Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study (preprint)

Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. We examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration. We found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence. Findings: highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.

COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: two prospective observational cohort studies (preprint)

Background The Delta (B.1.617.2) variant became the predominant UK circulating SARS-CoV-2 strain in May 2021. How Delta infection compares with previous variants is unknown. Methods This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. Findings 3,581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta vs. Alpha infection (including fever, sore throat and headache) and vice versa (dyspnoea). Symptom burden in the first week was higher with Delta vs. Alpha infection; however, the odds of any given symptom lasting [≥]7 days was either lower or unchanged. Illness duration [≥]28 days was lower with Delta vs. Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.47) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly (69-84%) reduced risk of Delta infection. Interpretation COVID-19 from Delta or Alpha infections is clinically similar. The Delta variant is more transmissible than Alpha; however, current vaccines show good efficacy against disease. Funding UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, Alzheimer's Society, and ZOE Limited.

Disentangling post-vaccination symptoms from early COVID-19 (preprint)

Background Identifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app. Design We conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria. Findings Differentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue). Interpretation Post-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread. Funding Zoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimer’s Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR). Research in context Evidence before this study There are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: “COVID-19” AND “Vaccination” AND (“mobile application” OR “web tool” OR “digital survey” OR “early detection” OR “Self-reported symptoms” OR “side-effects”). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies (“machine learning”) coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services. Added value of this study This study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals. Implications of all the available evidence Our study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated – to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.

Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK (preprint)

The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing. Methods Analysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses. Results Functionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%). Conclusions Long COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.

Post-vaccination SARS-CoV-2 infection: risk factors and illness profile in a prospective, observational community-based case-control study (preprint)

Background: Both BNT162b2 and ChAdOx1 vaccines show good efficacy in clinical trials and real-world data. However, some still contract SARS-CoV-2 post-vaccination. This study identifies risk factors associated with SARS-CoV-2 infection at least 14 days after first vaccination and describes characteristics of post-vaccination illness. Methods: Cases were UK adults reporting post-vaccination SARS-CoV-2 infection between 8th December 2020 and 1st May 2021, reporting on the COVID Symptom Study app. We assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection (vaccinated cases vs. negative-vaccinated controls); and vaccination with illness profile (vaccinated cases vs positive-unvaccinated controls). Findings: Post-vaccination infection risk was substantially higher in older adults with frailty (OR= 2.78, 95% CI [1.98-3.89], p-value<0.0001) and in individuals living in most deprived areas (OR vs. intermediate group=1.22, 95%CI [1.04-1.43], p-value=0.01). Risk was lower in individuals with a healthier diet (OR=0.73, 95%CI [0.62-0.86], p-value<0.0001) and without obesity (OR=0.6, 95% CI [0.44-0.82], p-value=0.001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, 95%CI [0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, 95%CI [0.42-0.61], p-value<0.0001). In the 60+ age group, risk of >28 days illness was lower following vaccination (OR=0.72 , 95%CI [0.51-1.00], p-value=0.05). Most symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, 95%CI [1.05-1.46], p-value=0.01). Interpretation: Our findings highlight reduced symptom burden and duration in those infected post-vaccination. Whilst reassuring, our data should prompt efforts to boost vaccine effectiveness in at-risk populations; moreover, targeted infection control measures will still be appropriate to minimise SARS-CoV-2 infection.

Attributes and predictors of Long-COVID: analysis of COVID cases and their symptoms collected by the Covid Symptoms Study App (preprint)

Reports of "Long-COVID", are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >28 days, 189 (4.5%) for >8 weeks and 95 (2.3%) for >12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increasing age, BMI and female sex. Experiencing more than five symptoms during the first week of illness was associated with Long-COVID, OR=3.53 [2.76;4.50]. Our model to predict long-COVID at 7 days, which gained a ROC-AUC of 76%, was replicated in an independent sample of 2472 antibody positive individuals. This model could be used to identify individuals for clinical trials to reduce long-term symptoms and target education and rehabilitation services.