Evaluation of post-vaccination immunoglobulin G antibodies and T-cell immune response after inoculation with different types and doses of SARS-CoV-2 vaccines: A retrospective cohort study.

Introduction: The induction and speed of production of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) immune biomarkers may vary by type and number of inoculated vaccine doses. This study aimed to explore variations in SARS-CoV-2 anti-spike (anti-S), anti-nucleocapsid (anti-N), and neutralizing immunoglobulin G (IgG) antibodies, and T-cell response by type and number of SARS-CoV-2 vaccine doses received. Methods: In a naturally exposed and SARS-CoV-2-vaccinated population, we quantified the anti-S, anti-N, and neutralizing IgG antibody concentration and assessed T-cell response. Data on socio-demographics, medical history, and history of SARS-CoV-2 infection and vaccination were collected. Furthermore, nasal swabs were collected to test for SARS-CoV-2 infection. Confounder-adjusted association between having equal or more than a median concentration of the three IgG antibodies and T-cell response by number and type of the inoculated vaccines was quantified. Results: We surveyed 952 male participants with a mean age of 35.5 years ± 8.4 standard deviations. Of them, 52.6% were overweight/obese, and 11.7% had at least one chronic comorbidity. Of the participants, 1.4, 0.9, 20.2, 75.2, and 2.2% were never vaccinated, primed with only one dose, primed with two doses, boosted with only one dose, and boosted with two doses, respectively. All were polymerase chain reaction-negative to SARS-CoV-2. BBIBP-CorV (Sinopharm) was the most commonly used vaccine (92.1%), followed by rAd26-S + rAd5-S (Sputnik V Gam-COVID-Vac) (1.5%) and BNT162b2 (Pfizer-BioNTech) (0.3%). Seropositivity to anti-S, anti-N, and neutralizing IgG antibodies was detected in 99.7, 99.9, and 99.3% of the study participants, respectively. The T-cell response was detected in 38.2% of 925 study participants. Every additional vaccine dose was significantly associated with increased odds of having ≥median concentration of anti-S [adjusted odds ratio (aOR), 1.34; 95% confidence interval (CI): 1.02-1.76], anti-N (aOR, 1.35; 95% CI: 1.03-1.75), neutralizing IgG antibodies (aOR, 1.29; 95% CI: 1.00-1.66), and a T-cell response (aOR, 1.48; 95% CI: 1.12-1.95). Compared with boosting with only one dose, boosting with two doses was significantly associated with increased odds of having ≥median concentration of anti-S (aOR, 13.8; 95% CI: 1.78-106.5), neutralizing IgG antibodies (aOR, 13.2; 95% CI: 1.71-101.9), and T-cell response (aOR, 7.22; 95% CI: 1.99-26.5) although not with anti-N (aOR, 0.41; 95% CI: 0.16-1.08). Compared with priming and subsequently boosting with BBIBP-CorV, all participants who were primed with BBIBP-CorV and subsequently boosted with BNT162b2 had ≥median concentration of anti-S and neutralizing IgG antibodies and 14.6-time increased odds of having a T-cell response (aOR, 14.63; 95% CI: 1.78-120.5). Compared with priming with two doses, boosting with the third dose was not associated, whereas boosting with two doses was significantly associated with having ≥median concentration of anti-S (aOR, 14.20; 95% CI: 1.85-109.4), neutralizing IgG (aOR, 13.6; 95% CI: 1.77-104.3), and T-cell response (aOR, 7.62; 95% CI: 2.09-27.8). Conclusion: Achieving and maintaining a high blood concentration of protective immune biomarkers that predict vaccine effectiveness is very critical to limit transmission and contain outbreaks. In this study, boosting with only one dose or with only BBIBP-CorV after priming with BBIBP-CorV was insufficient, whereas boosting with two doses, particularly boosting with the mRNA-based vaccine, was shown to be associated with having a high concentration of anti-S, anti-N, and neutralizing IgG antibodies and producing an efficient T-cell response.

Evaluation of post-vaccination immunoglobulin G antibodies and T-cell immune response after inoculation with different types and doses of SARS-CoV-2 vaccines: A retrospective cohort study

Introduction The induction and speed of production of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) immune biomarkers may vary by type and number of inoculated vaccine doses. This study aimed to explore variations in SARS-CoV-2 anti-spike (anti-S), anti-nucleocapsid (anti-N), and neutralizing immunoglobulin G (IgG) antibodies, and T-cell response by type and number of SARS-CoV-2 vaccine doses received. Methods In a naturally exposed and SARS-CoV-2–vaccinated population, we quantified the anti-S, anti-N, and neutralizing IgG antibody concentration and assessed T-cell response. Data on socio-demographics, medical history, and history of SARS-CoV-2 infection and vaccination were collected. Furthermore, nasal swabs were collected to test for SARS-CoV-2 infection. Confounder-adjusted association between having equal or more than a median concentration of the three IgG antibodies and T-cell response by number and type of the inoculated vaccines was quantified. Results We surveyed 952 male participants with a mean age of 35.5 years ± 8.4 standard deviations. Of them, 52.6% were overweight/obese, and 11.7% had at least one chronic comorbidity. Of the participants, 1.4, 0.9, 20.2, 75.2, and 2.2% were never vaccinated, primed with only one dose, primed with two doses, boosted with only one dose, and boosted with two doses, respectively. All were polymerase chain reaction-negative to SARS-CoV-2. BBIBP-CorV (Sinopharm) was the most commonly used vaccine (92.1%), followed by rAd26-S + rAd5-S (Sputnik V Gam-COVID-Vac) (1.5%) and BNT162b2 (Pfizer-BioNTech) (0.3%). Seropositivity to anti-S, anti-N, and neutralizing IgG antibodies was detected in 99.7, 99.9, and 99.3% of the study participants, respectively. The T-cell response was detected in 38.2% of 925 study participants. Every additional vaccine dose was significantly associated with increased odds of having ≥median concentration of anti-S [adjusted odds ratio (aOR), 1.34;95% confidence interval (CI): 1.02–1.76], anti-N (aOR, 1.35;95% CI: 1.03–1.75), neutralizing IgG antibodies (aOR, 1.29;95% CI: 1.00–1.66), and a T-cell response (aOR, 1.48;95% CI: 1.12–1.95). Compared with boosting with only one dose, boosting with two doses was significantly associated with increased odds of having ≥median concentration of anti-S (aOR, 13.8;95% CI: 1.78–106.5), neutralizing IgG antibodies (aOR, 13.2;95% CI: 1.71–101.9), and T-cell response (aOR, 7.22;95% CI: 1.99–26.5) although not with anti-N (aOR, 0.41;95% CI: 0.16–1.08). Compared with priming and subsequently boosting with BBIBP-CorV, all participants who were primed with BBIBP-CorV and subsequently boosted with BNT162b2 had ≥median concentration of anti-S and neutralizing IgG antibodies and 14.6-time increased odds of having a T-cell response (aOR, 14.63;95% CI: 1.78–120.5). Compared with priming with two doses, boosting with the third dose was not associated, whereas boosting with two doses was significantly associated with having ≥median concentration of anti-S (aOR, 14.20;95% CI: 1.85–109.4), neutralizing IgG (aOR, 13.6;95% CI: 1.77–104.3), and T-cell response (aOR, 7.62;95% CI: 2.09–27.8). Conclusion Achieving and maintaining a high blood concentration of protective immune biomarkers that predict vaccine effectiveness is very critical to limit transmission and contain outbreaks. In this study, boosting with only one dose or with only BBIBP-CorV after priming with BBIBP-CorV was insufficient, whereas boosting with two doses, particularly boosting with the mRNA-based vaccine, was shown to be associated with having a high concentration of anti-S, anti-N, and neutralizing IgG antibodies and producing an efficient T-cell response.

The impact of COVID-19 pandemic on depression and anxiety symptoms: Findings from the United Arab Emirates Healthy Future (UAEHFS) cohort study.

BACKGROUND: Significant concerns about mental health were raised during the COVID-19 pandemic. We investigated the prevalence of depression and anxiety symptoms among the participants of the United Arab Emirates Healthy Future Study (UAEHFS); a national cohort study. We further explored the change in the prevalence of depression symptoms among those with comparable pre-pandemic data. METHODS: A sample of UAEHFS participants were invited to complete a COVID-19 online questionnaire during the first wave of the pandemic. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire Depression Scale (PHQ-8) and the Generalized Anxiety Disorder-7 Scale (GAD-7) respectively. Unpaired analyses were done to examine the effect of COVID-19 on depression and anxiety symptoms during the pandemic. Paired analysis was conducted to examine the change in depression symptoms. RESULTS: During the pandemic, we reported a prevalence of 32.8% (95% CI: 27.0, 39.1) for depression and 26.4% (95% CI: 21.0, 32.6) for anxiety symptoms. Younger people reported higher levels of depression (40.4%) and anxiety (34.5%) symptoms. Females reported higher levels of depression (36.5%) and anxiety (32.7%) symptoms. In paired analysis, the prevalence of depression symptoms during the pandemic was 34% (95% CI: 26.5, 42.4) compared to 29.9% (95% CI: 22.7, 38.1) before the pandemic. No statistically significant difference was observed, p-value = 0.440. Adjusted multivariate logistic regression models for PHQ-8 and GAD-7 during the pandemic showed that participants, who were experiencing flu-like symptoms, had higher odds of reporting depression symptoms compared to those without symptoms. Additionally, age was significantly negatively associated with anxiety symptoms. CONCLUSIONS: Overall, we found that depression and anxiety symptoms were more prevalent among young people and females. However, we did not find a significant change in the prevalence of depression symptoms among those with comparable pre-pandemic data. Identifying vulnerable groups and understanding trajectories through longitudinal studies would help with planning for effective mental health interventions for the current and future pandemics.

Maternal Early-Life Risk Factors and Later Gestational Diabetes Mellitus: A Cross-Sectional Analysis of the UAE Healthy Future Study (UAEHFS).

Limited studies have focused on maternal early-life risk factors and the later development of gestational diabetes mellitus (GDM). We aimed to estimate the GDM prevalence and examine the associations of maternal early-life risk factors, namely: maternal birthweight, parental smoking at birth, childhood urbanicity, ever-breastfed, parental education attainment, parental history of diabetes, childhood overall health, childhood body size, and childhood height, with later GDM. This was a retrospective cross-sectional study using the UAE Healthy Future Study (UAEHFS) baseline data (February 2016 to April 2022) on 702 ever-married women aged 18 to 67 years. We fitted a Poisson regression to estimate the risk ratio (RR) for later GDM and its 95% confidence interval (CI). The GDM prevalence was 5.1%. In the fully adjusted model, females with low birthweight were four times more likely (RR 4.04, 95% CI 1.36-12.0) and females with a parental history of diabetes were nearly three times more likely (RR 2.86, 95% CI 1.10-7.43) to report later GDM. In conclusion, maternal birthweight and parental history of diabetes were significantly associated with later GDM. Close glucose monitoring during pregnancy among females with either a low birth weight and/or parental history of diabetes might help to prevent GDM among this high-risk group.