Changes in serum neutralizing antibody potency and breadth post SARS-CoV-2 mRNA vaccine boost

A better understanding of the durability and breadth of serum neutralizing antibody responses against multiple SARS-CoV-2 variants elicited by Covid-19 vaccines is crucial in addressing the current pandemic. In this study, we quantified the decay of serum neutralization antibodies (nAbs) after second and third doses of the original Covid-19 mRNA vaccine. Using an authentic virus neutralization assay, we found that decay half-lives of WA1- and Delta-nAbs were both ∼60 days post second and third vaccine dose. Unexpectedly, the durability of serum antibodies that neutralize three different Omicron subvariants (BA.1.1, BA.5, BA.2.12.1) was substantially better, with half-lives of ≥ 6 months. A booster dose of the original Covid-19 vaccine was also found to broaden antibody responses against SARS-CoV and four other sarbecoviruses, in addition to multiple SARS-CoV-2 strains. These findings suggest that repeated vaccinations with the Covid-19 vaccine may confer a degree of protection against future spillover of sarbecoviruses from animal reservoirs. Graphical abstract

Changes in serum-neutralizing antibody potency and breadth post-SARS-CoV-2 mRNA vaccine boost.

A better understanding of the durability and breadth of serum-neutralizing antibody responses against multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants elicited by COVID-19 vaccines is crucial in addressing the current pandemic. In this study, we quantified the decay of serum neutralization antibodies (nAbs) after second and third doses of the original COVID-19 mRNA vaccine. Using an authentic virus-neutralization assay, we found that decay half-lives of WA1- and Delta-nAbs were both ∼60 days after second and third vaccine dose. Unexpectedly, the durability of serum antibodies that neutralize three different Omicron subvariants (BA.1.1, BA.5, BA.2.12.1) was substantially better, with half-lives of ≥6 months. A booster dose of the original COVID-19 vaccine was also found to broaden antibody responses against SARS-CoV and four other sarbecoviruses, in addition to multiple SARS-CoV-2 strains. These findings suggest that repeated vaccinations with the COVID-19 vaccine may confer a degree of protection against future spillover of sarbecoviruses from animal reservoirs.

Emergence of SARS-CoV-2 escape mutations during Bamlanivimab therapy in a phase II randomized clinical trial.

SARS-CoV-2 mutations that cause resistance to monoclonal antibody (mAb) therapy have been reported. However, it remains unclear whether in vivo emergence of SARS-CoV-2 resistance mutations alters viral replication dynamics or therapeutic efficacy in the immune-competent population. As part of the ACTIV-2/A5401 randomized clinical trial (NCT04518410), non-hospitalized participants with symptomatic SARS-CoV-2 infection were given bamlanivimab (700 mg or 7,000 mg) or placebo treatment. Here¸ we report that treatment-emergent resistance mutations [detected through targeted Spike (S) gene next-generation sequencing] were significantly more likely to be detected after bamlanivimab 700 mg treatment compared with the placebo group (7% of 111 vs 0% of 112 participants, P = 0.003). No treatment-emergent resistance mutations among the 48 participants who received 7,000 mg bamlanivimab were recorded. Participants in which emerging mAb resistant virus mutations were identified showed significantly higher pretreatment nasopharyngeal and anterior nasal viral loads. Daily respiratory tract viral sampling through study day 14 showed the dynamic nature of in vivo SARS-CoV-2 infection and indicated a rapid and sustained viral rebound after the emergence of resistance mutations. Participants with emerging bamlanivimab resistance often accumulated additional polymorphisms found in current variants of concern/interest that are associated with immune escape. These results highlight the potential for rapid emergence of resistance during mAb monotherapy treatment that results in prolonged high-level respiratory tract viral loads. Assessment of viral resistance should be prioritized during the development and clinical implementation of antiviral treatments for COVID-19.

A simple model of COVID-19 explains disease severity and the effect of treatments.

Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.

Antiviral and clinical activity of bamlanivimab in a randomized trial of non-hospitalized adults with COVID-19.

Anti-SARS-CoV-2 monoclonal antibodies are mainstay COVID-19 therapeutics. Safety, antiviral, and clinical efficacy of bamlanivimab were evaluated in the randomized controlled trial ACTIV-2/A5401. Non-hospitalized adults were randomized 1:1 within 10 days of COVID-19 symptoms to bamlanivimab or blinded-placebo in two dose-cohorts (7000 mg, n = 94; 700 mg, n = 223). No differences in bamlanivimab vs placebo were observed in the primary outcomes: proportion with undetectable nasopharyngeal SARS-CoV-2 RNA at days 3, 7, 14, 21, and 28 (risk ratio = 0.82-1.05 for 7000 mg [p(overall) = 0.88] and 0.81-1.21 for 700 mg [p(overall) = 0.49]), time to symptom improvement (median 21 vs 18.5 days [p = 0.97], 7000 mg; 24 vs 20.5 days [p = 0.08], 700 mg), or grade 3+ adverse events. However, bamlanivimab was associated with lower day 3 nasopharyngeal viral levels and faster reductions in inflammatory markers and viral decay by modeling. This study provides evidence of faster reductions in nasopharyngeal SARS-CoV-2 RNA levels but not shorter symptom durations in non-hospitalized adults with early variants of SARS-CoV-2.

In vivo kinetics of SARS-CoV-2 infection and its relationship with a person's infectiousness.

The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person's infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission. Here, we develop viral dynamic models of SARS-CoV-2 infection and fit them to data to estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking viral load (VL) to infectiousness and show a person's infectiousness increases sublinearly with VL and that the logarithm of the VL in the upper respiratory tract is a better surrogate of infectiousness than the VL itself. Using data on VL and the predicted infectiousness, we further incorporated data on antigen and RT-PCR tests and compared their usefulness in detecting infection and preventing transmission. We found that RT-PCR tests perform better than antigen tests assuming equal testing frequency; however, more frequent antigen testing may perform equally well with RT-PCR tests at a lower cost but with many more false-negative tests. Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies.

Longitudinal SARS-CoV-2 seroprevalence in Portugal and antibody maintenance 12 months after infection.

During the COVID-19 pandemic, Portugal has experienced three distinct SARS-CoV-2 infection waves. We previously documented the prevalence of SARS-CoV-2 immunity, measured by specific antibodies, in September 2020, 6 months after the initial moderate wave. Here, we show the seroprevalence changes 6 months later, up to the second week of March 2021, shortly following the third wave, which was one of the most severe in the world, and 2 months following the start of the vaccination campaign. A longitudinal epidemiological study was conducted, with a stratified quota sample of the Portuguese population. Serological testing was performed, including ELISA determination of antibody class and titers. The proportion of seropositives, which was 2.2% in September 2020, rose sharply to 17.3% (95% CI: 15.8-18.8%) in March 2021. Importantly, circulating IgG and IgA antibody levels were very stable 6 months after the initial determination and up to a year after initial infection, indicating long-lasting infection immunity against SARS-CoV-2. Moreover, vaccinated people had higher IgG levels from 3 weeks post-vaccination when compared with previously infected people at the same time post-infection.

Prevalence of SARS-CoV-2 Antibodies after First 6 Months of COVID-19 Pandemic, Portugal.

In September 2020, we tested 13,398 persons in Portugal for antibodies against severe acute respiratory syndrome coronavirus 2 by using a quota sample stratified by age and population density. We found a seroprevalence of 2.2%, 3-4 times larger than the official number of cases at the end of the first wave of the pandemic.

Viral Load Kinetics of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospitalized Individuals With Coronavirus Disease 2019.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) kinetics remain understudied, including the impact of remdesivir. In hospitalized individuals, peak sputum viral load occurred in week 2 of symptoms, whereas viremia peaked within 1 week of symptom-onset, suggesting early systemic seeding of SARS-CoV-2. Remdesivir treatment was associated with faster viral decay.

Reply to Comment on Nogueira, P.J., et al. "The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases". J. Clin. Med. 2020, 9, 2368.

We thank Costa-Santos C [...].

The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases.

BACKGROUND: It is essential to study the effect of potential co-factors on the risk of death in patients infected by COVID-19. The identification of risk factors is important to allow more efficient public health and health services strategic interventions with a significant impact on deaths by COVID-19. This study aimed to identify factors associated with COVID-19 deaths in Portugal. METHODS: A national dataset with the first 20,293 patients infected with COVID-19 between 1 January and 21 April 2020 was analyzed. The primary outcome measure was mortality by COVID-19, measured (registered and confirmed) by Medical Doctors serving as health delegates on the daily death registry. A logistic regression model using a generalized linear model was used for estimating Odds Ratio (OR) with 95% confidence intervals (95% CI) for each potential risk indicator. RESULTS: A total of 502 infected patients died of COVID-19. The risk factors for increased odds of death by COVID-19 were: sex (male: OR = 1.47, ref = female), age ((56-60) years, OR = 6.01; (61-65) years, OR = 10.5; (66-70) years, OR = 20.4; (71-75) years, OR = 34; (76-80) years, OR = 50.9; (81-85) years, OR = 70.7; (86-90) years, OR = 83.2; (91-95) years, OR = 91.8; (96-104) years, OR = 140.2, ref = (0-55)), Cardiac disease (OR = 2.86), Kidney disorder (OR = 2.95), and Neuromuscular disorder (OR = 1.58), while condition (None (absence of precondition); OR = 0.49) was associated with a reduced chance of dying after adjusting for other variables of interest. CONCLUSIONS: Besides age and sex, preconditions justify the risk difference in mortality by COVID-19.