Age, Sex and BMI Relations with Anti-SARS-CoV-2-Spike IgG Antibodies after BNT162b2 COVID-19 Vaccine in Health Care Workers in Northern Greece

Development of a prediction nomogram for IgG levels among asymptomatic or mild patients with COVID-19

Objective

COVID-19 has evolved into a seasonal coronavirus disease, characterized by prolonged infection duration and repeated infections, significantly increasing the risk of patients developing long COVID. Our research focused on the immune responses in asymptomatic and mild cases, particularly the critical factors influencing serum immunoglobulin G (IgG) levels and their predictive value.

Methods

We conducted a retrospective analysis on data from 1939 asymptomatic or mildly symptomatic COVID-19 patients hospitalized between September 2022 and June 2023. Spearman methods were used to test the correlation between serum IgG and age, immunoglobulin M (IgM), procalcitonin (PCT), interleukin-6 (IL-6), nucleic acid conversion time, and BMI. Univariate and multivariate logistic regression analyses identified independent key factors influencing serum IgG levels, which were integrated and visualized in a nomogram. Finally, receiver operating characteristic (ROC) curves were plotted to predict the model's diagnostic performance by calculating the AUC.

Results

Mild patients showed higher levels of IgG, IgM, and longer nucleic acid conversion times than asymptomatic patients, and a lower proportion of them had received ≥ 3 COVID-19 vaccine doses. Serum IgG was positively correlated with serum IgM and negatively correlated with age, PCT, IL-6, and BMI. Notably, it showed a moderate negative correlation with nucleic acid conversion time (r = -0.578, P < 0.001). Logistic regression results showed that younger age, lower IL-6 levels, ≥ 3 doses of vaccine, and no comorbidities were independent predictors of serum IgG levels ≥ 21.08 g/L. We used age, IL-6 levels, vaccine doses, and comorbidities to create a nomogram for predicting serum IgG levels, with the area under the ROC curve reaching 0.772.

Conclusion

Age, IL-6 levels, vaccination status, and comorbidities were independent predictors of serum IgG levels in asymptomatic or mild COVID-19 patients, facilitating risk stratification and clinical decision-making. Notably, receiving ≥3 doses of the COVID-19 vaccine was the most beneficial factor for elevated serum IgG levels.

Obesity does not influence SARS-CoV-2 humoral vaccine immunogenicity

Obesity is a recognized factor influencing immune function and infectious disease outcomes. Characterization of the influence of obesity on SARS-CoV-2 humoral vaccine immunogenicity is required to properly tailor vaccine type (mRNA, viral-vector, protein subunit vaccines) and dosing schedule. Data from a prospective cohort study collected over 34 months was used to evaluate the slope of antibody production and decay and neutralizing capacity following SARS-CoV-2 vaccination in individuals with and without obesity at baseline. Most participants were female (65.4%), white (92.4%), and received mRNA vaccines. 210 were obese and 697 non-obese. Sex and infection-acquired immunity were identified as effect modifiers for the relationship between obesity and COVID-19 vaccine humoral immunogenicity. No consistent influence of obesity on peak titres, titre retention, antibody isotype (IgG, IgM, IgA), or neutralization was identified when controlling for other key variables. It may not be necessary to consider this variable when developing SARS-CoV-2 vaccine dosing strategies.

Non-cross-reactive epitopes dominate the humoral immune response to COVID-19 vaccination - kinetics of plasma antibodies, plasmablasts and memory B cells

Introduction

COVID-19 vaccines are highly effective in inducing protective immunity. While the serum antibody response to COVID-19 vaccination has been studied in depth, our knowledge of the underlying plasmablast and memory B cell (Bmem) responses is still incomplete. Here, we determined the antibody and B cell response to COVID-19 vaccination in a naïve population and contrasted it with the response to a single influenza vaccination in a primed cohort. In addition, we analyzed the antibody and B cell responses against the four endemic human coronaviruses (HCoVs).

Methods

Measurement of specific plasma IgG antibodies was combined with functional analyses of antibody-secreting plasmablasts and Bmems. SARS-CoV-2- and HCoV-specific IgG antibodies were quantified with an in-house bead-based multiplexed immunoassay.

Results

The antibody and B cell responses to COVID-19 vaccination reflected the kinetics of a prime-boost immunization, characterized by a slow and moderate primary response and a faster and stronger secondary response. In contrast, the influenza vaccinees possessed robust immune memory for the vaccine antigens prior to vaccination, and the recall vaccination moderately boosted antibody production and Bmem responses. Antibody levels and Bmem responses waned several months after the 2nd COVID-19 vaccination, but were restored upon the 3rd vaccination. The COVID-19 vaccine-induced antibodies mainly targeted novel, non-cross-reactive S1 epitopes of the viral spike protein, while cross-reactive S2 epitopes were less immunogenic. Booster vaccination not only strongly enhanced neutralizing antibodies against an original SARS-CoV-2 strain, but also induced neutralizing antibodies against the Omicron BA.2 variant. We observed a 100% plasma antibody prevalence against the S1 subunits of HCoVs, which was not affected by vaccination.

Discussion

Overall, by complementing classical serology with a functional evaluation of plasmablasts and memory B cells we provide new insights into the specificity of COVID-19 vaccine-induced antibody and B cell responses.

Determinants of SARS-CoV-2 IgG response and decay in Canadian healthcare workers: A prospective cohort study

INTRODUCTION

Healthcare workers (HCWs) from an interprovincial Canadian cohort gave serial blood samples to identify factors associated with anti-receptor binding domain (anti-RBD) IgG response to the SARS-CoV-2 virus.

METHODS

Members of the HCW cohort donated blood samples four months after their first SARS-CoV-2 immunization and again at 7, 10 and 13 months. Date and type of immunizations and dates of SARS-CoV-2 infection were collected at each of four contacts, together with information on immunologically-compromising conditions and current therapies. Blood samples were analyzed centrally for anti-RBD IgG and anti-nucleocapsid IgG (Abbott Architect, Abbott Diagnostics). Records of immunization and SARS-CoV-2 testing from public health agencies were used to assess the impact of reporting errors on estimates from the random-effects multivariable model fitted to the data.

RESULTS

2752 of 4567 vaccinated cohort participants agreed to donate at least one blood sample. Modelling of anti-RBD IgG titer from 8903 samples showed an increase in IgG with each vaccine dose and with first infection. A decrease in IgG titer was found with the number of months since vaccination or infection, with the sharpest decline after the third dose. An immunization regime that included mRNA1273 (Moderna) resulted in higher anti-RBD IgG. Participants reporting multiple sclerosis, rheumatoid arthritis or taking selective immunosuppressants, tumor necrosis factor inhibitors, calcineurin inhibitors and antineoplastic agents had lower anti-RBD IgG. Supplementary analyses showed higher anti-RBD IgG in those reporting side-effects of vaccination, no relation of anti-RBD IgG to obesity and lower titers in women immunized in early or mid-pregnancy. Sensitivity analysis results suggested no important bias in the self-report data.

CONCLUSION

Creation of a prospective cohort was central to the credibility of results presented here. Serial serology assessments, with longitudinal analysis, provided effect estimates with enhanced accuracy and a clearer understanding of medical and other factors affecting response to vaccination.

Surveillance of Antimicrobial Resistance and Multidrug Resistance Prevalence of Clinical Isolates in a Regional Hospital in Northern Greece

Antimicrobial resistance is a global health threat resulting in increased morbidity and mortality. This retrospective study aimed to estimate antimicrobial susceptibility and multidrug resistance prevalence of clinical isolates in a regional hospital in Northern Greece during the last 6 years by analyzing the annual reports of the Laboratory of Microbiology. A total of 12,274 strains of certain bacteria were isolated from both hospitalized and ambulatory patients from biological products, mainly urine (range 63-78% during the study period). E. coli was the most frequent pathogen found (37.4%). A significant increase in the number of the main pathogens causing hospital-acquired infections (Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterococcus faecium) was found in the time period of 2021-2023 compared to 2018-2020 (p < 0.0001). In total, 1767 multidrug-resistant bacterial strains were isolated, most of them belonging to Acinetobacter baumannii (36.4%) and Klebsiella pneumoniae (39.6%), and were located in the intensive care unit (ICU) (59.8%). Extensively drug resistance (XDR) and pan drug resistance (PDR) were significantly higher in 2021-2023 than in 2018-2020 (XDR: 641/1087 in 2021-2023 vs. 374/680 in 2018-2020 and PDR: 134/1087 in 2021-2023 vs. 25/680 in 2018-2020, p < 0.0001), resulting in an urgent need to establish certain strategies in order to eliminate this threatening condition.