Immune cell populations and induced immune responses at admission in patients hospitalized with vaccine breakthrough SARS-CoV-2 infections.

Background: Vaccine breakthrough SARS-CoV-2 infections are common and of clinical and public health concern. However, little is known about the immunological characteristics of patients hospitalized due to these infections. We aimed to investigate and compare immune cell subpopulations and induced immune responses in vaccinated and non-vaccinated patients hospitalized with severe COVID-19. Methods: A nested case-control study on adults (≥ 18 years) who received at least two doses of a mRNA-COVID-19 vaccine and were hospitalized with SARS-CoV-2 breakthrough infections and severe COVID-19 between January 7, 2021, and February 1, 2022, were eligible for inclusion. Age- and sex-matched non-vaccinated controls were identified. Immunophenotyping was performed using a custom-designed 10-color flow cytometry prefabricated freeze-dried antibody panel (DuraClone, Beckman Coulter (BC), Brea, Calif). TruCulture (Myriad RBM, Austin, USA) was used to assess induced immune response in whole blood, revealing different critical signaling pathways as a proxy for immune function. All samples were obtained within 48 hours of admission. Results: In total, 20 hospitalized patients with severe COVID-19 and a breakthrough SARS-CoV-2 infection were included, ten vaccinated and ten non-vaccinated patients. Vaccinated patients had lower concentrations of CD19 B cells (p = 0.035), naïve CD4 T cells (p = 0.015), a higher proportion of γδ1 T cells (p = 0.019), and higher unstimulated immune cell release of IL-10 (p = 0.015). Conclusion: We observed immunological differences between vaccinated and non-vaccinated patients hospitalized due to severe COVID-19 that indicate that vaccinated patients had lower B cell concentrations, lower concentrations of CD4 naïve T cells, a skewed gamma-delta V1/V2 ratio, and an exaggerated IL-10 response at admission. These results could indicate a suboptimal immune response involved in SARS-CoV-2 breakthrough infections that cause severe COVID-19 in vaccinated adults. However, the sample size was small, and further research is needed to confirm these results.

Erratum: Author Correction: Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients.

[This corrects the article DOI: 10.1038/s43856-022-00178-5.].

Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients.

Background: The immune pathogenesis underlying the diverse clinical course of COVID-19 is poorly understood. Currently, there is an unmet need in daily clinical practice for early biomarkers and improved risk stratification tools to help identify and monitor COVID-19 patients at risk of severe disease. Methods: We performed longitudinal assessment of stimulated immune responses in 30 patients hospitalized with COVID-19. We used the TruCulture whole-blood ligand-stimulation assay applying standardized stimuli to activate distinct immune pathways, allowing quantification of cytokine responses. We further characterized immune cell subsets by flow cytometry and used this deep immunophenotyping data to map the course of clinical disease within and between patients. Results: Here we demonstrate impairments in innate immune response pathways at time of COVID-19 hospitalization that are associated with the development of severe disease. We show that these impairments are transient in those discharged from hospital, as illustrated by functional and cellular immune reconstitution. Specifically, we identify lower levels of LPS-stimulated IL-1ß, and R848-stimulated IL-12 and IL-17A, at hospital admission to be significantly associated with increasing COVID-19 disease severity during hospitalization. Furthermore, we propose a stimulated immune response signature for predicting risk of developing severe or critical COVID-19 disease at time of hospitalization, to validate in larger cohorts. Conclusions: We identify early impairments in innate immune responses that are associated with subsequent COVID-19 disease severity. Our findings provide basis for early identification of patients at risk of severe disease which may have significant implications for the early management of patients hospitalized with COVID-19.

Prediction of Respiratory Failure and Mortality in COVID-19 Patients Using Long Pentraxin PTX3.

The course of COVID-19 is unpredictable, ranging from asymptomatic to respiratory failure and death. Prognostic biomarkers are urgently needed. We hypothesized that long pentraxin PTX3 could be a valuable plasma biomarker due to its essential role in inflammatory processes. In a prospective hospitalized COVID-19 derivation cohort (n = 126) during the spring of 2020, we measured PTX3 within 4 days of admission. The predictive value of mechanical ventilation (MV) and 30-day mortality compared with clinical parameters and other markers of inflammation were assessed by logistic regression analysis and expressed as odds ratio (OR) with 95% confidence interval (CI). Analyses were repeated in a prospective validation cohort (n = 112) of hospitalized patients with COVID-19 treated with remdesivir and dexamethasone. Thirty-day mortality in the derivation cohort was 26.2%. In patients who died, the median PTX3 concentration upon admission was 19.5 ng/mL (IQR: 12.5-33.3) versus 6.6 ng/mL (IQR 2.9-12.3) (p < 0.0001) for survivors. After adjustment for covariates, the odds of 30-day mortality increased two-fold for each doubling of PTX3 (OR 2.03 [95% CI: 1.23-3.34], p = 0.006), which was also observed in the validation cohort (OR 1.70 [95% CI: 1.09-2.67], p = 0.02). Similarly, PTX3 levels were associated with MV. After adjustment for covariates, OR of MV was 2.34 (95% CI: 1.33-4.12, p = 0.003) in the derivation cohort and 1.64 (95% CI: 1.03-2.62, p = 0.04) in the validation cohort. PTX3 appears to be a useful clinical biomarker to predict 30-day respiratory failure and mortality risk in COVID-19 patients treated with and without remdesivir and dexamethasone.

Risk Factors for Being Seronegative following SARS-CoV-2 Infection in a Large Cohort of Health Care Workers in Denmark.

Most individuals seroconvert after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but being seronegative is observed in 1 to 9%. We aimed to investigate the risk factors associated with being seronegative following PCR-confirmed SARS-CoV-2 infection. In a prospective cohort study, we screened health care workers (HCW) in the Capital Region of Denmark for SARS-CoV-2 antibodies. We performed three rounds of screening from April to October 2020 using an enzyme-linked immunosorbent assay (ELISA) method targeting SARS-CoV-2 total antibodies. Data on all participants' PCR for SARS-CoV-2 RNA were captured from national registries. The Kaplan-Meier method and Cox proportional hazards models were applied to investigate the probability of being seronegative and the related risk factors, respectively. Of 36,583 HCW, 866 (2.4%) had a positive PCR before or during the study period. The median (interquartile range [IQR]) age of 866 HCW was 42 (31 to 53) years, and 666 (77%) were female. After a median of 132 (range, 35 to 180) days, 21 (2.4%) of 866 were seronegative. In a multivariable model, independent risk factors for being seronegative were self-reported asymptomatic or mild infection hazard ratio (HR) of 6.6 (95% confidence interval [CI], 2.6 to 17; P < 0.001) and body mass index (BMI) of ≥30, HR 3.1 (95% CI, 1.1 to 8.8; P = 0.039). Only a few (2.4%) HCW were not seropositive. Asymptomatic or mild infection as well as a BMI above 30 were associated with being seronegative. Since the presence of antibodies against SARS-CoV-2 reduces the risk of reinfection, efforts to protect HCW with risk factors for being seronegative may be needed in future COVID-19 surges. IMPORTANCE Most individuals seroconvert after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but negative serology is observed in 1 to 9%. We found that asymptomatic or mild infection as well as a BMI above 30 were associated with being seronegative. Since the presence of antibodies against SARS-CoV-2 reduces the risk of reinfection, efforts to protect HCW with risk factors for being seronegative may be needed in future COVID-19 surges.