| 1. |
- Bermingham, Kate M., et al.
(author)
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Menopause is associated with postprandial metabolism, metabolic health and lifestyle : The ZOE PREDICT study
- 2022
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In: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 85
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Journal article (peer-reviewed)abstract
- Background: The menopause transition is associated with unfavourable alterations in health. However, postprandial metabolic changes and their mediating factors are poorly understood. Methods: The PREDICT 1 UK cohort (n=1002; pre- n=366, peri- n=55, and post-menopausal females n=206) assessed phenotypic characteristics, anthropometric, diet and gut microbiome data, and fasting and postprandial (0–6 h) cardiometabolic blood measurements, including continuous glucose monitoring (CGM) data. Differences between menopausal groups were assessed in the cohort and in an age-matched subgroup, adjusting for age, BMI, menopausal hormone therapy (MHT) use, and smoking status. Findings: Post-menopausal females had higher fasting blood measures (glucose, HbA1c and inflammation (GlycA), 6%, 5% and 4% respectively), sugar intakes (12%) and poorer sleep (12%) compared with pre-menopausal females (p<0.05 for all). Postprandial metabolic responses for glucose2hiauc and insulin2hiauc were higher (42% and 4% respectively) and CGM measures (glycaemic variability and time in range) were unfavourable post- versus pre-menopause (p<0.05 for all). In age-matched subgroups (n=150), postprandial glucose responses remained higher post-menopause (peak0-2h 4%). MHT was associated with favourable visceral fat, fasting (glucose and insulin) and postprandial (triglyceride6hiauc) measures. Mediation analysis showed that associations between menopause and metabolic health indicators (visceral fat, GlycA360mins and glycaemia (peak0-2h)) were in part mediated by diet and gut bacterial species. Interpretation: Findings from this large scale, in-depth nutrition metabolic study of menopause, support the importance of monitoring risk factors for type-2 diabetes and cardiovascular disease in mid-life to older women to reduce morbidity and mortality associated with oestrogen decline. Funding: Zoe Ltd.
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| 2. |
- Merino, Jordi, et al.
(author)
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Validity of continuous glucose monitoring for categorizing glycemic responses to diet : Implications for use in personalized nutrition
- 2022
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In: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165. ; 115:6, s. 1569-1576
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Journal article (peer-reviewed)abstract
- Background: Continuous glucose monitor (CGM) devices enable characterization of individuals' glycemic variation. However, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application in personalized nutrition recommendations. Objectives: We aimed to evaluate the concordance of 2 simultaneously worn CGM devices in measuring postprandial glycemic responses. Methods: Within ZOE PREDICT (Personalised Responses to Dietary Composition Trial) 1, 394 participants wore 2 CGM devices simultaneously [n = 360 participants with 2 Abbott Freestyle Libre Pro (FSL) devices; n = 34 participants with both FSL and Dexcom G6] for ≤14 d while consuming standardized (n = 4457) and ad libitum (n = 5738) meals. We examined the CV and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Within-subject meal ranking was assessed using Kendall τ rank correlation. Concordance between paired devices in time in range according to the American Diabetes Association cutoffs (TIRADA) and glucose variability (glucose CV) was also investigated. Results: The CV of glucoseiAUC0-2 h for standardized meals was 3.7% (IQR: 1.7%-7.1%) for intrabrand device and 12.5% (IQR: 5.1%-24.8%) for interbrand device comparisons. Similar estimates were observed for ad libitum meals, with intrabrand and interbrand device CVs of glucoseiAUC0-2 h of 4.1% (IQR: 1.8%-7.1%) and 16.6% (IQR: 5.5%-30.7%), respectively. Kendall τ rank correlation showed glucoseiAUC0-2h-derived meal rankings were agreeable between paired CGM devices (intrabrand: 0.9; IQR: 0.8-0.9; interbrand: 0.7; IQR: 0.5-0.8). Paired CGMs also showed strong concordance for TIRADA with a intrabrand device CV of 4.8% (IQR: 1.9%-9.8%) and an interbrand device CV of 3.2% (IQR: 1.1%-6.2%). Conclusions: Our data demonstrate strong concordance of CGM devices in monitoring glycemic responses and suggest their potential use in personalized nutrition.
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| 3. |
- Berry, Sarah E., et al.
(author)
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Human postprandial responses to food and potential for precision nutrition
- 2020
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In: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26:6, s. 964-973
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Journal article (peer-reviewed)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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| 4. |
- Tsereteli, Neli, et al.
(author)
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Impact of insufficient sleep on dysregulated blood glucose control under standardised meal conditions
- 2022
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In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 65:2, s. 356-365
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Journal article (peer-reviewed)abstract
- Aims/hypothesis: Sleep, diet and exercise are fundamental to metabolic homeostasis. In this secondary analysis of a repeated measures, nutritional intervention study, we tested whether an individual’s sleep quality, duration and timing impact glycaemic response to a breakfast meal the following morning. Methods: Healthy adults’ data (N = 953 [41% twins]) were analysed from the PREDICT dietary intervention trial. Participants consumed isoenergetic standardised meals over 2 weeks in the clinic and at home. Actigraphy was used to assess sleep variables (duration, efficiency, timing) and continuous glucose monitors were used to measure glycaemic variation (>8000 meals). Results: Sleep variables were significantly associated with postprandial glycaemic control (2 h incremental AUC), at both between- and within-person levels. Sleep period time interacted with meal type, with a smaller effect of poor sleep on postprandial blood glucose levels when high-carbohydrate (low fat/protein) (pinteraction = 0.02) and high-fat (pinteraction = 0.03) breakfasts were consumed compared with a reference 75 g OGTT. Within-person sleep period time had a similar interaction (high carbohydrate: pinteraction = 0.001, high fat: pinteraction = 0.02). Within- and between-person sleep efficiency were significantly associated with lower postprandial blood glucose levels irrespective of meal type (both p < 0.03). Later sleep midpoint (time deviation from midnight) was found to be significantly associated with higher postprandial glucose, in both between-person and within-person comparisons (p = 0.035 and p = 0.051, respectively). Conclusions/interpretation: Poor sleep efficiency and later bedtime routines are associated with more pronounced postprandial glycaemic responses to breakfast the following morning. A person’s deviation from their usual sleep pattern was also associated with poorer postprandial glycaemic control. These findings underscore sleep as a modifiable, non-pharmacological therapeutic target for the optimal regulation of human metabolic health. Trial registrationClinicalTrials.gov NCT03479866. Graphical abstract: [Figure not available: see fulltext.]
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| 5. |
- Merino, Jordi, et al.
(author)
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Interaction Between Type 2 Diabetes Prevention Strategies and Genetic Determinants of Coronary Artery Disease on Cardiometabolic Risk Factors
- 2020
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In: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 69:1, s. 112-120
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Journal article (peer-reviewed)abstract
- Coronary artery disease (CAD) is more frequent among individuals with dysglycemia. Preventive interventions for diabetes can improve cardiometabolic risk factors (CRFs), but it is unclear whether the benefits on CRFs are similar for individuals at different genetic risk for CAD. We built a 201-variant polygenic risk score (PRS) for CAD and tested for interaction with diabetes prevention strategies on 1-year changes in CRFs in 2,658 Diabetes Prevention Program (DPP) participants. We also examined whether separate lifestyle behaviors interact with PRS and affect changes in CRFs in each intervention group. Participants in both the lifestyle and metformin interventions had greater improvement in the majority of recognized CRFs compared with placebo (P < 0.001) irrespective of CAD genetic risk (Pinteraction > 0.05). We detected nominal significant interactions between PRS and dietary quality and physical activity on 1-year change in BMI, fasting glucose, triglycerides, and HDL cholesterol in individuals randomized to metformin or placebo, but none of them achieved the multiple-testing correction for significance. This study confirms that diabetes preventive interventions improve CRFs regardless of CAD genetic risk and delivers hypothesis-generating data on the varying benefit of increasing physical activity and improving diet on intermediate cardiovascular risk factors depending on individual CAD genetic risk profile.
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| 6. |
- Raghavan, Sridharan, et al.
(author)
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Interaction of diabetes genetic risk and successful lifestyle modification in the Diabetes Prevention Programme
- 2021
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In: Diabetes, Obesity and Metabolism. - : Wiley. - 1462-8902 .- 1463-1326. ; 23:4, s. 1030-1040
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Journal article (peer-reviewed)abstract
- Aim: To test whether diabetes genetic risk modifies the association of successful lifestyle changes with incident diabetes. Materials and methods: We studied 823 individuals randomized to the intensive lifestyle intervention (ILS) arm of the Diabetes Prevention Programme who were diabetes-free 1 year after enrolment. We tested additive and multiplicative interactions of a 67-variant diabetes genetic risk score (GRS) with achievement of three ILS goals at 1 year (≥7% weight loss, ≥150 min/wk of moderate leisure-time physical activity, and/or a goal for self-reported total fat intake) on the primary outcome of incident diabetes over 3 years of follow-up. Results: A lower GRS and achieving each or all three ILS goals were each associated with lower incidence of diabetes (all P < 0.05). Additive interactions were significant between the GRS and achievement of the weight loss goal (P < 0.001), physical activity goal (P = 0.02), and all three ILS goals (P < 0.001) for diabetes risk. Achievement of all three ILS goals was associated with 1.8 (95% CI 0.3, 3.4), 3.1 (95% CI 1.5, 4.7), and 3.9 (95% CI 1.6, 6.2) fewer diabetes cases/100-person-years in the first, second and third GRS tertiles (P < 0.001 for trend). Multiplicative interactions between the GRS and ILS goal achievement were significant for the diet goal (P < 0.001), but not for weight loss (P = 0.18) or physical activity (P = 0.62) goals. Conclusions: Genetic risk may identify high-risk subgroups for whom successful lifestyle modification is associated with greater absolute reduction in the risk of incident diabetes.
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| 7. |
- Vallat, Raphael, et al.
(author)
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How people wake up is associated with previous night’s sleep together with physical activity and food intake
- 2022
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1
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Journal article (peer-reviewed)abstract
- How people wake up and regain alertness in the hours after sleep is related to how they are sleeping, eating, and exercising. Here, in a prospective longitudinal study of 833 twins and genetically unrelated adults, we demonstrate that how effectively an individual awakens in the hours following sleep is not associated with their genetics, but instead, four independent factors: sleep quantity/quality the night before, physical activity the day prior, a breakfast rich in carbohydrate, and a lower blood glucose response following breakfast. Furthermore, an individual’s set-point of daily alertness is related to the quality of their sleep, their positive emotional state, and their age. Together, these findings reveal a set of non-genetic (i.e., not fixed) factors associated with daily alertness that are modifiable.
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