Multi-parameter comparison of a standardized mixed meal tolerance test in healthy and type 2 diabetic subjects: the PhenFlex challenge

Assessing metabolic flexibility response to a multifibre diet: a randomised-controlled trial

INTRODUCTION

Metabolic flexibility (MetF), defined as the ability to switch between fat and glucose oxidation, is increasingly recognised as a critical marker for assessing responses to dietary interventions. Previously, we showed that the consumption of multifibre bread improved insulin sensitivity and reduced low-density lipoprotein cholesterol (LDLc) levels in overweight and obese individuals. As a secondary objective, we aimed to explore whether our intervention could also improve MetF.

METHODS

In this study, 39 subjects at cardiometabolic risk participated in a double-blind, randomised, crossover trial lasting 8 weeks, repeated twice. During each phase, participants consumed either 150 g of standard bread daily or bread enriched with a mixture of seven dietary fibres. MetF response was assessed using a mixed-meal tolerance test (MMTT), analysing changes in respiratory quotient (∆RQ) measured using indirect calorimetry.

RESULTS

Although there were no significant differences in ∆RQ changes induced by dietary fibre between the two diets, these changes were positively correlated with postprandial triglyceride excursion (∆TG) at baseline. Subgroup analysis of baseline fasting and postprandial plasma metabolites was conducted to characterise MetF responders. These responders exhibited higher baseline fasting LDLc levels and greater post-MMTT ∆TG.

CONCLUSION

In conclusion, although dietary fibres did not directly impact MetF in this study, our findings highlight potential determinants of MetF response, warranting further investigation in dedicated future interventions.

A mixed meal tolerance test predicts onset of type 2 diabetes in Southwestern Indigenous adults

BACKGROUND/OBJECTIVE

To identify predictors of incident type 2 diabetes using a mixed meal tolerance test (MMTT).

METHODS

Adult Indigenous Americans without diabetes (n = 501) from a longitudinal cohort underwent at baseline a 4-h MMTT, measures of body composition, an oral glucose tolerance test, an intravenous glucose tolerance test for acute insulin response (AIR), and a hyperinsulinemic-euglycemic clamp for insulin action (M). Plasma glucose responses from the MMTT were quantified by the total and incremental area under the curve (AUC/iAUC).

RESULTS

At follow-up (median time 9.6 [inter-quartile range: 5.6-13.5] years), 169 participants were diagnosed with diabetes. Unadjusted Cox proportional hazards models, glucose AUC180-min (HR: 1.98, 95% CI: 1.67, 2.34, p < 0.0001), AUC240-min (HR: 1.93, 95% CI: 1.62, 2.31, p < 0.0001), and iAUC180-min (HR: 1.43, 95% CI: 1.20, 1.71, p < 0.0001) were associated with an increased risk of diabetes. After adjustment for covariates (age, sex, body fat percentage, M, AIR, Indigenous American heritage) in three subsequent models, AUC180-min (HR: 1.44, 95% CI: 1.10, 1.88, p = 0.007) and AUC240-min (HR: 1.41, 95% CI: 1.09, 1.84, p < 0.01) remained associated with increased risk of diabetes.

CONCLUSIONS

Glucose responses to a mixed meal predicted the development of type 2 diabetes. This indicates that a mixed nutritional challenge provides important information on disease risk.

CLINICAL TRIAL REGISTRY

ClinicalTrials.gov identifier : NCT00340132, NCT00339482.

Impact of fibre supplementation on microbiome and resilience in healthy participants: A randomized, placebo-controlled clinical trial

BACKGROUND AND AIMS

The gut microbiome exerts important roles in health, e.g., functions in metabolism and immunology. These functions are often exerted via short-chain fatty acid (SCFA) production by gut bacteria. Studies demonstrating causal relationships between interventions targeting the microbiome and clinical outcomes are limited. This study aimed to show a causal relationship between microbiome modulation through fibre intervention and health.

METHODS AND RESULTS

This randomized, double-blind, cross-over study included 65 healthy subjects, aged 45-70 years, with increased metabolic risk (i.e., body mass index [BMI] 25-30 kg/m2, low to moderate daily dietary fibre intake, <30g/day). Subjects took daily a fibre mixture of Acacia gum and carrot powder or placebo for 12 weeks, with an 8-week wash-out period. Faecal samples for measurement of SCFAs and microbiome analysis were collected every 4 weeks. Before and after each intervention period subjects underwent the mixed-meal PhenFlex challenge Test (PFT). Health effects were expressed as resilience to the stressors of the PFT and as fasting metabolic and inflammatory state. The fibre mixture exerted microbiome modulation, with an increase in β-diversity (p < 0.001). α-diversity was lower during fibre mixture intake compared to placebo after 4, 8 and 12 weeks (p = 0.002; p = 0.012; p = 0.031). There was no effect observed on faecal SCFA concentrations, nor on any of the primary clinical outcomes (Inflammatory resilience: p = 0.605, Metabolic resilience: p = 0.485).

CONCLUSION

Although the intervention exerted effects on gut microbiome composition, no effects on SCFA production, on resilience or fasting metabolic and inflammatory state were observed in this cohort. REGISTRATION NUMBER CLINICALTRIALS.GOV: NCT04829396.

Characterizing human postprandial metabolic response using multiway data analysis

INTRODUCTION

Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time.

OBJECTIVES

Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles.

METHODS

We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences.

RESULTS

Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state.

CONCLUSION

The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models

The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and β-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.

Human metabolic chambers reveal a coordinated metabolic-physiologic response to nutrition

The emerging field of precision nutrition is based on the notion that inter-individual responses across diets of different calorie-macronutrient content may contribute to inter-individual differences in metabolism, adiposity, and weight gain. Free-living diet studies have been traditionally challenged by difficulties in controlling adherence to prescribed calories and macronutrient content and rarely allow a period of metabolic stability prior to metabolic measures (to minimize influences of weight changes). In this context, key physiologic measures central to precision nutrition responses may be most precisely quantified via whole room indirect calorimetry over 24-h, in which precise control of activity and nutrition can be achieved. In addition, these studies represent unique "N of 1" human crossover metabolic-physiologic experiments during which specific molecular pathways central to nutrient metabolism may be discerned. Here, we quantified 263 circulating metabolites during a ≈40-day inpatient admission in which up to 94 participants underwent seven monitored 24-h nutritional interventions of differing macronutrient composition in a whole-room indirect calorimeter to capture precision metabolic responses. Broadly, we observed heterogenous responses in metabolites across dietary chambers, with the exception of carnitines which tracked with 24-h respiratory quotient. We identified excursions in shared metabolic species (e.g., carnitines, glycerophospholipids, amino acids) that mapped onto gold-standard calorimetric measures of substrate oxidation preference and lipid availability. These findings support a coordinated metabolic-physiologic response to nutrition, highlighting the relevance of these controlled settings to uncover biological pathways of energy utilization during precision nutrition studies.

Higher glucose and insulin responses to a mixed meal are associated with increased risk of diabetic retinopathy in Indigenous Americans

PURPOSE

Prior research has focused on glucose/insulin responses to meal challenges to create personalized diets to improve health, though it is unclear if these responses predict chronic diseases. We aimed to identify glucose and insulin responses to a mixed meal tolerance test (MMTT) that predict the development of diabetic retinopathy (DR) and compare the predictive abilities with the oral glucose tolerance test (OGTT).

METHODS

Indigenous American adults without diabetes (n = 168) underwent a 4-h MMTT, body composition assessment, and a 3-h OGTT at baseline. During follow-up (median 13.4 years), DR was diagnosed by direct ophthalmoscopy (n = 28) after onset of type 2 diabetes. Total and incremental area under the curve (AUC and iAUC) were calculated from glucose/insulin responses after the MMTT and OGTT.

RESULTS

In separate Cox proportional hazards models adjusted for age, sex, and body fat (%), MMTT glucose AUCs (180-min and 240-min) and iAUC (180-min) predicted DR (HR 1.50, 95% CI 1.06, 2.12; HR 1.50, 95% CI 1.05, 2.14; HR 1.58, 95% CI 1.01, 2.46). The predictive abilities were better than the fasting OGTT glucose (p < 0.01) but similar to the 120-min OGTT glucose (p = 0.53). MMTT insulin AUCs (180-min and 240-min) and iAUC (180-min) also predicted DR (HR 1.65, 95% CI 1.09, 2.51; HR 1.58, 95% CI 1.00, 2.35; HR 1.53 95% CI 1.06, 2.22) while insulin AUC and iAUC from the OGTT did not (p > 0.05).

CONCLUSIONS

Higher MMTT glucose and insulin responses predicted DR and were comparable to the OGTT, supporting the use of a meal challenge for precision nutrition.

TRIAL REGISTRATIONS

Clinical Trial Registry: ClinicalTrials.gov identifier: NCT00340132, NCT00339482.

Perspective: Council for Responsible Nutrition Science in Session. Optimizing Health with Nutrition-Opportunities, Gaps, and the Future

Achieving optimal health is an aspirational goal for the population, yet the definition of health remains unclear. The role of nutrition in health has evolved beyond correcting malnutrition and specific deficiencies and has begun to focus more on achieving and maintaining 'optimal' health through nutrition. As such, the Council for Responsible Nutrition held its October 2022 Science in Session conference to advance this concept. Here, we summarize and discuss the findings of their Optimizing Health through Nutrition - Opportunities and Challenges workshop, including several gaps that need to be addressed to advance progress in the field. Defining and evaluating various indices of optimal health will require overcoming these key gaps. For example, there is a strong need to develop better biomarkers of nutrient status, including more accurate markers of food intake, as well as biomarkers of optimal health that account for maintaining resilience-the ability to recover from or respond to stressors without loss to physical and cognitive performance. In addition, there is a need to identify factors that drive individualized responses to nutrition, including genotype, metabotypes, and the gut microbiome, and to realize the opportunity of precision nutrition for optimal health. This review outlines hallmarks of resilience, provides current examples of nutritional factors to optimize cognitive and performance resilience, and gives an overview of various genetic, metabolic, and microbiome determinants of individualized responses.

Phenotypic flexibility in nutrition research to quantify human variability: building the bridge to personalised nutrition

Phenotypic flexibility is a methodology that accurately assesses health in terms of mechanistic understanding of the interrelationship of multiple metabolic and physiological processes. This starts from the perspective that a healthy person is better able to cope with changes in environmental stressors that affect homeostasis compared to people with a compromised health state. The term 'phenotypic flexibility' expresses the cumulative ability of overarching physiological processes to return to homeostatic levels after short-term perturbations. The concept of phenotypic flexibility to define biomarkers for nutrition-related health was introduced in 2009 in the area of health optimisation and prevention and delay of non-communicable disease. The core approach consists of the combination of imposing a challenge test to the body followed by time-resolved analysis of multiple biomarkers. This new approach may better facilitate nutritional health research in intervention studies since it may show effects on early derailed physiological markers and the biomarker response can be extended by perturbing the system, thereby making them more sensitive in detecting health effects from food and nutrition. At the same time, interindividual variation can also be extended and compressed by challenge tests, facilitating the bridge to personalised nutrition. This review will overview where the science is in this research arena and what the phenotypic flexibility potential is for the nutrition field.

The entero-endocrine response following a mixed-meal tolerance test with a non-nutritive pre-load in participants with pre-diabetes and type 2 diabetes: A crossover randomized controlled trial proof of concept study

INTRODUCTION

This crossover randomized controlled trial (RCT) investigated differences in short-term entero-endocrine response to a mixed-meal tolerance test preceded by nutrient sensing between participants with pre-diabetes (pre-T2D) and type 2 diabetes (T2D). Additionally, differences in gut and oral microbiome composition between participants with a high and low entero-endocrine response were investigated.

RESEARCH DESIGN AND METHODS

Ten participants with pre-T2D and ten with T2D underwent three test days with pre-loads consisting of either swallowing water (control), or rinsing with a non-nutritive sweetener solution, or swallowing the sweetener solution before a mixed-meal tolerance test. Blood glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), glucagon, glucose, insulin and peptide YY (PYY) were determined at t = -20, 0, 15, 30, 60, 120 and 240 minutes. The composition of the oral and gut microbiome at baseline were also determined.

RESULTS

The entero-endocrine response differed by pre-loads, e.g. a lower PYY response after swallowing the non-nutritive sweetener (-3585.2pg/mL [95% CI: -6440.6; -729.8]; p = 0.01). But it also differed by T2D status, e.g. a higher glucose, glucagon and PYY response was found in participants with T2D, compared to those with pre-T2D. Evidence for associations between the oral and gut microbiome composition and the entero-endocrine response was limited. Still, the level of entero-endocrine response was associated with several oral microbiome measures. Higher oral anterior α-diversity was associated with a lower PYY response (e.g. Inverse Simpson index -1357pg/mL [95% CI -2378; -336; 1.24]), and higher oral posterior α-diversitywith a higher GIP response (e.g. Inverse Simpson index 6773pg/mL [95% CI 132; 13414]) in models adjusted for sex, age and T2D status.

CONCLUSIONS

Non-nutritive pre-loads influence the entero-endocrine response to a mixed-meal, and this effect varies based on (pre-)T2D status. The entero-endocrine response is likely not associated with the gut microbiome, and there is limited evidence for association with the α-diversity of the oral microbiome composition.

TRIAL REGISTRATION

Trial register: Netherlands Trial Register NTR7212, accessible through International Clinical Trials Registry Platform: ICTRP Search Portal (who.int).

The beneficial effect of sulforaphane on platelet responsiveness during caloric load: a single-intake, double-blind, placebo-controlled, crossover trial in healthy participants

Background and aims

As our understanding of platelet activation in response to infections and/or inflammatory conditions is growing, it is becoming clearer that safe, yet efficacious, platelet-targeted phytochemicals could improve public health beyond the field of cardiovascular diseases. The phytonutrient sulforaphane shows promise for clinical use due to its effect on inflammatory pathways, favorable pharmacokinetic profile, and high bioavailability. The potential of sulforaphane to improve platelet functionality in impaired metabolic processes has however hardly been studied in humans. This study investigated the effects of broccoli sprout consumption, as a source of sulforaphane, on urinary 11-dehydro-thromboxane B₂ (TXB₂), a stable thromboxane metabolite used to monitor eicosanoid biosynthesis and response to antithrombotic therapy, in healthy participants exposed to caloric overload.

Methods

In this double-blind, placebo-controlled, crossover trial 12 healthy participants were administered 16g of broccoli sprouts, or pea sprouts (placebo) followed by the standardized high-caloric drink PhenFlex given to challenge healthy homeostasis. Urine samples were collected during the study visits and analyzed for 11-dehydro-TXB₂, sulforaphane and its metabolites. Genotyping was performed using Illumina GSA v3.0 DTCBooster.

Results

Administration of broccoli sprouts before the caloric load reduced urinary 11-dehydro-TXB₂ levels by 50% (p = 0.018). The amount of sulforaphane excreted in the urine during the study visits correlated negatively with 11-dehydro-TXB₂ (r_s = -0.377, p = 0.025). Participants carrying the polymorphic variant NAD(P)H dehydrogenase quinone 1 (NQO1*2) showed decreased excretion of sulforaphane (p = 0.035).

Conclusion

Sulforaphane was shown to be effective in targeting platelet responsiveness after a single intake. Our results indicate an inverse causal relationship between sulforaphane and 11-dehydro-TXB₂, which is unaffected by the concomitant intake of the metabolic challenge. 11-Dehydro-TXB₂ shows promise as a non-invasive, sensitive, and suitable biomarker to investigate the effects of phytonutrients on platelet aggregation within hours.

Clinical trial registration

[https://clinicaltrials.gov/], identifier [NCT05146804].

The effects of early short-term insulin treatment vs. glimepiride on beta cell function in newly diagnosed type 2 diabetes with HbA1c above 9

BACKGROUND

Type 2 diabetes mellitus (T2D) is a complex metabolic impairment. Beta cell (BC) failure is the most challenging among its pathogenetic mechanisms. Recognizing reversible contributors to BC failure could guide individualized approach to early T2D treatment. The aim of this study was to compare early short-term insulin treatment vs. glimepiride, both added to metformin, on BC function, glycemic and lipid control, during 12-month follow-up.

METHODS

Eighty newly diagnosed T2D patients, 30-65 years of age, presenting with HbA1c ≥ 9% were enrolled in the study. They were randomly assigned to single-month initial insulin therapy (INS) added to metformin, or to glimepiride and metformin (OAD) as only treatment. Subjects assigned to initial insulin intervention were thereafter switched to OAD. C-peptide (C-Pep) was analyzed at baseline and 2 hours after standardized test meal (STM). All subjects were STM-retested after 3 and 12 months. HbA1c, serum lipids, BMI, HOMA IR, and HOMA B were assessed over follow-up.

RESULTS

HbA1c was lower in INS vs OAD at 3-months: 6.26 ± 0.18% vs 6.78 ± 0.10% (p = 0.016), remaining so by 12 months (p =0.056). BMI-adjusted ΔC-Pep was greater in INS vs. OAD at 3 months (4.60 ± 0.59 vs. 3.21 ± 0.34 m2 /kg; p = 0.044), persisting by 12months (4.57 ± 0.56 vs. 3.04 ± 0.34 m2/kg; p = 0.023). Average ΔC-Pep improvement from recruitment to 3 months was 100.8% in INS,vs. 51.3% in OAD. Prevalence of STM-ΔC-Pep response greater than 2.4 ng/mL had risen 3.2-fold by 12 months in the INS, vs. 2.4-fold only in the OAD group (p = 0.018).

DISCUSSION

Early short-term insulin intervention in newly diagnosed T2D improves beta cell function more than glimepiride, both added to metformin, resulting in a superior and longer lasting glycemic and lipid control.

Mixed meal tolerance testing highlights in diabetes altered branched-chain ketoacid metabolism and pathways associated with all-cause mortality

BACKGROUND

Elevated BCAA levels are strongly associated with diabetes, but how diabetes affects BCAA, branched-chain ketoacids (BCKAs), and the broader metabolome after a meal is not well known.

OBJECTIVE

To compare quantitative BCAA and BCKA levels in a multiracial cohort with and without diabetes after a mixed meal tolerance test (MMTT) as well as to explore the kinetics of additional metabolites and their associations with mortality in self-identified African Americans.

METHODS

We administered an MMTT to 11 participants without obesity or diabetes and 13 participants with diabetes (treated with metformin only) and measured the levels of BCKAs, BCAAs, and 194 other metabolites at 8 time points across 5 h. We used mixed models for repeated measurements to compare between group metabolite differences at each timepoint with adjustment for baseline. We then evaluated the association of top metabolites with different kinetics with all-cause mortality in the Jackson Heart Study (JHS) (N = 2441).

RESULTS

BCAA levels, after adjustment for baseline, were similar at all timepoints between groups, but adjusted BCKA kinetics were different between groups for α-ketoisocaproate (P = 0.022) and α-ketoisovalerate (P = 0.021), most notably diverging at 120 min post-MMTT. An additional 20 metabolites had significantly different kinetics across timepoints between groups, and 9 of these metabolites-including several acylcarnitines-were significantly associated with mortality in JHS, irrespective of diabetes status. The highest quartile of a composite metabolite risk score was associated with higher mortality (HR:1.57; 1.20, 2.05, P = 0.00094) than the lowest quartile.

CONCLUSIONS

BCKA levels remained elevated after an MMTT among participants with diabetes, suggesting that BCKA catabolism may be a key dysregulated process in the interaction of BCAA and diabetes. Metabolites with different kinetics after an MMTT may be markers of dysmetabolism and associated with increased mortality in self-identified African Americans.

Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.

Dynamic patterns of postprandial metabolic responses to three dietary challenges

Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis (ASCA) was conducted, revealing that the inter-individual variability accounted for 30 % of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

Chitin-glucan supplementation improved postprandial metabolism and altered gut microbiota in subjects at cardiometabolic risk in a randomized trial

Chitin-glucan (CG), an insoluble dietary fiber, has been shown to improve cardiometabolic disorders associated with obesity in mice. Its effects in healthy subjects has recently been studied, revealing its interaction with the gut microbiota. In this double-blind, randomized, cross-over, twice 3-week exploratory study, we investigated the impacts of CG on the cardiometabolic profile and gut microbiota composition and functions in 15 subjects at cardiometabolic risk. They consumed as a supplement 4.5 g of CG daily or maltodextrin as control. Before and after interventions, fasting and postprandial metabolic parameters and exhaled gases (hydrogen [H2] and methane [CH4]) were evaluated. Gut microbiota composition (16S rRNA gene sequencing analysis), fecal concentrations of bile acids, long- and short-chain fatty acids (LCFA, SCFA), zonulin, calprotectin and lipopolysaccharide binding protein (LBP) were analyzed. Compared to control, CG supplementation increased exhaled H2 following an enriched-fiber breakfast ingestion and decreased postprandial glycemia and triglyceridemia response to a standardized test meal challenge served at lunch. Of note, the decrease in postprandial glycemia was only observed in subjects with higher exhaled H2, assessed upon lactulose breath test performed at inclusion. CG decreased a family belonging to Actinobacteria phylum and increased 3 bacterial taxa: Erysipelotrichaceae UCG.003, Ruminococcaceae UCG.005 and Eubacterium ventriosum group. Fecal metabolites, inflammatory and intestinal permeability markers did not differ between groups. In conclusion, we showed that CG supplementation modified the gut microbiota composition and improved postprandial glycemic response, an early determinant of cardiometabolic risk. Our results also suggest breath H2 production as a non-invasive parameter of interest for predicting the effectiveness of dietary fiber intervention.

Assessing Insulin Sensitivity and Postprandial Triglyceridemic Response Phenotypes With a Mixed Macronutrient Tolerance Test

The use of meal challenge tests to assess postprandial responses in carbohydrate and fat metabolism is well established in clinical nutrition research. However, challenge meal compositions and protocols remain a variable. Here, we validated a mixed macronutrient tolerance test (MMTT), containing 56-g palm oil, 59-g sucrose, and 26-g egg white protein for the parallel determination of insulin sensitivity and postprandial triglyceridemia in clinically healthy subjects. The MMTT was administered in two study populations. In one, women with overweight/obese BMIs (n = 43) involved in an 8-week dietary intervention were administered oral glucose tolerance tests (OGTTs) and MMTTs within 2 days of each other after 0, 2, and 8 weeks of the dietary intervention. In the other, 340 men and women between 18 and 64 years of age, with BMI from 18–40 kg/m2, completed the MMTT as part of a broad nutritional phenotyping effort. Postprandial blood collected at 0, 0.5, 3, and 6 h was used to measure glucose, insulin, and clinical lipid panels. The MMTT postprandial insulin-dependent glucose disposal was evaluated by using the Matsuda Index algorithm and the 0- and 3 h blood insulin and glucose measures. The resulting MMTT insulin sensitivity index (ISIMMTT) was strongly correlated (r = 0.77, p &lt; 0.001) with the OGTT-dependent 2 h composite Matsuda index (ISIComposite), being related by the following equation: Log (ISIComposite) = [0.8751 x Log(ISIMMTT)] –0.2115. An area under the triglyceride excursion curve &gt;11.15 mg/mL h–1 calculated from the 0, 3, and 6 h blood draws established mild-to-moderate triglyceridemia in agreement with ∼20% greater prevalence of hypertriglyceridemia than fasting indications. We also demonstrated that the product of the 0 to 3 h and 3 to 6 h triglyceride rate of change as a function of the triglyceride incremental area under the curve optimally stratified subjects by postprandial response patterns. Notably, ∼2% of the population showed minimal triglyceride appearance by 6 h, while ∼25% had increasing triglycerides through 6 h. Ultimately, using three blood draws, the MMTT allowed for the simultaneous determination of insulin sensitivity and postprandial triglyceridemia in individuals without clinically diagnosed disease.

Clinical Trial Registration

[https://clinicaltrials.gov/], identifier [NCT02298725; NCT02367287].

Effects of a 13-Week Personalized Lifestyle Intervention Based on the Diabetes Subtype for People with Newly Diagnosed Type 2 Diabetes

A type 2 diabetes mellitus (T2DM) subtyping method that determines the T2DM phenotype based on an extended oral glucose tolerance test is proposed. It assigns participants to one of seven subtypes according to their β-cell function and the presence of hepatic and/or muscle insulin resistance. The effectiveness of this subtyping approach and subsequent personalized lifestyle treatment in ameliorating T2DM was assessed in a primary care setting. Sixty participants, newly diagnosed with (pre)diabetes type 2 and not taking diabetes medication, completed the intervention. Retrospectively collected data of 60 people with T2DM from usual care were used as controls. Bodyweight (p < 0.01) and HbA1c (p < 0.01) were significantly reduced after 13 weeks in the intervention group, but not in the usual care group. The intervention group achieved 75.0% diabetes remission after 13 weeks (fasting glucose ≤ 6.9 mmol/L and HbA1c < 6.5% (48 mmol/mol)); for the usual care group, this was 22.0%. Lasting (two years) remission was especially achieved in subgroups with isolated hepatic insulin resistance. Our study shows that a personalized diagnosis and lifestyle intervention for T2DM in a primary care setting may be more effective in improving T2DM-related parameters than usual care, with long-term effects seen especially in subgroups with hepatic insulin resistance.

Investigating the Postprandial Metabolome after Challenge Tests to Assess Metabolic Flexibility and Dysregulations Associated with Cardiometabolic Diseases

This review focuses on the added value provided by a research strategy applying metabolomics analyses to assess phenotypic flexibility in response to different nutritional challenge tests in the framework of metabolic clinical studies. We discuss findings related to the Oral Glucose Tolerance Test (OGTT) and to mixed meals with varying fat contents and food matrix complexities. Overall, the use of challenge tests combined with metabolomics revealed subtle metabolic dysregulations exacerbated during the postprandial period when comparing healthy and at cardiometabolic risk subjects. In healthy subjects, consistent postprandial metabolic shifts driven by insulin action were reported (e.g., a switch from lipid to glucose oxidation for energy fueling) with similarities between OGTT and mixed meals, especially during the first hours following meal ingestion while differences appeared in a wider timeframe. In populations with expected reduced phenotypic flexibility, often associated with increased cardiometabolic risk, a blunted response on most key postprandial pathways was reported. We also discuss the most suitable statistical tools to analyze the dynamic alterations of the postprandial metabolome while accounting for complexity in study designs and data structure. Overall, the in-depth characterization of the postprandial metabolism and associated phenotypic flexibility appears highly promising for a better understanding of the onset of cardiometabolic diseases.

Exploring dynamic metabolomics data with multiway data analysis: a simulation study

BACKGROUND

Analysis of dynamic metabolomics data holds the promise to improve our understanding of underlying mechanisms in metabolism. For example, it may detect changes in metabolism due to the onset of a disease. Dynamic or time-resolved metabolomics data can be arranged as a three-way array with entries organized according to a subjects mode, a metabolites mode and a time mode. While such time-evolving multiway data sets are increasingly collected, revealing the underlying mechanisms and their dynamics from such data remains challenging. For such data, one of the complexities is the presence of a superposition of several sources of variation: induced variation (due to experimental conditions or inborn errors), individual variation, and measurement error. Multiway data analysis (also known as tensor factorizations) has been successfully used in data mining to find the underlying patterns in multiway data. To explore the performance of multiway data analysis methods in terms of revealing the underlying mechanisms in dynamic metabolomics data, simulated data with known ground truth can be studied.

RESULTS

We focus on simulated data arising from different dynamic models of increasing complexity, i.e., a simple linear system, a yeast glycolysis model, and a human cholesterol model. We generate data with induced variation as well as individual variation. Systematic experiments are performed to demonstrate the advantages and limitations of multiway data analysis in analyzing such dynamic metabolomics data and their capacity to disentangle the different sources of variations. We choose to use simulations since we want to understand the capability of multiway data analysis methods which is facilitated by knowing the ground truth.

CONCLUSION

Our numerical experiments demonstrate that despite the increasing complexity of the studied dynamic metabolic models, tensor factorization methods CANDECOMP/PARAFAC(CP) and Parallel Profiles with Linear Dependences (Paralind) can disentangle the sources of variations and thereby reveal the underlying mechanisms and their dynamics.

Effect of Mori ramulus on the postprandial blood glucose levels and inflammatory responses of healthy subjects subjected to an oral high-fat/sucrose challenge: A double-blind, randomized, crossover clinical trial

Blood glucose is inadequately controlled in diabetes mellitus, causing various inflammation-related complications. This study aimed to investigate responses to an oral sucrose/lipid challenge in the context of glucose metabolism after consumption of Mori ramulus (MR) extract. In this study on healthy subjects, the optimal dose and safety of MR were confirmed in a preliminary pilot trial (n = 24), meanwhile, blood glucose, insulin, and inflammatory marker levels were detected via an oral sucrose/lipid tolerance test in the main trial (n = 36). In the main study, the blood glucose response was significantly decreased after 240 min in the MR group. Compared to the placebo group, the treatment group exhibited plasma insulin levels that were significantly increased at 120 min and decreased at 240 min. In conclusion, a single MR extract dose protects against inflammation induced by high-fat/sugar to maintain normal insulin secretion and thus helps to maintain postprandial blood glucose levels via an inflammatory mechanism.

Clinical- and omics-based models of subclinical atherosclerosis in healthy Chinese adults: a cross-sectional exploratory study

BACKGROUND

Classical risk factors, such as fasting cholesterol, blood pressure (BP), and diabetes status are used today to predict the risk of developing cardiovascular disease (CVD). However, accurate prediction remains limited, particularly in low-risk groups such as women and younger individuals. Growing evidence suggests that biomarker concentrations following consumption of a meal challenge are better and earlier predictors of disease development than biomarker concentrations.

OBJECTIVE

To test the hypothesis that postprandial responses of circulating biomarkers differ between healthy subjects with and without subclinical atherosclerosis (SA) in an Asian population at low risk of coronary artery disease (CAD).

METHODS

One hundred healthy Chinese subjects (46 women, 54 men) completed the study. Subjects consumed a mixed-meal test and 164 blood biomarkers were analyzed over 6 h by using a combination of chemical and NMR techniques. Models were trained using different methodologies (including logistic regression, elastic net, random forest, sparse partial least square) on a random 75% subset of the data, and their performance was evaluated on the remaining 25%.

RESULTS

We found that models based on baseline clinical parameters or fasting biomarkers could not reliably predict SA. By contrast, an omics model based on magnitude and timing of postprandial biomarkers achieved high performance [receiving operating characteristic (ROC) AUC: 91%; 95% CI: 77, 100). Investigation of key features of this model enabled derivation of a considerably simpler model, solely based on postprandial BP and age, with excellent performance (AUC: 91%; 95% CI: 78, 100).

CONCLUSION

We report a novel model to detect SA based on postprandial BP and age in a population of Asian subjects at low risk of CAD. The use of this model in large-scale CVD prevention programs should be explored. This trial was registered at ClinicalTrials.gov as NCT03531879.

Digital Resilience Biomarkers for Personalized Health Maintenance and Disease Prevention

Health maintenance and disease prevention strategies become increasingly prioritized with increasing health and economic burden of chronic, lifestyle-related diseases. A key element in these strategies is the empowerment of individuals to control their health. Self-measurement plays an essential role in achieving such empowerment. Digital measurements have the advantage of being measured non-invasively, passively, continuously, and in a real-world context. An important question is whether such measurement can sensitively measure subtle disbalances in the progression toward disease, as well as the subtle effects of, for example, nutritional improvement. The concept of resilience biomarkers, defined as the dynamic evaluation of the biological response to an external challenge, has been identified as a viable strategy to measure these subtle effects. In this review, we explore the potential of integrating this concept with digital physiological measurements to come to digital resilience biomarkers. Additionally, we discuss the potential of wearable, non-invasive, and continuous measurement of molecular biomarkers. These types of innovative measurements may, in the future, also serve as a digital resilience biomarker to provide even more insight into the personal biological dynamics of an individual. Altogether, digital resilience biomarkers are envisioned to allow for the measurement of subtle effects of health maintenance and disease prevention strategies in a real-world context and thereby give personalized feedback to improve health.

Serum metabolomic biomarkers of perceptual speed in cognitively normal and mildly impaired subjects with fasting state stratification

Cognitive decline is associated with both normal aging and early pathologies leading to dementia. Here we used quantitative profiling of metabolites involved in the regulation of inflammation, vascular function, neuronal function and energy metabolism, including oxylipins, endocannabinoids, bile acids, and steroid hormones to identify metabolic biomarkers of mild cognitive impairment (MCI). Serum samples (n = 212) were obtained from subjects with or without MCI opportunistically collected with incomplete fasting state information. To maximize power and stratify the analysis of metabolite associations with MCI by the fasting state, we developed an algorithm to predict subject fasting state when unknown (n = 73). In non-fasted subjects, linoleic acid and palmitoleoyl ethanolamide levels were positively associated with perceptual speed. In fasted subjects, soluble epoxide hydrolase activity and tauro-alpha-muricholic acid levels were negatively associated with perceptual speed. Other cognitive domains showed associations with bile acid metabolism, but only in the non-fasted state. Importantly, this study shows unique associations between serum metabolites and cognitive function in the fasted and non-fasted states and provides a fasting state prediction algorithm based on measurable metabolites.

Advantages of Studying the Metabolome in Response to Mixed-Macronutrient Challenges and Suggestions for Future Research Designs

Evaluating the postprandial response to a dietary challenge containing all macronutrients-carbohydrates, lipids, and protein-may provide stronger insights of metabolic health than a fasted measurement. Metabolomic profiling deepens the understanding of the homeostatic and adaptive response to a dietary challenge by classifying multiple metabolic pathways and biomarkers. A total of 26 articles were identified that measure the human blood metabolome or lipidome response to a mixed-macronutrient challenge. Most studies were cross-sectional, exploring the baseline and postprandial response to the dietary challenge. Large variations in study designs were reported, including the macronutrient and caloric composition of the challenge and the delivery of the challenge as a liquid shake or a solid meal. Most studies utilized a targeted metabolomics platform, assessing only a particular metabolic pathway, however, several studies utilized global metabolomics and lipidomics assays demonstrating the expansive postprandial response of the metabolome. The postprandial response of individual amino acids was largely dependent on the amino acid composition of the test meal, with the exception of alanine and proline, 2 nonessential amino acids. Long-chain fatty acids and unsaturated long-chain acylcarnitines rapidly decreased in response to the dietary challenges, representing the switch from fat to carbohydrate oxidation. Studies were reviewed that assessed the metabolome response in the context of obesity and metabolic diseases, providing insight on how weight status and disease influence the ability to cope with a nutrient load and return to homeostasis. Results demonstrate that the flexibility to respond to a substrate load is influenced by obesity and metabolic disease and flexibility alterations will be evident in downstream metabolites of fat, carbohydrate, and protein metabolism. In response, we propose suggestions for standardization between studies with the potential of creating a study exploring the postprandial response to a multitude of challenges with a variety of macronutrients.

The Effect of a Lifestyle Intervention on Type 2 Diabetes Pathophysiology and Remission: The Stevenshof Pilot Study

Although lifestyle interventions can lead to diabetes remission, it is unclear to what extent type 2 diabetes (T2D) remission alters or improves the underlying pathophysiology of the disease. Here, we assess the effects of a lifestyle intervention on T2D reversal or remission and the effects on the underlying pathology. In a Dutch primary care setting, 15 adults with an average T2D duration of 13.4 years who were (pharmacologically) treated for T2D received a diabetes subtyping ("diabetyping") lifestyle intervention (DLI) for six months, aiming for T2D remission. T2D subtype was determined based on an OGTT. Insulin and sulphonylurea (SU) derivative treatment could be terminated for all participants. Body weight, waist/hip ratio, triglyceride levels, HbA1c, fasting, and 2h glucose were significantly improved after three and six months of intervention. Remission and reversal were achieved in two and three participants, respectively. Indices of insulin resistance and beta cell capacity improved, but never reached healthy values, resulting in unchanged T2D subtypes. Our study implies that achieving diabetes remission in individuals with a longer T2D duration is possible, but underlying pathology is only minimally affected, possibly due to an impaired beta cell function. Thus, even when T2D remission is achieved, patients need to continue adhering to lifestyle therapy.

Healthy eating index patterns in adults by sex and age predict cardiometabolic risk factors in a cross-sectional study

BACKGROUND

Associations between diet and cardiometabolic disease (CMD) risk may vary in men and women owing to sex differences in eating habits and physiology. The current secondary analysis sought to determine the ability of sex differences in dietary patterns to discriminate groups with or without CMD risk factors (CMDrf) in the adult population and if this was influenced by age.

METHODS

Diet patterns and quality were evaluated using 24 h recall-based Healthy Eating Index (HEI-2015) in free-living apparently healthy men (n = 184) and women (n = 209) 18-65 y of age with BMIs of 18-44 kg/m2. Participants were stratified into low- and high-CMDrf groups based on the presence/absence of at least one CMDrf: BMI > 25 kg/m2; fasting triglycerides > 150 mg/dL; HDL cholesterol < 50 mg/dL-women or < 40 mg/dL-men; HOMA > 2; HbA1c > 5.7. Sex by age dietary patterns were stratified by multivariate analyses, with metabolic variable associations established by stepwise discriminant analysis.

RESULTS

Diet quality increased with age in both sexes (P < 0.01), while women showed higher fruit, vegetable and saturated fat intake as a percentage of total energy (P < 0.05). The total-HEI score (i.e. diet quality) was lower in the high-CMDrf group (P = 0.01), however, diet quality parameters predicted CMDrf presence more accurately when separated by sex. Lower 'total vegetable' intake in the high-CMDrf group in both sexes, while high-CMDrf men also had lower 'total vegetables', 'greens and beans' intake, and high-CMDrf women had lower 'total fruits', 'whole-fruits', 'total vegetables', 'seafood and plant-proteins', 'fatty acids', and 'saturated fats' intakes (P < 0.05). Moreover, 'dairy' intake was higher in high-CMDrf women but not in men (sex by 'dairy' interaction P = 0.01). Sex by age diet pattern models predicted CMDrf with a 93 and 89% sensitivity and 84 and 92% specificity in women and men, respectively.

CONCLUSIONS

Sex and age differences in dietary patterns classified participants with and without accepted CMDrfs, supporting an association between specific diet components and CMD risk that differs by sex. Including sex specific dietary patterns into health assessments may provide targeted nutritional guidance to reduce the burden of cardiovascular disease.

TRIAL REGISTRATION

ClinicalTrials.gov : NCT02367287 . ClinicalTrials.gov : NCT02298725 .

Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity

Although the composition of the human blood metabolome is influenced both by the health status of the organism and its dietary behavior, the interaction between these two factors has been poorly characterized. This study makes use of a previously published randomized controlled crossover acute intervention to investigate whether the blood metabolome of 15 healthy normal weight (NW) and 17 obese (OB) men having ingested three doses (500, 1000, 1500 kcal) of a high-fat (HF) meal can be used to identify metabolites differentiating these two groups. Among the 1024 features showing a postprandial response, measured between 0 h and 6 h, in the NW group, 135 were dose-dependent. Among these 135 features, 52 had fasting values that were significantly different between NW and OB men, and, strikingly, they were all significantly higher in OB men. A subset of the 52 features was identified as amino acids (e.g., branched-chain amino acids) and amino acid derivatives. As the fasting concentration of most of these metabolites has already been associated with metabolic dysfunction, we propose that challenging normal weight healthy subjects with increasing caloric doses of test meals might allow for the identification of new fasting markers associated with obesity.

Effects of mixed meal tolerance test on gastric emptying, glucose and lipid homeostasis in obese nonhuman primates

Meal ingestion elicits a variety of neuronal, physiological and hormonal responses that differ in healthy, obese or diabetic individuals. The mixed meal tolerance test (MMTT) is a well-established method to evaluate pancreatic β-cell reserve and glucose homeostasis in both preclinical and clinical research in response to calorically defined meal. Nonhuman primates (NHPs) are highly valuable for diabetic research as they can naturally develop type 2 diabetes mellitus (T2DM) in a way similar to the onset and progression of human T2DM. The purpose of this study was to investigate the reproducibility and effects of a MMTT containing acetaminophen on plasma glucose, insulin, C-peptide, incretin hormones, lipids, acetaminophen appearance (a surrogate marker for gastric emptying) in 16 conscious obese cynomolgus monkeys (Macaca fascicularis). Plasma insulin, C-peptide, TG, aGLP-1, tGIP, PYY and acetaminophen significantly increased after meal/acetaminophen administration. A subsequent study in 6 animals showed that the changes of plasma glucose, insulin, C-peptide, lipids and acetaminophen were reproducible. There were no significant differences in responses to the MMTT among the obese NHPs with (n = 11) or without (n = 5) hyperglycemia. Our results demonstrate that mixed meal administration induces significant secretion of several incretins which are critical for maintaining glucose homeostasis. In addition, the responses to the MMTTs are reproducible in NHPs, which is important when the MMTT is used for evaluating post-meal glucose homeostasis in research.

A Novel Personalized Systems Nutrition Program Improves Dietary Patterns, Lifestyle Behaviors and Health-Related Outcomes: Results from the Habit Study

Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (-256.2 kcal; p < 0.0001), carbohydrates (-22.1 g; p < 0.0039), sugar (-13.0 g; p < 0.0001), total fat (-17.3 g; p < 0.0001), saturated fat (-5.9 g; p = 0.0003) and PUFA (-2.5 g; p = 0.0065). Additionally, BMI (-0.6 kg/m2; p < 0.0001), body fat (-1.2%; p = 0.0192) and hip circumference (-5.8 cm; p < 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body's ability to adapt to environmental stressors, LDL (-0.44 mmol/L; p = 0.002) and total cholesterol (-0.49 mmol/L; p < 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups.

Changes in Plasma Metabolome Profiles Following Oral Glucose Challenge among Adult Chinese

Little is known about changes in plasma metabolome profiles during the oral glucose tolerance test (OGTT) in Chinese. We aimed to characterize plasma metabolomic profiles at 0 and 2 h of OGTT and their changes in individuals of different glycemic statuses. A total of 544 metabolites were detected at 0 and 2 h of OGTT by a nontarget strategy in subjects with normal glucose (n = 234), prediabetes (n = 281), and newly diagnosed type 2 diabetes (T2D) (n = 66). Regression model, mixed model, and partial least squares discrimination analysis were applied. Compared with subjects of normal glucose, T2D cases had significantly higher levels of glycerone at 0 h and 22 metabolites at 2 h of OGTT (false discovery rate (FDR) < 0.05, variable importance in projection (VIP) > 1). Seven of the twenty-two metabolites were also significantly higher in T2D than in prediabetes subjects at 2 h of OGTT (FDR < 0.05, VIP > 1). Two hours after glucose challenge, concentrations of 35 metabolites (normal: 18; prediabetes: 23; T2D: 13) significantly increased (FDR < 0.05, VIP > 1, fold change (FC) > 1.2), whereas those of 45 metabolites (normal: 36; prediabetes: 29; T2D: 18) significantly decreased (FDR < 0.05, VIP > 1, FC < 0.8). Distinct responses between cases and noncases were detected in metabolites including 4-imidazolone-5-acetate and 4-methylene-L-glutamine. More varieties of distinct metabolites across glycemic statuses were observed at 2 h of OGTT compared with fasting state. Whether the different patterns and responsiveness of certain metabolites in T2D reflect a poor resilience of specific metabolic pathways in regaining glucose homeostasis merits further study.

The Circadian Clock, Shift Work, and Tissue-Specific Insulin Resistance

Obesity and type 2 diabetes (T2D) have become a global health concern. The prevalence of obesity and T2D is significantly higher in shift workers compared to people working regular hours. An accepted hypothesis is that the increased risk for metabolic health problems arises from aberrantly timed eating behavior, that is, eating out of synchrony with the biological clock. The biological clock is part of the internal circadian timing system, which controls not only the sleep/wake and feeding/fasting cycle, but also many metabolic processes in the body, including the timing of our eating behavior, and processes involved in glucose homeostasis. Rodent studies have shown that eating out of phase with the endogenous clock results in desynchronization between rhythms of the central and peripheral clock systems and between rhythms of different tissue clocks (eg, liver and muscle clock). Glucose homeostasis is a complex process that involves multiple organs. In the healthiest situation, functional rhythms of these organs are synchronized. We hypothesize that desynchronization between different metabolically active organs contributes to alterations in glucose homeostasis. Here we summarize the most recent information on desynchronization between organs due to shift work and shifted food intake patterns and introduce the concept of phenotypic flexibility, a validated test to assess the contribution of each organ to insulin resistance (IR) in humans. We propose this test as a way to provide further insight into the possible desynchronization between tissue clocks. Because different types of IR benefit from different therapeutic approaches, we also describe different chronotherapeutic strategies to promote synchrony within and between metabolically active organs.

Obese Older Type 2 Diabetes Mellitus Patients with Muscle Insulin Resistance Benefit from an Enriched Protein Drink during Combined Lifestyle Intervention: The PROBE Study

(1) Background: Recent research showed that subtypes of patients with type 2 diabetes may differ in response to lifestyle interventions based on their organ-specific insulin resistance (IR). (2) Methods: 123 Subjects with type 2 diabetes were randomized into 13-week lifestyle intervention, receiving either an enriched protein drink (protein+) or an isocaloric control drink (control). Before and after the intervention, anthropometrical and physiological data was collected. An oral glucose tolerance test was used to calculate indices representing organ insulin resistance (muscle, liver, and adipose tissue) and β-cell functioning. In 82 study-compliant subjects (per-protocol), we retrospectively examined the intervention effect in patients with muscle IR (MIR, n = 42) and without MIR (no-MIR, n = 40). (3) Results: Only in patients from the MIR subgroup that received protein+ drink, fasting plasma glucose and insulin, whole body, liver and adipose IR, and appendicular skeletal muscle mass improved versus control. Lifestyle intervention improved body weight and fat mass in both subgroups. Furthermore, for the MIR subgroup decreased systolic blood pressure and increased VO2peak and for the no-MIR subgroup, a decreased 2-h glucose concentration was found. (4) Conclusions: Enriched protein drink during combined lifestyle intervention seems to be especially effective on increasing muscle mass and improving insulin resistance in obese older, type 2 diabetes patients with muscle IR.

Next Generation Health Claims Based on Resilience: The Example of Whole-Grain Wheat

Health claims on foods are a way of informing consumers about the health benefits of a food product. Traditionally, these claims are based on scientific evaluation of markers originating from a pharmacological view on health. About a decade ago, the definition of health has been rephrased to 'the ability to adapt' that opened up the possibility for a next generation of health claims based on a new way of quantifying health by evaluating resilience. Here, we would like to introduce an opportunity for future scientific substantiation of health claims on food products by using whole-grain wheat as an example. Characterization of the individual whole wheat grain food product or whole wheat flour would probably be considered as sufficiently characterized by the European Food Safety Authority, while the food category whole grain is not specific enough. Meta-analysis provides the scientific evidence that long-term whole-grain wheat consumption is beneficial for health, although results from single 'gold standard' efficacy studies are not always straight forward based on classic measurement methods. Future studies may want to underpin the scientific argumentation that long-term whole grain wheat consumption improves resilience, by evaluating the disruption and rate of a selected panel of blood markers in response to a standardized oral protein glucose lipid tolerance test and aggregated into biomarkers with substantiated physiological benefits, to make a next-generation health claim for whole-grain wheat achievable in the near future.

Evaluation of Food-Intake Behavior in a Healthy Population: Personalized vs. One-Size-Fits-All

In public health initiatives, generic nutrition advice (GNA) from national guidelines has a limited effect on food-intake improvement. Personalized nutrition advice (PNA) may enable dietary behavior change. A monocentric, randomized, parallel, controlled clinical trial was performed in males (n = 55) and females (n = 100) aged 25 to 70 years. Participants were allocated to control, GNA or PNA groups. The PNA group consisted of automatically generated dietary advice based on personal metabolic health parameters, dietary intake, anthropometric and hemodynamic measures, gender and age. Participants who received PNA (n = 51) improved their nutritional intake status for fruits P (p < 0.0001), whole grains (p = 0.008), unsalted nuts (p < 0.0001), fish (p = 0.0003), sugar-sweetened beverages (p = 0.005), added salt (p = 0.003) and less unhealthy choices (p = 0.002), whereas no improvements were observed in the control and GNA group. PNA participants were encouraged to set a goal for one or multiple food categories. Goal-setting led to greater improvement of food categories within the PNA group including; unsalted nuts (p < 0.0001), fruits (p = 0.0001), whole grains (p = 0.005), fish (p = 0.0001), dairy (p = 0.007), vegetables (p = 0.01) and unhealthy choices (p = 0.02). In a healthy population, participants receiving PNA changed their food-intake behavior more favorably than participants receiving GNA or no advice. When personal goals were set, nutritional behavior was more prone to change.

A new randomization procedure based on multiple covariates and applicable to parallel studies with simultaneous enrollment of all subjects prior to intervention

BACKGROUND

Parallel intervention studies involving volunteers usually require a procedure to allocate the subjects to study-arms. Statistical models to evaluate the different outcomes of the study-arms will include study-arm as a factor along with any covariate that might affect the results. To ensure that the effects of the covariates are confounded to the least possible extent with the effects of the arms, stratified randomization can be applied. However, there is at present no clear-cut procedure when there are multiple covariates.

METHODS

For parallel study designs with simultaneous enrollment of all subjects prior to intervention, we propose a D-optimal blocking procedure to allocate subjects with known values of the covariates to the study arms. We prove that the procedure minimizes the variances of the baseline differences between the arms corrected for the covariates. The procedure uses standard statistical software.

RESULTS

We demonstrate the potential of the method by an application to a human parallel nutritional intervention trial with three arms and 162 healthy volunteers. The covariates were gender, age, body mass index, an initial composite health score, and a categorical indicator called first-visit group, defining groups of volunteers who visit the clinical centre on the same day (17 groups). Volunteers were allocated equally to the study-arms by the D-optimal blocking procedure. The D-efficiency of the model connecting an outcome with the study-arms and correcting for the covariates equals 99.2%. We simulated 10,000 random allocations of subjects to arms either unstratified or stratified by first-visit group. Intervals covering the middle 95% of the D-efficiencies for these allocations were [82.0, 92.0] and [93.2, 98.4], respectively.

CONCLUSIONS

Allocation of volunteers to study-arms with a D-optimal blocking procedure with the values of the covariates as inputs substantially improves the efficiency of the statistical model that connects the response with the study arms and corrects for the covariates.

TRIAL REGISTRATION

Dutch Trial Register NL7054 ( NTR7259 ). Registered May 15, 2018.

Measuring health promotion: translating science into policy

Commonly, it is the end of life when our health is deteriorating, that many will make drastic lifestyle changes to improve their quality of life. However, it is increasingly recognized that bringing good health-promoting behaviors into practice as early in life as possible has the most significant impact across the maximal healthspan. The WHO has brought clarity to health promotion over the last fifteen years, always centering on language relating to a process of enabling people to increase control over, and to improve, their physical, mental and social health. A good healthspan is not just freedom from morbidity and mortality, it is that joie de vivre ("joy of living") that should accompany every day of our lifespan. Therefore, health promotion includes not only the health sector, but also needs individual commitment to achieve that target of a healthspan aligned with the lifespan. This paper explores health promotion and health literacy, and how to design appropriate nutritional studies to characterize contributors to a positive health outcome, the role the human microbiome plays in promoting health and addressing and alleviating morbidity and diseases, and finally how to characterize phenotypic flexibility and a physiologic resilience that we must maintain as our structural and functional systems are bombarded with the insults and perturbations of life.

From lifespan to healthspan: the role of nutrition in healthy ageing

Across the globe, there has been a marked increase in longevity, but significant inequalities remain. These are exacerbated by inadequate access to proper nutrition and health care services and to reliable information to make the decisions related to nutrition and health care. Many in economically developing as well as developed societies are plagued with the double-burden of energy excess and undernutrition. This has resulted in mental and physical deterioration, increased non-communicable disease rates, lost productivity, increased medical costs and reduced quality of life. While adequate nutrition is fundamental to good health at all stages of the life course, the impact of diet on prolonging good quality of life during ageing remains unclear. For progress to continue, there is need for new and/or innovative approaches to promoting health as individuals age, as well as qualitative and quantitative biomarkers and other accepted tools that can measure improvements in physiological integrity throughout life. A framework for progress has been proposed by the World Health Organization in their Global Strategy and Action Plan on Ageing and Health. Here, we focused on the impact of nutrition within this framework, which takes a broad, person-centred emphasis on healthy ageing, stressing the need to better understand each individual's intrinsic capacity, their functional abilities at various life stages, and the impact of their mental, and physical health, as well as the environments they inhabit.

Postprandial Metabolism is Impaired in Overweight Normoglycemic Young Adults without Family History of Diabetes

While the risk factors for Type 2 diabetes (T2DM) are known, early predictive markers of transition from normal to a prediabetes state are unidentified. We studied the basal metabolism and metabolic response to a mixed-meal challenge in 110 healthy subjects in the age group of 18 to 40 years (Male:Female = 1:1); grouped into first degree relatives of patients with T2DM (n = 30), those with a body mass index >23 kg/m² but <30 kg/m² (n = 30), those with prediabetes (n = 20) and normal controls (n = 30). We performed an untargeted metabolomics analysis of plasma and related that with clinical and biochemical parameters, markers of inflammation, and insulin sensitivity. Similar to prediabetes subjects, overweight subjects had insulin resistance and significantly elevated levels of C-peptide, adiponectin and glucagon and lower level of ghrelin. Metabolites such as MG(22:2(13Z, 16Z)/0:0/0:0) and LysoPC (15:0) were reduced in overweight and prediabetes subjects. Insulin sensitivity was significantly lower in men. Fasting levels of uric acid, xanthine, and glycochenodeoxycholic-3-glucuronide were elevated in men. However, both lysophospholipids and antioxidant defense metabolites were higher in women. Impaired postprandial metabolism and insulin sensitivity in overweight normoglycemic young adults indicates a risk of developing hyperglycemia. Our results also indicate a higher risk of diabetes in young men.

Nutrition interventions for healthy ageing across the lifespan: a conference report

Thanks to advances in modern medicine over the past century, the world’s population has experienced a marked increase in longevity. However, disparities exist that lead to groups with both shorter lifespan and significantly diminished health, especially in the aged. Unequal access to proper nutrition, healthcare services, and information to make informed health and nutrition decisions all contribute to these concerns. This in turn has hastened the ageing process in some and adversely affected others’ ability to age healthfully. Many in developing as well as developed societies are plagued with the dichotomy of simultaneous calorie excess and nutrient inadequacy. This has resulted in mental and physical deterioration, increased non-communicable disease rates, lost productivity and quality of life, and increased medical costs. While adequate nutrition is fundamental to good health, it remains unclear what impact various dietary interventions may have on improving healthspan and quality of life with age. With a rapidly ageing global population, there is an urgent need for innovative approaches to health promotion as individual’s age. Successful research, education, and interventions should include the development of both qualitative and quantitative biomarkers and other tools which can measure improvements in physiological integrity throughout life. Data-driven health policy shifts should be aimed at reducing the socio-economic inequalities that lead to premature ageing. A framework for progress has been proposed and published by the World Health Organization in its Global Strategy and Action Plan on Ageing and Health. This symposium focused on the impact of nutrition on this framework, stressing the need to better understand an individual’s balance of intrinsic capacity and functional abilities at various life stages, and the impact this balance has on their mental and physical health in the environments they inhabit.

Effects of a whole diet approach on metabolic flexibility, insulin sensitivity and postprandial glucose responses in overweight and obese adults - A randomized controlled trial

BACKGROUND & AIMS

Metabolic flexibility is the ability to adapt fuel oxidation to fuel availability. Metabolic inflexibility has been associated with obesity, the metabolic syndrome and insulin resistance, and can be improved by exercise or weight loss. Dietary changes can modulate metabolic flexibility; however, the effect of a whole diet approach on metabolic flexibility has never been studied. Therefore, our objective was to assess the effect of a healthy diet (HD), as compared to a typical Western diet (WD), on several fasting and postprandial markers of metabolic flexibility and insulin sensitivity.

METHODS

In this parallel randomized trial, overweight or obese men and women (50-70 years; BMI 25-35 kg/m²) consumed a healthy diet (HD; high in fruits and vegetables, pulses, fibers, nuts, fatty fish, and low in high-glycemic carbohydrates; n = 19) or a typical Western diet (WD; n = 21) for six weeks, following a two-week run-in period. The change in respiratory quotient upon insulin stimulation (ΔRQ), and insulin sensitivity, expressed as the M-value, were both determined with a hyperinsulinemic euglycemic clamp. Additionally, other fasting and postprandial markers of metabolic flexibility were assessed during a 5-h high-fat high-glycemic mixed meal challenge.

RESULTS

ΔRQ (p = 0.730) and insulin sensitivity (p = 0.802) were not significantly affected by diet. Postprandial RQ did also not show significant differences (p = 0.610), whereas postprandial glucose excursions were significantly higher in the HD group at T30 (p = 0.014) and T45 (p = 0.026) after mixed meal ingestion (p = 0.037). Fasting glucose (p = 0.530) and HbA1c (p = 0.124) remained unchanged, whereas decreases in fasting insulin (p = 0.038) and the HOMA-IR (p = 0.050) were significantly more pronounced with the HD.

CONCLUSION

A healthy diet for six weeks, without further life-style changes, did not improve metabolic flexibility and whole-body insulin sensitivity, when compared to a Western-style diet. It remains to be determined whether the short time increase in postprandial glucose is physiologically relevant or detrimental to metabolic health. This trial was registered at clinicaltrials.gov as NCT02519127.

Whole Grain Wheat Consumption Affects Postprandial Inflammatory Response in a Randomized Controlled Trial in Overweight and Obese Adults with Mild Hypercholesterolemia in the Graandioos Study

BACKGROUND

Whole grain wheat (WGW) consumption is associated with health benefits in observational studies. However, WGW randomized controlled trial (RCT) studies show mixed effects.

OBJECTIVES

The health impact of WGW consumption was investigated by quantification of the body's resilience, which was defined as the "ability to adapt to a standardized challenge."

METHODS

A double-blind RCT was performed with overweight and obese (BMI: 25-35 kg/m2) men (n = 19) and postmenopausal women (n = 31) aged 45-70 y, with mildly elevated plasma total cholesterol (>5 mmol/L), who were randomly assigned to either 12-wk WGW (98 g/d) or refined wheat (RW). Before and after the intervention a standardized mixed-meal challenge was performed. Plasma samples were taken after overnight fasting and postprandially (30, 60, 120, and 240 min). Thirty-one biomarkers were quantified focusing on metabolism, liver, cardiovascular health, and inflammation. Linear mixed-models evaluated fasting compared with postprandial intervention effects. Health space models were used to evaluate intervention effects as composite markers representing resilience of inflammation, liver, and metabolism.

RESULTS

Postprandial biomarker changes related to liver showed decreased alanine aminotransferase by WGW (P = 0.03) and increased β-hydroxybutyrate (P = 0.001) response in RW. Postprandial changes related to inflammation showed increased C-reactive protein (P = 0.001), IL-6 (P = 0.02), IL-8 (P = 0.007), and decreased IL-1B (P = 0.0002) in RW and decreased C-reactive protein (P < 0.0001), serum amyloid A (P < 0.0001), IL-8 (P = 0.02), and IL-10 (P < 0.0001) in WGW. Health space visualization demonstrated diminished inflammatory (P < 0.01) and liver resilience (P < 0.01) by RW, whereas liver resilience was rejuvenated by WGW (P < 0.05).

CONCLUSIONS

Twelve-week 98 g/d WGW consumption can promote liver and inflammatory resilience in overweight and obese subjects with mildly elevated plasma cholesterol. The health space approach appeared appropriate to evaluate intervention effects as composite markers. This trial was registered at www.clinicaltrials.gov as NCT02385149.

Microstructure of starch-based meals with either palm or soybean oils alter in vitro starch digestibility with no major effects on glycaemic responses

Glycaemic response (GR) to starch-based meals depends on their food composition and microstructure. We studied the effect of palm and soybean oils on the microstructure of a solid starch-oil-gluten matrix, on the starch gelatinisation and in vitro digestibility. Additionally, a pilot cross-over study was carried out to assess GR after eating gelatinised starch/gluten-based foods with the addition of either palm or soybean oil in 8 young non-diabetic female volunteers (ISRCTN39636850). Both types of foods generated similar starch gelatinisation temperature. Starch/gluten-based food with soybean oil had rougher microstructure compared to food with palm oil, showing a higher initial and lower final in vitro digestion. Administration of starch/gluten-based meals with either palm or soybean oils to volunteers show very similar postprandial glucose or insulin responses. In conclusion, differences in fatty acid composition changes food microstructure and in vitro starch digestibility, with no major effects on glycaemic responses in female volunteers.

Biomarkers in Stress Related Diseases/Disorders: Diagnostic, Prognostic, and Therapeutic Values

Various internal and external factors negatively affect the homeostatic equilibrium of organisms at the molecular to the whole-body level, inducing the so-called state of stress. Stress affects an organism's welfare status and induces energy-consuming mechanisms to combat the subsequent ill effects; thus, the individual may be immunocompromised, making them vulnerable to pathogens. The information presented here has been extensively reviewed, compiled, and analyzed from authenticated published resources available on Medline, PubMed, PubMed Central, Science Direct, and other scientific databases. Stress levels can be monitored by the quantitative and qualitative measurement of biomarkers. Potential markers of stress include thermal stress markers, such as heat shock proteins (HSPs), innate immune markers, such as Acute Phase Proteins (APPs), oxidative stress markers, and chemical secretions in the saliva and urine. In addition, stress biomarkers also play critical roles in the prognosis of stress-related diseases and disorders, and therapy guidance. Moreover, different components have been identified as potent mediators of cardiovascular, central nervous system, hepatic, and nephrological disorders, which can also be employed to evaluate these conditions precisely, but with stringent validation and specificity. Considerable scientific advances have been made in the detection, quantitation, and application of these biomarkers. The present review describes the current progress of identifying biomarkers, their prognostic, and therapeutic values.

Biomarkers in Stress Related Diseases/Disorders: Diagnostic, Prognostic, and Therapeutic Values

Various internal and external factors negatively affect the homeostatic equilibrium of organisms at the molecular to the whole-body level, inducing the so-called state of stress. Stress affects an organism's welfare status and induces energy-consuming mechanisms to combat the subsequent ill effects; thus, the individual may be immunocompromised, making them vulnerable to pathogens. The information presented here has been extensively reviewed, compiled, and analyzed from authenticated published resources available on Medline, PubMed, PubMed Central, Science Direct, and other scientific databases. Stress levels can be monitored by the quantitative and qualitative measurement of biomarkers. Potential markers of stress include thermal stress markers, such as heat shock proteins (HSPs), innate immune markers, such as Acute Phase Proteins (APPs), oxidative stress markers, and chemical secretions in the saliva and urine. In addition, stress biomarkers also play critical roles in the prognosis of stress-related diseases and disorders, and therapy guidance. Moreover, different components have been identified as potent mediators of cardiovascular, central nervous system, hepatic, and nephrological disorders, which can also be employed to evaluate these conditions precisely, but with stringent validation and specificity. Considerable scientific advances have been made in the detection, quantitation, and application of these biomarkers. The present review describes the current progress of identifying biomarkers, their prognostic, and therapeutic values.

Current and Future Nutritional Strategies to Modulate Inflammatory Dynamics in Metabolic Disorders

Obesity, type 2 diabetes, and other metabolic disorders have a large impact on global health, especially in Western countries. An important hallmark of metabolic disorders is chronic low-grade inflammation. A key player in chronic low-grade inflammation is dysmetabolism, which is defined as the inability to keep homeostasis resulting in loss of lipid control, oxidative stress, inflammation, and insulin resistance. Although often not yet detectable in the circulation, chronic low-grade inflammation can be present in one or multiple organs. The response to a metabolic challenge containing lipids may magnify dysfunctionalities at the tissue level, causing an overflow of inflammatory markers into the circulation and hence allow detection of early low-grade inflammation. Here, we summarize the evidence of successful application of metabolic challenge tests in type 2 diabetes, metabolic syndrome, obesity, and unhealthy aging. We also review how metabolic challenge tests have been successfully applied to evaluate nutritional intervention effects, including an "anti-inflammatory" mixture, dark chocolate, whole grain wheat and overfeeding. Additionally, we elaborate on future strategies to (re)gain inflammatory flexibility. Through epigenetic and metabolic regulation, the inflammatory response may be trained by regular mild and metabolic triggers, which can be understood from the perspective of trained immunity, hormesis and pro-resolution. New strategies to optimize dynamics of inflammation may become available.

Extended indirect calorimetry with isotopic CO2 sensors for prolonged and continuous quantification of exogenous vs. total substrate oxidation in mice

Indirect calorimetry (InCa) estimates whole-body energy expenditure and total substrate oxidation based on O₂ consumption and CO₂ production, but does not allow for the quantification of oxidation of exogenous substrates with time. To achieve this, we incorporated ¹³CO₂ and ¹²CO₂ gas sensors into a commercial InCa system and aimed to demonstrate their performance and added value. As a performance indicator, we showed the discriminative oscillations in ¹³CO₂ enrichment associated with food intake in mice fed diets containing naturally low (wheat) vs high (maize) ¹³C enrichment. To demonstrate the physiological value, we quantified exogenous vs total carbohydrate and fat oxidation continuously, in real time in mice varying in fat mass. Diet-induced obese mice were fed a single liquid mixed meal containing ¹³C-isotopic tracers of glucose or palmitate. Over 13 h, ~70% glucose and ~48% palmitate ingested were oxidised. Exogenous palmitate oxidation depended on body fat mass, which was not the case for exogenous glucose oxidation. We conclude that extending an InCa system with ¹³CO₂ and ¹²CO₂ sensors provides an accessible and powerful technique for real-time continuous quantification of exogenous and whole-body substrate oxidation in mouse models of human metabolic physiology.