Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19

Hu, Z.; van der Ploeg, K.; Chakraborty, S.; S Arunachalam, P.; Mori, D. M.; Jacobson, K. B.; Bonilla, H.; Parsonnet, J.; Andrews, J. R.; Hedlin, H.; de la Parte, L.; Dantzler, K.; Ty, M.; Tan, G. S.; Blish, C. A.; Takahashi, S.; Rodriguez-Barraquer, I.; Greenhouse, B.; Butte, A. J.; Singh, U.; Pulendran, B.; Wang, T. T.; Jagannathan, P.

The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, mild to moderate infections are an important contributor to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of clinical and virologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial of Peginterferon Lambda for treatment of SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We define early immune signatures, including plasma levels of RIG-I and the CCR2 ligands (MCP1, MCP2 and MCP3), associated with control of oropharyngeal viral load, the degree of symptom severity, and immune memory (including SARS-CoV-2-specific T cell responses and spike (S) protein-binding IgG levels). We found that individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine had similar early immune trajectories to those observed in this natural infection cohort, including the induction of both inflammatory cytokines (e.g. MCP1) and negative immune regulators (e.g. TWEAK). Finally, we demonstrate that machine learning models using 8-10 plasma protein markers measured early within the course of infection are able to accurately predict symptom severity, T cell memory, and the antibody response post-infection.