Hepatic insulin resistance and muscle insulin resistance are characterized by distinct postprandial plasma metabolite profiles: a cross-sectional study DOI Creative Commons
Anouk Gijbels, Balázs Erdős, Inez Trouwborst

et al.

Cardiovascular Diabetology, Journal Year: 2024, Volume and Issue: 23(1)

Published: March 16, 2024

Abstract Background Tissue-specific insulin resistance (IR) predominantly in muscle (muscle IR) or liver (liver has previously been linked to distinct fasting metabolite profiles, but postprandial profiles have not investigated tissue-specific IR yet. Given the importance of metabolic impairments pathophysiology cardiometabolic diseases, we compared plasma response a high-fat mixed meal between individuals with predominant IR. Methods This cross-sectional study included data from 214 women and men BMI 25–40 kg/m 2 , aged 40–75 years, was assessed using sensitivity index (MISI) hepatic (HIRI), which were calculated glucose responses during 7-point oral tolerance test. Plasma samples collected before (T = 0) after 30, 60, 120, 240 min) consumption 247 measures, including lipoproteins, cholesterol, triacylglycerol (TAG), ketone bodies, amino acids, quantified nuclear magnetic resonance spectroscopy. Differences iAUCs tested ANCOVA adjustment for age, sex, center, BMI, waist-to-hip ratio. P -values adjusted false discovery rate (FDR) 0.05 Benjamini–Hochberg method. Results Sixty-eight significantly different Liver characterized by greater large VLDL ( p 0.004), very 0.002), medium-sized LDL particles 0.026), TAG small 0.025), 0.003), all subclasses (all < 0.05), HDL 0.011), In IR, fatty acid (FA) profile consisted higher percentage saturated FA 0.013), lower polyunsaturated 0.008), Conclusion People more unfavorable those

Language: Английский

Microbiome epidemiology and association studies in human health DOI
Hannah VanEvery, Eric A. Franzosa, Long H. Nguyen

et al.

Nature Reviews Genetics, Journal Year: 2022, Volume and Issue: 24(2), P. 109 - 124

Published: Oct. 5, 2022

Language: Английский

Citations

56
Research gaps and opportunities in precision nutrition: an NIH workshop report DOI Creative Commons
Bruce Y. Lee, José M. Ordovás, Elizabeth J. Parks

et al.

American Journal of Clinical Nutrition, Journal Year: 2022, Volume and Issue: 116(6), P. 1877 - 1900

Published: Aug. 30, 2022

Language: Английский

Citations

47
Precision nutrition: Maintaining scientific integrity while realizing market potential DOI Creative Commons
Silvia Berciano,

Juliana Peboni Figueiredo,

Tristin D. Brisbois

et al.

Frontiers in Nutrition, Journal Year: 2022, Volume and Issue: 9

Published: Sept. 2, 2022

Precision Nutrition (PN) is an approach to developing comprehensive and dynamic nutritional recommendations based on individual variables, including genetics, microbiome, metabolic profile, health status, physical activity, dietary pattern, food environment as well socioeconomic psychosocial characteristics. PN can help answer the question “What should I eat be healthy?”, recognizing that what healthful for one may not same another, understanding responses diet change over time. The growth of market has been driven by increasing consumer interest in individualized products services coupled with advances technology, analytics, omic sciences. However, important concerns are evident regarding adequacy scientific substantiation supporting claims current services. An additional limitation accessing cost diagnostic tests wearable devices. Despite these challenges, holds great promise a tool improve healthspan reduce healthcare costs. Accelerating advancement will require: (a) investment multidisciplinary collaborations enable development user-friendly tools applying technological omics, sensors, artificial intelligence, big data management, analytics; (b) engagement professionals payers support equitable broader adoption medicine shifts toward preventive personalized approaches; (c) system-wide collaboration between stakeholders advocate continued evidence-based PN, develop regulatory framework maintain trust engagement, allow reach its full potential.

Language: Английский

Citations

40
Menopause is associated with postprandial metabolism, metabolic health and lifestyle: The ZOE PREDICT study DOI Creative Commons
Kate Bermingham,

Inbar Linenberg,

Wendy L. Hall

et al.

EBioMedicine, Journal Year: 2022, Volume and Issue: 85, P. 104303 - 104303

Published: Oct. 18, 2022

BackgroundThe menopause transition is associated with unfavourable alterations in health. However, postprandial metabolic changes and their mediating factors are poorly understood.MethodsThe PREDICT 1 UK cohort (n=1002; pre- n=366, peri- n=55, post-menopausal females n=206) assessed phenotypic characteristics, anthropometric, diet gut microbiome data, fasting (0–6 h) cardiometabolic blood measurements, including continuous glucose monitoring (CGM) data. Differences between menopausal groups were the an age-matched subgroup, adjusting for age, BMI, hormone therapy (MHT) use, smoking status.FindingsPost-menopausal had higher measures (glucose, HbA1c inflammation (GlycA), 6%, 5% 4% respectively), sugar intakes (12%) poorer sleep compared pre-menopausal (p<0.05 all). Postprandial responses glucose2hiauc insulin2hiauc (42% respectively) CGM (glycaemic variability time range) post- versus pre-menopause In subgroups (n=150), remained post-menopause (peak0-2h 4%). MHT was favourable visceral fat, (glucose insulin) (triglyceride6hiauc) measures. Mediation analysis showed that associations health indicators (visceral GlycA360mins glycaemia (peak0-2h)) part mediated by bacterial species.InterpretationFindings from this large scale, in-depth nutrition study of menopause, support importance risk type-2 diabetes cardiovascular disease mid-life to older women reduce morbidity mortality oestrogen decline.FundingZoe Ltd.

Language: Английский

Citations

32
Digital Biomarkers for Personalized Nutrition: Predicting Meal Moments and Interstitial Glucose with Non-Invasive, Wearable Technologies DOI Open Access
W van den Brink,

Tim J. van den Broek,

Salvator Palmisano

et al.

Nutrients, Journal Year: 2022, Volume and Issue: 14(21), P. 4465 - 4465

Published: Oct. 24, 2022

Digital health technologies may support the management and prevention of disease through personalized lifestyle interventions. Wearables smartphones are increasingly used to continuously monitor in everyday life, targeting maintenance. Here, we aim demonstrate potential wearables (1) detect eating moments (2) predict explain individual glucose levels healthy individuals, ultimately supporting self-management. Twenty-four individuals collected continuous data from interstitial monitoring, food logging, activity, sleep tracking over 14 days. We demonstrated use monitoring activity detecting with a prediction model showing an accuracy 92.3% (87.2-96%) 76.8% (74.3-81.2%) training test datasets, respectively. Additionally, showed peaks tracking, overall mean absolute error 0.32 (+/-0.04) mmol/L for 0.62 (+/-0.15) data. With Shapley additive explanations, personal elements important predicting were identified, providing basis advice. Pending further validation these digital biomarkers, they show promise type 2 diabetes recommendations.

Language: Английский

Citations

32
Effect of Personalized Nutrition on Dietary, Physical Activity, and Health Outcomes: A Systematic Review of Randomized Trials DOI Open Access
Sangeetha Shyam,

Ke Xin Lee,

Angeline Shu Wei Tan

et al.

Nutrients, Journal Year: 2022, Volume and Issue: 14(19), P. 4104 - 4104

Published: Oct. 2, 2022

Personalized nutrition is an approach that tailors advice to individuals based on individual's genetic information. Despite interest among scholars, the impact of this lifestyle habits and health has not been adequately explored. Hence, a systematic review randomized trials reporting effects personalized dietary, physical activity, outcomes was conducted. A search seven electronic databases manual resulted in identifying nine relevant trials. Cochrane's Risk Bias used determine trials' methodological quality. Although were moderate high quality, findings did show consistent benefits improving behavioral, or outcomes. There also lack evidence from regions other than North America Europe with diseases, affecting generalizability results. Furthermore, complex relationship between genes, interventions, may have contributed scarcity positive findings. We suggested several areas for improvement future regarding nutrition.

Language: Английский

Citations

30
Prebiotic Consumption Alters Microbiota but Not Biological Markers of Stress and Inflammation or Mental Health Symptoms in Healthy Adults: A Randomized, Controlled, Crossover Trial DOI Creative Commons
Annemarie R. Mysonhimer, Corinne N. Cannavale,

Melisa A. Bailey

et al.

Journal of Nutrition, Journal Year: 2023, Volume and Issue: 153(4), P. 1283 - 1296

Published: Feb. 24, 2023

Language: Английский

Citations

21
Periodontal Disease and Other Adverse Health Outcomes Share Risk Factors, including Dietary Factors and Vitamin D Status DOI Open Access
William B. Grant, Barbara M. van Amerongen, Barbara J. Boucher

et al.

Nutrients, Journal Year: 2023, Volume and Issue: 15(12), P. 2787 - 2787

Published: June 17, 2023

For nearly a century, researchers have associated periodontal disease (PD) with risks of other adverse health outcomes such as cardiovascular disease, diabetes mellitus, and respiratory diseases, well pregnancy outcomes. Those findings led to the hypothesis that PD causes those either by increasing systemic inflammation or action periodontopathic bacteria. However, experiments largely failed support hypothesis. Instead, association is casual, not causal, due shared underlying modifiable risk factors, including smoking, diet, obesity, low levels physical activity, vitamin D status. Diabetes mellitus also considered factor for PD, whereas red processed meat are most important dietary factors diabetes. Because generally develops before outcomes, diagnosis can alert patients they could reduce lifestyle changes. In addition, type 2 often be reversed rapidly adopting an anti-inflammatory, nonhyperinsulinemic diet emphasizes healthful, whole plant-based foods. This review describes evidence proinflammatory prohyperinsulinemia diets status We make recommendations regarding patterns, food groups, serum 25-hydroxyvitamin concentrations. Oral professionals should routinely inform their severe many making appropriate

Language: Английский

Citations

16
Genetic and gut microbiome determinants of SCFA circulating and fecal levels, postprandial responses and links to chronic and acute inflammation DOI Creative Commons
Ana Nogal, Francesco Asnicar, Amrita Vijay

et al.

Gut Microbes, Journal Year: 2023, Volume and Issue: 15(1)

Published: Aug. 1, 2023

Short-chain fatty acids (SCFA) are involved in immune system and inflammatory responses. We comprehensively assessed the host genetic gut microbial contribution to a panel of eight serum stool SCFAs two cohorts (TwinsUK, n = 2507; ZOE PREDICT-1, 328), examined their postprandial changes explored links with chronic acute responses healthy individuals trauma patients. report low concordance between circulating fecal SCFAs, significant most heritable component (average h2: 14%(SD 14%); 12%(SD 6%)). Furthermore, we find that microbiome can accurately predict levels (AUC>0.71) while presenting weaker associations serum. Finally, different correlation patterns markers depending on type response (chronic or trauma). Our results illustrate breadth physiological relevance human metabolic highlighting need for deeper understanding this important class molecules.

Language: Английский

Citations

16
Characterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study DOI Open Access
Kate Bermingham, Mohsen Mazidi, Paul W. Franks

et al.

Nutrients, Journal Year: 2023, Volume and Issue: 15(11), P. 2638 - 2638

Published: June 5, 2023

Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, correlations with fasting values inter- intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort.In study (n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by Nightingale NMR panel (4 6 h after 3.7 MJ mixed nutrient meal, second 2.2 at 4 h) serum samples. For each metabolite, over time was evaluated using linear modelling intraclass correlation coefficients (ICC) calculated.Postprandially, 85% (of metabolites) significantly changed from (47% increased, 53% decreased; Kruskal-Wallis), 37 measures increasing >25% 14 >50%. The largest changes observed very large lipoprotein particles ketone bodies. Seventy-one percent of circulating metabolites strongly correlated (Spearman's rho >0.80) between timepoints, 5% weakly (rho <0.50). median ICC 0.91 (range 0.08-0.99). lowest ICCs (ICC <0.40, 4% measures) found for glucose, pyruvate, bodies (β-hydroxybutyrate, acetoacetate, acetate) lactate.In this large-scale study, highly variable individuals sequential meals. Findings suggest that challenge may yield responses divergent measures, specifically glycolysis, essential amino acid, body size metabolites.

Language: Английский

Citations

14