Abstract 820: NSAIDs and colorectal cancer risk: Results from genome-wide interaction scans

Nonsteroidal anti-inflammatory drugs (NSAIDs) are consistently shown in epidemiological and clinical studies to exert chemo-preventive effects on colorectal cancer (CRC). Specifically, aspirin binds irreversibly to COX1/2 enzymes, attenuating pro-inflammatory signaling pathways, but it can also exert protective effects via Wnt-β-catenin signaling, circulating inflammatory cytokines, and platelet mediated mechanisms. In this analysis, we conduct genome-wide interaction scans on a large CRC dataset to expand upon previous work and identify novel G x NSAIDs interactions.

We pooled epidemiological and imputed genetic data from 72,667 individuals (41,876 controls, and 30,806 cases) of European descent from 31 studies. Genotypes were imputed to the Haplotype Reference Consortium panel. Regular use of aspirin and combined aspirin/non-aspirin NSAIDs (henceforth termed ‘nsaidsALL') were harmonized across studies and measured as ever/never at reference time. We employed several statistical methods in our GWIS: traditional logistic regression with an interaction term, case-only analyses, joint tests (2df/3df), two-step methods. We also assessed interactions between CRC polygenic risk scores (PRS) and aspirin/nsaidsALL on additive and multiplicative scales. PRS was modeled categorically (quartiles) and continuously as a per 1 SD increase from the minimum value. All models were adjusted for age, sex, study, and ancestry.

Aspirin (OR=0.789, 95% CI=0.753-0.826) and nsaidsALL (OR=0.760; 95% CI=0.726-0.793) use were inversely associated with CRC risk. Using standard logistic regression, we identified a genome-wide significant interaction between rs72833769 (chromosome 6 intergenic region upstream of PHACTR1) and both aspirin and nsaidsALL (p = 4.0e-09, p = 1.3e-08, respectively). An additional genome-wide interaction locus was identified for nsaidsALL only, on rs35118762 (p = 2.2e-08), located in the Major Histocompatibility Complex region and in close linkage with a previously identified marginal GWAS hit (rs9271695). We identified another region of interest using two-step methods tagged by SNP rs350047 (aspirin pgxe = 1.1e-05, nsaidsALL pgxe = 4.4e-05). This region also coincides with another previously identified marginal GWAS hit (rs12514517), and is notable for being upstream of PTGER4, an important receptor for aspirin mediated inflammatory response signaling. For interactions with PRS, we observed a significant super-additive interaction for both aspirin (RERI=0.102, p=7e-08) and nsaidsALL use (RERI=0.132, p=4.6e-12). Results were similar when modeling PRS categorically. There were no multiplicative scale interactions between PRS and any NSAID use.

GWIS for aspirin and nsaidsALL use identified several loci of interest that warrant follow-up in functional studies.

Citation Format: Andre E. Kim, David A. Drew, Yi Lin, Conghui Qu, John P. Morrison, Stephanie Bien, Victor Moreno, Graham Casey, Ulrike Peters, Andrew T. Chan, W James Gauderman. NSAIDs and colorectal cancer risk: Results from genome-wide interaction scans [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 820.

Association of social distancing and face mask use with risk of COVID-19

Given the continued burden of COVID-19 worldwide, there is a high unmet need for data on the effect of social distancing and face mask use to mitigate the risk of COVID-19. We examined the association of community-level social distancing measures and individual face mask use with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported 'always' use of face mask was associated with a 62% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. Despite mass vaccination campaigns in many parts of the world, continued efforts at social distancing and face mask use remain critically important in reducing the spread of COVID-19.

Dietary fiber intake, the gut microbiome, and chronic systemic inflammation in a cohort of adult men

BACKGROUND

A higher intake of dietary fiber is associated with a decreased risk of chronic inflammatory diseases such as cardiovascular disease and inflammatory bowel disease. This may function in part due to abrogation of chronic systemic inflammation induced by factors such as dysbiotic gut communities. Data regarding the detailed influences of long-term and recent intake of differing dietary fiber sources on the human gut microbiome are lacking.

METHODS

In a cohort of 307 generally healthy men, we examined gut microbiomes, profiled by shotgun metagenomic and metatranscriptomic sequencing, and long-term and recent dietary fiber intake in relation to plasma levels of C-reactive protein (CRP), an established biomarker for chronic inflammation. Data were analyzed using multivariate linear mixed models.

RESULTS

We found that inflammation-associated gut microbial configurations corresponded with higher CRP levels. A greater intake of dietary fiber was associated with shifts in gut microbiome composition, particularly Clostridiales, and their potential for carbohydrate utilization via polysaccharide degradation. This was particularly true for fruit fiber sources (i.e., pectin). Most striking, fiber intake was associated with significantly greater CRP reduction in individuals without substantial Prevotella copri carriage in the gut, whereas those with P. copri carriage maintained stable CRP levels regardless of fiber intake.

CONCLUSIONS

Our findings offer human evidence supporting a fiber-gut microbiota interaction, as well as a potential specific mechanism by which gut-mediated systemic inflammation may be mitigated.

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

BACKGROUND

The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility.

METHODS

We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates.

FINDINGS

From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6-0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56-0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38-0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02-1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant.

INTERPRETATION

The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant.

FUNDING

Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

BACKGROUND

The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility.

METHODS

We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, R_t, for the two incidence estimates.

FINDINGS

From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6-0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56-0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38-0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the R_t of B.1.1.7 by a factor of 1·35 (95% CI 1·02-1·69) relative to pre-existing variants. However, R_t fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant.

INTERPRETATION

The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant.

FUNDING

Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.

Modest effects of dietary supplements during the COVID-19 pandemic: insights from 445 850 users of the COVID-19 Symptom Study app

OBJECTIVES

Dietary supplements may ameliorate SARS-CoV-2 infection, although scientific evidence to support such a role is lacking. We investigated whether users of the COVID-19 Symptom Study app who regularly took dietary supplements were less likely to test positive for SARS-CoV-2 infection.

DESIGN

App-based community survey.

SETTING

445 850 subscribers of an app that was launched to enable self-reported information related to SARS-CoV-2 infection for use in the general population in the UK (n=372 720), the USA (n=45 757) and Sweden (n=27 373).

MAIN EXPOSURE

Self-reported regular dietary supplement usage (constant use during previous 3 months) in the first waves of the pandemic up to 31 July 2020.

MAIN OUTCOME MEASURES

SARS-CoV-2 infection confirmed by viral RNA reverse transcriptase PCR test or serology test before 31 July 2020.

RESULTS

In 372 720 UK participants (175 652 supplement users and 197 068 non-users), those taking probiotics, omega-3 fatty acids, multivitamins or vitamin D had a lower risk of SARS-CoV-2 infection by 14% (95% CI (8% to 19%)), 12% (95% CI (8% to 16%)), 13% (95% CI (10% to 16%)) and 9% (95% CI (6% to 12%)), respectively, after adjusting for potential confounders. No effect was observed for those taking vitamin C, zinc or garlic supplements. On stratification by sex, age and body mass index (BMI), the protective associations in individuals taking probiotics, omega-3 fatty acids, multivitamins and vitamin D were observed in females across all ages and BMI groups, but were not seen in men. The same overall pattern of association was observed in both the US and Swedish cohorts.

CONCLUSION

In women, we observed a modest but significant association between use of probiotics, omega-3 fatty acid, multivitamin or vitamin D supplements and lower risk of testing positive for SARS-CoV-2. We found no clear benefits for men nor any effect of vitamin C, garlic or zinc. Randomised controlled trials are required to confirm these observational findings before any therapeutic recommendations can be made.

Aspirin Modulation of the Colorectal Cancer-Associated Microbe Fusobacterium nucleatum

Aspirin is a chemopreventive agent for colorectal adenoma and cancer (CRC) that, like many drugs inclusive of chemotherapeutics, has been investigated for its effects on bacterial growth and virulence gene expression. Given the evolving recognition of the roles for bacteria in CRC, in this work, we investigate the effects of aspirin with a focus on one oncomicrobe-Fusobacterium nucleatum We show that aspirin and its primary metabolite salicylic acid alter F. nucleatum strain Fn7-1 growth in culture and that aspirin can effectively kill both actively growing and stationary Fn7-1. We also demonstrate that, at levels that do not inhibit growth, aspirin influences Fn7-1 gene expression. To assess whether aspirin modulation of F. nucleatum may be relevant in vivo, we use the ApcMin/+ mouse intestinal tumor model in which Fn7-1 is orally inoculated daily to reveal that aspirin-supplemented chow is sufficient to inhibit F. nucleatum-potentiated colonic tumorigenesis. We expand our characterization of aspirin sensitivity across other F. nucleatum strains, including those isolated from human CRC tissues, as well as other CRC-associated microbes, enterotoxigenic Bacteroides fragilis, and colibactin-producing Escherichia coli Finally, we determine that individuals who use aspirin daily have lower fusobacterial abundance in colon adenoma tissues, as determined by quantitative PCR performed on adenoma DNA. Together, our data support that aspirin has direct antibiotic activity against F. nucleatum strains and suggest that consideration of the potential effects of aspirin on the microbiome holds promise in optimizing risk-benefit assessments for use of aspirin in CRC prevention and management.IMPORTANCE There is an increasing understanding of the clinical correlations and potential mechanistic roles of specific members of the gut and tumoral microbiota in colorectal cancer (CRC) initiation, progression, and survival. However, we have yet to parlay this knowledge into better CRC outcomes through microbially informed diagnostic, preventive, or therapeutic approaches. Here, we demonstrate that aspirin, an established CRC chemopreventive, exhibits specific effects on the CRC-associated Fusobacterium nucleatum in culture, an animal model of intestinal tumorigenesis, and in human colonic adenoma tissues. Our work proposes a potential role for aspirin in influencing CRC-associated bacteria to prevent colorectal adenomas and cancer, beyond aspirin's canonical anti-inflammatory role targeting host tissues. Future research, such as studies investigating the effects of aspirin on fusobacterial load in patients, will help further elucidate the prospect of using aspirin to modulate F. nucleatumin vivo for improving CRC outcomes.

Postprandial glycaemic dips predict appetite and energy intake in healthy individuals

Understanding how to modulate appetite in humans is key to developing successful weight loss interventions. Here, we showed that postprandial glucose dips 2-3 h after a meal are a better predictor of postprandial self-reported hunger and subsequent energy intake than peak glucose at 0-2 h and glucose incremental area under the blood glucose curve at 0-2 h. We explore the links among postprandial glucose, appetite and subsequent energy intake in 1,070 participants from a UK exploratory and US validation cohort, who consumed 8,624 standardized meals followed by 71,715 ad libitum meals, using continuous glucose monitors to record postprandial glycaemia. For participants eating each of the standardized meals, the average postprandial glucose dip at 2-3 h relative to baseline level predicted an increase in hunger at 2-3 h (r = 0.16, P < 0.001), shorter time until next meal (r = -0.14, P < 0.001), greater energy intake at 3-4 h (r = 0.19, P < 0.001) and greater energy intake at 24 h (r = 0.27, P < 0.001). Results were directionally consistent in the US validation cohort. These data provide a quantitative assessment of the relevance of postprandial glycaemia in appetite and energy intake modulation.

Attributes and predictors of long COVID

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called '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 analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app¹. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.

Aspirin Use and Risk of Colorectal Cancer Among Older Adults

Importance

Although aspirin is recommended for the prevention of colorectal cancer (CRC) among adults aged 50 to 59 years, recent data from a randomized clinical trial suggest a lack of benefit and even possible harm among older adults.

Objective

To examine the association between aspirin use and the risk of incident CRC among older adults.

Design, Setting, and Participants

A pooled analysis was conducted of 2 large US cohort studies, the Nurses' Health Study (June 1, 1980-June 30, 2014) and Health Professionals Follow-up Study (January 1, 1986-January 31, 2014). A total of 94 540 participants aged 70 years or older were included and followed up to June 30, 2014, for women or January 31, 2014, for men. Participants with a diagnosis of any cancer, except nonmelanoma skin cancer, or inflammatory bowel disease were excluded. Statistical analyses were conducted from December 2019 to October 2020.

Main Outcomes and Measures

Cox proportional hazards models were used to calculate multivariable adjusted hazard ratios (HRs) and 95% CIs for incident CRC.

Results

Among the 94 540 participants (mean [SD] age, 76.4 [4.9] years for women, 77.7 [5.6] years for men; 67 223 women [71.1%]; 65 259 White women [97.1%], 24 915 White men [96.0%]) aged 70 years or older, 1431 incident cases of CRC were documented over 996 463 person-years of follow-up. After adjustment for other risk factors, regular use of aspirin was associated with a significantly lower risk of CRC at or after age 70 years compared with nonregular use (HR, 0.80; 95% CI, 0.72-0.90). However, the inverse association was evident only among aspirin users who initiated aspirin use before age 70 years (HR, 0.80; 95% CI, 0.67-0.95). In contrast, initiating aspirin use at or after 70 years was not significantly associated with a lower risk of CRC (HR, 0.92; 95% CI, 0.76-1.11).

Conclusions and Relevance

Initiating aspirin at an older age was not associated with a lower risk of CRC in this pooled analysis of 2 cohort studies. In contrast, those who used aspirin before age 70 years and continued into their 70s or later had a reduced risk of CRC.

A Combined Proteomics and Mendelian Randomization Approach to Investigate the Effects of Aspirin-Targeted Proteins on Colorectal Cancer

BACKGROUND

Evidence for aspirin's chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk.

METHODS

Human colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labeling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N = 3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N = 31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls).

RESULTS

Altered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2, and ARFIP2 expression, and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR: 1.08, 95% CI, 1.03-1.13; OR: 3.33, 95% CI, 2.46-4.50; and OR: 1.15, 95% CI, 1.02-1.29, respectively).

CONCLUSIONS

MCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation, indicating a possible role in aspirin's reduction of metastasis.

IMPACT

Our approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

Racial and ethnic differences in COVID-19 vaccine hesitancy and uptake

BACKGROUND

Racial and ethnic minorities have been disproportionately impacted by COVID-19. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy and limited access may result in disparities in uptake.

METHODS

We performed a cohort study among U.S. and U.K. participants in the smartphone-based COVID Symptom Study (March 24, 2020-February 16, 2021). We used logistic regression to estimate odds ratios (ORs) of COVID-19 vaccine hesitancy (unsure/not willing) and receipt.

RESULTS

In the U.S. ( n =87,388), compared to White non-Hispanic participants, the multivariable ORs of vaccine hesitancy were 3.15 (95% CI: 2.86 to 3.47) for Black participants, 1.42 (1.28 to 1.58) for Hispanic participants, 1.34 (1.18 to 1.52) for Asian participants, and 2.02 (1.70 to 2.39) for participants reporting more than one race/other. In the U.K. ( n =1,254,294), racial and ethnic minorities had similarly elevated hesitancy: compared to White participants, their corresponding ORs were 2.84 (95% CI: 2.69 to 2.99) for Black participants, 1.66 (1.57 to 1.76) for South Asian participants, 1.84 (1.70 to 1.98) for Middle East/East Asian participants, and 1.48 (1.39 to 1.57) for participants reporting more than one race/other. Among U.S. participants, the OR of vaccine receipt was 0.71 (0.64 to 0.79) for Black participants, a disparity that persisted among individuals who specifically endorsed a willingness to obtain a vaccine. In contrast, disparities in uptake were not observed in the U.K.

CONCLUSIONS

COVID-19 vaccine hesitancy was greater among racial and ethnic minorities, and Black participants living in the U.S. were less likely to receive a vaccine than White participants. Lower uptake among Black participants in the U.S. during the initial vaccine rollout is attributable to both hesitancy and disparities in access.

Optimal symptom combinations to aid COVID-19 case identification: Analysis from a community-based, prospective, observational cohort

Objectives

Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.

Methods

UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.

Findings

UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.

Interpretation

We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.

Optimal symptom combinations to aid COVID-19 case identification: analysis from a community-based, prospective, observational cohort

OBJECTIVES

Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.

METHODS

UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.

FINDINGS

UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.

INTERPRETATION

We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.

Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study

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.

Cancer and Risk of COVID-19 Through a General Community Survey

Individuals with cancer may be at high risk for coronavirus disease 2019 (COVID-19) and adverse outcomes. However, evidence from large population-based studies examining whether cancer and cancer-related therapy exacerbates the risk of COVID-19 infection is still limited. Data were collected from the COVID Symptom Study smartphone application since March 29 through May 8, 2020. Among 23,266 participants with cancer and 1,784,293 without cancer, we documented 10,404 reports of a positive COVID-19 test. Compared with participants without cancer, those living with cancer had a 60% increased risk of a positive COVID-19 test. Among patients with cancer, current treatment with chemotherapy or immunotherapy was associated with a 2.2-fold increased risk of a positive test. The association between cancer and COVID-19 infection was stronger among participants >65 years and males. Future studies are needed to identify subgroups by tumor types and treatment regimens who are particularly at risk for COVID-19 infection and adverse outcomes.

Fibroblast growth factor 23 and cognitive impairment: The health, aging, and body composition study

BACKGROUND

Concentrations of fibroblast growth factor 23 (FGF-23), a hormone that regulates phosphorus and vitamin D metabolism, increase as kidney function declines. Excess fibroblast growth factor 23 may impact brain function through promotion of vascular disease or through direct effects on neuronal tissue.

METHODS

In the Healthy Aging and Body Composition Study, a longitudinal observational cohort of well-functioning older adults, intact serum FGF-23 was assayed in 2,738 individuals. Cognitive function was assessed at baseline and longitudinally at years 3, 5, and 8 by administration of the Modified Mini Mental State Examination (3MSE), a test of global cognitive function, and the Digit Symbol Substitution Test (DSST), a test primarily of executive function. The associations between FGF-23 and baseline cognitive function and incident cognitive impairment were evaluated using logistic and Poisson regression respectively, and were adjusted for demographics, baseline estimated glomerular filtration rate (eGFR), urine albumin/creatinine ratio, comorbidity, and other measures of mineral metabolism including soluble klotho.

RESULTS

The mean (SD) age was 74(3) years, with 51% female, and 39% black. The median (25th, 75th) FGF-23 concentration was 47 pg/mL (37, 60). Three hundred ninety-two individuals had prevalent cognitive impairment by the 3MSE and 461 by the DSST. There was no observed association between FGF-23 and baseline cognitive function for either cognitive test. There were 277 persons with incident cognitive impairment by 3MSE, and 333 persons with incident cognitive impairment by DSST. In fully adjusted models, each two-fold higher concentration of baseline FGF-23 was not associated with incident cognitive impairment by the 3MSE (IRR = 1.02[0.88, 1.19] fully adjusted model) or by the DSST (IRR = 0.98 [0.84, 1.15]. We saw no difference when analyses were stratified by eGFR greater than or less than 60 ml/min/1.73m2.

CONCLUSION

Intact FGF-23 was not associated with baseline cognitive function or incident cognitive impairment in this cohort well-functioning older adults.

Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study

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 2.8 million app users in England provided 120 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-1 studies. On 28 September 2020 we estimated 15,841 (95% CI 14,023-17,885) daily cases, a prevalence of 0.53% (95% CI 0.45-0.60), and R(t) of 1.17 (95% credible interval 1.15-1.19) in England. On a geographically granular level, on 28 September 2020 we detected 15 of the 20 regions with highest incidence according to Government test data, with indications that our method may be able to detect rapid case increases in regions where Government testing provision is more limited.

INTERPRETATION

Self-reported data from mobile applications can provide an agile resource to inform policymakers during 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.

Association of social distancing and masking with risk of COVID-19

Given the continued burden of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) disease (COVID-19) across the U.S., there is a high unmet need for data to inform decision-making regarding social distancing and universal masking. We examined the association of community-level social distancing measures and individual masking with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported masking was associated with a 63% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. In the current environment of relaxed social distancing mandates and practices, universal masking may be particularly important in mitigating risk of infection.

FGF23 and Cause-Specific Mortality in Community-Living Individuals-The Health, Aging, and Body Composition Study

OBJECTIVES

Fibroblast growth factor (FGF)-23 is a key regulator of mineral metabolism and has been linked with left ventricular hypertrophy in animal models. Most existing epidemiologic studies evaluated a C-terminal FGF23 assay which measures both the intact (active) hormone and inactive fragments. The relationship of intact FGF23 with cause-specific mortality is unknown.

DESIGN

Prospective analyses of data from Health, Aging, & Body Composition (HABC) study.

SETTING

Community-living adults aged 70 to 79 years with longitudinal follow up.