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.

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.

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.

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.

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.

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.

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.

Mechanism-Based Biomarker Prediction for Low-Grade Inflammation in Liver and Adipose Tissue.

Metabolic disorders, such as obesity and type 2 diabetes have a large impact on global health, especially in industrialized countries. Tissue-specific chronic low-grade inflammation is a key contributor to complications in metabolic disorders. To support therapeutic approaches to these complications, it is crucial to gain a deeper understanding of the inflammatory dynamics and to monitor them on the individual level. To this end, blood-based biomarkers reflecting the tissue-specific inflammatory dynamics would be of great value. Here, we describe an in silico approach to select candidate biomarkers for tissue-specific inflammation by using a priori mechanistic knowledge from pathways and tissue-derived molecules. The workflow resulted in a list of candidate markers, in part consisting of literature confirmed biomarkers as well as a set of novel, more innovative biomarkers that reflect inflammation in the liver and adipose tissue. The first step of biomarker verification was on murine tissue gene-level by inducing hepatic inflammation and adipose tissue inflammation through a high-fat diet. Our data showed that in silico predicted hepatic markers had a strong correlation to hepatic inflammation in the absence of a relation to adipose tissue inflammation, while others had a strong correlation to adipose tissue inflammation in the absence of a relation to liver inflammation. Secondly, we evaluated the human translational value by performing a curation step in the literature using studies that describe the regulation of the markers in human, which identified 9 hepatic (such as Serum Amyloid A, Haptoglobin, and Interleukin 18 Binding Protein) and 2 adipose (Resistin and MMP-9) inflammatory biomarkers at the highest level of confirmation. Here, we identified and pre-clinically verified a set of in silico predicted biomarkers for liver and adipose tissue inflammation which can be of great value to study future development of therapeutic/lifestyle interventions to combat metabolic inflammatory complications.

A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data.

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospective cohort data from Boramae medical center in Korea (n = 1328). To obtain binary performance measures, we selected healthy controls versus oxidative disease cases based on the "health space" statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO)/elastic net regression with 10-fold cross-validation. A proposed fine-tune model included 16 features out of the full spectrum of diverse and complex data. The predictive performance was externally evaluated by generating receiver operating characteristic curves with area under the curve of 0.949 (CI 0.925 to 0.974), sensitivity of 0.923 (CI 0.879 to 0.967), and specificity of 0.855 (CI 0.795 to 0.915). Moreover, the discrimination power was confirmed by applying the proposed diagnostic model to the full dataset consisting of subjects with various degrees of oxidative stress. The results provide a feasible approach for stratifying the oxidative stress risks in the healthy population and selecting appropriate strategies for individual subjects toward implementing data-driven precision nutrition.

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.

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.

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.

Effect of an Enriched Protein Drink on Muscle Mass and Glycemic Control during Combined Lifestyle Intervention in Older Adults with Obesity and Type 2 Diabetes: A Double-Blind RCT.

BACKGROUND: Weight loss is key to treatment of older adults with obesity and type 2 diabetes, but also a risk for muscle mass loss. This study investigated whether a whey protein drink enriched with leucine and vitamin D could preserve muscle mass and improve glycemic control during combined lifestyle intervention in this population. METHODS: 123 older adults with obesity and type 2 diabetes were randomized into a 13-week lifestyle intervention with dietary advice and exercise, receiving either the enriched protein drink (test) or an isocaloric control (control). Muscle mass was assessed with dual-energy X-ray absorptiometry and glycemic control by oral glucose tolerance test. Statistical analyses were performed using a linear mixed model. RESULTS: There was a nonsignificant increase in leg muscle mass (+0.28 kg; 95% CI, -0.01 to 0.56) and a significant increase in appendicular muscle mass (+0.36 kg; 95% CI, 0.005 to 0.71) and total lean mass (+0.92 kg; 95% CI, 0.19 to 1.65) in test vs. control. Insulin sensitivity (Matsuda index) also increased in test vs. control (+0.52; 95% CI, 0.07 to 0.97). CONCLUSIONS: Use of an enriched protein drink during combined lifestyle intervention shows beneficial effects on muscle mass and glycemic control in older adults with obesity and type 2 diabetes.

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 ß-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.

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.

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.