Longitudinal analysis of SARS-CoV-2 reinfection reveals distinct kinetics and emergence of cross-neutralizing antibodies to variants of concern.

The ongoing evolution of SARS-CoV-2 continues to raise new questions regarding the duration of immunity to reinfection with emerging variants. To address these knowledge gaps, controlled investigations in established animal models are needed to assess duration of immunity induced by each SARS-CoV-2 lineage and precisely evaluate the extent of cross-reactivity and cross-protection afforded. Using the Syrian hamster model, we specifically investigated duration of infection acquired immunity to SARS-CoV-2 ancestral Wuhan strain over 12 months. Plasma spike- and RBD-specific IgG titers against ancestral SARS-CoV-2 peaked at 4 months post-infection and showed a modest decline by 12 months. Similar kinetics were observed with plasma virus neutralizing antibody titers which peaked at 2 months post-infection and showed a modest decline by 12 months. Reinfection with ancestral SARS-CoV-2 at regular intervals demonstrated that prior infection provides long-lasting immunity as hamsters were protected against severe disease when rechallenged at 2, 4, 6, and 12 months after primary infection, and this coincided with the induction of high virus neutralizing antibody titers. Cross-neutralizing antibody titers against the B.1.617.2 variant (Delta) progressively waned in blood over 12 months, however, re-infection boosted these titers to levels equivalent to ancestral SARS-CoV-2. Conversely, cross-neutralizing antibodies to the BA.1 variant (Omicron) were virtually undetectable at all time-points after primary infection and were only detected following reinfection at 6 and 12 months. Collectively, these data demonstrate that infection with ancestral SARS-CoV-2 strains generates antibody responses that continue to evolve long after resolution of infection with distinct kinetics and emergence of cross-reactive and cross-neutralizing antibodies to Delta and Omicron variants and their specific spike antigens.

The influenza universe in an mRNA vaccine.

An mRNA-lipid nanoparticle vaccine protects animals from 20 influenza lineages.

After the virus has cleared-Can preclinical models be employed for Long COVID research?

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) can cause the life-threatening acute respiratory disease called COVID-19 (Coronavirus Disease 2019) as well as debilitating multiorgan dysfunction that persists after the initial viral phase has resolved. Long COVID or Post-Acute Sequelae of COVID-19 (PASC) is manifested by a variety of symptoms, including fatigue, dyspnea, arthralgia, myalgia, heart palpitations, and memory issues sometimes affecting between 30% and 75% of recovering COVID-19 patients. However, little is known about the mechanisms causing Long COVID and there are no widely accepted treatments or therapeutics. After introducing the clinical aspects of acute COVID-19 and Long COVID in humans, we summarize the work in animals (mice, Syrian hamsters, ferrets, and nonhuman primates (NHPs)) to model human COVID-19. The virology, pathology, immune responses, and multiorgan involvement are explored. Additionally, any studies investigating time points longer than 14 days post infection (pi) are highlighted for insight into possible long-term disease characteristics. Finally, we discuss how the models can be leveraged for treatment evaluation, including pharmacological agents that are currently in human clinical trials for treating Long COVID. The establishment of a recognized Long COVID preclinical model representing the human condition would allow the identification of mechanisms causing disease as well as serve as a vehicle for evaluating potential therapeutics.

The Intersection of Age and Influenza Severity: Utility of Ferrets for Dissecting the Age-Dependent Immune Responses and Relevance to Age-Specific Vaccine Development.

Many factors impact the host response to influenza virus infection and vaccination. Ferrets have been an indispensable reagent for influenza virus research for almost one hundred years. One of the most significant and well-known factors affecting human disease after infection is host age. Another significant factor is the virus, as strain-specific disease severity is well known. Studying age-related impacts on viral infection and vaccination outcomes requires an animal model that reflects both the physiological and immunological changes that occur with human aging, and sensitivity to differentially virulent influenza viruses. The ferret is uniquely susceptible to a plethora of influenza viruses impacting humans and has proven extremely useful in studying the clinical and immunological pictures of influenza virus infection. Moreover, ferrets developmentally have several of the age-related physiological changes that occur in humans throughout infancy, adulthood, old age, and pregnancy. In this review, we discuss ferret susceptibility to influenza viruses, summarize previous influenza studies using ferrets as models of age, and finally, highlight the application of ferret age models in the pursuit of prophylactic and therapeutic agents to address age-related influenza disease severity.

Sex and age bias viral burden and interferon responses during SARS-CoV-2 infection in ferrets.

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) hospitalizations and deaths disportionally affect males and older ages. Here we investigated the impact of male sex and age comparing sex-matched or age-matched ferrets infected with SARS-CoV-2. Differences in temperature regulation was identified for male ferrets which was accompanied by prolonged viral replication in the upper respiratory tract after infection. Gene expression analysis of the nasal turbinates indicated that 1-year-old female ferrets had significant increases in interferon response genes post infection which were delayed in males. These results provide insight into COVID-19 and suggests that older males may play a role in viral transmission due to decreased antiviral responses.

Centenarians and extremely old people living with frailty can elicit durable SARS-CoV-2 spike specific IgG antibodies with virus neutralization functions following virus infection as determined by serological study.

BACKGROUND: The SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2) has led to more than 165 million COVID-19 cases and >3.4 million deaths worldwide. Epidemiological analysis has revealed that the risk of developing severe COVID-19 increases with age. Despite a disproportionate number of older individuals and long-term care facilities being affected by SARS-CoV-2 and COVID-19, very little is understood about the immune responses and development of humoral immunity in the extremely old person after SARS-CoV-2 infection. Here we conducted a serological study to investigate the development of humoral immunity in centenarians following a SARS-CoV-2 outbreak in a long-term care facility. METHODS: Extreme aged individuals and centenarians who were residents in a long-term care facility and infected with or exposed to SARS-CoV-2 were investigated between April and June 2020 for the development of antibodies to SARS-CoV-2. Blood samples were collected from positive and bystander individuals 30 and 60 days after original diagnosis of SARS-CoV-2 infection. Plasma was used to quantify IgG, IgA, and IgM isotypes and subsequent subclasses of antibodies specific for SARS-CoV-2 spike protein. The function of anti-spike was then assessed by virus neutralization assays against the native SARS-CoV-2 virus. FINDINGS: Fifteen long-term care residents were investigated for SARS-CoV-2 infection. All individuals had a Clinical Frailty scale score ≥5 and were of extreme older age or were centenarians. Six women with a median age of 98.8 years tested positive for SARS-CoV-2. Anti-spike IgG antibody titers were the highest titers observed in our cohort with all IgG positive individuals having virus neutralization ability. Additionally, 5 out of the 6 positive participants had a robust IgA anti-SARS-CoV-2 response. In all 5, antibodies were detected after 60 days from initial diagnosis.

Development and deployment of COVID-19 vaccines for those most vulnerable.

Development of safe and effective COVID-19 vaccines is a global priority and the best hope for ending the COVID-19 pandemic. Remarkably, in less than 1 year, vaccines have been developed and shown to be efficacious and are already being deployed worldwide. Yet, many challenges remain. Immune senescence and comorbidities in aging populations and immune dysregulation in populations living in low-resource settings may impede vaccine effectiveness. Distribution of vaccines among these populations where vaccine access is historically low remains challenging. In this Review, we address these challenges and provide strategies for ensuring that vaccines are developed and deployed for those most vulnerable.

Comparison of real-time and droplet digital PCR to detect and quantify SARS-CoV-2 RNA in plasma.

BACKGROUND: The presence of SARS-CoV-2 RNA in plasma has been linked to disease severity and mortality. We compared RT-qPCR to droplet digital PCR (ddPCR) to detect SARS-CoV-2 RNA in plasma from COVID-19 patients (mild, moderate, and critical disease). METHODS: The presence/concentration of SARS-CoV-2 RNA in plasma was compared in three groups of COVID-19 patients (30 outpatients, 30 ward patients and 30 ICU patients) using both RT-qPCR and ddPCR. Plasma was obtained in the first 24h following admission, and RNA was extracted using eMAG. ddPCR was performed using Bio-Rad SARS-CoV-2 detection kit, and RT-qPCR was performed using GeneFinder™ COVID-19 Plus RealAmp Kit. Statistical analysis was performed using Statistical Package for the Social Science. RESULTS: SARS-CoV-2 RNA was detected, using ddPCR and RT-qPCR, in 91% and 87% of ICU patients, 27% and 23% of ward patients and 3% and 3% of outpatients. The concordance of the results obtained by both methods was excellent (Cohen's kappa index = 0.953). RT-qPCR was able to detect 34/36 (94.4%) patients positive for viral RNA in plasma by ddPCR. Viral RNA load was higher in ICU patients compared with the other groups (P < .001), by both ddPCR and RT-qPCR. AUC analysis revealed Ct values (RT-qPCR) and viral RNA load values (ddPCR) can similarly differentiate between patients admitted to wards and to the ICU (AUC of 0.90 and 0.89, respectively). CONCLUSION: Both methods yielded similar prevalence of RNAemia between groups, with ICU patients showing the highest (>85%). RT-qPCR was as useful as ddPCR to detect and quantify SARS-CoV-2 RNAemia in plasma.

Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19.

BACKGROUND: COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. METHODS: A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. RESULTS: The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p < 0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non-survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183-12.968], 0.025), viral RNA load (N1) (1.962 [1.244-3.096], 0.004); viral RNA load (N2) (2.229 [1.382-3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia). CONCLUSIONS: SARS-CoV-2 RNAemia and viral RNA load in plasma are associated with critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.