Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app

Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of ’urban hotspots’. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors

Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app

Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of ’urban hotspots’. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors

Characterizing blood metabolomics profiles associated with self-reported food intakes in female twins

Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult female twins from the TwinsUK cohort. For each metabolite, linear regression analysis was undertaken in the discovery group (excluding MZ twin pairs discordant [≥1 SD apart] for food group intake) with each food group as a predictor adjusting for age, batch effects, BMI, family relatedness and multiple testing (1.17x10-6 = 0.05/[71 food groups x 601 detected metabolites]). Significant results were then replicated (non-targeted: P<0.05; targeted: same direction) in the MZ discordant twin group and results from both analyses meta-analyzed. We identified and replicated 180 significant associations with 39 food groups (P<1.17x10-6), overall consisting of 106 different metabolites (74 known and 32 unknown), including 73 novel associations. In particular we identified trans-4-hydroxyproline as a potential marker of red meat intake (0.075[0.009]; P = 1.08x10-17), ergothioneine as a marker of mushroom consumption (0.181[0.019]; P = 5.93x10-22), and three potential markers of fruit consumption (top association: apple and pears): including metabolites derived from gut bacterial transformation of phenolic compounds, 3-phenylpropionate (0.024[0.004]; P = 1.24x10-8) and indolepropionate (0.026[0.004]; P = 2.39x10-9), and threitol (0.033[0.003]; P = 1.69x10-21). With the largest nutritional metabolomics dataset to date, we have identified 73 novel candidate biomarkers of food intake for potential use in nutritional epidemiological studies. We compiled our findings into the DietMetab database (http://www.twinsuk.ac.uk/dietmetab-data/), an online tool to investigate our top associations

Definitive zygosity scores in the peas in the pod questionnaire is a sensitive and accurate assessment of the zygosity of adult twins

Twin researchers face the challenge of accurately determining the zygosity of twins for research. As part of the annual questionnaire between 1999 and 2006, 8,307 twins from the TwinsUK registry were asked to complete five questions (independently from their co-twin) to ascertain their self-perceived zygosity during childhood on up to five separate occasions. This questionnaire is known as the ‘peas in the pod’ questionnaire (PPQ), but there is little evidence of its validation. Answers were scored and classified as monozygotic (MZ), dizygotic (DZ), or unknown zygosity (UZ) and were compared with 4,484 twins with genotyping data who had not been selected for zygosity. Of these, 3,859 individuals (46.5% of those who had a zygosity from PPQ) had zygosity classified by both the PPQ and genotyping. Of the 708 individual twins whose answers meant that they were consistently classed as MZ in the PPQ, 683 (96.5%) were MZ within the genotype data. Of the 945 individual twins consistently classed as DZ within questionnaire, 936 (99.0%) were DZ in the genotype data. Where both twins scored MZ consistently across multiple questionnaires, 99.6% were MZ on genotyping, 99.7% were DZ on genotyping if both twins consistently scored DZ. However, for the initial questionnaire, 88.6% of those scoring as MZ were genotypically MZ and 98.7% DZ. For twin pairs where both scored UZ, 94.7% were DZ. Using the PPQ on a single occasion provided a definitive classification of whether the twin was MZ or DZ with an overall accuracy of 86.9%, increasing to 97.9% when there was a consistent classification of zygosity across multiple questionnaires. This study has shown that the PPQ questionnaire is an excellent proxy indicator of zygosity in the absence of genotyping information.</jats:p

Pathways represented by associated metabolites for general food groups.

<p>Fig 2 shows a stacked histogram of the number of associated metabolites representing each superpathway (a) and subpathway (b) by general food group intake.</p