Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial

Plasma metabolite profiles of meat intake and their association with cardiovascular disease risk: A population-based study in Swedish cohorts

BACKGROUND

Higher meat intake has been associated with adverse health outcomes, including cardiovascular disease (CVD). This study investigated plasma metabolites associated with meat intake and their relation with cardiometabolic biomarkers, subclinical CVD markers, and incident CVD.

METHODS

Associations between self-reported meat intake and 1272 plasma metabolites were investigated in the SCAPIS cohort (n = 8,819; ages 50-64). Meat-associated metabolites were further examined for relation with subclinical CVD markers in the POEM cohort (n = 502; age 50) and incident CVD in the EpiHealth cohort (n = 2,278; ages 45-75; 107 incident cases over 9.6 years follow-up). Meat intake was categorized into white, unprocessed red, and processed red meat. Linear regression analyzed associations between meat intake, metabolites and cardiometabolic biomarkers, and subclinical CVD markers, while Cox models evaluated association between meat-associated metabolites and incident CVD.

RESULTS

After correction for multiple testing, 458, 368, and 403 metabolites were associated with white, unprocessed red, and processed red meat, respectively. Processed red meat-associated metabolites were associated with higher levels of fasting insulin, hemoglobin A1c, and lipoprotein(a), and were inversely associated with maximal oxygen consumption. Two metabolites, 1-palmitoyl-2-linoleoyl-GPE (16:0/18:2) (hazard ratios (HR: 1.32; 95 % CI: 1.08, 1.62)) and glutamine degradant (HR: 1.35; 95 % CI: 1.07, 1.72), that were inversely associated with intake of all meat types, were also associated with a higher risk of incident CVD.

CONCLUSIONS

This study provides comprehensive analysis of self-reported meat intake and plasma metabolites. The findings may enhance our understanding of the relationship between meat intake and CVD, and provide insights into underlying mechanisms.

Precision nutrition for cardiometabolic diseases

Precision nutrition is a vibrant and rapidly evolving field of scientific research and innovation with the potential to deliver health, societal and economic benefits by improving healthcare delivery and policies. Advances in deep phenotyping technologies, digital tools and artificial intelligence have made possible early proof-of-concept research that expands the understanding of within- and between-person variability in responses to diet. These studies illustrate the promise of precision nutrition to complement the traditional 'one size fits all' dietary guidelines, which, while considering broad life-stage and disease-specific nutritional requirements, often lack the granularity to account fully for individual variations in nutritional needs and dietary responses. Despite these developments, however, considerable challenges remain before precision nutrition can be implemented on a broader scale. This Review examines the current state of precision nutrition research, with a focus on its application to reducing the incidence and burden of cardiometabolic diseases. We critically examine the evidence base, explore the potential benefits and discuss the challenges and opportunities ahead.

Diet Item Details: Reporting Checklist for Feeding Studies Measuring the Dietary Metabolome (DID-METAB Checklist)-Explanation and Elaboration Report on the Development of the Checklist by the DID-METAB Delphi Working Group

Metabolomics is a postgenomic, systems-based discipline offering valuable applications in nutrition research, including the use of objective biomarkers to characterize dietary intake and metabolic responses more accurately. A scoping review identified the need for reporting guidance on dietary information in the form of a checklist to ensure reproducibility of human feeding studies that are measuring the diet-related metabolome. In this study, we aimed to gain consensus on a core outcome set pertaining to diet-related item details (DIDs) and recommendations for reporting DIDs to inform development of a reporting checklist. The goal of this checklist is to guide researchers on the minimum level of content and detail required for reporting dietary information in human feeding studies measuring the metabolome. A 2-stage online Delphi process encompassing 5 survey rounds with international experts in clinical trial design, feeding study intervention implementation, metabolomics, and/or human biospecimen analyses was conducted. A core outcome set encompassing 29 DIDs and accompanying recommendations was developed across 5 domains: dietary intervention-modeling (8 DIDs), dietary intervention-implementation (3 DIDs), dietary assessment (9 DIDs), adherence and compliance monitoring (4 DIDs), and bias (5 DIDs). The reporting guideline (DID-METAB Checklist) was generated and accepted by the international expert working group in the final survey round. All experts agreed that relevant journals should include the checklist as a suggested reporting tool for relevant studies and/or used alongside existing reporting tools. This report provides examples, explanations and elaboration for each recommendation including examples from published literature and references. The DID-METAB Checklist will be a key tool to advance the standardized reporting for feeding studies assessing the metabolome. Implementation of this tool will enable the ability to better interpret data and ensure global utility of results for furthering the advancement of metabolomics in nutrition research and future precision and personalized nutrition strategies.

Impact of formula protein quantity and source on infant metabolism: serum, urine, and fecal metabolomes of a randomized controlled study

BACKGROUND

Human milk offers significant health benefits for infants; however, when not feasible, infant formula serves as an alternative. The higher protein content in infant formula is thought to contribute to the distinct metabolic profiles observed in formula-fed infants compared with those fed human milk.

OBJECTIVES

This study investigates the impact of formula protein quantity and whey protein types on the serum, urine, and fecal metabolomes of infants.

METHODS

A secondary analysis was performed on a random subset of 200 well-characterized per-protocol infants who completed a prospective, randomized, double-blind controlled trial. Infants were randomly assigned to 1 of 3 groups: standard formula, protein-reduced formula with α-lactalbumin-enriched whey, or protein-reduced formula with casein glycomacropeptide-reduced whey, along with an observational reference group of exclusively breastfed infants. Serum, urine, and fecal metabolites were quantified using 1H nuclear magnetic resonance spectroscopy at baseline (1-2 mo), 4, and 6 mo of age. Dietary intake was assessed monthly ≤6 mo of age.

RESULTS

Formula protein content and type of whey protein used significantly influenced the amino acid profile and associated catabolic markers in serum and urine but had minimal impact on the fecal metabolome. Reduced protein formulas yielded metabolome profiles closer to those of breastfed infants compared with standard formula. Despite these improvements, infants fed human milk still demonstrated enhanced branched-chain amino acid (BCAA) oxidation and a greater capacity to eliminate catabolic waste products from BCAA metabolism over infants consuming protein-reduced formulas.

CONCLUSIONS

Comprehensive metabolomics profiling of serum, urine, and feces captures molecular-level changes and informs potential strategies for formula optimization. Both the quantity and source of protein significantly influenced the metabolic profiles of formula-fed infants. However, modifications in protein alone cannot fully resolve the metabolic differences between formula-fed and breastfed infants, highlighting the complexity of mimicking the human milk feeding-associated metabolic profile. This study was registered at clinicaltrials.gov as NCT02410057.

Integration of LC-MS-based untargeted and targeted metabolomics to uncover novel whole-grain wheat dietary intake biomarkers in the plasma of the Chinese population

Biomarkers of food intake (BFIs) for whole grains (WGs) would enable more precise dietary assessments and help investigate WG's health effects. However, no reports have been published on the biomarkers that reflect the intake of WG wheat in the Chinese diet. In an acute, randomized, crossover intervention study performed on 22 Chinese subjects, WG wheat BFI candidates were screened using an LC-HRMS untargeted metabolomics technique. Screening results indicate that alkylresorcinol (AR) metabolites are WG wheat-specific metabolites. These metabolites were systematically characterized by in vitro metabolism reaction, and the matched high-throughput LC-MS/MS-targeted quantitative method was developed. Time-response plots generated via targeted analysis revealed AR oxidation products (AR-OOH) and their sulfate conjugates (AR-OOH-sul) increased rapidly following the WG wheat consumption, which were identified as novel and short-term WG wheat BFIs. Another attractive biomarker was glucuronidated ARs (AR-glu), which can distinguish between WG and refined grain (RG) groups 24 h after WG wheat ingestion and is considered a promising medium- and long-term biomarker. Subsequently an independent dose-response study was performed for 38 volunteers who consumed different WG wheat amounts (0, 25, 50 or 100 g) for further validation. Identified BFIs perform well in classifying participants into WG wheat consumers or non-consumers, and could capture dose-dependent changes with WG intake increased. Overall, this is the first study to discover and validate WG BFIs in the Chinese population via dietary intervention trials, indicating the potential usefulness for WG wheat intake assessments and dietary compliance monitoring. Future work will examine their use in large-scale free-living populations.

Recent advances in applying metabolomics to uncover dietary impact on cardiometabolic health

PURPOSE OF REVIEW

Cardiometabolic diseases are a major global health concern, with diet playing a crucial role in their prevention and management. Recent advancements in the identification of metabolic signatures related to dietary patterns offer a more objective assessment of individualized dietary exposure and provide deeper insights into diet-disease associations.

RECENT FINDINGS

Recent studies have shown that distinct metabolic signatures are associated with the adherence to various dietary patterns. These signatures show even stronger associations with cardiometabolic disease incidence, independent of traditional risk factors and self-reported adherence to such dietary patterns. Emerging dietary approaches, such as sustainable diets, health outcome-focused diets, and population data-driven dietary patterns, also hold promise for improving cardiometabolic health. Additionally, metabolic signatures could offer insights into diet-disease associations in underrepresented populations, addressing genetic and lifestyle differences.

SUMMARY

Application of metabolomics provides a more precise understanding of how dietary patterns influence cardiometabolic health. Although the number of studies remains limited, and current evidence is inconsistent, the approach has significant potential for improving clinical and public health strategies. Future research should prioritize prospective studies and address population- and outcome-specific dietary needs to enable targeted interventions that optimize cardiometabolic health.

A Metabolome Wide Association Study of Fruit and Vegetable Consumption and Associations with Cardiovascular Disease Risk Factors: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP) Study

BACKGROUND

Epidemiologic evidence linking blood pressure (BP) and body weight-lowering effects with fruit and vegetable consumption mostly relies on self-reported dietary assessment prone to misreport and under- or overestimation of relationships.

OBJECTIVES

We aimed to characterize objective 24-h urinary metabolites and a derived metabolite score associated with fruit and vegetable intake and assessed their associations with BP and BMI, with validation across cohorts.

METHODS

We used untargeted proton nuclear magnetic resonance spectroscopy (1H NMR) of 2 timed repeated 24-h urine collections from free-living participants from the US (n = 2032) and the UK (n = 449) of the cross-sectional International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP). We evaluated correlations between fruit and vegetable intake assessed by 24-h dietary recalls with 7100 1H NMR features, adjusted for confounders and multiple testing. We related identified metabolites and a metabolite score with BP and BMI using extensively adjusted multiple linear regression models.

RESULTS

We characterized 11 1H NMR-derived 24-h urinary metabolites related to fruit and vegetable intake, reproducible across multiple 24-h urine collections of both cohorts. Proline betaine, citrate, N-methylproline, scyllo-inositol, 2-hydroxy-2-(4-methyl cyclohex-3-en-1-yl) propoxyglucuronide, and proline were associated with fruit intake, specifically with Rutaceae intake, whereas S-methyl-L-cysteine sulfoxide and S-methyl-L-cysteine sulfoxide metabolite were associated with Brassicaceae intake. The metabolite score, explaining 39.8% of fruit and vegetable intake, was inversely associated with systolic BP [-1.65 mmHg; 95% confidence interval (CI): -2.68, -0.62; P < 0.002] and BMI (-1.21 kg/m2; 95% CI: -1.62, -0.78; P < 0.0001). These associations were, to a large extent, explained by urinary citrate excretion.

CONCLUSIONS

We identified 1H NMR-derived urinary metabolites associated with fruit and vegetable consumption, consistent and reproducible between urine collections and across populations. A higher fruit and vegetable-related metabolite score showed associations with lower systolic BP and BMI, mainly mediated by citrate, but would need confirmation in further studies.

Urine Metabolomics during a Legume Diet Intervention Suggests Altered Metabolic Signatures and Potential New Intake Markers: First Insights

Given the general increase in legume consumption worldwide, there is a need to characterize the resulting human metabolic adaptations in order to demonstrate potential legume diet/health relationships. A nuclear magnetic resonance (NMR) metabolomics urine study was carried out on a small cohort (n = 18) to characterize the excretory effects of a pilot longitudinal 8-week legume-based dietary intervention. Despite the expected high interindividual variability in the excreted metabolome, the results suggested a nonlinear metabolic response, with higher metabolic activity in the first 4 weeks and a tendency toward baseline at the end of the intervention. The excretion of isoleucine, leucine, and threonine increased, along with metabolite changes suggestive of activation of the tricarboxylic acid cycle (through anaplerosis), ketogenesis, fat catabolism, and glycoprotein biosynthesis. Gut microbiota adaptations were also suggested based on the increased excretion of 2-hydroxyisobutyrate, allantoin, and hippurate. Increased levels of trigonelline were consistent with its role as a legume intake marker, whereas malonate and pseudouridine were suggested as possible additional markers. Correlation of NMR data with nutritional parameters aided putative explanatory hypotheses to be advanced. Our results suggest a dynamic response to legume consumption, mainly through increased amino acid excretion and altered energy metabolism, while advancing potential new markers of legume intake. These results require confirmation in larger cohorts but pave the way for an informed interpretation of the effects of legume-based diets on human health.

Recommendations for Designing, Conducting, and Reporting Feeding Trials in Nutrition Research

Double-blind, placebo-controlled, randomized controlled trials are the gold standard for clinical trials in nutrition science. For trials of whole diets, dietary counseling is advantageous as they offer clinical translatability although can vary in the fidelity of the intended intervention from participant to participant and across studies. Feeding trials, in which most or all food is provided, offer high precision and can provide proof-of-concept evidence that a dietary intervention is efficacious and can also better evaluate the effect of known quantities of foods and nutrients on physiology. However, they come with additional methodological complexities. Feeding trials also call for a variety of unique methodological considerations, not least of which relate to the design and delivery of diets to participants. This review aims to provide a comprehensive summary of recommendations for design and conduct of feeding trials, encompassing domiciled and nondomiciled feeding trials. Several pertinent aspects of trial design and methodology are discussed, including defining the study population to maximize retention, safety, and generalizability of findings, recommendations for design of control interventions and optimizing blinding, and specific considerations for clinical populations. A detailed stepwise process for menu design, development, validation, and delivery are also presented. These recommendations aim to facilitate methodologic consistency and execution of high-quality feeding trials, ultimately facilitating improved understanding of the role of diet in treating disease and the underpinning mechanisms.

Impact of a legumes diet on the human gut microbiome articulated with fecal and plasma metabolomes: A pilot study

BACKGROUND & AIMS

Legumes intake is known to be associated with several health benefits the origins of which is still a matter of debate. This paper addresses a pilot small cohort to probe for metabolic aspects of the interplay between legumes intake, human metabolism and gut microbiota.

METHODS

Untargeted nuclear magnetic resonance (NMR) metabolomics of blood plasma and fecal extracts was carried out, in tandem with qPCR analysis of feces, to assess the impact of an 8-week pilot legumes diet intervention on the fecal and plasma metabolomes and gut microbiota of 19 subjects.

RESULTS

While the high inter-individual variability hindered the detection of statistically significant changes in the gut microbiome, increased fecal glucose and decreased threonine levels were noted. Correlation analysis between the microbiome and fecal metabolome lead to putative hypotheses regarding the metabolic activities of prevalent bacteria groups (Clostridium leptum subgroup, Roseburia spp., and Faecalibacterium prausnitzii). These included elevated fecal glucose as a preferential energy source, the involvement of valerate/isovalerate and reduced protein degradation in gut microbiota. Plasma metabolomics advanced mannose and betaine as potential markers of legume intake and unveiled a decrease in formate and ketone bodies, the latter suggesting improved energy utilization through legume carbohydrates. Amino acid metabolism was also apparently affected, as suggested by lowered urea, histidine and threonine levels.

CONCLUSIONS

Despite the high inter-individual gut microbiome variability characterizing the small cohort addressed, combination of microbiological measurements and untargeted metabolomics unveiled several metabolic effects putatively related to legumes intake. If confirmed in larger cohorts, our findings will support the inclusion of legumes in diets and contribute valuable new insight into the origins of associated health benefits.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Towards nutrition with precision: unlocking biomarkers as dietary assessment tools

Precision nutrition requires precise tools to monitor dietary habits. Yet current dietary assessment instruments are subjective, limiting our understanding of the causal relationships between diet and health. Biomarkers of food intake (BFIs) hold promise to increase the objectivity and accuracy of dietary assessment, enabling adjustment for compliance and misreporting. Here, we update current concepts and provide a comprehensive overview of BFIs measured in urine and blood. We rank BFIs based on a four-level utility scale to guide selection and identify combinations of BFIs that specifically reflect complex food intakes, making them applicable as dietary instruments. We discuss the main challenges in biomarker development and illustrate key solutions for the application of BFIs in human studies, highlighting different strategies for selecting and combining BFIs to support specific study designs. Finally, we present a roadmap for BFI development and implementation to leverage current knowledge and enable precision in nutrition research.

Diet shapes the metabolite profile in the intact human ileum, which affects PYY release

The human ileum contains a high density of enteroendocrine L-cells, which release the appetite-suppressing hormones glucagon-like peptide-1 (GLP-1) and peptide tyrosine tyrosine (PYY) in response to food intake. Recent evidence highlighted the potential role of food structures in PYY release, but the link between food structures, ileal metabolites, and appetite hormone release remains unclear owing to limited access to intact human ileum. In a randomized crossover trial (ISRCTN11327221; isrctn.com), we investigated the role of human ileum in GLP-1 and PYY release by giving healthy volunteers diets differing in fiber and food structure: high-fiber (intact or disrupted food structures) or low-fiber disrupted food structures. We used nasoenteric tubes to sample chyme from the intact distal ileum lumina of humans in the fasted state and every 60 min for 480 min postprandially. We demonstrate the highly dynamic, wide-ranging molecular environment of the ileum over time, with a substantial decrease in ileum bacterial numbers and bacterial metabolites after food intake. We also show that high-fiber diets, independent of food structure, increased PYY release compared with a low-fiber diet during 0 to 240 min postprandially. High-fiber diets also increased ileal stachyose, and a disrupted high-fiber diet increased certain ileal amino acids. Treatment of human ileal organoids with ileal fluids or an amino acid and stachyose mixture stimulated PYY expression in a similar profile to blood PYY concentrations, confirming the role of ileal metabolites in PYY release. Our study demonstrates the diet-induced changes over time in the metabolite environment of intact human ileum, which play a role in PYY release.

Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.

Influence of the brain‑gut axis on neuroinflammation in cerebral ischemia‑reperfusion injury (Review)

Stroke, a debilitating cerebrovascular ailment, poses significant threats to human life and health. The intricate interplay between the gut‑brain‑microbiota axis (GBMA) and cerebral ischemia‑reperfusion has increasingly become a focal point of scientific exploration, emerging as a pivotal research avenue in stroke pathophysiology. In the present review, the authors delved into the nexus between the GBMA and neuroinflammation observed post‑stroke. The analysis underscored the pivotal roles of histone deacetylase 3 and neutrophil extracellular traps subsequent to stroke incidents. The influence of gut microbial compositions and their metabolites, notably short‑chain fatty acids and trimethylamine N‑oxide, on neuroinflammatory processes, was further elucidated. The involvement of immune cells, especially regulatory T‑cells, and the intricate signaling cascades including cyclic GMP‑AMP synthase/stimulator of interferon genes/Toll‑like receptor, further emphasized the complex regulatory mechanisms of GBMA in cerebral ischemia/reperfusion injury (CI/RI). Collectively, the present review offered a comprehensive perspective on the metabolic, immune and inflammatory modulations orchestrated by GBMA, augmenting the understanding of its role in neuroinflammation following CI/RI.

Obesity surgery and neural correlates of human eating behaviour: A systematic review of functional MRI studies

Changes in eating behaviour including reductions in appetite and food intake, and healthier food cue reactivity, reward, hedonics and potentially also preference, contribute to weight loss and its health benefits after obesity surgery. Functional magnetic resonance imaging (fMRI) has been increasingly used to interrogate the neural correlates of eating behaviour in obesity, including brain reward-cognitive systems, changes after obesity surgery, and links with alterations in the gut-hormone-brain axis. Neural responses to food cues can be measured by changes in blood oxygen level dependent (BOLD) signal in brain regions involved in reward processing, including caudate, putamen, nucleus accumbens, insula, amygdala, orbitofrontal cortex, and top-down inhibitory control, including dorsolateral prefrontal cortex (dlPFC). This systematic review aimed to examine: (i) results of human fMRI studies involving obesity surgery, (ii) important methodological differences in study design across studies, and (iii) correlations and associations of fMRI findings with clinical outcomes, other eating behaviour measures and mechanistic measures. Of 741 articles identified, 23 were eligible for inclusion: 16 (69.6%) longitudinal, two (8.7%) predictive, and five (21.7%) cross-sectional studies. Seventeen studies (77.3%) included patients having Roux-en-Y gastric bypass (RYGB) surgery, six (26.1%) vertical sleeve gastrectomy (VSG), and five (21.7%) laparoscopic adjustable gastric banding (LAGB). The majority of studies (86.0%) were identified as having a very low risk of bias, though only six (27.3%) were controlled interventional studies, with none including randomisation to surgical and control interventions. The remaining studies (14.0%) had a low risk of bias driven by their control groups not having an active treatment. After RYGB surgery, food cue reactivity often decreased or was unchanged in brain reward systems, and there were inconsistent findings as to whether reductions in food cue reactivity was greater for high-energy than low-energy foods. There was minimal evidence from studies of VSG and LAGB surgeries for changes in food cue reactivity in brain reward systems, though effects of VSG surgery on food cue reactivity in the dlPFC were more consistently found. There was consistent evidence for post-operative increases in satiety gut hormones glucagon-like-peptide 1 (GLP-1) and peptide YY (PYY) mediating reduced food cue reactivity after RYGB surgery, including two interventional studies. Methodological heterogeneity across studies, including nutritional state, nature of food cues, post-operative timing, lack of control groups for order effects and weight loss or dietary/psychological advice, and often small sample sizes, limited the conclusions that could be drawn, especially for correlational analyses with clinical outcomes, other eating behaviour measures and potential mediators. This systematic review provides a detailed data resource for those performing or analysing fMRI studies of obesity surgery and makes suggestions to help improve reporting and design of such studies, as well as future directions.

Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes

Rationale

Evidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers.

Methods

From the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated.

Results

There were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group.

Conclusion

Metabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks.

Lipid emulsion structure, digestion behavior, physiology, and health: a scoping review and future directions

Research investigating the effects of the food matrix on health is needed to untangle many unresolved questions in nutritional science. Emulsion structure plays a fundamental role in this inquiry; however, the effects of oil-in-water emulsion structure on broad metabolic, physiological, and health-related outcomes have not been comprehensively reviewed. This systematic scoping review targets this gap and examines methodological considerations for the field of relating food structure and health. MEDLINE, Web of Science, and CAB Direct were searched from inception to December 2022, returning 3106 articles, 52 of which were eligible for inclusion. Many investigated emulsion lipid droplet size and/or gastric colloidal stability and their relation to postprandial weight-loss-related outcomes. The present review also identifies numerous novel relationships between emulsion structures and health-related outcomes. "Omics" endpoints present an exciting avenue for more comprehensive analysis in this area, yet interpretation remains difficult. Identifying valid surrogate biomarkers for long-term outcomes and disease risk will be a turning point for food structure research, leading to breakthroughs in the pace and utility of research that generates advancements in health. The review's findings and recommendations aim to support new hypotheses, future trial design, and evidence-based emulsion design for improved health and well-being.

Precision medicine for cardiometabolic disease: a framework for clinical translation

Cardiometabolic disease is a major threat to global health. Precision medicine has great potential to help to reduce the burden of this common and complex disease cluster, and to enhance contemporary evidence-based medicine. Its key pillars are diagnostics; prediction (of the primary disease); prevention (of the primary disease); prognosis (prediction of complications of the primary disease); treatment (of the primary disease or its complications); and monitoring (of risk exposure, treatment response, and disease progression or remission). To contextualise precision medicine in both research and clinical settings, and to encourage the successful translation of discovery science into clinical practice, in this Series paper we outline a model (the EPPOS model) that builds on contemporary evidence-based approaches; includes precision medicine that improves disease-related predictions by stratifying a cohort into subgroups of similar characteristics, or using participants' characteristics to model treatment outcomes directly; includes personalised medicine with the use of a person's data to objectively gauge the efficacy, safety, and tolerability of therapeutics; and subjectively tailors medical decisions to the individual's preferences, circumstances, and capabilities. Precision medicine requires a well functioning system comprised of multiple stakeholders, including health-care recipients, health-care providers, scientists, health economists, funders, innovators of medicines and technologies, regulators, and policy makers. Powerful computing infrastructures supporting appropriate analysis of large-scale, well curated, and accessible health databases that contain high-quality, multidimensional, time-series data will be required; so too will prospective cohort studies in diverse populations designed to generate novel hypotheses, and clinical trials designed to test them. Here, we carefully consider these topics and describe a framework for the integration of precision medicine in cardiometabolic disease.

Dietary Assessment and Metabolomic Methodologies in Human Feeding Studies: A Scoping Review

Dietary metabolomics is a relatively objective approach to identifying new biomarkers of dietary intake and for use alongside traditional methods. However, methods used across dietary feeding studies vary, thus making it challenging to compare results. The objective of this study was to synthesize methodological components of controlled human feeding studies designed to quantify the diet-related metabolome in biospecimens, including plasma, serum, and urine after dietary interventions. Six electronic databases were searched. Included studies were as follows: 1) conducted in healthy adults; 2) intervention studies; 3) feeding studies focusing on dietary patterns; and 4) measured the dietary metabolome. From 12,425 texts, 50 met all inclusion criteria. Interventions were primarily crossover (n = 25) and parallel randomized controlled trials (n = 22), with between 8 and 395 participants. Seventeen different dietary patterns were tested, with the most common being the "High versus Low-Glycemic Index/Load" pattern (n = 11) and "Typical Country Intake" (n = 11); with 32 providing all or the majority (90%) of food, 16 providing some food, and 2 providing no food. Metabolites were identified in urine (n = 31) and plasma/serum (n = 30). Metabolites were quantified using liquid chromatography, mass spectroscopy (n = 31) and used untargeted metabolomics (n = 37). There was extensive variability in the methods used in controlled human feeding studies examining the metabolome, including dietary patterns tested, biospecimen sample collection, and metabolomic analysis techniques. To improve the comparability and reproducibility of controlled human feeding studies examining the metabolome, it is important to provide detailed information about the dietary interventions being tested, including information about included or restricted foods, food groups, and meal plans provided. Strategies to control for individual variability, such as a crossover study design, statistical adjustment methods, dietary-controlled run-in periods, or providing standardized meals or test foods throughout the study should also be considered. The protocol for this review has been registered at Open Science Framework (https://doi.org/10.17605/OSF.IO/DAHGS).

Effects of Sample Dilution on Nuclear Magnetic Resonance-Derived Metabolic Profiles of Human Urine

Traditionally, a relatively big urine volume (e.g., 500 μL) is used in nuclear magnetic resonance (NMR)-based human metabolomics, which is not feasible for studies with limited/precious samples. Although urine may be diluted before conventional high-throughput metabolomics analysis, the comprehensive effect of urine dilution on metabolic profiles is unknown. Here, for the first time, we systematically investigated the effect of urine dilution on 1H NMR metabolic profiles, by evaluating signal detectability, integration, signal-to-noise ratio (SNR), chemical shift (δ) and its variation, and signal overlapping of 47 metabolites in 10 volunteers. We observed significant linear changes along with increased dilution, including decreased integration and SNR, altered δ, decreased intersample variation of δ, and increased separation between overlapped signals, e.g., lactate and threonine, β-d-glucose and an unassigned signal, and histidine and 3-methylhistidine. We further tested the 40% dilution level (i.e., employing 300 μL urine) in an epidemiological study containing 1018 pregnant women from the Tongji-Shuangliu Birth Cohort, showing acceptable detectability and chemical shift variability for most of the 47 metabolites profiled. It indicated that mild (e.g., 40%) dilution of human urine can largely preserve the high-abundance metabolites profiled, reduce intersample chemical shift variations, and increase separations of overlapped signals, which is an improvement of routine sample preparation methods in NMR-based metabolomics and is applicable for studies with limited urine volumes, including large-scale epidemiological studies.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Diet-induced Weight Loss and Phenotypic Flexibility Among Healthy Overweight Adults: A Randomized Trial

BACKGROUND

The capacity of an individual to respond to changes in food intake so that postprandial metabolic perturbations are resolved, and metabolism returns to its pre-prandial state, is called phenotypic flexibility. This ability may be a more important indicator of current health status than metabolic markers in a fasting state.

AIM

In this parallel randomized controlled trial study, an energy-restricted healthy diet and 2 dietary challenges were used to assess the effect of weight loss on phenotypic flexibility.

METHODS

Seventy-two volunteers with overweight and obesity underwent a 12-wk dietary intervention. The participants were randomized to a weight loss group (WLG) with 20% less energy intake or a weight-maintenance group (WMG). At weeks 1 and 12, participants were assessed for body composition by MRI. Concurrently, markers of metabolism and insulin sensitivity were obtained from the analysis of plasma metabolome during 2 different dietary challenges-an oral glucose tolerance test (OGTT) and a mixed-meal tolerance test.

RESULTS

Intended weight loss was achieved in the WLG (-5.6 kg, P < 0.0001) and induced a significant reduction in total and regional adipose tissue as well as ectopic fat in the liver. Amino acid-based markers of insulin action and resistance such as leucine and glutamate were reduced in the postprandial phase of the OGTT in the WLG by 11.5% and 28%, respectively, after body weight reduction. Weight loss correlated with the magnitude of changes in metabolic responses to dietary challenges. Large interindividual variation in metabolic responses to weight loss was observed.

CONCLUSION

Application of dietary challenges increased sensitivity to detect metabolic response to weight loss intervention. Large interindividual variation was observed across a wide range of measurements allowing the identification of distinct responses to the weight loss intervention and mechanistic insight into the metabolic response to weight loss.

Role of metabolomics in the delivery of precision nutrition

Precision nutrition aims to deliver personalised dietary advice to individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies for furthering the field of precision nutrition. Metabolomics in particular is highly attractive as measurement of metabolites can capture information on food intake, levels of bioactive compounds and the impact of diets on endogenous metabolism. These aspects contain useful information for precision nutrition. Furthermore using metabolomic profiles to identify subgroups or metabotypes is attractive for the delivery of personalised dietary advice. Combining metabolomic derived metabolites with other parameters in prediction models is also an exciting avenue for understanding and predicting response to dietary interventions. Examples include but not limited to role of one carbon metabolism and associated co-factors in blood pressure response. Overall, while evidence exists for potential in this field there are also many unanswered questions. Addressing these and clearly demonstrating that precision nutrition approaches enable adherence to healthier diets and improvements in health will be key in the near future.

Comparison of the relative impacts of acute consumption of an inulin-enriched diet, milk kefir or a commercial probiotic product on the human gut microbiome and metabolome

It has been established that the human gut microbiota is central to health, and, consequently, there has been a growing desire to positively modulate its composition and/or function through, for example, the use of fermented foods, prebiotics or probiotics. Here, we compare the relative impact of the daily consumption of an inulin-enriched diet (n = 10), a commercial probiotic-containing fermented milk product (FMP) (n = 10), or a traditional kefir FMP (n = 9), over a 28-day period on the gut microbiome and urine metabolome of healthy human adults. None of the treatments resulted in significant changes to clinical parameters or biomarkers tested. However, shotgun metagenomic analysis revealed that kefir consumption resulted in a significant change in taxonomy, in the form of an increased abundance of the sub-dominant FMP-associated species Lactococcus raffinolactis, which further corresponded to shifts in the urine metabolome. Overall, our results indicated that daily consumption of a single portion of kefir alone resulted in detectable changes to the gut microbiota and metabolome of consumers.

Dietary metabolome profiles of a Healthy Australian Diet and a Typical Australian Diet: protocol for a randomised cross-over feeding study in Australian adults

INTRODUCTION

Traditional dietary assessment methods such as 24-hour recalls and food frequency questionnaires rely on self-reported data and are prone to error, bias and inaccuracy. Identification of dietary metabolites associated with different dietary patterns can provide objective markers of whole diet patterns that account for metabolism and individual responses to dietary interventions. Additionally, few studies have investigated country-specific healthy and unhealthy dietary patterns using metabolomics. Therefore, the current study aims to identify urinary and plasma metabolites that characterise a 'healthy' (aligned with current national dietary guidelines) and an 'unhealthy' dietary pattern (Typical Australian Diet) in Australian adults.

METHODS AND ANALYSIS

The Diet Quality Feeding Study (DQFS) is an 8-week cross-over feeding study that will recruit 40 healthy adults from the Hunter region (NSW, Australia). Data collected includes biospecimens (whole blood, urine, stool) for quantification of dietary metabolite biomarkers; questionnaires (medical history/demographic, physical activity, quality of life); physical measures (anthropometry, body composition, waist circumference, blood pressure, arterial pressure); skin carotenoids and dietary intake (24-hour recalls, food frequency questionnaire). Participants will attend the research facility every 2 weeks (end of the run-in, each diet intervention and washout period) for collection of physical measures. All food will be provided to participants for each dietary intervention period, and participants will return to their usual diet during the run-in and washout periods. Targeted and untargeted metabolomics using liquid chromatography-mass spectrometry and/or proton nuclear magnetic resonance (1H-NMR) spectroscopy will be used to identify metabolites in biospecimens associated with dietary intake.

ETHICS AND DISSEMINATION

This study is approved by the Hunter New England Human Research Ethics Committee (HNEHREC; 2022/ETH01649) and the University of Newcastle's Human Research Ethics Committee (HREC; H-2022-0330). Findings will be disseminated to study participants, funding bodies supporting the DQFS, peer-review publications and presented at scientific conferences within the field of research.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ACTRN12622001321730).

Environmental Planning and Non-Communicable Diseases: A Systematic Review on the Role of the Metabolomic Profile

Non-communicable diseases (NCDs) are the major cause of death worldwide and have economic, psychological, and social impacts. Air pollution is the second, contributing to NCDs-related deaths. Metabolomics are a useful diagnostic and prognostic tool for NCDs, as they allow the identification of biomarkers linked to emerging pathologic processes. The aim of the present study was to review the scientific literature on the application of metabolomics profiling in NCDs and to discuss environmental planning actions to assist healthcare systems and public managers based on early metabolic diagnosis. The search was conducted following PRISMA guidelines using Web of Science, Scopus, and PubMed databases with the following MeSH terms: "metabolomics" AND "noncommunicable diseases" AND "air pollution". Twenty-nine studies were eligible. Eleven involved NCDs prevention, eight addressed diabetes mellitus, insulin resistance, systemic arterial hypertension, or metabolic syndrome. Six studies focused on obesity, two evaluated nonalcoholic fatty liver disease, two studied cancer, and none addressed chronic respiratory diseases. The studies provided insights into the biological pathways associated with NCDs. Understanding the cost of delivering care where there will be a critical increase in NCDs prevalence is crucial to achieving universal health coverage and improving population health by allocating environmental planning and treatment resources.

The Association of Metabolomic Profiles of a Healthy Lifestyle with Heart Failure Risk in a Prospective Study

Lifestyle has been linked to the incidence of heart failure, but the underlying biological mechanisms remain unclear. Using the metabolomic, lifestyle, and heart failure data of the UK Biobank, we identified and validated healthy lifestyle-related metabolites in a matched case-control and cohort study, respectively. We then evaluated the association of healthy lifestyle-related metabolites with heart failure (HF) risk and the added predictivity of these healthy lifestyle-associated metabolites for HF. Of 161 metabolites, 8 were identified to be significantly related to healthy lifestyle. Notably, omega-3 fatty acids and docosahexaenoic acid (DHA) positively associated with a healthy lifestyle score (HLS) and exhibited a negative association with heart failure risk. Conversely, creatinine negatively associated with a HLS, but was positively correlated with the risk of HF. Adding these three metabolites to the classical risk factor prediction model, the prediction accuracy of heart failure incidence can be improved as assessed by the C-statistic (increasing from 0.806 [95% CI, 0.796-0.816] to 0.844 [95% CI, 0.834-0.854], p-value < 0.001). A healthy lifestyle is associated with significant metabolic alterations, among which metabolites related to healthy lifestyle may be critical for the relationship between healthy lifestyle and HF. Healthy lifestyle-related metabolites might enhance HF prediction, but additional validation studies are necessary.

Position statement on nutrition therapy for overweight and obesity: nutrition department of the Brazilian association for the study of obesity and metabolic syndrome (ABESO-2022)

Obesity is a chronic disease resulting from multifactorial causes mainly related to lifestyle (sedentary lifestyle, inadequate eating habits) and to other conditions such as genetic, hereditary, psychological, cultural, and ethnic factors. The weight loss process is slow and complex, and involves lifestyle changes with an emphasis on nutritional therapy, physical activity practice, psychological interventions, and pharmacological or surgical treatment. Because the management of obesity is a long-term process, it is essential that the nutritional treatment contributes to the maintenance of the individual's global health. The main diet-related causes associated with excess weight are the high consumption of ultraprocessed foods, which are high in fats, sugars, and have high energy density; increased portion sizes; and low intake of fruits, vegetables, and grains. In addition, some situations negatively interfere with the weight loss process, such as fad diets that involve the belief in superfoods, the use of teas and phytotherapics, or even the avoidance of certain food groups, as has currently been the case for foods that are sources of carbohydrates. Individuals with obesity are often exposed to fad diets and, on a recurring basis, adhere to proposals with promises of quick solutions, which are not supported by the scientific literature. The adoption of a dietary pattern combining foods such as grains, lean meats, low-fat dairy, fruits, and vegetables, associated with an energy deficit, is the nutritional treatment recommended by the main international guidelines. Moreover, an emphasis on behavioral aspects including motivational interviewing and the encouragement for the individual to develop skills will contribute to achieve and maintain a healthy weight. Therefore, this Position Statement was prepared based on the analysis of the main randomized controlled studies and meta-analyses that tested different nutrition interventions for weight loss. Topics in the frontier of knowledge such as gut microbiota, inflammation, and nutritional genomics, as well as the processes involved in weight regain, were included in this document. This Position Statement was prepared by the Nutrition Department of the Brazilian Association for the Study of Obesity and Metabolic Syndrome (ABESO), with the collaboration of dietitians from research and clinical fields with an emphasis on strategies for weight loss.

The gut-derived metabolites as mediators of the effect of healthy nutrition on the brain

Nutrition is now well recognized to be an environmental factor which positively or negatively influences the risk to develop neurological and psychiatric disorders. The gut microbiota has recently been shown to be an important actor mediating the relationship between environmental factors, including nutrition, and brain function. While its composition has been widely studied and associated with the risk of brain diseases, the mechanisms underlying the relationship between the gut and brain diseases remain to be explored. The wide range of bioactive molecules produced by the gut microbiota, called gut-derived metabolites (GDM), represent new players in the gut to brain interactions and become interesting target to promote brain health. The aim of this narrative review is to highlight some GDMs of interest that are produced in response to healthy food consumption and to summarize what is known about their potential effects on brain function. Overall, GDMs represent future useful biomarkers for the development of personalized nutrition. Indeed, their quantification after nutritional interventions is a useful tool to determine individuals' ability to produce microbiota-derived bioactive compounds upon consumption of specific food or nutrients. Moreover, GDMs represent also a new therapeutic approach to counteract the lack of response to conventional nutritional interventions.

Translation of nutrigenomic research for personalised and precision nutrition for cancer prevention and for cancer survivors

Personalised and precision nutrition uses information on individual characteristics and responses to nutrients, foods and dietary patterns to develop targeted nutritional advice that is more effective in improving the diet and health of each individual. Moving away from the conventional 'one size fits all', such targeted intervention approaches may pave the way to better population health, including lower burden of non-communicable diseases. To date, most personalised and precision nutrition approaches have been focussed on tackling obesity and cardiometabolic diseases with limited efforts directed to cancer prevention and for cancer survivors. Advances in understanding the biological basis of cancer and of the role played by diet in cancer prevention and in survival after cancer diagnosis, mean that it is timely to test and to apply such personalised and precision nutrition approaches in the cancer area. This endeavour can take advantage of the enhanced understanding of interactions between dietary factors, individual genotype and the gut microbiome that impact on risk of, and survival after, cancer diagnosis. Translation of these basic research into public health action should include real-time acquisition of nutrigenomic and related data and use of AI-based data integration methods in systems approaches that can be scaled up using mobile devices.

Associations between the Gut Microbiota, Urinary Metabolites, and Diet in Women during the Third Trimester of Pregnancy

Background

Pregnancy causes many metabolic and physiologic changes. However, associations between gut microbiota, dietary intake, and urinary metabolites are poorly characterized in pregnant women.

Objectives

The research objective was to identify dietary and microbial associations with urinary metabolites during pregnancy to elucidate potential biomarkers and microbial targets to improve maternal-fetal health. This is a secondary outcome of the study.

Methods

Pregnant women (n = 27) in the Pregnancy EAting and POstpartum Diapers pilot study provided dietary intake information in addition to fecal and urine samples at 36 wk gestation. The gut microbiota was characterized following fecal DNA extraction and 16S rRNA gene sequencing. Urinary metabolites were identified using liquid chromatography high-resolution mass spectrometry.

Results

Urinary glycocholate was consistently and negatively correlated with α-carotene intake. There were 9 significant correlations between microbial taxa and urinary metabolites and 13 significant correlations between microbial taxa and dietary intake. On average, Bacteroides were the most abundant taxon in the participants' gut microbiotas. Notably, the gut microbiotas of some pregnant women were not dominated by this taxon. Bacteroides-dominant women consumed more protein, fat, and sodium, and their gut microbiotas had lower alpha diversity than those of nondominant participants.

Conclusions

Several urinary metabolites and microbial taxa were associated with maternal diet and gastrointestinal community composition during the third trimester of pregnancy. Future work should determine the mechanisms underlying the associations identified herein.

Physical activity can improve diabetes patients' glucose control; A systematic review and meta-analysis

Background

Glycemic control is vital to patient care, and it is still the most important treatment goal for reducing organ damage and other complications associated with diabetes. Physical activity is one of the factors that affects glycemic management. Therefore, the aim of this systematic review and meta-analysis was to find, evaluate, and synthesize the best available information on the link between physical exercise and glycemic control in Ethiopian diabetes patients.

Methods

Pubmed, Science Direct, Google Scholar and African Journals Online were the databases searched. In addition, gray literature were explored. All papers chosen for inclusion in the review underwent a thorough critical appraisal utilizing the Joanna Briggs Institute's standardized critical appraisal instruments (JBI critical appraisal checklist-2017). For statistical analysis and descriptive synthesis, quantitative articles were combined. The Odds ratio and their 95% confidence intervals were generated. Papers that were of excellent quality but lacked the main outcome (physical activity) for meta-analysis were subjected to descriptive synthesis.

Results

The finding of this meta-analysis showed diabetes patients who were physically active had controlled their blood glucose levels by 2.4 times compared to their counter (Odds ratio = 2.40, 95% Confidence Interval = 1.57,3.69). The duration of disease was found to be the most commonly reported predictor for poor glycemic control followed by dietary habits, patients' sex and age.

Conclusion

Physical activity, which is a simple and inexpensive therapy for diabetes patients, can help them control their blood glucose levels. Patients with diabetes who have had it for a long time should be aware of the need of regular physical activity in maintaining blood glucose control.

Gastrointestinal, vaginal, nasopharyngeal, and breast milk microbiota profiles and breast milk metabolomic changes in Gambian infants over the first two months of lactation: A prospective cohort study

Microbiota composition in breast milk affects intestinal and respiratory microbiota colonization and the mucosal immune system's development in infants. The metabolomic content of breast milk is thought to interact with the microbiota and may influence developing infant immunity. One hundred seven Gambian mothers and their healthy, vaginally delivered, exclusively breastfed infants were included in our study. We analyzed 32 breast milk samples, 51 maternal rectovaginal swabs and 30 infants' rectal swabs at birth. We also analyzed 9 breast milk samples and 18 infants' nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA gene sequencing to determine the microbiota composition. Metabolomic profiling analysis was performed on colostrum and mature breast milk samples using a multiplatform approach combining 1-H Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry. Bacterial communities were distinct in composition and diversity across different sample types. Breast milk composition changed over the first 60 days of lactation. α-1,4- and α-1,3-fucosylated human milk oligosaccharides, and other 33 key metabolites in breast milk (monosaccharides, sugar alcohols and fatty acids) increased between birth and day 60 of life. This study's results indicate that infant gut and respiratory microbiota are unique bacterial communities, distinct from maternal gut and breast milk, respectively. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changes may contribute to the infant's immunological, metabolic, and neurological development and could consist the basis for future interventions to correct disrupted early life microbial colonization.

Metabolic profiles of ultra-processed food consumption and their role in obesity risk in British children

BACKGROUND & AIMS

Higher consumption of ultra-processed foods (UPF) has been associated with childhood obesity, but underlying mechanisms remain unclear. We investigated plasma nuclear magnetic resonance metabolic profiles of higher UPF consumption and their role in obesity risk in the British ALSPAC cohort.

METHODS

We performed cross-sectional and prospective metabolome wide association analyses of UPF, calculated from food diaries using the NOVA classification. In cross-sectional analysis, we tested the association between UPF consumption and metabolic profile at 7 years (N = 4528), and in the prospective analysis we tested the association between UPF consumption at 13 years and metabolic profile at 17 years (N = 3086). Effects of UPF-associated metabolites at 7 years on subsequent fat mass accumulation were assessed using growth curve models.

RESULTS

At 7 years, UPF was associated with 115 metabolic traits including lower levels of branched-chain and aromatic amino acids and higher levels of citrate, glutamine, and monounsaturated fatty acids, which were also associated with greater fat mass accumulation. Reported intake of nutrients mediated associations with most metabolites, except for citrate.

CONCLUSIONS

UPF consumption among British children is associated with perturbation of multiple metabolic traits, many of which contribute to child obesity risk.

Multi-omic phenotyping reveals host-microbe responses to bariatric surgery, glycaemic control and obesity

Background

Resolution of type 2 diabetes (T2D) is common following bariatric surgery, particularly Roux-en-Y gastric bypass. However, the underlying mechanisms have not been fully elucidated.

Methods

To address this we compare the integrated serum, urine and faecal metabolic profiles of participants with obesity ± T2D (n = 80, T2D = 42) with participants who underwent Roux-en-Y gastric bypass or sleeve gastrectomy (pre and 3-months post-surgery; n = 27), taking diet into account. We co-model these data with shotgun metagenomic profiles of the gut microbiota to provide a comprehensive atlas of host-gut microbe responses to bariatric surgery, weight-loss and glycaemic control at the systems level.

Results

Here we show that bariatric surgery reverses several disrupted pathways characteristic of T2D. The differential metabolite set representative of bariatric surgery overlaps with both diabetes (19.3% commonality) and body mass index (18.6% commonality). However, the percentage overlap between diabetes and body mass index is minimal (4.0% commonality), consistent with weight-independent mechanisms of T2D resolution. The gut microbiota is more strongly correlated to body mass index than T2D, although we identify some pathways such as amino acid metabolism that correlate with changes to the gut microbiota and which influence glycaemic control.

Conclusion

We identify multi-omic signatures associated with responses to surgery, body mass index, and glycaemic control. Improved understanding of gut microbiota - host co-metabolism may lead to novel therapies for weight-loss or diabetes. However, further experiments are required to provide mechanistic insight into the role of the gut microbiota in host metabolism and establish proof of causality.

Relationship between Metal Exposures, Dietary Macronutrient Intake, and Blood Glucose Levels of Informal Electronic Waste Recyclers in Ghana

While metal exposures are generally high among informal electronic waste (e-waste) recyclers, the joint effect of metals and dietary macronutrients on their metabolic health is unknown. Therefore, we investigated the relationship between metal exposures, dietary macronutrients intake, and blood glucose levels of e-waste recyclers at Agbogbloshie using dietary information (48-h recall survey), blood metals (Pb & Cd), and HbA1C levels of 151 participants (100 e-waste recyclers and 51 controls from the Accra, Ghana) in March 2017. A linear regression model was used to estimate the joint relationship between metal exposures, dietary macronutrient intake, and blood glucose levels. Except for dietary proteins, both groups had macronutrient deficiencies. Diabetes prevalence was significantly higher among controls. Saturated fat, OMEGA-3, and cholesterol intake were associated with significant increases in blood glucose levels of recyclers. In a joint model, while 1 mg of cholesterol consumed was associated with a 0.7% increase in blood glucose, 1 g/L of Pb was found to significantly increase blood glucose levels by 0.9% among recyclers. Although the dietary consumption of cholesterol and fat was not high, it is still possible that exposure to Pb and Cd may still increase the risk of diabetes among both e-waste recyclers and the general population.

Characterization of diet-dependent temporal changes in circulating short-chain fatty acid concentrations: A randomized crossover dietary trial

BACKGROUND

Production of SCFAs from food is a complex and dynamic saccharolytic fermentation process mediated by both human and gut microbial factors. Knowledge of SCFA production and of the relation between SCFA profiles and dietary patterns is lacking.

OBJECTIVES

Temporal changes in SCFA concentrations in response to 2 contrasting diets were investigated using a novel GC-MS method.

METHODS

Samples were obtained from a randomized, controlled, crossover trial designed to characterize the metabolic response to 4 diets. Participants (n = 19) undertook these diets during an inpatient stay (of 72 h). Serum samples were collected 2 h after breakfast (AB), after lunch (AL), and after dinner (AD) on day 3, and a fasting sample (FA) was obtained on day 4. The 24-h urine samples were collected on day 3. In this substudy, samples from the 2 extreme diets representing a diet with high adherence to WHO healthy eating recommendations and a typical Western diet were analyzed using a bespoke GC-MS method developed to detect and quantify 10 SCFAs and precursors in serum and urine samples.

RESULTS

Considerable interindividual variation in serum SCFA concentrations was observed across all time points, and temporal fluctuations were observed for both diets. Although the sample collection timing exerted a greater magnitude of effect on circulating SCFA concentrations, the unhealthy diet was associated with a lower concentration of acetic acid (FA: coefficient: -17.0; SE: 5.8; P-trend = 0.00615), 2-methylbutyric acid (AL: coefficient: -0.1; SE: 0.028; P-trend = 4.13 × 10-4 and AD: coefficient: -0.1; SE: 0.028; P-trend = 2.28 × 10-3), and 2-hydroxybutyric acid (FA: coefficient: -15.8; SE: 5.11; P-trend: 4.09 × 10-3). In contrast, lactic acid was significantly higher in the unhealthy diet (AL: coefficient: 750.2; SE: 315.2; P-trend = 0.024 and AD: coefficient: 1219.3; SE: 322.6; P-trend: 8.28 × 10-4).

CONCLUSIONS

The GC-MS method allowed robust mapping of diurnal patterns in SCFA concentrations, which were affected by diet, and highlighted the importance of standardizing the timing of SCFA measurements in dietary studies. This trial was registered on the NIHR UK clinical trial gateway and with ISRCTN as ISRCTN43087333.

Biomarkers of Fruit Intake Using a Targeted Metabolomics Approach: an Observational Cross-Sectional Analysis of the ELSA-Brasil Study

BACKGROUND

Advances in technology have led to the identification of a greater number of metabolites related to diet. Although fruit intake biomarkers have been reported in some studies, these findings require further replication, considering the relevance of fruits for diet quality and health.

OBJECTIVES

The aim of this study was to explore the associations of a set of potential urinary biomarkers of diet, assessed using a targeted metabolomics approach, with self-reported fruit intake data in participants of a computer-assisted 24-h dietary recall (GloboDiet software) validation study.

METHODS

A total of 93 individuals aged 43-72 y, 54% female, participated in this study. The subjects were a subsample of the Longitudinal Study of Adult Health (ELSA-Brasil). A 24-h dietary recall was obtained with the aid of GloboDiet software matching a 24-h urine sample from each participant. Candidate biomarkers were selected in a literature search and identified in urine by LC coupled to high-resolution MS. Spearman correlation analyses were performed between fruit intake and each biomarker.

RESULTS

Spearman correlation analysis showed that total fruits intake was significantly correlated with citric acid (ρ = 0.213, P = 0.041), ferulic acid sulfate I (ρ = 0.240, P = 0.020), hesperetin glucuronide/homoeriodictyol glucuronide (ρ = 0.303, P = 0.003), hydroxyhippuric acid (ρ = 0.239, P = 0.021), homovanillic alcohol sulfate (ρ = 0.339, P = 0.001), methylgallic acid sulfate (ρ = 0.268, P = 0.009), naringenin glucuronide (NG; ρ = 0.278, P = 0.007), proline betaine (PB; ρ = 0.305, P = 0.003), syringic acid sulfate (ρ = 0.210, P = 0.044), and sinapic acid sulfate (ρ = 0.412, P < 0.001). Among them, 3 have been described in literature as promising biomarkers for intake of total fruit, oranges, and citrus fruit: NG, hesperetin glucuronide, and PB.

CONCLUSIONS

Associations of total fruits intake with urinary measurements indicate the potential usefulness of dietary biomarkers in the Brazilian population as a complement to self-reported dietary assessments.

Healthful eating patterns, serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos

AIMS/HYPOTHESIS

We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes.

METHODS

We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors.

RESULTS

We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RRper SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (pinteraction = 0.0001), HEI-2015 (pinteraction = 0.020) or hPDI (pinteraction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively.

CONCLUSIONS/INTERPRETATION

Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.

Nutrition for precision health: The time is now

Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi-tiered "omics" makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene-diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

A healthy dietary metabolic signature is associated with a lower risk for type 2 diabetes and coronary artery disease

BACKGROUND

The global burden of cardiovascular disease and type 2 diabetes could be decreased by improving dietary factors, but identification of groups suitable for interventional approaches can be difficult. Reporting of dietary intake is prone to errors, and measuring of metabolites has shown promise in determining habitual dietary intake. Our aim is to create a metabolic signature that is associated with healthy eating and test if it associates with type 2 diabetes and coronary artery disease risk.

METHODS

Using plasma metabolite data consisting of 111 metabolites, partial least square (PLS) regression was used to identify a metabolic signature associated with a health conscious food pattern in the Malmö Offspring Study (MOS, n = 1538). The metabolic signature's association with dietary intake was validated in the Malmö Diet and Cancer study (MDC, n = 2521). The associations between the diet-associated metabolic signature and incident type 2 diabetes and coronary artery disease (CAD) were tested using Cox regression in MDC and logistic regression in Malmö Preventive Project (MPP, n = 1083). Modelling was conducted unadjusted (model 1), adjusted for potential confounders (model 2) and additionally for potential mediators (model 3).

RESULTS

The metabolic signature was associated with lower risk for type 2 diabetes in both MDC (hazard ratio: 0.58, 95% CI 0.52-0.66, per 1 SD increment of the metabolic signature) and MPP (odds ratio: 0.54, 95% CI 0.44-0.65 per 1 SD increment of the metabolic signature) in model 2. The results were attenuated but remained significant in model 3 in both MDC (hazard ratio 0.73, 95% CI 0.63-0.83) and MPP (odds ratio 0.70, 95% CI 0.55-0.88). The diet-associated metabolic signature was also inversely associated with lower risk of CAD in both MDC and MPP in model 1, but the association was non-significant in model 3.

CONCLUSIONS

In this proof-of-concept study, we identified a healthy diet-associated metabolic signature, which was inversely associated with future risk for type 2 diabetes and coronary artery disease in two different cohorts. The association with diabetes was independent of traditional risk factors and might illustrate an effect of health conscious dietary intake on cardiometabolic health.

Urinary and plasma metabolome of farm mink (Neovison vison) after an intervention with raw or cooked poultry offal: a 1H NMR investigation

The introduction of high amounts of cooked poultry offal in mink feed has been associated with health problems in growing mink. Cooking mink feed is a convenient way of reducing microbiological activity, but it may have a negative effect on raw material quality and animal welfare. This study investigates growth and health of mink fed raw or cooked poultry offal and describes urinary and blood plasma metabolic changes related to the feeding. A total of 65 male mink were divided in three feeding groups, two fed cooked offal and one group fed raw offal, and the plasma and urine samples were collected at 3 time points during the growth. Both bio-fluids and feed samples were measured by ¹H NMR spectroscopy and resulted metabolomics data were analysed using univariate and multivariate statistical methods that revealed dominating effect of the mink growth stages and to a less extent the feeding regime. Metabolome differences in relation to low body mass index (BMI) and kidney lesions were observed in plasma. Disease and decrease in BMI was associated with high creatinine and dimethylglycine content in plasma. These molecules were also particularly indicative of the cooked feeds. Moreover, low urinary taurine levels were also associated with disease and low BMI. Individual mink appeared to show negative effects of the cooked feed diet, including impaired growth and gross pathological lesions involving the kidneys. This may be related to the absorption of essential metabolites such as amino acids and fats, necessary for mink growth, that are negatively impacted by the cooking process.

Blood pressure interactions with the DASH dietary pattern, sodium, and potassium: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP)

BACKGROUND

Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet enhances potassium intake and reduces sodium intake and blood pressure (BP), but the underlying metabolic pathways are unclear.

OBJECTIVES

Among free-living populations, we delineated metabolic signatures associated with the DASH diet adherence, 24-hour urinary sodium and potassium excretions, and the potential metabolic pathways involved.

METHODS

We used 24-hour urinary metabolic profiling by proton nuclear magnetic resonance spectroscopy to characterize the metabolic signatures associated with the DASH dietary pattern score (DASH score) and 24-hour excretion of sodium and potassium among participants in the United States (n = 2164) and United Kingdom (n = 496) enrolled in the International Study of Macro- and Micronutrients and Blood Pressure (INTERMAP). Multiple linear regression and cross-tabulation analyses were used to investigate the DASH-BP relation and its modulation by sodium and potassium. Potential pathways associated with DASH adherence, sodium and potassium excretion, and BP were identified using mediation analyses and metabolic reaction networks.

RESULTS

Adherence to the DASH diet was associated with urinary potassium excretion (correlation coefficient, r = 0.42; P < 0.0001). In multivariable regression analyses, a 5-point higher DASH score (range, 7 to 35) was associated with a lower systolic BP by 1.35 mmHg (95% CI, -1.95 to -0.80 mmHg; P = 1.2 × 10-5); control of the model for potassium but not sodium attenuated the DASH-BP relation. Two common metabolites (hippurate and citrate) mediated the potassium-BP and DASH-BP relationships, while 5 metabolites (succinate, alanine, S-methyl cysteine sulfoxide, 4-hydroxyhippurate, and phenylacetylglutamine) were found to be specific to the DASH-BP relation.

CONCLUSIONS

Greater adherence to the DASH diet is associated with lower BP and higher potassium intake across levels of sodium intake. The DASH diet recommends greater intake of fruits, vegetables, and other potassium-rich foods that may replace sodium-rich processed foods and thereby influence BP through overlapping metabolic pathways. Possible DASH-specific pathways are speculated but confirmation requires further study. INTERMAP is registered as NCT00005271 at www.clinicaltrials.gov.

Metabolic syndrome in rural Peruvian adults living at high altitudes using different cookstoves

This study determined the prevalence of metabolic syndrome (MetS) in open fire stoves and improved cookstoves users (ICS) in the rural Peruvian Andes. Participants answered a socioeconomic questionnaire, one 24-hour food recall and underwent a physical examination. We analysed data from 385 participants, 190 (112 women and 78 men) were ICS users and 195 (123 women and 72 men) were open fire stove users. The prevalence of MetS was 21.3, 26.4% in women and 13.3% in men. We found no statistically significant association between the type of cookstove and MetS. Body mass index and altitude were important determinants of MetS. Research on cardiometabolic diseases and open fire stove use contributes to understanding the effect of household air pollution on health in high altitude populations.

The Biology of Veganism: Plasma Metabolomics Analysis Reveals Distinct Profiles of Vegans and Non-Vegetarians in the Adventist Health Study-2 Cohort

It is unclear how vegetarian dietary patterns influence plasma metabolites involved in biological processes regulating chronic diseases. We sought to identify plasma metabolic profiles distinguishing vegans (avoiding meat, eggs, dairy) from non-vegetarians (consuming ≥28 g/day red meat) of the Adventist Health Study-2 cohort using global metabolomics profiling with ultra-performance liquid chromatography mass spectrometry (UPLC-MS/MS). Differences in abundance of metabolites or biochemical subclasses were analyzed using linear regression models, adjusting for surrogate and confounding variables, with cross-validation to simulate results from an independent sample. Random forest was used as a learning tool for classification, and principal component analysis was used to identify clusters of related metabolites. Differences in covariate-adjusted metabolite abundance were identified in over 60% of metabolites (586/930), after adjustment for false discovery. The vast majority of differentially abundant metabolites or metabolite subclasses showed lower abundance in vegans, including xanthine, histidine, branched fatty acids, acetylated peptides, ceramides, and long-chain acylcarnitines, among others. Many of these metabolite subclasses have roles in insulin dysregulation, cardiometabolic phenotypes, and inflammation. Analysis of metabolic profiles in vegans and non-vegetarians revealed vast differences in these two dietary groups, reflecting differences in consumption of animal and plant products. These metabolites serve as biomarkers of food intake, many with potential pathophysiological consequences for cardiometabolic diseases.

Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health

Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1H NMR spectroscopy in a multicountry study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N-methylnicotinic acid, urea, and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food consumption and also had higher capacity in discriminating children's diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.

The Metabolomic Effects of Tripeptide Gut Hormone Infusion Compared to Roux-en-Y Gastric Bypass and Caloric Restriction

CONTEXT

The gut-derived peptide hormones glucagon-like peptide-1 (GLP-1), oxyntomodulin (OXM), and peptide YY (PYY) are regulators of energy intake and glucose homeostasis and are thought to contribute to the glucose-lowering effects of bariatric surgery.

OBJECTIVE

To establish the metabolomic effects of a combined infusion of GLP-1, OXM, and PYY (tripeptide GOP) in comparison to a placebo infusion, Roux-en-Y gastric bypass (RYGB) surgery, and a very low-calorie diet (VLCD).

DESIGN AND SETTING

Subanalysis of a single-blind, randomized, placebo-controlled study of GOP infusion (ClinicalTrials.gov NCT01945840), including VLCD and RYGB comparator groups.

PATIENTS AND INTERVENTIONS

Twenty-five obese patients with type 2 diabetes or prediabetes were randomly allocated to receive a 4-week subcutaneous infusion of GOP (n = 14) or 0.9% saline control (n = 11). An additional 22 patients followed a VLCD, and 21 underwent RYGB surgery.

MAIN OUTCOME MEASURES

Plasma and urine samples collected at baseline and 4 weeks into each intervention were subjected to cross-platform metabolomic analysis, followed by unsupervised and supervised modeling approaches to identify similarities and differences between the effects of each intervention.

RESULTS

Aside from glucose, very few metabolites were affected by GOP, contrasting with major metabolomic changes seen with VLCD and RYGB.

CONCLUSIONS

Treatment with GOP provides a powerful glucose-lowering effect but does not replicate the broader metabolomic changes seen with VLCD and RYGB. The contribution of these metabolomic changes to the clinical benefits of RYGB remains to be elucidated.