Reduced sensitivity of infectious SARS-CoV-2 variant B.1.617.2 to monoclonal antibodies and sera from convalescent and vaccinated individuals (preprint)

The SARS-CoV-2 B.1.617 lineage emerged in October 2020 in India. It has since then become dominant in some indian regions and further spread to many countries. The lineage includes three main subtypes (B1.617.1, B.1617.2 and B.1.617.3), which harbour diverse Spike mutations in the N-terminal domain (NTD) and the receptor binding domain (RBD) which may increase their immune evasion potential. B.1.617.2 is believed to spread faster than the other versions. Here, we isolated infectious B.1.617.2 from a traveller returning from India. We examined its sensitivity to monoclonal antibodies (mAbs) and to antibodies present in sera from COVID-19 convalescent individuals or vaccine recipients, in comparison to other viral lineages. B.1.617.2 was resistant to neutralization by some anti-NTD and anti-RBD mAbs, including Bamlanivimab, which were impaired in binding to the B.1.617.2 Spike. Sera from convalescent patients collected up to 12 months post symptoms and from Pfizer Comirnaty vaccine recipients were 3 to 6 fold less potent against B.1.617.2, relative to B.1.1.7. Sera from individuals having received one dose of AstraZeneca Vaxzevria barely inhibited B.1.617.2. Thus, B.1.617.2 spread is associated with an escape to antibodies targeting non-RBD and RBD Spike epitopes.

Evolution of human antibody responses up to one year after SARS-CoV-2 infection (preprint)

Assessment of the kinetics of SARS-CoV-2 antibodies is essential to predict protection against reinfection and durability of vaccine protection. Here, we longitudinally measured Spike (S) and Nucleocapsid (N)-specific antibodies in 1,309 healthcare workers (HCW) including 393 convalescent COVID-19 and 916 COVID-19 negative HCW up to 405 days. From M1 to M7-9 after infection, SARS-CoV-2 antibodies decreased moderately in convalescent HCW in a biphasic model, with men showing a slower decay of anti-N (p=0.02), and a faster decay of anti-S (p=0.0008) than women. At M11-13, anti-N antibodies dramatically decreased (half-life: 210 days) while anti-S stabilized (half-life: 630 days) at a median of 2.41 log Arbitrary Units (AU)/mL (Interquartile Range (IQR): 2.11 -2.75). One case of reinfection was recorded in convalescent HCW (0.47 per 100 person-years) versus 50 in COVID-19 negative HCW (10.11 per 100 person-years). Correlation with live-virus neutralization assay revealed that variants D614G and B.1.1.7, but not B.1.351, were sensitive to anti-S antibodies at 2.3 log AU/mL, while IgG [≥] 3 log AU/mL neutralized all three variants. After SARS-CoV-2 vaccination, anti-S levels reached 4 logs regardless of pre-vaccination IgG levels, type of vaccine, and number of doses. Our study demonstrates a long-term persistence of anti-S IgG antibodies that may protect against reinfection. By significantly increasing cross-neutralizing antibody titers, a single-dose vaccination strengthens protection against escape mutants.

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality (preprint)

Despite advances in COVID-19 management, it is unclear how to recognize patients who evolve towards death. This would allow for better risk stratification and targeting for early interventions. However, the explosive increase in correlates of COVID-19 severity complicates biomarker prioritisation. To identify early biological predictors of mortality, we performed an immunovirological assessment (SARS-CoV-2 viral RNA, cytokines and tissue injury markers, antibody responses) on plasma samples collected from 144 hospitalised COVID-19 patients 11 days after symptom onset and used to test models predicting mortality within 60 days of symptom onset. In the discovery cohort (n=61, 13 fatalities), high SARS-CoV-2 vRNA, low RBD-specific IgG levels, low SARS-CoV-2-specific antibody-dependent cellular cytotoxicity, and elevated levels of several cytokines and lung injury markers were strongly associated with increased mortality in the entire cohort and the subgroup on mechanical ventilation. Model selection revealed that a three-variable model of vRNA, age and sex was very robust at identifying patients who will succumb to COVID-19 (AUC=0.86, adjusted HR for log-transformed vRNA=3.5; 95% CI: 2.0-6.0). This model remained robust in an independent validation cohort (n=83, AUC=0.85). Quantification of plasma SARS-CoV-2 RNA can help understand the heterogeneity of disease trajectories and identify patients who may benefit from new therapies.