A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who ...reported loss of smell and taste was higher in those with a positive test result (4,668 of 7,178 individuals; 65.03%) than in those with a negative test result (2,436 of 11,223 participants; 21.71%) (odds ratio = 6.74; 95% confidence interval = 6.31-7.21). A model combining symptoms to predict probable infection was applied to the data from all app users who reported symptoms (805,753) and predicted that 140,312 (17.42%) participants are likely to have COVID-19.
Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United ...Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866.
The Pfizer-BioNTech (BNT162b2) and the Oxford-AstraZeneca (ChAdOx1 nCoV-19) COVID-19 vaccines have shown excellent safety and efficacy in phase 3 trials. We aimed to investigate the safety and ...effectiveness of these vaccines in a UK community setting.
In this prospective observational study, we examined the proportion and probability of self-reported systemic and local side-effects within 8 days of vaccination in individuals using the COVID Symptom Study app who received one or two doses of the BNT162b2 vaccine or one dose of the ChAdOx1 nCoV-19 vaccine. We also compared infection rates in a subset of vaccinated individuals subsequently tested for SARS-CoV-2 with PCR or lateral flow tests with infection rates in unvaccinated controls. All analyses were adjusted by age (≤55 years vs >55 years), sex, health-care worker status (binary variable), obesity (BMI <30 kg/m2vs ≥30 kg/m2), and comorbidities (binary variable, with or without comorbidities).
Between Dec 8, and March 10, 2021, 627 383 individuals reported being vaccinated with 655 590 doses: 282 103 received one dose of BNT162b2, of whom 28 207 received a second dose, and 345 280 received one dose of ChAdOx1 nCoV-19. Systemic side-effects were reported by 13·5% (38 155 of 282 103) of individuals after the first dose of BNT162b2, by 22·0% (6216 of 28 207) after the second dose of BNT162b2, and by 33·7% (116 473 of 345 280) after the first dose of ChAdOx1 nCoV-19. Local side-effects were reported by 71·9% (150 023 of 208 767) of individuals after the first dose of BNT162b2, by 68·5% (9025 of 13 179) after the second dose of BNT162b2, and by 58·7% (104 282 of 177 655) after the first dose of ChAdOx1 nCoV-19. Systemic side-effects were more common (1·6 times after the first dose of ChAdOx1 nCoV-19 and 2·9 times after the first dose of BNT162b2) among individuals with previous SARS-CoV-2 infection than among those without known past infection. Local effects were similarly higher in individuals previously infected than in those without known past infection (1·4 times after the first dose of ChAdOx1 nCoV-19 and 1·2 times after the first dose of BNT162b2). 3106 of 103 622 vaccinated individuals and 50 340 of 464 356 unvaccinated controls tested positive for SARS-CoV-2 infection. Significant reductions in infection risk were seen starting at 12 days after the first dose, reaching 60% (95% CI 49–68) for ChAdOx1 nCoV-19 and 69% (66–72) for BNT162b2 at 21–44 days and 72% (63–79) for BNT162b2 after 45–59 days.
Systemic and local side-effects after BNT162b2 and ChAdOx1 nCoV-19 vaccination occur at frequencies lower than reported in phase 3 trials. Both vaccines decrease the risk of SARS-CoV-2 infection after 12 days.
ZOE Global, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, UK Medical Research Council, Wellcome Trust, UK Research and Innovation, American Gastroenterological Association.
The human gut microbiome plays a key role in human health
, but 16S characterization lacks quantitative functional annotation
. The fecal metabolome provides a functional readout of microbial ...activity and can be used as an intermediate phenotype mediating host-microbiome interactions
. In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability (H
) = 17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits.
BACKGROUND—The bulk of cardiovascular disease risk is not explained by traditional risk factors. Recent advances in mass spectrometry allow the identification and quantification of hundreds of lipid ...species. Molecular lipid profiling by mass spectrometry may improve cardiovascular risk prediction.
METHODS AND RESULTS—Lipids were extracted from 685 plasma samples of the prospective population-based Bruneck Study (baseline evaluation in 2000). One hundred thirty-five lipid species from 8 different lipid classes were profiled by shotgun lipidomics with the use of a triple-quadrupole mass spectrometer. Levels of individual species of cholesterol esters (CEs), lysophosphatidylcholines, phosphatidylcholines, phosphatidylethanolamines (PEs), sphingomyelins, and triacylglycerols (TAGs) were associated with cardiovascular disease over a 10-year observation period (2000–2010, 90 incident events). Among the lipid species with the strongest predictive value were TAGs and CEs with a low carbon number and double-bond content, including TAG(54:2) and CE(16:1), as well as PE(36:5) (P=5.1×10, 2.2×10, and 2.5×10, respectively). Consideration of these 3 lipid species on top of traditional risk factors resulted in improved risk discrimination and classification for cardiovascular disease (cross-validated ΔC index, 0.0210 95% confidence interval, 0.0010-0.0422; integrated discrimination improvement, 0.0212 95% confidence interval, 0.0031-0.0406; and continuous net reclassification index, 0.398 95% confidence interval, 0.175-0.619). A similar shift in the plasma fatty acid composition was associated with cardiovascular disease in the UK Twin Registry (n=1453, 45 cases).
CONCLUSIONS—This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease. Molecular lipid species constitute promising new biomarkers that outperform the conventional biochemical measurements of lipid classes currently used in clinics.
We present the results of a GWAS of food liking conducted on 161,625 participants from the UK-Biobank. Liking was assessed over 139 specific foods using a 9-point scale. Genetic correlations coupled ...with structural equation modelling identified a multi-level hierarchical map of food-liking with three main dimensions: "Highly-palatable", "Acquired" and "Low-caloric". The Highly-palatable dimension is genetically uncorrelated from the other two, suggesting that independent processes underlie liking high reward foods. This is confirmed by genetic correlations with MRI brain traits which show with distinct associations. Comparison with the corresponding food consumption traits shows a high genetic correlation, while liking exhibits twice the heritability. GWAS analysis identified 1,401 significant food-liking associations which showed substantial agreement in the direction of effects with 11 independent cohorts. In conclusion, we created a comprehensive map of the genetic determinants and associated neurophysiological factors of food-liking.
The diversity and activity of leukocytes is controlled by genetic and environmental influences to maintain balanced immune responses. However, the relative contribution of environmental compared with ...genetic factors that affect variations in immune traits is unknown. Here we analyse 23,394 immune phenotypes in 497 adult female twins. 76% of these traits show a predominantly heritable influence, whereas 24% are mostly influenced by environment. These data highlight the importance of shared childhood environmental influences such as diet, infections or microbes in shaping immune homeostasis for monocytes, B1 cells, γδ T cells and NKT cells, whereas dendritic cells, B2 cells, CD4
T and CD8
T cells are more influenced by genetics. Although leukocyte subsets are influenced by genetics and environment, adaptive immune traits are more affected by genetics, whereas innate immune traits are more affected by environment.
Despite recent discoveries of genetic variants associated with autoimmunity and infection, genetic control of the human immune system during homeostasis is poorly understood. We undertook a ...comprehensive immunophenotyping approach, analyzing 78,000 immune traits in 669 female twins. From the top 151 heritable traits (up to 96% heritable), we used replicated GWAS to obtain 297 SNP associations at 11 genetic loci, explaining up to 36% of the variation of 19 traits. We found multiple associations with canonical traits of all major immune cell subsets and uncovered insights into genetic control for regulatory T cells. This data set also revealed traits associated with loci known to confer autoimmune susceptibility, providing mechanistic hypotheses linking immune traits with the etiology of disease. Our data establish a bioresource that links genetic control elements associated with normal immune traits to common autoimmune and infectious diseases, providing a shortcut to identifying potential mechanisms of immune-related diseases.
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•Resource of heritabilities and genetic associations of 80,000 immune traits in 669 twins•Genetic associations with immune cell frequencies and surface protein expression levels•Of the top 150 traits, 11 genetic loci explained up to 36% of variation of 19 traits•Loci include autoimmune susceptibility genes, providing etiological hypotheses
The study of a large and homogenous population of human twins identifies numerous genetic loci controlling the phenotype or number of functionally important immune subsets in the blood, providing a database to test associations of any genetic locus with more than 78,000 different immune traits.
RATIONALE:One measure of protein glycosylation (GlycA) has been reported to predict higher cardiovascular risk by reflecting inflammatory pathways.
OBJECTIVE:The main objective of this study is to ...assess the role of a comprehensive panel of IgG glycosylation traits on traditional risk factors for cardiovascular disease and on presence of subclinical atherosclerosis in addition to GlycA.
METHODS AND RESULTS:We measured 76 IgG glycosylation traits in 2970 women (age range, 40–79 years) from the TwinsUK cohort and correlated it to their estimated 10-year atherosclerotic cardiovascular disease risk score and their carotid and femoral plaque measured by ultrasound imaging. Eight IgG glycan traits are associated with the 10-year atherosclerotic cardiovascular disease risk score after adjusting for multiple tests and for individual risk factors—5 with increased risk and 3 with decreased risk. These glycans replicated in 967 women from ORCADES cohort (Orkney Complex Disease Study), and 6 of them were also associated in 845 men. A linear combination of IgG glycans and GlycA is also associated with presence of carotid (odds ratio, 1.55; 95% confidence interval, 1.25–1.93; P=7.5×10) and femoral (odds ratio, 1.32; 95% confidence interval, 1.06–1.64; P=0.01) plaque in a subset of women with atherosclerosis data after adjustment for traditional risk factors. One specific glycosylation trait, GP18-the percentage of FA2BG2S1 glycan in total IgG glycans, was negatively correlated with very-low-density lipoprotein and triglyceride levels in serum and with presence of carotid plaque (odds ratio, 0.60; 95% confidence interval, 0.50–0.71; P=5×10).
CONCLUSIONS:We find molecular pathways linking IgG to arterial lesion formation. Glycosylation traits are independently associated with subclinical atherosclerosis. One specific trait related to the sialylated N-glycan is negatively correlated with cardiovascular disease risk, very-low-density lipoprotein and triglyceride serum levels, and presence of carotid plaque.
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 (0.0750.009; P = 1.08x10-17), ergothioneine as a marker of mushroom consumption (0.1810.019; 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 (0.0240.004; P = 1.24x10-8) and indolepropionate (0.0260.004; P = 2.39x10-9), and threitol (0.0330.003; 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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK