Back

Divergent early antibody responses define COVID-19 disease trajectories

Chakraborty, S.; Gonzalez, J. C.; Sievers, B. L.; Mallajosyula, V.; Dubey, M.; Cheng, Y.-L. B.; Tran, K. Q. T.; Chakraborty, S.; Cassidy, A.; Chen, S. T.; Sinnott, A.; Gelbart, T.; Golan, Y.; Prahl, M.; Singh, U.; Kim-Schulze, S.; Sherwood, R.; Zhang, S.; Marron, T. U.; Gnjatic, S.; Gaw, S. L.; Nadeau, K. C.; Merad, M.; Jagannathan, P.; Tan, G. S.; Wang, T. T.

2021-05-25 immunology
10.1101/2021.05.25.445649 bioRxiv
Show abstract

A damaging inflammatory response is strongly implicated in the pathogenesis of severe COVID-19 but mechanisms contributing to this response are unclear. In two prospective cohorts, early non-neutralizing, afucosylated, anti-SARS-CoV-2 IgG predicted progression from mild, to more severe COVID-19. In contrast to the antibody structures that predicted disease progression, antibodies that were elicited by mRNA SARS-CoV-2 vaccines were low in Fc afucosylation and enriched in sialylation, both modifications that reduce the inflammatory potential of IgG. To study the biology afucosylated IgG immune complexes, we developed an in vivo model which revealed that human IgG-Fc{gamma}R interactions can regulate inflammation in the lung. Afucosylated IgG immune complexes induced inflammatory cytokine production and robust infiltration of the lung by immune cells. By contrast, vaccine elicited IgG did not promote an inflammatory lung response. Here, we show that IgG-Fc{gamma}R interactions can regulate inflammation in the lung and define distinct lung activities associated with the IgG that predict severe COVID-19 and protection against SARS-CoV-2. One Sentence SummaryDivergent early antibody responses predict COVID-19 disease trajectory and mRNA vaccine response and are functionally distinct in vivo.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.