Cohort Profile: Longitudinal population-based study of COVID-19 in UK adults (COVIDENCE UK)

BackgroundCoronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is estimated to have caused more than 18 million deaths worldwide as of end-May 2022. MethodsCOVIDENCE UK is a longitudinal population-based study that investigates risk factors for, and impacts of, COVID-19 in UK residents aged [≥]16 years. A unique feature is the capacity to support trial-within-cohort studies to evaluate interventions for prevention of COVID-19 and other acute respiratory illnesses. Participants complete a detailed online baseline questionnaire capturing self-reported information relating to their socio-demographic characteristics, occupation, lifestyle, quality of life, weight, height, longstanding medical conditions, medication use, vaccination status, diet and supplemental micronutrient intake. Follow-up on-line questionnaires capturing incident symptoms of COVID-19 and other acute respiratory infections, incident swab test-confirmed COVID-19, doses of SARS-CoV-2 vaccine received, and quality of life are completed at monthly intervals. ResultsThe study was launched on 1st May 2020 and closed to recruitment on 6th October 2021. A total of 19,981 participants enrolled and consented to 5-year follow-up with medical record linkage. Their mean age was 59.1 years (range 16.0 to 94.4 years), 70.2% were female, and 93.7% identified their ethnic origin as White. Analyses conducted to date have provided key insights into risk factors for SARS-CoV-2 infection and COVID-19 disease, determinants of SARS-CoV-2 vaccine immunogenicity and efficacy, and impacts of COVID-19 on health economic outcomes. The cohort has also supported conduct of a Phase 3 randomised trial-within-cohort study (CORONAVIT) evaluating implementation of a test-and-treat approach to correcting sub-optimal vitamin D status on incidence and severity of acute respiratory infections, including COVID-19. ConclusionsThe COVIDENCE UK dataset represents a valuable resource containing granular information on factors influencing susceptibility to, and impacts of, COVID-19 in UK adults. Researchers wishing to access anonymised participant-level data should contacting the corresponding author for further information.

Brain Injury in COVID-19 is Associated with Autoinflammation and Autoimmunity

COVID-19 has been associated with many neurological complications including stroke, delirium and encephalitis. Furthermore, many individuals experience a protracted post-viral syndrome which is dominated by neuropsychiatric symptoms, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of severe COVID-19 more broadly. We sought to investigate the dynamics of, and relationship between, serum markers of brain injury (neurofilament light [NfL], Glial Fibrillary Acidic Protein [GFAP] and total Tau) and markers of dysregulated host response including measures of autoinflammation (proinflammatory cytokines) and autoimmunity. Brain injury biomarkers were measured using the Quanterix Simoa HDx platform, cytokine profiling by Luminex (R&D) and autoantibodies by a custom protein microarray. During hospitalisation, patients with COVID-19 demonstrated elevations of NfL and GFAP in a severity-dependant manner, and there was evidence of ongoing active brain injury at follow-up 4 months later. Raised NfL and GFAP were associated with both elevations of pro-inflammatory cytokines and the presence of autoantibodies; autoantibodies were commonly seen against lung surfactant proteins as well as brain proteins such as myelin associated glycoprotein, but reactivity was seen to a large number of different antigens. Furthermore, a distinct process characterised by elevation of serum total Tau was seen in patients at follow-up, which appeared to be independent of initial disease severity and was not associated with dysregulated immune responses in the same manner as NfL and GFAP.

Reliability of multi-modal MRI-derived brain phenotypes for multi-site assessment of neuropsychiatric complications of SARS-CoV-2 infection

BackgroundMagnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. MethodsA multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI) and arterial spin labelling (ASL) was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N=8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (Kings College London). Over 2,000 Imaging Derived Phenotypes (IDPs) measuring both data quality and regional image properties of interest were automatically estimated by customised UKB image processing pipelines. Components of variance and intra-class correlations were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. ResultsIntra-class correlations for many IDPs indicated good-to-excellent between-site reliability. First considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, but there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. ConclusionThese results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonization of data collected from sites using scanners supplied by different manufacturers. These protocols have already been adopted for MRI assessments of post-COVID patients in the UK as part of the COVID-CNS consortium.

Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies

BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable. AimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing. Method59,482 participants in 12 UK longitudinal adult population studies with data collected prior to and during the COVID-19 pandemic. Within each study we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies. ResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption. ConclusionPeople experiencing psychological distress pre-pandemic have been more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening the existing inequalities in mental health.

Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK)

BackgroundRisk factors for severe COVID-19 include older age, male sex, obesity, Black or Asian ethnicity and underlying medical conditions. Whether these factors also influence susceptibility to developing COVID-19 is uncertain. MethodsWe undertook a prospective, population-based cohort study (COVIDENCE UK) from 1st May 2020 to 5th February 2021. Baseline information on potential risk factors was captured by online questionnaire. Monthly follow-up questionnaires captured incident COVID-19. We used logistic regression models to estimate multivariable-adjusted odds ratios (aORs) for associations between potential risk factors and risk of COVID-19. FindingsWe recorded 446 incident cases of COVID-19 in 15,227 participants (2.9%). Increased risk of developing COVID-19 was independently associated with Asian/Asian British vs. White ethnicity (aOR 2.31, 95% CI 1.35-3.95), household overcrowding (aOR per additional 0.5 people/bedroom 1.26, 1.11-1.43), any vs. no visits to/from other households in previous week (aOR 1.33, 1.07-1.64), number of visits to indoor public places (aOR per extra visit per week 1.05, 1.01-1.09), frontline occupation excluding health/social care vs. no frontline occupation (aOR 1.49, 1.12-1.98), and raised body mass index (BMI) (aOR 1.51 [1.20-1.90] for BMI 25.0-30.0 kg/m2 and 1.38 [1.05-1.82] for BMI >30.0 kg/m2 vs. BMI <25.0 kg/m2). Atopic disease was independently associated with decreased risk (aOR 0.76, 0.59-0.98). No independent associations were seen for age, sex, other medical conditions, diet, or micronutrient supplement use. InterpretationAfter rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased risk of developing COVID-19, while atopic disease was associated with decreased risk. FundingBarts Charity, Health Data Research UK

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19

The COVID-19 pandemic death toll now surpasses two million individuals and there is a need for early identification of individuals at increased risk of mortality. Host genetic variation partially drives the immune and biochemical responses to COVID-19 that lead to risk of mortality. We identify and prioritise blood proteins and biomarkers that may indicate increased risk for severe COVID-19, via a proteome Mendelian randomization approach by collecting genome-wide association study (GWAS) summary statistics for >4,000 blood proteins. After multiple testing correction, troponin I3, cardiac type (TNNI3) had the strongest effect (odds ratio (O.R.) of 6.86 per standard deviation increase in protein level), with proteinase 3 (PRTN3) (O.R.=2.48), major histocompatibility complex, class II, DQ alpha 2 (HLA-DQA2) (O.R.=2.29), the C4A-C4B heterodimer (O.R.=1.76) and low-density lipoprotein receptor-related protein associated protein 1 (LRPAP1) (O.R.=1.73) also being associated with higher odds of severe COVID-19. Conversely, major histocompatibility complex class I polypeptide-related sequence A (MHC1A) (O.R.=0.6) and natural cytotoxicity triggering receptor 3 (NCR3) (O.R.=0.46) were associated with lower odds. These proteins are involved in heart muscle contraction, natural killer and antigen presenting cells, and the major histocompatibility complex. Based on these findings, it may be possible to better predict which patients may develop severe COVID-19 and to design better treatments targeting the implicated mechanisms.