Classification of obesity targeted personalized dietary weight loss management based on carbohydrate tolerance

Association Between the Postprandial Response to an Oral Glucose Tolerance Test and Anthropometric Changes After an 8-Week Low-Calorie Formula Diet - Results From the Lifestyle Intervention (LION) Study

SCOPE

Interindividual variations in postprandial metabolism and weight loss outcomes have been reported. The literature suggests links between postprandial metabolism and weight regulation. Therefore, the study aims to evaluate if postprandial glucose metabolism after a glucose load predicts anthropometric outcomes of a weight loss intervention.

METHODS AND RESULTS

Anthropometric data from adults with obesity (18-65 years, body mass index [BMI] 30.0-39.9 kg m-2) are collected pre- and post an 8-week formula-based weight loss intervention. An oral glucose tolerance test (OGTT) is performed at baseline, from which postprandial parameters are derived from glucose and insulin concentrations. Linear regression models explored associations between these parameters and anthropometric changes (∆) postintervention. A random forest model is applied to identify predictive parameters for anthropometric outcomes after intervention. Postprandial parameters after an OGTT of 158 participants (63.3% women, age 45 ± 12, BMI 34.9 ± 2.9 kg m-2) reveal nonsignificant associations with changes in anthropometric parameters after weight loss (p > 0.05). Baseline fat-free mass (FFM) and sex are primary predictors for ∆ FFM [kg].

CONCLUSION

Postprandial glucose metabolism after a glucose load does not predict anthropometric outcomes after short-term weight loss via a formula-based low-calorie diet in adults with obesity.

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.

Metabotyping for Precision Nutrition and Weight Management: Hype or Hope?

PURPOSE OF REVIEW

Precision nutrition requires a solid understanding of the factors that determine individual responses to dietary treatment. We review the current state of knowledge in identifying human metabotypes - based on circulating biomarkers - that can predict weight loss or other relevant physiological outcomes in response to diet treatment.

RECENT FINDINGS

Not many studies have been conducted in this area and the ones identified here are heterogeneous in design and methodology, and therefore difficult to synthesize and draw conclusions. The basis of the creation of metabotypes varies widely, from using thresholds for a single metabolite to using complex algorithms to generate multi-component constructs that include metabolite and genetic information. Furthermore, available studies are a mix of hypothesis-driven and hypothesis-generating studies, and most of them lack experimental testing in human trials. Although this field of research is still in its infancy, precision-based dietary intervention strategies focusing on the metabotype group level hold promise for designing more effective dietary treatments for obesity.

The energy balance model of obesity: beyond calories in, calories out

A recent Perspective article described the "carbohydrate-insulin model (CIM)" of obesity, asserting that it "better reflects knowledge on the biology of weight control" as compared with what was described as the "dominant energy balance model (EBM)," which fails to consider "biological mechanisms that promote weight gain." Unfortunately, the Perspective conflated and confused the principle of energy balance, a law of physics that is agnostic as to obesity mechanisms, with the EBM as a theoretical model of obesity that is firmly based on biology. In doing so, the authors presented a false choice between the CIM and a caricature of the EBM that does not reflect modern obesity science. Here, we present a more accurate description of the EBM where the brain is the primary organ responsible for body weight regulation operating mainly below our conscious awareness via complex endocrine, metabolic, and nervous system signals to control food intake in response to the body's dynamic energy needs as well as environmental influences. We also describe the recent history of the CIM and show how the latest "most comprehensive formulation" abandons a formerly central feature that required fat accumulation in adipose tissue to be the primary driver of positive energy balance. As such, the new CIM can be considered a special case of the more comprehensive EBM but with a narrower focus on diets high in glycemic load as the primary factor responsible for common obesity. We review data from a wide variety of studies that address the validity of each model and demonstrate that the EBM is a more robust theory of obesity than the CIM.

Are Dietary Proteins the Key to Successful Body Weight Management? A Systematic Review and Meta-Analysis of Studies Assessing Body Weight Outcomes after Interventions with Increased Dietary Protein

The primary aim was to systematically review the current evidence investigating if dietary interventions rich in protein lead to improved body weight management in adults with excessive body weight. The secondary aim was to investigate potential modifying effects of phenotyping. A systematic literature search in PubMed, Web of Science, and Cochrane Library identified 375 randomized controlled trials with 43 unique trials meeting the inclusion criteria. The Cochrane collaboration tool was used for a thorough risk of bias assessment. Based on 37 studies evaluating effects of dietary protein on body weight, the participants with increased protein intake (ranging from 18–59 energy percentage [E%]) were found to reduce body weight by 1.6 (1.2; 2.0) kg (mean [95% confidence interval]) compared to controls (isocaloric interventions with energy reduction introduced in certain studies). Individuals with prediabetes were found to benefit more from a diet high in protein compared to individuals with normoglycemia, as did individuals without the obesity risk allele (AA genotype) compared to individuals with the obesity risk alleles (AG and GG genotypes). Thus, diets rich in protein would seem to have a moderate beneficial effect on body weight management.

Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

Plasma glucose and insulin responses following an oral glucose challenge are representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals' challenge test responses has been shown to underlie the effectiveness of lifestyle intervention. Currently, this heterogeneity is overlooked due to a lack of methods to quantify the interconnected dynamics in the glucose and insulin time-courses. Here, a physiology-based mathematical model of the human glucose-insulin system is personalized to elucidate the heterogeneity in individuals' responses using a large population of overweight/obese individuals (n = 738) from the DIOGenes study. The personalized models are derived from population level models through a systematic parameter selection pipeline that may be generalized to other biological systems. The resulting personalized models showed a 4-5 fold decrease in discrepancy between measurements and model simulation compared to population level. The estimated model parameters capture relevant features of individuals' metabolic health such as gastric emptying, endogenous insulin secretion and insulin dependent glucose disposal into tissues, with the latter also showing a significant association with the Insulinogenic index and the Matsuda insulin sensitivity index, respectively.

Innovations in Infant Feeding: Future Challenges and Opportunities in Obesity and Cardiometabolic Disease

The field of nutrition in early life, as an effective tool to prevent and treat chronic diseases, has attracted a large amount of interest over recent years. The vital roles of food products and nutrients on the body’s molecular mechanisms have been demonstrated. The knowledge of the mechanisms and the possibility of controlling them via what we eat has opened up the field of precision nutrition, which aims to set dietary strategies in order to improve health with the greatest effectiveness. However, this objective is achieved only if the genetic profile of individuals and their living conditions are also considered. The relevance of this topic is strengthened considering the importance of nutrition during childhood and the impact on the development of obesity. In fact, the prevalence of global childhood obesity has increased substantially from 1990 and has now reached epidemic proportions. The current narrative review presents recent research on precision nutrition and its role on the prevention and treatment of obesity during pediatric years, a novel and promising area of research.

Diet and exercise in the prevention and treatment of type 2 diabetes mellitus

Evidence from observational studies and randomized trials suggests that prediabetes and type 2 diabetes mellitus (T2DM) can develop in genetically susceptible individuals in parallel with weight (that is, fat) gain. Accordingly, studies show that weight loss can produce remission of T2DM in a dose-dependent manner. A weight loss of ~15 kg, achieved by calorie restriction as part of an intensive management programme, can lead to remission of T2DM in ~80% of patients with obesity and T2DM. However, long-term weight loss maintenance is challenging. Obesity and T2DM are associated with diminished glucose uptake in the brain that impairs the satiating effect of dietary carbohydrate; therefore, carbohydrate restriction might help maintain weight loss and maximize metabolic benefits. Likewise, increases in physical activity and fitness are an important contributor to T2DM remission when combined with calorie restriction and weight loss. Preliminary studies suggest that a precision dietary management approach that uses pretreatment glycaemic status to stratify patients can help optimize dietary recommendations with respect to carbohydrate, fat and dietary fibre. This approach might lead to improved weight loss maintenance and glycaemic control. Future research should focus on better understanding the individual response to dietary treatment and translating these findings into clinical practice.

Novel Insights into the Pathogenesis and Management of the Metabolic Syndrome

The metabolic syndrome, by definition, is not a disease but is a clustering of individual metabolic risk factors including abdominal obesity, hyperglycemia, hypertriglyceridemia, hypertension, and low high-density lipoprotein cholesterol levels. These risk factors could dramatically increase the prevalence of type 2 diabetes and cardiovascular disease. The reported prevalence of the metabolic syndrome varies, greatly depending on the definition used, gender, age, socioeconomic status, and the ethnic background of study cohorts. Clinical and epidemiological studies have clearly demonstrated that the metabolic syndrome starts with central obesity. Because the prevalence of obesity has doubly increased worldwide over the past 30 years, the prevalence of the metabolic syndrome has markedly boosted in parallel. Therefore, obesity has been recognized as the leading cause for the metabolic syndrome since it is strongly associated with all metabolic risk factors. High prevalence of the metabolic syndrome is not unique to the USA and Europe and it is also increasing in most Asian countries. Insulin resistance has elucidated most, if not all, of the pathophysiology of the metabolic syndrome because it contributes to hyperglycemia. Furthermore, a major contributor to the development of insulin resistance is an overabundance of circulating fatty acids. Plasma fatty acids are derived mainly from the triglycerides stored in adipose tissues, which are released through the action of the cyclic AMP-dependent enzyme, hormone sensitive lipase. This review summarizes the latest concepts in the definition, pathogenesis, pathophysiology, and diagnosis of the metabolic syndrome, as well as its preventive measures and therapeutic strategies in children and adolescents.

Potential Cardiometabolic Health Benefits of Full-Fat Dairy: The Evidence Base

Since their inception in 1980, the Dietary Guidelines for Americans have promoted low- or fat-free dairy foods. Removing fat from dairy does not reduce putatively beneficial nutrients per serving, including calcium, vitamin D, and potassium. Additionally, links between saturated fat and dietary cholesterol intakes with cardiovascular disease risk have helped to sustain the view that low-fat dairy foods should be recommended. Emerging evidence shows that the consumption of full-fat dairy foods has a neutral or inverse association with adverse cardiometabolic health outcomes, including atherosclerotic cardiovascular disease, type 2 diabetes, and associated risk factors. Thus, although low-fat dairy is a practical, practice-based recommendation, its superiority compared with full-fat dairy is not obviously supported by results from recent prospective cohort studies or intervention trials. To evaluate the emerging science on full-fat dairy, a group of nutrition experts convened to summarize and discuss the scientific evidence regarding the health effects of consuming full-fat dairy foods. Future studies should focus on full-fat dairy foods (milk, yogurt, and cheese) in the context of recommended dietary patterns and consider meal composition and metabolic phenotype in assessing the relation between full-fat dairy consumption and cardiometabolic health.

Perspective: Metabotyping-A Potential Personalized Nutrition Strategy for Precision Prevention of Cardiometabolic Disease

Diet is an important, modifiable lifestyle factor of cardiometabolic disease risk, and an improved diet can delay or even prevent the onset of disease. Recent evidence suggests that individuals could benefit from diets adapted to their genotype and phenotype: that is, personalized nutrition. A novel strategy is to tailor diets for groups of individuals according to their metabolic phenotypes (metabotypes). Randomized controlled trials evaluating metabotype-specific responses and nonresponses are urgently needed to bridge the current gap of knowledge with regard to the efficacy of personalized strategies in nutrition. In this Perspective, we discuss the concept of metabotyping, review the current literature on metabotyping in the context of cardiometabolic disease prevention, and suggest potential strategies for metabotype-based nutritional advice for future work. We also discuss potential determinants of metabotypes, including gut microbiota, and highlight the use of metabolomics to define effective markers for cardiometabolic disease-related metabotypes. Moreover, we hypothesize that people at high risk for cardiometabolic diseases have distinct metabotypes and that individuals grouped into specific metabotypes may respond differently to the same diet, which is being tested in a project of the Joint Programming Initiative: A Healthy Diet for a Healthy Life.

Biomarkers of a Healthy Nordic Diet-From Dietary Exposure Biomarkers to Microbiota Signatures in the Metabolome

Whole diets and dietary patterns are increasingly highlighted in modern nutrition and health research instead of single food items or nutrients alone. The Healthy Nordic Diet is a dietary pattern typically associated with beneficial health outcomes in observational studies, but results from randomized controlled trials are mixed. Dietary assessment is one of the greatest challenges in observational studies and compliance is a major challenge in dietary interventions. During the last decade, research has shown the great importance of the gut microbiota in health and disease. Studies have have both shown that the Nordic diet affects the gut microbiota and that the gut microbiota predicts the effects of such a diet. Rapid technique developments in the area of high-throughput mass spectrometry have enabled the large-scale use of metabolomics both as an objective measurement of dietary intake as well as in providing the final readout of the endogenous metabolic processes and the impact of the gut microbiota. In this review, we give an update on the current status on biomarkers that reflect a Healthy Nordic Diet or individual components thereof (food intake biomarkers), biomarkers that show the effects of a Healthy Nordic Diet and biomarkers reflecting the role of a Healthy Nordic Diet on the gut microbiota as well as how the gut microbiota or derived molecules may be used to predict the effects of a Healthy Nordic Diet on different outcomes.

Pretreatment Prevotella-to-Bacteroides ratio and markers of glucose metabolism as prognostic markers for dietary weight loss maintenance

BACKGROUND/OBJECTIVES

Pre-treatment gut microbial Prevotella-to-Bacteroides (P/B) ratio and markers of glucose metabolism (i.e., fasting glucose and insulin) have been suggested as biomarkers for optimal weight management. However, both biomarkers need further validation, and the interactions between them for optimal weight management are largely unknown. To investigate differences in weight loss maintenance between subjects with low and high P/B ratio and the potential interactions with markers of glucose metabolism and dietary fiber intake.

SUBJECTS/METHODS

Following an 8-week weight loss period using meal replacement products, subjects losing ≥ 8% of their initial body weight were randomized to one of three protein supplements or maltodextrin for a 24-week weight maintenance period. Habitual diet was consumed along with the supplements expected to constitute 10-15% of total energy. For this analysis we stratified the participants into low and high strata based on median values of pre-intervention P/B ratio, pre-weight loss Homeostatic model assessment of insulin resistance (HOMA-IR) (<2.33 or > 2.33), and dietary fiber intake during the intervention (< 28.5 or > 28.5 g/10 MJ).

RESULTS

Regardless of weight maintenance regimen, subjects with high P/B ratio (n = 63) regained 1.5 (95% CI 0.4, 2.7) kg body weight (P = 0.007) more than subjects with low P/B ratio (n = 63). The regain among subjects with high P/B ratio was particular evident if HOMA-IR was high and dietary fiber intake was low. Consequently, in the high P/B strata, subjects with high HOMA-IR and low fiber intake (n = 17) regained 5.3 (95% CI 3.3, 7.3) kg (P < 0.001) more body weight compared with participants with low HOMA-IR and high fiber intake (n = 16).

CONCLUSIONS

Subjects with high P/B ratio were more susceptible to regain body weight compared with subjects with low P/B ratio, especially when dietary fiber intake was low and glucose metabolism was impaired. These observations underline that both the P/B ratio and markers of glucose metabolism should be considered as important biomarkers within personalized nutrition for optimal weight management.