Deciphering the quality of SARS-CoV-2 specific T-cell response associated with disease severity, immune memory and heterologous response

SARS-CoV-2 specific T-cell response has been associated with disease severity, immune memory and heterologous response to endemic coronaviruses. However, an integrative approach combining a comprehensive analysis of the quality of SARS-CoV-2 specific T-cell response with antibody levels in these three scenarios is needed. In the present study, we found that, in acute infection, while mild disease was associated with high T-cell polyfunctionality biased to IL-2 production and inversely correlated with anti-S IgG levels, combinations only including IFN-γ with the absence of perforin production predominated in severe disease. Seven months after infection, both non-hospitalised and previously hospitalised patients presented robust anti-S IgG levels and SARS-CoV-2 specific T-cell response. In addition, only previously hospitalised patients showed a T-cell exhaustion profile. Finally, combinations including IL-2 in response to S protein of endemic coronaviruses were the ones associated with SARS-CoV-2 S-specific T-cell response in pre-COVID-19 healthy donors’ samples. These results could have implications for protective immunity against SARS-CoV-2 and recurrent COVID-19 and may help for the design of new prototypes and boosting vaccine strategies

Innate and adaptive immune defects associated with lower SARS-CoV-2 BNT162b2 mRNA vaccine response in elderly people

The immune factors associated with impaired SARS-CoV-2 vaccine response in the elderly are mostly unknown. We studied old and young people vaccinated with SARS-CoV-2 BNT162b2 mRNA before and after the first and second dose. Aging was associated with a lower anti-RBD IgG levels and a decreased magnitude and polyfunctionality of SARS-CoV-2 specific T cell response. The dramatic decrease in thymic function in the elderly, which fueled alteration in T cell homeostasis, and lower CD161+ T cell levels were associated with decreased T cell response two months after vaccination. Additionally, a deficient dendritic cell (DC) homing, activation and Toll like receptor (TLR)-mediated function, along with a proinflammatory functional profile in monocytes, were observed in the elderly, which was also related to lower specific T cell response after vaccination. These findings might be relevant for the improvement of the current vaccination strategies and for the development of new vaccine prototypes.This study was funded by Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades, Junta de Andalucia (CV20-85418 and P20_00906, DOC-01659 and DOC-00963); Consejeria de Salud, Junta de Andalucia (RH-0037-2020), Instituto de Salud Carlos III (CP19/00159, FI17/00186, FI19/00083, PI19/01172, CM20/00243) Fondos FEDER, and National Spanish Research Council (CSIC).N

Immune defects associated with lower SARS-CoV-2 BNT162b2 mRNA vaccine response in aged people

The immune factors associated with impaired SARS-CoV-2 vaccine response in elderly people are mostly unknown. We studied individuals older than 60 and younger than 60 years, who had been vaccinated with SARS-CoV-2 BNT162b2 mRNA, before and after the first and second dose. Aging was associated with a lower anti–RBD IgG levels and a decreased magnitude and polyfunctionality of SARS-CoV-2–specific T cell response. The dramatic decrease in thymic function in people > 60 years, which fueled alteration in T cell homeostasis, and their lower CD161+ T cell levels were associated with decreased T cell response 2 months after vaccination. Additionally, deficient DC homing, activation, and TLR-mediated function, along with a proinflammatory functional profile in monocytes, were observed in the > 60-year-old group, which was also related to lower specific T cell response after vaccination. These findings might be relevant for the improvement of the current vaccination strategies and for the development of new vaccine prototypes.This work was supported by the Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía grants CV20-85418 and P20_00906 and by research contracts DOC-01659 and DOC-00963, as well as by Consejería de Salud, Junta de Andalucía research contract RH-0037-2020 and Instituto de Salud Carlos III CP19/00159, FI17/00186, FI19/00083, PI19/01127, and CM20/00243 from Fondos FEDER. ERM was supported by the Spanish Research Council (CSIC). We thank all the community volunteers, participants from the IBiS, Chema Niño, and the nursing staff from Virgen del Rocío University Hospital who have taken part in this project. We also thank Alicia Gutierrez and Esperanza Muñoz for reviewing the manuscript. In memoriam Silvio Manuel Pérez Martín.Peer reviewe

Migration and activation marker expressing in monocytes subset in mild and several/critical patients (S/C)

S2 Fig. Migration and activation marker expressing in monocytes subset in mild and several/critical patients (S/C).Peer reviewe

S1 Fig - Clinical, laboratory data and inflammatory biomarkers at baseline as early discharge predictors in hospitalized SARS-CoV-2 infected patients

A, Predictive models for hospital discharge during the first week in mild patients. B, Predictive models for worsening of clinical status during the first week in patients who were admitted mildly ill. AUC, area under the curve.Peer reviewe

Activation, homing and maturation marker expression in different monocyte subsets

Data are expressed by percentage and interquartile range. Medians fluorescence intensitive (MFI) were calculated in those markets that have a high rate of expression.Peer reviewe

Baseline characteristics of the mild patients who were discharged and worsened during the first week

Quantitative variables are expressing as number (percentage) or median (interquartile range). Pa value for differences between patients who were or not discharged. Pb value for differences between patients who who did and did not get wore. SpO2, peripheral capillary oxygen saturation; CRP, C-reactive protein; LDH, Lactate dehydrogenase; NLR, neutrophil/lymphocyte ratio.Peer reviewe

Receiver operating curve (ROC) analyses to evaluate the ability of clinical and laboratory data to predict worse prognosis during the first week

AUC, area under the curve; SE, sensitivity; S, specificity; PPV, positive predictive value; NPV, negative predictive value. SpO2, peripheral capillary oxygen saturation; CRP, C-reactive protein; LDH, Lactate dehydrogenase; NLR, neutrophil/lymphocyte ratio; TNF-α; tumor necrosis factor α; IL-6, interleukine-6; IL-8, interleukine-8; IL-1β, interleukine-1β; MIP-1β, macrophage inflammatory proteins 1β; sCD25, soluble receptor interleukine-2; IP-10, interferon γ-induced protein 10.Peer reviewe

Clinical, laboratory data and inflammatory biomarkers at baseline as early discharge predictors in hospitalized SARS-CoV-2 infected patients

Background The SARS-CoV-2 pandemic has overwhelmed hospital services due to the rapid transmission of the virus and its severity in a high percentage of cases. Having tools to predict which patients can be safely early discharged would help to improve this situation. Methods Patients confirmed as SARS-CoV-2 infection from four Spanish hospitals. Clinical, demographic, laboratory data and plasma samples were collected at admission. The patients were classified into mild and severe/critical groups according to 4-point ordinal categories based on oxygen therapy requirements. Logistic regression models were performed in mild patients with only clinical and routine laboratory parameters and adding plasma pro-inflammatory cytokine levels to predict both early discharge and worsening. Results 333 patients were included. At admission, 307 patients were classified as mild patients. Age, oxygen saturation, Lactate Dehydrogenase, D-dimers, neutrophil-lymphocyte ratio (NLR), and oral corticosteroids treatment were predictors of early discharge (area under curve (AUC), 0.786; sensitivity (SE) 68.5%; specificity (S), 74.5%; positive predictive value (PPV), 74.4%; and negative predictive value (NPV), 68.9%). When cytokines were included, lower interferon-γ-inducible protein 10 and higher Interleukin 1 beta levels were associated with early discharge (AUC, 0.819; SE, 91.7%; S, 56.6%; PPV, 69.3%; and NPV, 86.5%). The model to predict worsening included male sex, oxygen saturation, no corticosteroids treatment, C-reactive protein and Nod-like receptor as independent factors (AUC, 0.903; SE, 97.1%; S, 68.8%; PPV, 30.4%; and NPV, 99.4%). The model was slightly improved by including the determinations of interleukine-8, Macrophage inflammatory protein-1 beta and soluble IL-2Rα (CD25) (AUC, 0.952; SE, 97.1%; S, 98.1%; PPV, 82.7%; and NPV, 99.6%). Conclusions Clinical and routine laboratory data at admission strongly predict non-worsening during the first two weeks; therefore, these variables could help identify those patients who do not need a long hospitalization and improve hospital overcrowding. Determination of pro-inflammatory cytokines moderately improves these predictive capacities.This work was supported by Consejeria de Salud y Familia (research Project COVID-0005-2020 and Research Contract RH-0037-2020 to JV); Consejería de Transformación Económica, Industria, Conocimiento y Universidades (PY20/01276 to APG); Instituto de Salud Carlos III (CP19/00159 to AGV, CP19/00146 to AR, FI19/00304 to EMM, FI19/00083 to MCGC, "a way to make Europe, and COV20/00698 to support COHVID-GS), Red Temática de Investigación Cooperativa en SIDA (RD16/0025/0020, RD16/0025/0006 and RD16/0025/0026), Fondos FEDER; Centro de Investigación Biomédica en Red de Enfermedades Infecciosas-ISCIII (CB21/13/00020) Madrid, Spain. ERM was supported by the Spanish Research Council (CSIC). AR is also supported by a grant from IISPV through the project “2019/IISPV/05” (Boosting Young Talent), by GeSIDA through the “III Premio para Jóvenes Investigadores”. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewe

Receiver operating curve (ROC) analyses to evaluate the ability of clinical and laboratory data to predict discharge during the first week

AUC, area under the curve; SE, sensitivity; S, specificity; PPV, positive predictive value; NPV, negative predictive value. SpO2, peripheral capillary oxygen saturation; CRP, C-reactive protein; LDH, Lactate dehydrogenase; NLR, neutrophil/lymphocyte ratio; TNF-α; tumor necrosis factor α; IL-6, interleukine-6; IL-8, interleukine-8; IL-1β, interleukine-1β; MIP-1β, macrophage inflammatory proteins 1β; sCD25, soluble receptor interleukine-2; IP-10, interferon γ-induced protein 10.Peer reviewe