An official website of the United States government
SARS-CoV-2 infection can result in a range of outcomes from asymptomatic/mild disease to severe COVID-19/fatality. In this study, we investigated the differential expression of small noncoding RNAs (sncRNAs) between patient cohorts defined by disease severity. We collected plasma samples, stratified these based on clinical outcomes, and sequenced their circulating sncRNAs. Excitingly, we found YRNA HY4 displays significant differential expression (p=0.025) between patients experiencing mild and severe disease. In agreement with recent reports identifying plasma YRNAs as indicators of influenza infection severity, our results strongly suggest that circulating HY4 levels represent a powerful prognostic indicator of likely SARS-CoV-2 patient infection outcome.
more »
« less
Understanding Neutrophil Dynamics during COVID-19 Infection
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in varied clinical outcomes, with virus-induced chronic inflammation and tissue injury being associated with enhanced disease pathogenesis. To determine the role of tissue damage on immune populations recruitment and function, a mathematical model of innate immunity following SARS-CoV-2 infection has been proposed. The model was fitted to published longitudinal immune marker data from patients with mild and severe COVID-19 disease and key parameters were estimated for each clinical outcome. Analytical, bifurcation, and numerical investigations were conducted to determine the effect of parameters and initial conditions on long-term dynamics. The results were used to suggest changes needed to achieve immune resolution.
more »
« less
- Award ID(s):
- 2051820
- PAR ID:
- 10435887
- Date Published:
- Journal Name:
- Applied Sciences
- Volume:
- 13
- Issue:
- 4
- ISSN:
- 2076-3417
- Page Range / eLocation ID:
- 2409
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)The future trajectory of the coronavirus disease 2019 (COVID-19) pandemic hinges on the dynamics of adaptive immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, salient features of the immune response elicited by natural infection or vaccination are still uncertain. We use simple epidemiological models to explore estimates for the magnitude and timing of future COVID-19 cases, given different assumptions regarding the protective efficacy and duration of the adaptive immune response to SARS-CoV-2, as well as its interaction with vaccines and nonpharmaceutical interventions. We find that variations in the immune response to primary SARS-CoV-2 infections and a potential vaccine can lead to markedly different immune landscapes and burdens of critically severe cases, ranging from sustained epidemics to near elimination. Our findings illustrate likely complexities in future COVID-19 dynamics and highlight the importance of immunological characterization beyond the measurement of active infections for adequately projecting the immune landscape generated by SARS-CoV-2 infections.more » « less
-
Abstract BackgroundFour severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants predominated in the United States since 2021. Understanding disease severity related to different SARS-CoV-2 variants remains limited. MethodViral genome analysis was performed on SARS-CoV-2 clinical isolates circulating March 2021 through March 2022 in Cleveland, Ohio. Major variants were correlated with disease severity and patient outcomes. ResultsIn total 2779 patients identified with either Alpha (n = 1153), Gamma (n = 122), Delta (n = 808), or Omicron variants (n = 696) were selected for analysis. No difference in frequency of hospitalization, intensive care unit (ICU) admission, and death were found among Alpha, Gamma, and Delta variants. However, patients with Omicron infection were significantly less likely to be admitted to the hospital, require oxygen, or admission to the ICU (χ2 = 12.8, P < .001; χ2 = 21.6, P < .002; χ2 = 9.6, P = .01, respectively). In patients whose vaccination status was known, a substantial number had breakthrough infections with Delta or Omicron variants (218/808 [26.9%] and 513/696 [73.7%], respectively). In breakthrough infections, hospitalization rate was similar regardless of variant by multivariate analysis. No difference in disease severity was identified between Omicron subvariants BA.1 and BA.2. ConclusionsDisease severity associated with Alpha, Gamma, and Delta variants is comparable while Omicron infections are significantly less severe. Breakthrough disease is significantly more common in patients with Omicron infection.more » « less
-
The emergence of new virus variants, including the Omicron variant (B.1.1.529) of SARS-CoV-2, can lead to reduced vaccine effectiveness (VE) and the need for new vaccines or vaccine doses if the extent of immune evasion is severe. Neutralizing antibody titers have been shown to be a correlate of protection for SARS-CoV-2 and other pathogens, and could be used to quickly estimate vaccine effectiveness for new variants. However, no model currently exists to provide precise VE estimates for a new variant against severe disease for SARS-CoV-2 using robust datasets from several populations. We developed predictive models for VE against COVID-19 symptomatic disease and hospitalization across a 54-fold range of mean neutralizing antibody titers. For two mRNA vaccines (mRNA-1273, BNT162b2), models fit without Omicron data predicted that infection with the BA.1 Omicron variant increased the risk of hospitalization 2.8–4.4-fold and increased the risk of symptomatic disease 1.7–4.2-fold compared to the Delta variant. Out-of-sample validation showed that model predictions were accurate; all predictions were within 10% of observed VE estimates and fell within the model prediction intervals. Predictive models using neutralizing antibody titers can provide rapid VE estimates, which can inform vaccine booster timing, vaccine design, and vaccine selection for new virus variants.more » « less
-
Although COVID-19 transmission has been reduced by the advent of vaccinations and a variety of rapid monitoring techniques, the SARS-CoV-2 virus itself has shown a remarkable ability to mutate and persist. With this long track record of immune escape, researchers are still exploring prophylactic treatments to curtail future SARS-CoV-2 variants. Specifically, much focus has been placed on the antiviral lectin Griffithsin in preventing spike protein-mediated infection via the hACE2 receptor (direct infection). However, an oft-overlooked aspect of SARS-CoV-2 infection is viral capture by attachment receptors such as DC-SIGN, which is thought to facilitate the initial stages of COVID-19 infection in the lung tissue (called trans-infection). In addition, while immune escape is dictated by mutations in the spike protein, coronaviral virions also incorporate M, N, and E structural proteins within the particle. In this paper, we explored how several structural facets of both the SARS-CoV-2 virion and the antiviral lectin Griffithsin can affect and attenuate the infectivity of SARS-CoV-2 pseudovirus. We found that Griffithsin was a better inhibitor of hACE2-mediated direct infection when the coronaviral M protein is present compared to when it is absent (possibly providing an explanation regarding why Griffithsin shows better inhibition against authentic SARS-CoV-2 as opposed to pseudotyped viruses, which generally do not contain M) and that Griffithsin was not an effective inhibitor of DC-SIGN-mediated trans-infection. Furthermore, we found that DC-SIGN appeared to mediate trans-infection exclusively via binding to the SARS-CoV-2 spike protein, with no significant effect observed when other viral proteins (M, N, and/or E) were present. These results provide etiological data that may help to direct the development of novel antiviral treatments, either by leveraging Griffithsin binding to the M protein as a novel strategy to prevent SARS-CoV-2 infection or by narrowing efforts to inhibit trans-infection to focus on DC-SIGN binding to SARS-CoV-2 spike protein.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/app13042409
