Studies in mice and humans have revealed intriguing associations between host genetics and the microbiome. Here we report a 16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs, a subset ...of which was previously reported. Tripling the sample narrowed the confidence intervals around heritability estimates and uncovered additional heritable taxa, some of which are validated in other studies. Repeat sampling of subjects showed heritable taxa to be temporally stable. A candidate gene approach uncovered associations between heritable taxa and genes related to diet, metabolism, and olfaction. We replicate an association between Bifidobacterium and the lactase (LCT) gene locus and identify an association between the host gene ALDH1L1 and the bacteria SHA-98, suggesting a link between formate production and blood pressure. Additional genes detected are involved in barrier defense and self/non-self recognition. Our results indicate that diet-sensing, metabolism, and immune defense are important drivers of human-microbiome co-evolution.
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•16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs•Heritable bacterial taxa are temporally stable•Bifidobacterium associates with lactase gene variants; formate production links to blood pressure•Gene-microbe links involve genes related to diet, metabolism, olfaction, and defense
Does host genotype shape the microbiome? Goodrich et al. present a gut microbiome analysis of 1,126 twin pairs, which extends the association between host genetics and select bacterial taxa. Lactase nonpersistence was linked to higher levels of Bifidobacteria. Other gene/microbe links relate to diet and barrier defense.
According to the Our World in Data COVID-19 database, In Europe, the number of confirmed cases reported between December, 2021, and March, 2022 (omicron period) has exceeded all previously reported ...cases. To assess the association between long COVID (outcome) and the infection period (exposure), we applied a univariate logistic regression model adjusted by sex, IMD, age, the presence of comorbidities, vaccination status (one, two, or three doses), and body-mass index, all of which are related to the risk of long COVID.3 We stratified the analysis according to the time elapsed between infection and most recent vaccination considering three groups, 3 months, 3–6 months, and more than 6 months, to allow for potential waning of immunity from vaccination. ...to enable swift reporting, the period of assessment of omicron cases was slightly shorter than for the delta variant, and assessment of longer durations of long COVID (eg, >12 weeks) was not possible.
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 is inhabited by trillions of microorganisms composing a dynamic ecosystem implicated in health and disease. The composition of the gut microbiota is unique to each individual and tends ...to remain relatively stable throughout life, yet daily transient fluctuations are observed. Diet is a key modifiable factor influencing the composition of the gut microbiota, indicating the potential for therapeutic dietary strategies to manipulate microbial diversity, composition, and stability. While diet can induce a shift in the gut microbiota, these changes appear to be temporary. Whether prolonged dietary changes can induce permanent alterations in the gut microbiota is unknown, mainly due to a lack of long-term human dietary interventions, or long-term follow-ups of short-term dietary interventions. It is possible that habitual diets have a greater influence on the gut microbiota than acute dietary strategies. This review presents the current knowledge around the response of the gut microbiota to short-term and long-term dietary interventions and identifies major factors that contribute to microbiota response to diet. Overall, further research on long-term diets that include health and microbiome measures is required before clinical recommendations can be made for dietary modulation of the gut microbiota for health.
The human gut microbiome has been associated with many health factors but variability between studies limits exploration of effects between them. Gut microbiota profiles are available for >2700 ...members of the deeply phenotyped TwinsUK cohort, providing a uniform platform for such comparisons. Here, we present gut microbiota association analyses for 38 common diseases and 51 medications within the cohort. We describe several novel associations, highlight associations common across multiple diseases, and determine which diseases and medications have the greatest association with the gut microbiota. These results provide a reference for future studies of the gut microbiome and its role in human health.
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.
The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic ...potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.
Several circulating metabolites derived from bacterial protein fermentation have been found to be inversely associated with renal function but the timing and disease severity is unclear. The aim of ...this study is to explore the relationship between indoxyl-sulfate, p-cresyl-sulfate, phenylacetylglutamine and gut-microbial profiles in early renal function decline.
Indoxyl-sulfate (Beta(SE) = -2.74(0.24); P = 8.8x10-29), p-cresyl-sulfate (-1.99(0.24), P = 4.6x10-16), and phenylacetylglutamine(-2.73 (0.25), P = 1.2x10-25) were inversely associated with eGFR in a large population base cohort (TwinsUK, n = 4439) with minimal renal function decline. In a sub-sample of 855 individuals, we analysed metabolite associations with 16S gut microbiome profiles (909 profiles, QIIME 1.7.0). Three Operational Taxonomic Units (OTUs) were significantly associated with indoxyl-sulfate and 52 with phenylacetylglutamine after multiple testing; while one OTU was nominally associated with p-cresyl sulfate. All 56 microbial members belong to the order Clostridiales and are represented by anaerobic Gram-positive families Christensenellaceae, Ruminococcaceae and Lachnospiraceae. Within these, three microbes were also associated with eGFR.
Our data suggest that indoxyl-sulfate, p-cresyl-sulfate and phenylacetylglutamine are early markers of renal function decline. Changes in the intestinal flora associated with these metabolites are detectable in early kidney disease. Future efforts should dissect this relationship to improve early diagnostics and therapeutics strategies.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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