| 1. |
- Asnicar, Francesco, et al.
(författare)
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Blue poo : Impact of gut transit time on the gut microbiome using a novel marker
- 2021
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Ingår i: Gut. - : BMJ. - 0017-5749 .- 1468-3288. ; 70:9, s. 1665-1674
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Tidskriftsartikel (refereegranskat)abstract
- Background and aims: Gut transit time is a key modulator of host-microbiome interactions, yet this is often overlooked, partly because reliable methods are typically expensive or burdensome. The aim of this single-arm, single-blinded intervention study is to assess (1) the relationship between gut transit time and the human gut microbiome, and (2) the utility of the a € blue dye' method as an inexpensive and scalable technique to measure transit time. Methods: We assessed interactions between the taxonomic and functional potential profiles of the gut microbiome (profiled via shotgun metagenomic sequencing), gut transit time (measured via the blue dye method), cardiometabolic health and diet in 863 healthy individuals from the PREDICT 1 study. Results: We found that gut microbiome taxonomic composition can accurately discriminate between gut transit time classes (0.82 area under the receiver operating characteristic curve) and longer gut transit time is linked with specific microbial species such as Akkermansia muciniphila, Bacteroides spp and Alistipes spp (false discovery rate-adjusted p values <0.01). The blue dye measure of gut transit time had the strongest association with the gut microbiome over typical transit time proxies such as stool consistency and frequency. Conclusions: Gut transit time, measured via the blue dye method, is a more informative marker of gut microbiome function than traditional measures of stool consistency and frequency. The blue dye method can be applied in large-scale epidemiological studies to advance diet-microbiome-health research. Clinical trial registry website https://clinicaltrials.gov/ct2/show/NCT03479866 and trial number NCT03479866.
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| 2. |
- Asnicar, Francesco, et al.
(författare)
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Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals
- 2021
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 27:2, s. 321-332
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Tidskriftsartikel (refereegranskat)abstract
- The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease.
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| 3. |
- Bermingham, Kate M., et al.
(författare)
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Characterisation of Fasting and Postprandial NMR Metabolites : Insights from the ZOE PREDICT 1 Study
- 2023
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Ingår i: Nutrients. - 2072-6643. ; 15:11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, their correlations with fasting values and their inter- and intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort. Methods: In the ZOE PREDICT 1 study (n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by a Nightingale NMR panel in fasting and postprandial (4 and 6 h after a 3.7 MJ mixed nutrient meal, with a second 2.2 MJ mixed nutrient meal at 4 h) serum samples. For each metabolite, inter- and intra-individual variability over time was evaluated using linear mixed modelling and intraclass correlation coefficients (ICC) were calculated. Results: Postprandially, 85% (of 250 metabolites) significantly changed from fasting at 6 h (47% increased, 53% decreased; Kruskal–Wallis), with 37 measures increasing by >25% and 14 increasing by >50%. The largest changes were observed in very large lipoprotein particles and ketone bodies. Seventy-one percent of circulating metabolites were strongly correlated (Spearman’s rho >0.80) between fasting and postprandial timepoints, and 5% were weakly correlated (rho <0.50). The median ICC of the 250 metabolites was 0.91 (range 0.08–0.99). The lowest ICCs (ICC <0.40, 4% of measures) were found for glucose, pyruvate, ketone bodies (β-hydroxybutyrate, acetoacetate, acetate) and lactate. Conclusions: In this large-scale postprandial metabolomic study, circulating metabolites were highly variable between individuals following sequential mixed meals. Findings suggest that a meal challenge may yield postprandial responses divergent from fasting measures, specifically for glycolysis, essential amino acid, ketone body and lipoprotein size metabolites.
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| 4. |
- Berry, Sarah E., et al.
(författare)
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Human postprandial responses to food and potential for precision nutrition
- 2020
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26:6, s. 964-973
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 5. |
- Mazidi, Mohsen, et al.
(författare)
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Meal-induced inflammation : postprandial insights from the Personalised REsponses to DIetary Composition Trial (PREDICT) study in 1000 participants
- 2021
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Ingår i: The American journal of clinical nutrition. - : Elsevier BV. - 1938-3207 .- 0002-9165. ; 114:3, s. 1028-1038
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Meal-induced metabolic changes trigger an acute inflammatory response, contributing to chronic inflammation and associated diseases. OBJECTIVES: We aimed to characterize variability in postprandial inflammatory responses using traditional (IL-6) and novel [glycoprotein acetylation (GlycA)] biomarkers of inflammation and dissect their biological determinants with a focus on postprandial glycemia and lipemia. METHODS: Postprandial (0-6 h) glucose, triglyceride (TG), IL-6, and GlycA responses were measured at multiple intervals after sequential mixed-nutrient meals (0 h and 4 h) in 1002 healthy adults aged 18-65 y from the PREDICT (Personalised REsponses to DIetary Composition Trial) 1 study, a single-arm dietary intervention study. Measures of habitual diet, blood biochemistry, gut microbiome composition, and visceral fat mass (VFM) were also collected. RESULTS: The postprandial changes in GlycA and IL-6 concentrations were highly variable between individuals. Participants eliciting an increase in GlycA and IL-6 (60% and 94% of the total participants, respectively) had mean 6-h increases of 11% and 190%, respectively. Peak postprandial TG and glucose concentrations were significantly associated with 6-h GlycA (r = 0.83 and r = 0.24, respectively; both P < 0.001) but not with 6-h IL-6 (both P > 0.26). A random forest model revealed the maximum TG concentration was the strongest postprandial TG predictor of postprandial GlycA and structural equation modeling revealed that VFM and fasting TG were most strongly associated with fasting and postprandial GlycA. Network Mendelian randomization demonstrated a causal link between VFM and fasting GlycA, mediated (28%) by fasting TG. Individuals eliciting enhanced GlycA responses had higher predicted cardiovascular disease risk (using the atherosclerotic disease risk score) than the rest of the cohort. CONCLUSIONS: The variable postprandial increases in GlycA and their associations with TG metabolism highlight the importance of modulating TG in concert with obesity to reduce GlycA and associated low-grade inflammation-related diseases.This trial was registered at clinicaltrials.gov as NCT03479866.
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