Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19. Research square Hu, Z., van der Ploeg, K., Chakraborty, S., Arunachalam, P., Mori, D., Jacobson, K., Bonilla, H., Parsonnet, J., Andrews, J., Hedlin, H., de la Parte, L., Dantzler, K., Ty, M., Tan, G., Blish, C., Takahashi, S., Rodriguez-Barraquer, I., Greenhouse, B., Butte, A., Singh, U., Pulendran, B., Wang, T., Jagannathan, P. 2022

Abstract

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, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial in 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 identify early immune signatures, including plasma RIG-I levels, early interferon signaling, and related cytokines (CXCL10, MCP1, MCP-2 and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2 specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizera"BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine learning models using 7-10 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset.

View details for DOI 10.21203/rs.3.rs-847082/v1

View details for PubMedID 35132407