Understanding humoral responses to SARS-CoV-2 is critical for improving diagnostics, therapeutics, and vaccines. Deep serological profiling of 232 COVID-19 patients and 190 pre-COVID-19 era controls using VirScan revealed over 800 epitopes in the SARS-CoV-2 proteome, including 10 epitopes likely recognized by neutralizing antibodies. Pre-existing antibodies in controls recognized SARS-CoV-2 ORF1, while only COVID-19 patients primarily recognized spike and nucleoprotein. A machine learning model trained on VirScan data predicted SARS-CoV-2 exposure history with 99% sensitivity and 98% specificity; a rapid Luminex-based diagnostic was developed from the most discriminatory SARS-CoV-2 peptides. Individuals with more severe COVID-19 exhibited stronger and broader SARS-CoV-2 responses, weaker antibody responses to prior infections, and higher incidence of CMV and HSV-1, possibly influenced by demographic covariates. Among hospitalized patients, males make greater SARS-CoV-2 antibody responses than females.

Mechanisms underlying severe COVID-19 disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNAseq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell type-specific intracellular death signatures, cellular ACE2 expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.