Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2 infection

Swadling, Leo; Diniz, Mariana O.; Schmidt, Nathalie M.; Amin, Oliver E.; Chandran, Aneesh; Shaw, Emily; Pade, Corinna; Gibbons, Joseph M.; Bert, Nina Le; Tan, Anthony T.; Tham, Christine Y.L.; Tan, Cedric; Kucyowicz, Stephanie; Aidoo-Micah, Gloryanne; Rosenheim, Joshua; Davies, J. W.; Jensen, Melanie P; Joy, George; McCoy, Laura E; Valdes, Ana M.; Dorp, Lucy van; Altmann, Daniel M.; Boyton, Rosemary J.; Manisty, Charlotte; Treibel, Thomas A.; Moon, James; Investigators, COVIDsortium; Balloux, François; McKnight, Áine; Noursadeghi, Mahdad; Bertoletti, Antonio; Maini, Mala K.

doi:10.1101/2021.06.26.21259239

Cited by 41 publications

(24 citation statements)

References 59 publications

(78 reference statements)

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“…The resulting CD4+ T cells could potentially help naive B cells participate in subsequent responses to vaccines and infections, which may help explain the poor correlations we observed between memory B cell frequencies and the magnitude of the recall responses in cancer patients. Given that T cells reduce viral loads and disease even when neutralizing antibody levels are low 38,40,41,73 , these data suggest that vaccination will confer at least partial protection and reduce the likelihood of severe COVID-19 in most cancer patients.…”

Section: Discussionmentioning

confidence: 94%

Immune Responses to COVID-19 mRNA Vaccines in Patients with Solid Tumors on Active, Immunosuppressive Cancer Therapy

Shroff

Chalasani

Wei

et al. 2021

Preprint

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Vaccines against SARS-CoV-2 have shown high efficacy, but immunocompromised participants were excluded from controlled clinical trials. We evaluated immune responses to the Pfizer/BioNTech mRNA vaccine in solid tumor patients (n=52) on active cytotoxic anti-cancer therapy. These responses were compared to a control cohort that also received the Pfizer/BioNTech vaccine (n=50). Using live SARS-CoV-2 assays, neutralizing antibodies were detected in 67% and 80% of cancer patients after the first and second immunizations, respectively, with a 3-fold increase in median titers after the booster. Similar trends were observed in serum antibodies against the receptor-binding domain (RBD) and S2 regions of Spike protein, and in IFN𝛾+ Spike-specific T cells. The magnitude of each of these responses was diminished relative to the control cohort. We therefore quantified RBD- and Spike S1-specific memory B cell subsets as predictors of anamnestic responses to viral exposures or additional immunizations. After the second vaccination, Spike-specific plasma cell-biased memory B cells were observed in most cancer patients at levels similar to those of the control cohort after the first immunization. These data suggest that a third immunization might elevate antibody responses in cancer patients to levels seen in healthy individuals after the second dose. Trials should be conducted to test these predictions.

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Section: Discussionmentioning

confidence: 94%

Immune Responses to COVID-19 mRNA Vaccines in Patients with Solid Tumors on Active, Immunosuppressive Cancer Therapy

Shroff

Chalasani

Wei

et al. 2021

Preprint

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“…Mallajosyula et al demonstrated that patients with milder COVID-19 had CD8 + T cells specific for conserved epitopes [31]. Swadling et al demonstrated that abortive infection, which does not lead to seroconversion, is associated with the expansion of pre-existing T cells [32]. In both instances the conserved CD8 + T-cell epitopes were predominantly encoded in ORF1ab.…”

Section: Discussionmentioning

confidence: 99%

Low antigen abundance limits efficient T-cell recognition of highly conserved regions of SARS-CoV-2

Swaminathan

Lineburg

Ambalathingal

et al. 2021

Preprint

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Understanding the immune response to severe acute respiratory syndrome coronavirus (SARS-CoV-2) is critical to overcome the current coronavirus disease (COVID-19) pandemic. Efforts are being made to understand the potential cross-protective immunity of memory T cells, induced by prior encounters with seasonal coronaviruses, in providing protection against severe COVID-19. In this study we assessed T-cell responses directed against highly conserved regions of SARS-CoV-2. Epitope mapping revealed 16 CD8 + T-cell epitopes across the nucleocapsid (N), spike (S) and ORF3a proteins of SARS-CoV-2 and five CD8 + T-cell epitopes encoded within the highly conserved regions of the ORF1ab polyprotein of SARS-CoV-2. Comparative sequence analysis showed high conservation of SARS-CoV-2 ORF1ab T-cell epitopes in seasonal coronaviruses. Paradoxically, the immune responses directed against the conserved ORF1ab epitopes were infrequent and subdominant in both convalescent and unexposed participants. This subdominant immune response was consistent with a low abundance of ORF1ab encoded proteins in SARS-CoV-2 infected cells. Overall, these observations suggest that while cross-reactive CD8 + T cells likely exist in unexposed individuals, they are not common and therefore are unlikely to play a significant role in providing broad pre-existing immunity in the community.

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“…There is indirect evidence for heterogeneity of biological susceptibility before the pandemic, based on studies showing that 20-50% of unexposed individuals had cross-reactive T cell responses to SARS-CoV-2 antigens [17]. Although later studies suggested that these cross-reactive T cell responses protect against infection [18,19], no study has directly quantified the relation of infection risk to T cell reactivity in samples taken before the pandemic. In principle, the contribution of heterogeneity of connectivity to the immunity coefficient λ could be calculated from population-based surveys of the variance of contact rates between individuals.…”

Section: Quantifying Heterogeneitymentioning

confidence: 99%

Limitations of models for guiding policy in the COVID-19 pandemic

Wood

2022

Preprint

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At the outset of the COVID-19 epidemic in the UK, infectious disease modellers advised the government that unless a lockdown was imposed, most of the population would be infected within a few months and critical care capacity would be overwhelmed. This paper investigates the quantitative arguments underlying these predictions, and draws lessons for future policy.The modellers assumed that within age bands all individuals were equally susceptible and equally connected, leading to predictions that more than 80% of the population would be infected in the first wave of an unmitigated epidemic. Models that relax this unrealistic assumption to allow for selective removal of the most susceptible and connected individuals predict much smaller epidemic sizes. In most European countries no more than 10% of the population was infected in the first wave, irrespective of what restrictions were imposed. The modellers assumed that about 2% of those infected would require critical care, far higher than the proportion who entered critical care in the first wave, and failed to identify the key role of nosocomial transmission in overloading health systems. Model-based forecasts that only a lockdown could suppress the epidemic relied on a survey of contact rates in 2006, with no information on the types of contact most relevant to aerosol transmission or on heterogeneity of contact rates.In future epidemics, modellers should communicate the uncertainties associated with their assumptions and data, especially when these models are used to recommend policies that have high societal costs and are hard to reverse. Recognition of the gap between models and reality also implies a need to rebalance in favour of greater reliance on rapid studies of real-world transmission, robust model criticism, and acceptance that when measurements contradict model predictions it is the model that needs to be changed.

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Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2 infection

Cited by 41 publications

References 59 publications

Immune Responses to COVID-19 mRNA Vaccines in Patients with Solid Tumors on Active, Immunosuppressive Cancer Therapy

Immune Responses to COVID-19 mRNA Vaccines in Patients with Solid Tumors on Active, Immunosuppressive Cancer Therapy

Low antigen abundance limits efficient T-cell recognition of highly conserved regions of SARS-CoV-2

Limitations of models for guiding policy in the COVID-19 pandemic

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