In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 23, Heft 6, S. 316-321
AbstractSusceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.
In: Kehoe , P G , Turner , N , Howden , B , Jarutyte , L , Clegg , S L , Malone , I B , Barnes , J , Nielsen , C , Sudre , C H , Wilson , A , Thai , N J , Blair , P S , Coulthard , E , Lane , J A , Passmore , P , Taylor , J , Mutsaerts , H-J , Thomas , D L , Fox , N C , Wilkinson , I , Ben-Shlomo , Y & RADAR investigators 2021 , ' Safety and efficacy of losartan for the reduction of brain atrophy in clinically diagnosed Alzheimer's disease (the RADAR trial) : a double-blind, randomised, placebo-controlled, phase 2 trial ' , Lancet Neurology , vol. 20 , no. 11 , pp. 895-906 . https://doi.org/10.1016/S1474-4422(21)00263-5
BACKGROUND: Drugs modifying angiotensin II signalling could reduce Alzheimer's disease pathology, thus decreasing the rate of disease progression. We investigated whether the angiotensin II receptor antagonist losartan, compared with placebo, could reduce brain volume loss, as a measure of disease progression, in clinically diagnosed mild-to-moderate Alzheimer's disease. METHODS: In this double-blind, multicentre, randomised controlled trial, eligible patients aged 55 years or older, previously untreated with angiotensin II drugs and diagnosed (National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria) with mild-to-moderate Alzheimer's disease, and who had capacity to consent, were recruited from 23 UK National Health Service hospital trusts. After undergoing a 4-week, open-label phase of active treatment then washout, participants were randomly assigned (1:1) oral over-encapsulated preparations of either 100 mg losartan (after an initial two-dose titration stage) or matched placebo daily for 12 months. Randomisation, minimised by age and baseline medial temporal lobe atrophy score, was undertaken online or via pin-access service by telephone. Participants, their study companions, and study personnel were masked to group assignment. The primary outcome, analysed by the intention-to-treat principle (ie, participants analysed in the group to which they were randomised, without imputation for missing data), was change in whole brain volume between baseline and 12 months, measured using volumetric MRI and determined by boundary shift interval (BSI) analysis. The trial is registered with the International Standard Randomised Controlled Trial Register (ISRCTN93682878) and the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT 2012-003641-15), and is completed. FINDINGS: Between July 22, 2014, and May 17, 2018, 261 participants entered the open-label phase. 211 were randomly assigned losartan (n=105) or placebo (n=106). Of 197 (93%) participants who completed the study, 171 (81%) had complete primary outcome data. The mean brain volume (BSI) reduction was 19·1 mL (SD 10·3) in the losartan group and 20·0 mL (10·8) in the placebo group. The difference in total volume reduction between groups was -2·29 mL (95% CI -6·46 to 0·89; p=0·14). The number of adverse events was low (22 in the losartan group and 20 in the placebo group) with no differences between treatment groups. There was one treatment-related death per treatment group. INTERPRETATION: 12 months of treatment with losartan was well tolerated but was not effective in reducing the rate of brain atrophy in individuals with clinically diagnosed mild-to-moderate Alzheimer's disease. Further research is needed to assess the potential therapeutic benefit from earlier treatment in patients with milder cognitive impairment or from longer treatment periods. FUNDING: Efficacy and Mechanism Evaluation Programme (UK Medical Research Council and National Institute for Health Research).
BACKGROUND: In children, SARS-CoV-2 infection is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, one of the largest UK citizen participatory epidemiological studies to date. METHODS: In this prospective cohort study, data from UK school-aged children (age 5-17 years) were reported by an adult proxy. Participants were voluntary, and used a mobile application (app) launched jointly by Zoe Limited and King's College London. Illness duration and symptom prevalence, duration, and burden were analysed for children testing positive for SARS-CoV-2 for whom illness duration could be determined, and were assessed overall and for younger (age 5-11 years) and older (age 12-17 years) groups. Children with longer than 1 week between symptomatic reports on the app were excluded from analysis. Data from symptomatic children testing negative for SARS-CoV-2, matched 1:1 for age, gender, and week of testing, were also assessed. FINDINGS: 258 790 children aged 5-17 years were reported by an adult proxy between March 24, 2020, and Feb 22, 2021, of whom 75 529 had valid test results for SARS-CoV-2. 1734 children (588 younger and 1146 older children) had a positive SARS-CoV-2 test result and calculable illness duration within the study timeframe (illness onset between Sept 1, 2020, and Jan 24, 2021). The most common symptoms were headache (1079 [62·2%] of 1734 children), and fatigue (954 [55·0%] of 1734 children). Median illness duration was 6 days (IQR 3-11) versus 3 days (2-7) in children testing negative, and was positively associated with age (Spearman's rank-order rs 0·19, p<0·0001). Median illness duration was longer for older children (7 days, IQR 3-12) than younger children (5 days, 2-9). 77 (4·4%) of 1734 children had illness duration of at least 28 days, more commonly in older than younger children (59 [5·1%] of 1146 older children vs 18 [3·1%] of 588 younger children; p=0·046). The commonest symptoms experienced by these children during the first 4 weeks of illness were fatigue (65 [84·4%] of 77), headache (60 [77·9%] of 77), and anosmia (60 [77·9%] of 77); however, after day 28 the symptom burden was low (median 2 symptoms, IQR 1-4) compared with the first week of illness (median 6 symptoms, 4-8). Only 25 (1·8%) of 1379 children experienced symptoms for at least 56 days. Few children (15 children, 0·9%) in the negatively tested cohort had symptoms for at least 28 days; however, these children experienced greater symptom burden throughout their illness (9 symptoms, IQR 7·7-11·0 vs 8, 6-9) and after day 28 (5 symptoms, IQR 1·5-6·5 vs 2, 1-4) than did children who tested positive for SARS-CoV-2. INTERPRETATION: Although COVID-19 in children is usually of short duration with low symptom burden, some children with COVID-19 experience prolonged illness duration. Reassuringly, symptom burden in these children did not increase with time, and most recovered by day 56. Some children who tested negative for SARS-CoV-2 also had persistent and burdensome illness. A holistic approach for all children with persistent illness during the pandemic is appropriate. FUNDING: Zoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, and Alzheimer's Society.
BACKGROUND: Drugs modifying angiotensin II signalling could reduce Alzheimer's disease pathology, thus decreasing the rate of disease progression. We investigated whether the angiotensin II receptor antagonist losartan, compared with placebo, could reduce brain volume loss, as a measure of disease progression, in clinically diagnosed mild-to-moderate Alzheimer's disease. METHODS: In this double-blind, multicentre, randomised controlled trial, eligible patients aged 55 years or older, previously untreated with angiotensin II drugs and diagnosed (National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria) with mild-to-moderate Alzheimer's disease, and who had capacity to consent, were recruited from 23 UK National Health Service hospital trusts. After undergoing a 4-week, open-label phase of active treatment then washout, participants were randomly assigned (1:1) oral over-encapsulated preparations of either 100 mg losartan (after an initial two-dose titration stage) or matched placebo daily for 12 months. Randomisation, minimised by age and baseline medial temporal lobe atrophy score, was undertaken online or via pin-access service by telephone. Participants, their study companions, and study personnel were masked to group assignment. The primary outcome, analysed by the intention-to-treat principle (ie, participants analysed in the group to which they were randomised, without imputation for missing data), was change in whole brain volume between baseline and 12 months, measured using volumetric MRI and determined by boundary shift interval (BSI) analysis. The trial is registered with the International Standard Randomised Controlled Trial Register (ISRCTN93682878) and the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT 2012–003641–15), and is completed. FINDINGS: Between July 22, 2014, and May 17, 2018, 261 participants entered the open-label phase. 211 were randomly assigned losartan (n=105) or ...
In: Varsavsky , T , Graham , M S , Canas , L S , Ganesh , S , Capedevilla Pujol , J , Sudre , C H , Murray , B , Modat , M , Cardoso , M J , Astley , C M , Drew , D A , Nguyen , L H , Fall , T , Gomez , M F , Franks , P W , Chan , A T , Davies , R , Wolf , J , Steves , C J , Spector , T D & Ourselin , S 2021 , ' Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application : a prospective, observational study ' , The Lancet Public Health , vol. 6 , no. 1 , pp. E21-E29 . https://doi.org/10.1016/S2468-2667(20)30269-3
Background: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. Methods: In this prospective, observational study, we did modelling using longitudinal, self-reported data from users of the COVID Symptom Study app in England between March 24, and Sept 29, 2020. Beginning on April 28, in England, the Department of Health and Social Care allocated RT-PCR tests for COVID-19 to app users who logged themselves as healthy at least once in 9 days and then reported any symptom. We calculated incidence of COVID-19 using the invited swab (RT-PCR) tests reported in the app, and we estimated prevalence using a symptom-based method (using logistic regression) and a method based on both symptoms and swab test results. We used incidence rates to estimate the effective reproduction number, R(t), modelling the system as a Poisson process and using Markov Chain Monte-Carlo. We used three datasets to validate our models: the Office for National Statistics (ONS) Community Infection Survey, the Real-time Assessment of Community Transmission (REACT-1) study, and UK Government testing data. We used geographically granular estimates to highlight regions with rapidly increasing case numbers, or hotspots. Findings: From March 24 to Sept 29, 2020, a total of 2 873 726 users living in England signed up to use the app, of whom 2 842 732 (98·9%) provided valid age information and daily assessments. These users provided a total of 120 192 306 daily reports of their symptoms, and recorded the results of 169 682 invited swab tests. On a national level, our estimates of incidence and prevalence showed a similar sensitivity to changes to those reported in the ONS and REACT-1 studies. On Sept 28, 2020, we estimated an incidence of 15 841 (95% CI 14 023–17 885) daily cases, a prevalence of 0·53% (0·45–0·60), and R(t) of 1·17 (1·15–1·19) in England. On a geographically granular level, on Sept 28, 2020, we detected 15 (75%) of the 20 regions with highest incidence according to government test data. Interpretation: Our method could help to detect rapid case increases in regions where government testing provision is lower. Self-reported data from mobile applications can provide an agile resource to inform policy makers during a quickly moving pandemic, serving as a complementary resource to more traditional instruments for disease surveillance. Funding: Zoe Global, 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.
BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: In this prospective, observational study, we did modelling using longitudinal, self-reported data from users of the COVID Symptom Study app in England between March 24, and Sept 29, 2020. Beginning on April 28, in England, the Department of Health and Social Care allocated RT-PCR tests for COVID-19 to app users who logged themselves as healthy at least once in 9 days and then reported any symptom. We calculated incidence of COVID-19 using the invited swab (RT-PCR) tests reported in the app, and we estimated prevalence using a symptom-based method (using logistic regression) and a method based on both symptoms and swab test results. We used incidence rates to estimate the effective reproduction number, R(t), modelling the system as a Poisson process and using Markov Chain Monte-Carlo. We used three datasets to validate our models: the Office for National Statistics (ONS) Community Infection Survey, the Real-time Assessment of Community Transmission (REACT-1) study, and UK Government testing data. We used geographically granular estimates to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: From March 24 to Sept 29, 2020, a total of 2 873 726 users living in England signed up to use the app, of whom 2 842 732 (98·9%) provided valid age information and daily assessments. These users provided a total of 120 192 306 daily reports of their symptoms, and recorded the results of 169 682 invited swab tests. On a national level, our estimates of incidence and prevalence showed a similar sensitivity to changes to those reported in the ONS and REACT-1 studies. On Sept 28, 2020, we estimated an incidence of 15 841 (95% CI 14 023–17 885) daily cases, a prevalence of 0·53% (0·45–0·60), and R(t) of 1·17 (1·15–1·19) in England. On a geographically granular level, on Sept ...
BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: We performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence and effective reproduction number. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: More than 2.6 million app users in England provided 115 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence showed similar sensitivity to changes as two national community surveys: the ONS and REACT studies. On a geographically granular level, our estimates were able to highlight regions before they were subject to local government lockdowns. Between 12 May and 29 September we were able to flag between 35–80% of regions appearing in the Government's hotspot list. INTERPRETATION: Self-reported data from mobile applications can provide a cost-effective and agile resource to inform a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance. FUNDING: Zoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimer's Society.