School of Medicine
Joshua Gillard, Radboud Institute for Molecular Life Sciences
Han Chen, Stanford University School of Medicine
Eileen S. Tsai, Stanford University School of Medicine
Laura S. Peterson, Stanford University School of Medicine
Kazuo Ando, Stanford University School of Medicine
Monali Manohar, Stanford University School of Medicine
Evan Do, Stanford University School of Medicine
Gopal K.R. Chinthrajah, Stanford University School of Medicine
Christopher M. Warren, Stanford University School of Medicine
Rich Wittman, Stanford University School of Medicine
Justin G. Meyeroqitz, Stanford University School of Medicine
Edward A. Ganio, Stanford University School of Medicine
Ina A. Stelzer, Stanford University School of Medicine
Xiaoyuan Han, University of the PacificFollow
Franck Verdonk, Stanford University School of Medicine
Dyani K. Gaudilliere, Stanford University School of Medicine
Nilanjan Mukherjee, Stanford University School of Medicine
Amy S. Tsai, Stanford University School of Medicine
Kristen K. Rumer, Stanford University School of Medicine
Sizun Jiang, Stanford University School of Medicine
Sergio Ivan Valdes Ferrer, Instituto Nacional de Ciencias Médicas y Nutrición
J. Daniel Kelly, University of California, San Francisco
David Furman, Buck Institute for Research on Aging
Nima Aghaeepour, Stanford University School of Medicine
Martin S. Angst, Stanford University School of Medicine
Scott D. Boyd, Stanford University School of Medicine
Benjamin A. Pinsky, Stanford University School of Medicine
Garry P. Nolan, Stanford University School of Medicine
Kari C. Nadeau, Stanford University
Brice Gaudilliere, Stanford University
David R. McIlwain, Stanford University School of Medicine

Document Type

Article

Publication Title

bioRxiv

DOI

10.1101/2021.02.09.430269

Publication Date

2-12-2021

Abstract

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression.

Comments

This is an unpublished pre-print that has not undergone peer review. It should not be considered conclusive, used to inform clinical practice, or referenced by the media as validated information.

Share

COinS