Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer’s and coronary disease pathways
Lihua Wang,
Daniel Western,
Jigyasha Timsina,
Charlie Repaci,
Won-Min Song,
Joanne Norton,
Pat Kohlfeld,
John Budde,
Sharlee Climer,
Omar H. Butt,
Daniel Jacobson,
Michael Garvin,
Alan R. Templeton,
Shawn Campagna,
Jane O’Halloran,
Rachel Presti,
Charles W. Goss,
Philip A. Mudd,
Beau M. Ances,
Bin Zhang,
Yun Ju Sung,
Carlos Cruchaga
Affiliations
Lihua Wang
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Daniel Western
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Jigyasha Timsina
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Charlie Repaci
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Won-Min Song
Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Joanne Norton
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Pat Kohlfeld
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
John Budde
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
Sharlee Climer
Department of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA
Omar H. Butt
Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
Daniel Jacobson
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Michael Garvin
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Alan R. Templeton
Department of Biology, Washington University School of Medicine, St Louis, MO, USA
Shawn Campagna
Department of Chemistry, University of Tennessee, Knoxville, TN, USA
Jane O’Halloran
Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
Rachel Presti
Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
Charles W. Goss
Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
Philip A. Mudd
Department of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA
Beau M. Ances
Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
Bin Zhang
Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Yun Ju Sung
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
Carlos Cruchaga
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA; The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, USA; Corresponding author
Summary: Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer’s disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer’s disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.