HLA Alleles, COVID-19 Vaccine Antibody Response and Real-World Breakthrough Outcomes (preprint)

The rapid development, approval, and global distribution of COVID-19 vaccines represent an unprecedented intervention in public health history, with over 13 billion doses administered worldwide in two years. However, our understanding of the HLA genetic underpinnings of COVID-19 vaccine-induced antibody responses and their clinical implications for breakthrough outcomes remain limited. To bridge this knowledge gap, we designed and performed a series of genetic and epidemiological analyses among 368,098 vaccinated individuals, and a subset of 194,371 participants who had antibody serology tests. Firstly, we corroborated earlier findings that SNPs associated with antibody response were predominantly located in Major Histocompatibility Complex region, and that the expansive HLA-DQB1*06 allele family was linked to better antibody responses. However, our findings contest the claim that DQB1*06 alleles alone significantly impact breakthrough risks. Additionally, our results suggest that the specific DQB1*06:04 subtype could be the true causal allele, as opposed to the previously reported DQB1*06:02. Secondly, we identified and validated six new functional HLA alleles that independently contribute to vaccine-induced antibody responses. Moreover, we unravelled additive effects of variations across multiple HLA genes that, concurrently, change the risk of clinically relevant breakthrough COVID-19 outcomes. Finally, we detangled the overall vaccine effectiveness and showed that antibody positivity accounts for approximately 20% protection against breakthrough infection and 50% against severe outcomes. These novel findings provide robust population evidence demonstrating how variations within HLA genes strongly, collectively, and causally influence vaccine-induced antibody responses, and the risk of COVID-19 breakthrough infection and related outcomes, with implications for subsequent functional research and personalised vaccination.

Disparities in SARS-CoV-2 case rates by ethnicity, religion, measures of socio-economic position, English proficiency, and self-reported disability: cohort study of 39 million people in England during the Alpha and Delta waves (preprint)

Objective To examine socio-demographic disparities in SARS-CoV-2 case rates during the second (Alpha) and third (Delta) waves of the COVID-19 pandemic. Design Retrospective, population-based cohort study. Setting Resident population of England. Participants 39,006,194 people aged 10 years and over who were enumerated at the 2011 Census, registered with the National Health Service (NHS) and alive on 1 September 2020. Main outcome measures Testing positive for SARS-CoV-2 during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. We calculated age-standardised case rates by socio-demographic characteristics and used logistic regression models to estimate adjusted odds ratios (ORs). Results During the study period, 5,767,584 individuals tested positive for SARS-CoV-2. In the second wave, the fully-adjusted odds of having a positive test, relative to the White British group, were highest for the Bangladeshi (OR: 1.88, 95% CI 1.86 to 1.90) and Pakistani (1.81, 1.79 to 1.82) ethnic groups. Relative to the Christian group, Muslim and Sikh religious groups had fully-adjusted ORs of 1.58 (1.57 to 1.59) and 1.74 (1.72 to 1.76), respectively. Greater area deprivation, disadvantaged socio-economic position, living in a care home and low English language proficiency were also associated with higher odds of having a positive test. However, the disparities between groups varied over time. Being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of testing positive during the third wave. Conclusion There are large socio-demographic disparities on SARS-CoV-2 cases which have varied between different waves of the pandemic. Research is now urgently needed to understand why these disparities exist to inform policy interventions in future waves or pandemics. What is already known on this topic People with pre-existing health conditions or disability, ethnic minority groups, the elderly, some religious groups, people with low socio-economic status, and those living in deprived areas have been disproportionately affected by the COVID-19 pandemic in terms of risk of infection and adverse outcomes. What this study adds Using linked data on 39 million people in England, we found that during the second wave, COVID-19 case rates were highest among the Bangladeshi and Pakistani ethnic groups, the Muslim religious group, individuals from deprived areas and of low socio-economic position; during the third wave, being Christian, White British, non-disabled, and from a more advantaged socio-economic position were all associated with increased odds of receiving a positive test Adjusting for geographical factors, socio-demographic characteristics, and pre-pandemic health status explained some, but not all, of the excess risk When stratifying the dataset by broad age groups, the odds of receiving a positive test remained higher among the Bangladeshi and Pakistani ethnic groups aged 65 years and over during the third wave, which may partly explain the continued elevated mortality rates in these groups

Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine roll-out: a retrospective, population-based cohort study (preprint)

Objectives To assess whether ethnic differences in COVID-19 mortality in England have continued into the third wave and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors. Design Cohort study of 28.8 million adults using data from the Office for National Statistics Public Health Data Asset. Setting People living in private households or communal establishments in England. Participants 28,816,020 adults (47% male) aged 30-100 years in 2020 (mean age = 56), who were present at the 2011 Census and alive on 8 December 2020. Main outcome measures Death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021) of the pandemic. We calculated hazard ratios (HRs) separately for males to females to summarise the association between ethnic group and death involving COVID-19 in each wave, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status. Results Age-adjusted HRs of death involving COVID-19 were higher for most ethnic minority groups than the White British group during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African and Black Caribbean). In both waves, HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. The only groups where fully-adjusted HRs remained elevated were the Bangladeshi group (men: 2.19, 95% CI 1.72 to 2.78; women: 2.12, 95% CI 1.58 to 2.86) and men from the Pakistani group (1.24, 95% CI 1.06 to 1.46). Conclusion Public health strategies to increase vaccination uptake in ethnic minority groups could reduce disparities in COVID-19 mortality that cannot be accounted for by pre-existing risk factors. What is already known on this topic Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic during the first and second waves. COVID-19 vaccination uptake is also lower among many ethnic minority groups, particularly Bangladeshi, Black African, Black Caribbean, and Pakistani groups. There is a paucity of research into whether ethnic disparities in COVID-19 mortality have continued into the third wave and the extent to which differences in vaccination uptake contribute to differences in COVID-19 mortality. What this study adds Using linked data on 28.8 million adults in England, we find that rates of COVID-19 mortality have remained higher than the White British group for most ethnic minority groups during the vaccine roll-out, notably for the Bangladeshi, Black African, Black Caribbean, and Pakistani groups. After adjustment for geographical factors, sociodemographic characteristics, pre-pandemic health status, and vaccination status, the only groups with elevated rates of COVID-19 mortality during the third wave were the Bangladeshi group and men from the Pakistani group, suggesting that increasing vaccination uptake in ethnic minority groups could reduce ethnic disparities in COVID-19 mortality.

Population Based Mean Vitamin-D Levels In 19 European Countries & COVID-19 Mortality (preprint)

Background: Reports early in the epidemic linking low mean national Vitamin D level with increased COVID-19 death, and until recently little research on the impact of Vitamin-D deficiency on severity of COVID-19, led to this update of the initial report studying mortality up to the end of January 2021. Methods: : Coronavirus pandemic data for 19 European countries were downloaded from Our World in Data, which was last updated on January 24, 2021. Data from March 21, 2020 to January 22, 2021 were included in the statistical analysis. Vitamin-D (25)-HD mean data were collected by literature review. Poisson mixed-effect model was used to model the data. Results: : European countries with Vitamin-D (25)-HD mean less than or equal to 50 have higher COVID-19 death rates as compared with European countries with Vitamin-D (25)-HD mean greater than 50, relative risk of 2.155 (95% CI: 1.068 - 4.347, p-value = 0.032). A statistically significant negative moderate Spearman rank correlation was observed between Vitamin-D (25)-HD mean and the number of COVID-19 deaths for each 14-day period during the COVID-19 pandemic time period. Conclusions: : The observation of the significantly lower COVID-19 mortality rates in countries with lowest annual sun exposure but highest mean Vitamin-D (25)-HD levels provides support for the use of food fortification. The need to consider re-configuring vaccine strategy due to emergence of large number of COVID-19 variants provides an opportunity to undertake such therapeutic randomized control trials.

Feasibility of a Saliva-Based Covid-19 Screening Program in Abu Dhabi Primary Schools (preprint)

The pandemic has forced closures of primary schools resulting in loss of learning time on a global scale. In addition to face coverings, social distancing, and hand hygiene, an efficient testing method is important to mitigate spread of COVID-19 in schools. We evaluated the feasibility of a saliva-based SARS-CoV-2 PCR testing program on 18 primary schools in the Emirate of Abu Dhabi, United Arab Emirates. Qualitative results show that children 4 to 5 years had difficulty producing an adequate saliva specimen compared to those 6 to 12 years. A short training video on saliva collection beforehand helps demystify the process for students and parents alike. Informed consent was challenging and should be done beforehand by school health nurses or other medical professionals to reassure parents and maximize participation. Telephone interviews with school administrators resulted in an overall 83.3% response rate. 93% of school administrators had a positive experience with saliva testing and felt the program improved the safety of their schools. 73% of respondents supported the ongoing use of saliva testing for SARS-CoV-2 on their school campuses. On-campus saliva testing is a feasible option for primary schools to screen for COVID-19 in their student population to help keep their campuses safe and open for learning.

Mean Vitamin D levels in 19 European Countries & COVID-19 Mortality over 10 months (preprint)

ObjectivesReports early in the epidemic linking low mean national Vitamin D level with increased COVID-19 death, and until recently little research on the impact of Vitamin D deficiency on severity of COVID-19, led to this update of the initial report studying mortality up to the end of January 2021. Design and SettingCoronavirus pandemic data for 19 European countries were downloaded from Our World in Data, which was last updated on January 24, 2021. Data from March 21, 2020 to January 22, 2021 were included in the statistical analysis. Vitamin-D (25)-HD mean data were collected by literature review. Poisson mixed-effect model was used to model the data. ResultsEuropean countries with Vitamin-D (25)-HD mean less than or equal to 50 have higher COVID-19 death rates as compared with European countries with Vitamin-D (25)-HD mean greater than 50, relative risk of 2.155 (95% CI: 1.068 - 4.347, p-value = 0.032). A statistically significant negative moderate Spearman rank correlation was observed between Vitamin-D (25)-HD mean and the number of COVID-19 deaths for each 14-day period during the COVID-19 pandemic time period. ConclusionsThe observation of the significantly lower COVID-19 mortality rates in countries with lowest annual sun exposure but highest mean Vitamin-D (25)-HD levels provides support for the use of food fortification. The need to consider re-configuring vaccine strategy due to emergence of large number of COVID-19 variants provides an opportunity to undertake such therapeutic randomized control trials.

Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study (preprint)

Existing prognostic tools mainly focus on predicting the risk of mortality among patients with coronavirus disease 2019. However, clinical evidence suggests that COVID-19 can result in non-mortal complications that affect patient prognosis. To support patient risk stratification, we aimed to develop a prognostic system that predicts complications common to COVID-19. In this retrospective study, we used data collected from 3,352 COVID-19 patient encounters admitted to 18 facilities between April 1 and April 30, 2020, in Abu Dhabi (AD), UAE. The hospitals were split based on geographical proximity to assess for our proposed system's learning generalizability, AD Middle region and AD Western & Eastern regions, A and B, respectively. Using data collected during the first 24 hours of admission, the machine learning-based prognostic system predicts the risk of developing any of seven complications during the hospital stay. The complications include secondary bacterial infection, AKI, ARDS, and elevated biomarkers linked to increased patient severity, including d-dimer, interleukin-6, aminotransferases, and troponin. During training, the system applies an exclusion criteria, hyperparameter tuning, and model selection for each complication-specific model. The system achieves good accuracy across all complications and both regions. In test set A (587 patient encounters), the system achieves 0.91 AUROC for AKI and >0.80 AUROC for most of the other complications. In test set B (225 patient encounters), the respective system achieves 0.90 AUROC for AKI, elevated troponin, and elevated interleukin-6, and >0.80 AUROC for most of the other complications. The best performing models, as selected by our system, were mainly gradient boosting models and logistic regression. Our results show that a data-driven approach using machine learning can predict the risk of such complications with high accuracy.

Microfluidic nano-scale qPCR enables ultra-sensitive detection of SARS-CoV-2 (preprint)

BackgroundA major challenge in controlling the COVID-19 pandemic is the high false-negative rate of the commonly used standard RT-PCR methods for SARS-CoV-2 detection in clinical samples. Accurate detection is particularly challenging in samples with low viral loads that are below the limit of detection (LoD) of standard one- or two-step RT-PCR methods. MethodsWe implement a three-step approach for SARS-CoV-2 detection and quantification that employs reverse transcription, targeted cDNA preamplification and nano-scale qPCR based on the Fluidigm 192.24 microfluidic chip. We validate the method using both positive controls and nasopharyngeal swab samples. ResultsUsing SARS-CoV-2 synthetic RNA and plasmid controls, we demonstrate that the addition of a preamplification step enhances the LoD of the Fluidigm method by 1,000-fold, enabling detection below 1 copy/l. We applied this method to analyze 182 clinical NP swab samples previously diagnosed using a standard RT-qPCR protocol (91 positive, 91 negative) and demonstrate reproducible detection of SARS-CoV-2 over five orders of magnitude (< 1 to 106 viral copies/l). Crucially, we detect SARS-CoV-2 with relatively low viral load estimates (<1 to 40 viral copies/l) in 17 samples with negative clinical diagnosis, indicating a potential false negative rate of 18.7% by clinical diagnostic procedures. ConclusionThe three-step nano-scale RT-qPCR method can robustly detect SARS-CoV-2 in samples with relatively low viral loads (< 1 viral copy/l) and has the potential to reduce the false negative rate of standard RT-PCR-based diagnostic tests for SARS-CoV-2 and other viral infections. SummaryWe test, implement and report the results of a microfluidic RT-qPCR assay system involving sequential RT, preamplification and nano-scale qPCR that can robustly detect SARS-CoV-2 in clinical samples with viral loads less than 1 copy/ul.