Minor Changes in the Composition and Function of the Gut Microbiota During a 12-Week Whole Grain Wheat or Refined Wheat Intervention Correlate with Liver Fat in Overweight and Obese Adults.

BACKGROUND: Whole grain wheat (WGW) products are advocated as a healthy choice when compared with refined wheat (RW). One proposed mechanism for these health benefits is via the microbiota, because WGW contains multiple fibers. WGW consumption has been proposed to ameliorate nonalcoholic fatty liver disease, in which microbiota might play a role. OBJECTIVES: We investigated the effect of WGW compared with RW intervention on the fecal microbiota composition and functionality, and correlated intervention-induced changes in bacteria with changes in liver health parameters in adults with overweight or obesity. METHODS: We used data of a 12-wk double-blind, randomized, controlled, parallel trial to examine the effects of a WGW (98 g/d) or RW (98 g/d) intervention on the secondary outcomes fecal microbiota composition, predicted microbiota functionality, and stool consistency in 37 women and men (aged 45-70 y, BMI 25-35 kg/m2). The changes in microbiota composition, measured using 16S ribosomal RNA gene sequencing, after a 12-wk intervention were analyzed with nonparametric tests, and correlated with changes in liver fat and circulating concentrations of liver enzymes including alanine transaminase, aspartate transaminase, γ-glutamyltransferase, and serum amyloid A. RESULTS: The WGW intervention increased the mean (± SD) relative abundances of Ruminococcaceae_UCG-014 (baseline: 2.2 ± 4.6%, differential change over time (Δ) 0.51 ± 4.2%), Ruminiclostridium_9 (baseline: 0.065 ± 0.11%, Δ 0.054 ± 0.14%), and Ruminococcaceae_NK4A214_group (baseline: 0.37 ± 0.56%, Δ 0.17 ± 0.83%), and also the predicted pathway acetyl-CoA fermentation to butyrate II (baseline: 0.23 ± 0.062%, Δ 0.035 ± 0.059%), compared with the RW intervention (P values <0.05). A change in Ruminococcaceae_NK4A214_group was positively correlated with the change in liver fat, in both the WGW (ρ = 0.54; P = 0.026) and RW (ρ = 0.67; P = 0.024) groups. CONCLUSIONS: In middle-aged overweight and obese adults, a 12-wk WGW intervention increased the relative abundance of a number of bacterial taxa from the family Ruminococcaceae and increased predicted fermentation pathways when compared with an RW intervention. Potential protective health effects of replacement of RW by WGW on metabolic organs, such as the liver, via modulation of the microbiota, deserve further investigation.This trial was registered at clinicaltrials.gov as NCT02385149.

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.

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 ß-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.

Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements.

Health has been defined as the capability of the organism to adapt to challenges. In this study, we tested to what extent comprehensively phenotyped individuals reveal differences in metabolic responses to a standardized mixed meal tolerance test (MMTT) and how these responses change when individuals experience moderate weight loss. Metabolome analysis was used in 70 healthy individuals. with profiling of ∼300 plasma metabolites during an MMTT over 8 h. Multivariate analysis of plasma markers of fatty acid catabolism identified 2 distinct metabotype clusters (A and B). Individuals from metabotype B showed slower glucose clearance, had increased intra-abdominal adipose tissue mass and higher hepatic lipid levels when compared with individuals from metabotype A. An NMR-based urine analysis revealed that these individuals also to have a less healthy dietary pattern. After a weight loss of ∼5.6 kg over 12 wk, only the subjects from metabotype B showed positive changes in the glycemic response during the MMTT and in markers of metabolic diseases. Our study in healthy individuals demonstrates that more comprehensive phenotyping can reveal discrete metabotypes with different outcomes in a dietary intervention and that markers of lipid catabolism in plasma could allow early detection of the metabolic syndrome.-Fiamoncini, J., Rundle, M., Gibbons, H., Thomas, E. L., Geillinger-Kästle, K., Bunzel, D., Trezzi, J.-P., Kiselova-Kaneva, Y., Wopereis, S., Wahrheit, J., Kulling, S. E., Hiller, K., Sonntag, D., Ivanova, D., van Ommen, B., Frost, G., Brennan, L., Bell, J. Daniel, H. Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements.

Determinants of postprandial plasma bile acid kinetics in human volunteers.

Bile acids (BA) are signaling molecules with a wide range of biological effects, also identified among the most responsive plasma metabolites in the postprandial state. We here describe this response to different dietary challenges and report on key determinants linked to its interindividual variability. Healthy men and women (n = 72, 62 ± 8 yr, mean ± SE) were enrolled into a 12-wk weight loss intervention. All subjects underwent an oral glucose tolerance test and a mixed-meal tolerance test before and after the intervention. BA were quantified in plasma by liquid chromatography-tandem mass spectrometry combined with whole genome exome sequencing and fecal microbiota profiling. Considering the average response of all 72 subjects, no effect of the successful weight loss intervention was found on plasma BA profiles. Fasting and postprandial BA profiles revealed high interindividual variability, and three main patterns in postprandial BA response were identified using multivariate analysis. Although the women enrolled were postmenopausal, effects of sex difference in BA response were evident. Exome data revealed the contribution of preselected genes to the observed interindividual variability. In particular, a variant in the SLCO1A2 gene, encoding the small intestinal BA transporter organic anion-transporting polypeptide-1A2 (OATP1A2), was associated with delayed postprandial BA increases. Fecal microbiota analysis did not reveal evidence for a significant influence of bacterial diversity and/or composition on plasma BA profiles. The analysis of plasma BA profiles in response to two different dietary challenges revealed a high interindividual variability, which was mainly determined by genetics and sex difference of host with minimal effects of the microbiota.NEW & NOTEWORTHY Considering the average response of all 72 subjects, no effect of the successful weight loss intervention was found on plasma bile acid (BA) profiles. Despite high interindividual variability, three main patterns in postprandial BA response were identified using multivariate analysis. A variant in the SLCO1A2 gene, encoding the small intestinal BA transporter organic anion-transporting polypeptide-1A2 (OATP1A2), was associated with delayed postprandial BA increases in response to both the oral glucose tolerance test and the mixed-meal tolerance test.

The Network Library: a framework to rapidly integrate network biology resources.

MOTIVATION: Much of the biological knowledge accumulated over the last decades is stored in different databases governed by various organizations and institutes. Integrating and connecting these vast knowledge repositories is an extremely useful method to support life sciences research and help formulate novel hypotheses. RESULTS: We developed the Network Library (NL), a framework and toolset to rapidly integrate different knowledge sources to build a network biology resource that matches a specific research question. As a use-case we explore the interactions of genes related to heart failure with miRNAs and diseases through the integration of 6 databases. AVAILABILITY AND IMPLEMENTATION: The NL is open-source, developed in Java and available on Github (https://github.com/gsummer). CONTACT: georg.summer@gmail.com.

Metabolic Profiling Reveals Differences in Plasma Concentrations of Arabinose and Xylose after Consumption of Fiber-Rich Pasta and Wheat Bread with Differential Rates of Systemic Appearance of Exogenous Glucose in Healthy Men.

BACKGROUND: The consumption of products rich in cereal fiber and with a low glycemic index is implicated in a lower risk of metabolic diseases. Previously, we showed that the consumption of fiber-rich pasta compared with bread resulted in a lower rate of appearance of exogenous glucose and a lower glucose clearance rate quantified with a dual-isotope technique, which was in accordance with a lower insulin and glucose-dependent insulinotropic polypeptide response. OBJECTIVE: To gain more insight into the acute metabolic consequences of the consumption of products resulting in differential glucose kinetics, postprandial metabolic profiles were determined. METHODS: In a crossover study, 9 healthy men [mean ± SEM age: 21 ± 0.5 y; mean ± SEM body mass index (kg/m2): 22 ± 0.5] consumed wheat bread (132 g) and fresh pasta (119 g uncooked) enriched with wheat bran (10%) meals. A total of 134 different metabolites in postprandial plasma samples (at -5, 30, 60, 90, 120, and 180 min) were quantified by using a gas chromatography-mass spectrometry-based metabolomics approach (secondary outcomes). Two-factor ANOVA and advanced multivariate statistical analysis (partial least squares) were applied to detect differences between both food products. RESULTS: Forty-two different postprandial metabolite profiles were identified, primarily representing pathways related to protein and energy metabolism, which were on average 8% and 7% lower after the men consumed pasta rather than bread, whereas concentrations of arabinose and xylose were 58% and 53% higher, respectively. Arabinose and xylose are derived from arabinoxylans, which are important components of wheat bran. The higher bioavailability of arabinose and xylose after pasta intake coincided with a lower rate of appearance of glucose and amino acids. We speculate that this higher bioavailability is due to higher degradation of arabinoxylans by small intestinal microbiota, facilitated by the higher viscosity of arabinoxylans after pasta intake than after bread intake. CONCLUSION: This study suggests that wheat bran, depending on the method of processing, can increase the viscosity of the meal bolus in the small intestine and interfere with macronutrient absorption in healthy men, thereby influencing postprandial glucose and insulin responses. This trial was registered at www.controlled-trials.com as ISRCTN42106325.

Improving selection of markers in nutrition research: evaluation of the criteria proposed by the ILSI Europe Marker Validation Initiative.

The conduct of high-quality nutrition research requires the selection of appropriate markers as outcomes, for example as indicators of food or nutrient intake, nutritional status, health status or disease risk. Such selection requires detailed knowledge of the markers, and consideration of the factors that may influence their measurement, other than the effects of nutritional change. A framework to guide selection of markers within nutrition research studies would be a valuable tool for researchers. A multidisciplinary Expert Group set out to test criteria designed to aid the evaluation of candidate markers for their usefulness in nutrition research and subsequently to develop a scoring system for markers. The proposed criteria were tested using thirteen markers selected from a broad range of nutrition research fields. The result of this testing was a modified list of criteria and a template for evaluating a potential marker against the criteria. Subsequently, a semi-quantitative system for scoring a marker and an associated template were developed. This system will enable the evaluation and comparison of different candidate markers within the same field of nutrition research in order to identify their relative usefulness. The ranking criteria of proven, strong, medium or low are likely to vary according to research setting, research field and the type of tool used to assess the marker and therefore the considerations for scoring need to be determined in a setting-, field- and tool-specific manner. A database of such markers, their interpretation and range of possible values would be valuable to nutrition researchers.

The insulin resistance phenotype (muscle or liver) interacts with the type of diet to determine changes in disposition index after 2 years of intervention: the CORDIOPREV-DIAB randomised clinical trial.

AIMS/HYPOTHESIS: The aim of the study was to determine whether basal insulin resistance (IR) phenotype (muscle and/or liver) determines the effect of long-term consumption of a Mediterranean diet or a low-fat diet on tissue-specific IR and beta cell function. METHODS: The study was performed in 642 patients included in The effect of an olive oil rich Mediterranean diet on type 2 diabetes mellitus risk and incidence study (CORDIOPREV-DIAB). A total of 327 patients were randomised to a Mediterranean diet (35% fat; 22% from monounsaturated fatty acids) and 315 to a low-fat diet (<28% fat). At baseline, the patients were classified into four phenotypes according to the type of IR: (1) no IR; (2) muscle IR; (3) liver IR; (4) muscle + liver IR. The hepatic insulin resistance index (HIRI), muscular insulin sensitivity index (MISI) and disposition index were analysed at baseline and after 2 years of follow-up. RESULTS: At baseline, 322 patients presented no IR, 106 presented muscle IR, 109 presented liver IR, and 105 presented muscle + liver IR. With both dietary interventions, HIRI decreased in all patients (p < 0.001) and MISI increased in muscle IR and muscle + liver IR patients (p < 0.01). Long-term intake of the Mediterranean diet increased the disposition index and insulinogenic index in the muscle IR patients (p = 0.042 and p = 0.044, respectively) and the disposition index in the muscle + liver IR patients (p = 0.048), whereas the low-fat diet increased the disposition index in the liver IR patients (p = 0.017). CONCLUSIONS/INTERPRETATION: Although both diets improve insulin sensitivity, there are differences based on basal IR phenotypes. Moreover, according to insulinogenic and disposition index data, a low-fat diet might be more beneficial to patients with liver IR, whereas patients with muscle IR and muscle + liver IR might benefit more from a Mediterranean diet. Trial registration ClinicalTrials.gov NCT00924937 FUNDING: The study was supported by the Ministerio de Economia y Competitividad (AGL2012/39615) and by the Ministerio de Ciencia e Innovacion (PIE14/00005 and PI13/00023).

Quantifying phenotypic flexibility as the response to a high-fat challenge test in different states of metabolic health.

Metabolism maintains homeostasis at chronic hypercaloric conditions, activating postprandial response mechanisms, which come at the cost of adaptation processes such as energy storage, eventually with negative health consequences. This study quantified the metabolic adaptation capacity by studying challenge response curves. After a high-fat challenge, the 8 h response curves of 61 biomarkers related to adipose tissue mass and function, systemic stress, metabolic flexibility, vascular health, and glucose metabolism was compared between 3 metabolic health stages: 10 healthy men, before and after 4 wk of high-fat, high-calorie diet (1300 kcal/d extra), and 9 men with metabolic syndrome (MetS). The MetS subjects had increased fasting concentrations of biomarkers representing the 3 core processes, glucose, TG, and inflammation control, and the challenge response curves of most biomarkers were altered. After the 4 wk hypercaloric dietary intervention, these 3 processes were not changed, as compared with the preintervention state in the healthy subjects, whereas the challenge response curves of almost all endocrine, metabolic, and inflammatory processes regulating these core processes were altered, demonstrating major molecular physiologic efforts to maintain homeostasis. This study thus demonstrates that change in challenge response is a more sensitive biomarker of metabolic resilience than are changes in fasting concentrations.

The effect of a combined lifestyle intervention with and without protein drink on inflammation in older adults with obesity and type 2 diabetes.

BACKGROUND: Chronic low-grade inflammatory profile (CLIP) is one of the pathways involved in type 2 diabetes (T2D). Currently, there is limited evidence for ameliorating effects of combined lifestyle interventions on CLIP in type 2 diabetes. We investigated whether a 13-week combined lifestyle intervention, using hypocaloric diet and resistance exercise plus high-intensity interval training with or without consumption of a protein drink, affected CLIP in older adults with T2D. METHODS: In this post-hoc analysis of the PROBE study 114 adults (≥55 years) with obesity and type 2 (pre-)diabetes had measurements of C-reactive protein (CRP), pro-inflammatory cytokines interleukin (IL)-6, tumor-necrosis-factor (TNF)-α, and monocyte chemoattractant protein (MCP)-1, anti-inflammatory cytokines IL-10, IL-1 receptor antagonist (RA), and soluble tumor-necrosis-factor receptor (sTNFR)1, adipokines leptin and adiponectin, and glycation biomarkers carboxymethyl-lysine (CML) and soluble receptor for advanced glycation end products (sRAGE) from fasting blood samples. A linear mixed model was used to evaluate change in inflammatory biomarkers after lifestyle intervention and effect of the protein drink. Linear regression analysis was performed with parameters of body composition (by dual-energy X-ray absorptiometry) and parameters of insulin resistance (by oral glucose tolerance test). RESULTS: There were no significant differences in CLIP responses between the protein and the control groups. For all participants combined, IL-1RA, leptin and adiponectin decreased after 13 weeks (p = 0.002, p < 0.001 and p < 0.001), while ratios TNF-α/IL-10 and TNF-α/IL-1RA increased (p = 0.003 and p = 0.035). CRP increased by 12 % in participants with low to average CLIP (pre 1.91 ± 0.39 mg/L, post 2.13 ± 1.16 mg/L, p = 0.006) and decreased by 36 % in those with high CLIP (pre 5.14 mg/L ± 1.20, post 3.30 ± 2.29 mg/L, p < 0.001). Change in leptin and IL-1RA was positively associated with change in fat mass (ß = 0.133, p < 0.001; ß = 0.017, p < 0.001) and insulin resistance (ß = 0.095, p = 0.024; ß = 0.020, p = 0.001). Change in lean mass was not associated with any of the biomarkers. CONCLUSION: 13 weeks of combined lifestyle intervention, either with or without protein drink, reduced circulating adipokines and anti-inflammatory cytokine IL-1RA, and increased inflammatory ratios TNF-α/IL-10 and TNF-α/IL-1RA in older adults with obesity and T2D. Effect on CLIP was inversely related to baseline inflammatory status.

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.

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.

Identification of prognostic and diagnostic biomarkers of glucose intolerance in ApoE3Leiden mice.

The prevalence of diabetes mellitus Type 2 could be significantly reduced by early identification of subjects at risk, allowing for better prevention and earlier treatment. Glucose intolerance (GI) is a hallmark of the prediabetic stage. This study aims at identifying 1) prognostic biomarkers predicting the risk of developing GI later in life and 2) diagnostic biomarkers reflecting the degree of already manifest GI. To this end, disease development was followed over time in mice, and biomarkers were identified using lipidomics and transcriptomics. Young adult ApoE3Leiden mice were treated a high-fat diet for 12 wk to induce GI. Blood was collected before and during disease development. The individual extent of GI was determined with a glucose tolerance test and the area under the curve (AUC) was calculated for each animal. Subject-specific AUC values were correlated to the plasma lipidome (t = 0) and the white blood cell (WBC) transcriptome (t = 0, 6, and 12 wk) to identify prognostic and diagnostic biomarkers, respectively. The plasma ratio of specific free fatty acids prior to high-fat feeding (C16:1/C16:0, C18:1/C18:0 and C18:2/C22:6) was significantly correlated with the AUC and predictive for future GI. Subsequently, the expression level of specific WBC genes (Acss2, Arfgap1, Tfrc, Cox6b2, Barhl2, Abcb4, Cyp4b1, Sars2, Fgf16, and Tceal8) reflected the individual degree of GI during disease progression. Specific plasma free fatty acids as well as their ratio can be used to predict future GI. The expression levels of specific WBC genes can serve as easy accessible markers to diagnose and monitor already existing GI.

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 ß-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.

Effects of a 12-week whole-grain or refined wheat intervention on plasma acylcarnitines, bile acids and signaling lipids, and association with liver fat: A post-hoc metabolomics study of a randomized controlled trial.

Background: We previously showed that whole-grain wheat (WGW) consumption had beneficial effects on liver fat accumulation, as compared to refined wheat (RW). The mechanisms underlying these effects remain unclear. Objective: In this study, we investigated the effects of WGW vs. RW consumption on plasma metabolite levels to explore potential underlying mechanisms of the preventive effect of WGW consumption on liver fat accumulation. Methods: Targeted metabolomics of plasma obtained from a concluded 12-week double-blind, randomized controlled trial was performed. Fifty overweight or obese men and women aged 45-70 years with mildly elevated levels of plasma cholesterol were randomized to either 98 g/d of WGW or RW products. Before and after the intervention, a total of 89 fasting plasma metabolite concentrations including acylcarnitines, trimethylamine-N-oxide (TMAO), choline, betaine, bile acids, and signaling lipids were quantified by UPLC-MS/MS. Intrahepatic triglycerides (IHTG) were quantified by 1H-MRS, and multiple liver markers, including circulating levels of ß-hydroxybutyrate, alanine transaminase (ALT), aspartate transaminase (AST), γ-glutamyltransferase (γ-GT), serum amyloid A (SAA), and C-reactive protein, were assessed. Results: The WGW intervention increased plasma concentrations of four out of 52 signaling lipids-lysophosphatidic acid C18:2, lysophosphatidylethanolamine C18:1 and C18:2, and platelet-activating factor C18:2-and decreased concentrations of the signaling lipid lysophosphatidylglycerol C20:3 as compared to RW intervention, although these results were no longer statistically significant after false discovery rate (FDR) correction. Plasma concentrations of the other metabolites that we quantified were not affected by WGW or RW intervention. Changes in the above-mentioned metabolites were not correlated to change in IHTG upon the intervention. Conclusion: Plasma acylcarnitines, bile acids, and signaling lipids were not robustly affected by the WGW or RW interventions, which makes them less likely candidates to be directly involved in the mechanisms that underlie the protective effect of WGW consumption or detrimental effect of RW consumption on liver fat accumulation. Clinical trial registration: [www.ClinicalTrials.gov], identifier [NCT02385149].

Digital Biomarkers for Personalized Nutrition: Predicting Meal Moments and Interstitial Glucose with Non-Invasive, Wearable Technologies.

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

Comparative Analysis of the Effects of Fish Oil and Fenofibrate on Plasma Metabolomic Profiles in Overweight and Obese Individuals.

SCOPE: The drug fenofibrate and dietary fish oils can effectively lower circulating triglyceride (TG) concentrations. However, a detailed comparative analysis of the effects on the plasma metabolome is missing. METHODS AND RESULTS: Twenty overweight and obese subjects participate in a double-blind, cross-over intervention trial and receive in a random order 3.7 g day-1 n-3 fatty acids, 200 mg fenofibrate, or placebo treatment for 6 weeks. Four hundred twenty plasma metabolites are measured via gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). Among the treatments, 237 metabolites are significantly different, of which 22 metabolites change in the same direction by fish oil and fenofibrate, including a decrease in several saturated TG-species. Fenofibrate additionally changes 33 metabolites, including a decrease in total cholesterol, and total lysophosphatidylcholine (LPC), whereas 54 metabolites are changed by fish oil, including an increase in unsaturated TG-, LPC-, phosphatidylcholine-, and cholesterol ester-species. All q < 0.05. CONCLUSION: Fenofibrate and fish oil reduce several saturated TG-species markedly. These reductions have been associated with a decreased risk for developing cardiovascular disease (CVD). Interestingly, fish oil consumption increases several unsaturated lipid species, which have also been associated with a reduced CVD risk. Altogether, this points towards the power of fish oil to change the plasma lipid metabolome in a potentially beneficial way.

Plasma Metabolic Signatures of Healthy Overweight Subjects Challenged With an Oral Glucose Tolerance Test.

Insulin secretion following ingestion of a carbohydrate load affects a multitude of metabolic pathways that simultaneously change direction and quantity of interorgan fluxes of sugars, lipids and amino acids. In the present study, we aimed at identifying markers associated with differential responses to an OGTT a population of healthy adults. By use of three metabolite profiling platforms, we assessed these postprandial responses of a total of 202 metabolites in plasma of 72 healthy volunteers undergoing comprehensive phenotyping and of which half enrolled into a weight-loss program over a three-month period. A standard oral glucose tolerance test (OGTT) served as dietary challenge test to identify changes in postprandial metabolite profiles. Despite classified as healthy according to WHO criteria, two discrete clusters (A and B) were identified based on the postprandial glucose profiles with a balanced distribution of volunteers based on gender and other measures. Cluster A individuals displayed 26% higher postprandial glucose levels, delayed glucose clearance and increased fasting plasma concentrations of more than 20 known biomarkers of insulin resistance and diabetes previously identified in large cohort studies. The volunteers identified by canonical postprandial responses that form cluster A may be called pre-pre-diabetics and defined as "at risk" for development of insulin resistance. Moreover, postprandial changes in selected fatty acids and complex lipids, bile acids, amino acids, acylcarnitines and sugars like mannose revealed marked differences in the responses seen in cluster A and cluster B individuals that sustained over the entire challenge test period of 240 min. Almost all metabolites, including glucose and insulin, returned to baseline values at the end of the test (at 240 min), except a variety of amino acids and here those that have been linked to diabetes development. Analysis of the corresponding metabolite profile in a fasting blood sample may therefore allow for early identification of these subjects at risk for insulin resistance without the need to undergo an OGTT.