Weight loss at your fingertips: personalized nutrition with fasting glucose and insulin using a novel statistical approach

Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes

PURPOSE OF REVIEW

Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.

RECENT FINDINGS

The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.

Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity

Background

Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss success.

Methods

Within the 8-month multicenter dietary intervention study DiOGenes, we classified a low weight-losers (low-WL) group and a high-WL group based on median weight loss percentage (9.9%) from 281 individuals. Using RNA sequencing, we identified the significantly differentially expressed genes between high-WL and low-WL at baseline and their enriched pathways. We used this information together with support vector machines with linear kernel to build classifier models that predict the weight loss classes.

Results

Prediction models based on a selection of genes that are associated with the discovered pathways 'lipid metabolism' (max AUC = 0.74, 95% CI [0.62-0.86]) and 'response to virus' (max AUC = 0.72, 95% CI [0.61-0.83]) predicted the weight-loss classes high-WL/low-WL significantly better than models based on randomly selected genes (P < 0.01). The performance of the models based on 'response to virus' genes is highly dependent on those genes that are also associated with lipid metabolism. Incorporation of baseline clinical factors into these models did not noticeably enhance the model performance in most of the runs. This study demonstrates that baseline adipose tissue gene expression data, together with supervised machine learning, facilitates the characterization of the determinants of successful weight loss.

Nordic dietary patterns and cardiometabolic outcomes: a systematic review and meta-analysis of prospective cohort studies and randomised controlled trials

AIMS/HYPOTHESIS

Nordic dietary patterns that are high in healthy traditional Nordic foods may have a role in the prevention and management of diabetes. To inform the update of the EASD clinical practice guidelines for nutrition therapy, we conducted a systematic review and meta-analysis of Nordic dietary patterns and cardiometabolic outcomes.

METHODS

We searched MEDLINE, EMBASE and The Cochrane Library from inception to 9 March 2021. We included prospective cohort studies and RCTs with a follow-up of ≥1 year and ≥3 weeks, respectively. Two independent reviewers extracted relevant data and assessed the risk of bias (Newcastle-Ottawa Scale and Cochrane risk of bias tool). The primary outcome was total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs. Secondary outcomes in the prospective cohort studies were CVD mortality, CHD incidence and mortality, stroke incidence and mortality, and type 2 diabetes incidence; in the RCTs, secondary outcomes were other established lipid targets (non-HDL-cholesterol, apolipoprotein B, HDL-cholesterol, triglycerides), markers of glycaemic control (HbA_1c, fasting glucose, fasting insulin), adiposity (body weight, BMI, waist circumference) and inflammation (C-reactive protein), and blood pressure (systolic and diastolic blood pressure). The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach was used to assess the certainty of the evidence.

RESULTS

We included 15 unique prospective cohort studies (n=1,057,176, with 41,708 cardiovascular events and 13,121 diabetes cases) of people with diabetes for the assessment of cardiovascular outcomes or people without diabetes for the assessment of diabetes incidence, and six RCTs (n=717) in people with one or more risk factor for diabetes. In the prospective cohort studies, higher adherence to Nordic dietary patterns was associated with 'small important' reductions in the primary outcome, total CVD incidence (RR for highest vs lowest adherence: 0.93 [95% CI 0.88, 0.99], p=0.01; substantial heterogeneity: I²=88%, p_Q<0.001), and similar or greater reductions in the secondary outcomes of CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). Inverse dose-response gradients were seen for total CVD incidence, CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). No studies assessed CHD or stroke mortality. In the RCTs, there were small important reductions in LDL-cholesterol (mean difference [MD] -0.26 mmol/l [95% CI -0.52, -0.00], p_MD=0.05; substantial heterogeneity: I²=89%, p_Q<0.01), and 'small important' or greater reductions in the secondary outcomes of non-HDL-cholesterol, apolipoprotein B, insulin, body weight, BMI and systolic blood pressure (p<0.05). For the other outcomes there were 'trivial' reductions or no effect. The certainty of the evidence was low for total CVD incidence and LDL-cholesterol; moderate to high for CVD mortality, established lipid targets, adiposity markers, glycaemic control, blood pressure and inflammation; and low for all other outcomes, with evidence being downgraded mainly because of imprecision and inconsistency.

CONCLUSIONS/INTERPRETATION

Adherence to Nordic dietary patterns is associated with generally small important reductions in the risk of major CVD outcomes and diabetes, which are supported by similar reductions in LDL-cholesterol and other intermediate cardiometabolic risk factors. The available evidence provides a generally good indication of the likely benefits of Nordic dietary patterns in people with or at risk for diabetes.

REGISTRATION

ClinicalTrials.gov NCT04094194.

FUNDING

Diabetes and Nutrition Study Group of the EASD Clinical Practice.

Appraisal of Triglyceride-Related Markers as Early Predictors of Metabolic Outcomes in the PREVIEW Lifestyle Intervention: A Controlled Post-hoc Trial

Background: Individuals with pre-diabetes are commonly overweight and benefit from dietary and physical activity strategies aimed at decreasing body weight and hyperglycemia. Early insulin resistance can be estimated via the triglyceride glucose index {TyG = Ln [TG (mg/dl) × fasting plasma glucose (FPG) (mg/dl)/2]} and the hypertriglyceridemic-high waist phenotype (TyG-waist), based on TyG x waist circumference (WC) measurements. Both indices may be useful for implementing personalized metabolic management. In this secondary analysis of a randomized controlled trial (RCT), we aimed to determine whether the differences in baseline TyG values and TyG-waist phenotype predicted individual responses to type-2 diabetes (T2D) prevention programs. Methods: The present post-hoc analyses were conducted within the Prevention of Diabetes through Lifestyle intervention and population studies in Europe and around the world (PREVIEW) study completers (n = 899), a multi-center RCT conducted in eight countries (NCT01777893). The study aimed to reduce the incidence of T2D in a population with pre-diabetes during a 3-year randomized intervention with two sequential phases. The first phase was a 2-month weight loss intervention to achieve ≥8% weight loss. The second phase was a 34-month weight loss maintenance intervention with two diets providing different amounts of protein and different glycemic indices, and two physical activity programs with different exercise intensities in a 2 x 2 factorial design. On investigation days, we assessed anthropometrics, glucose/lipid metabolism markers, and diet and exercise questionnaires under standardized procedures. Results: Diabetes-related markers improved during all four lifestyle interventions. Higher baseline TyG index (p < 0.001) was associated with greater reductions in body weight, fasting glucose, and triglyceride (TG), while a high TyG-waist phenotype predicted better TG responses, particularly in those randomized to physical activity (PA) of moderate intensity. Conclusions: Two novel indices of insulin resistance (TyG and TyG-waist) may allow for a more personalized approach to avoiding progression to T2D. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01777893 reference, identifier: NCT01777893.

What is the promise of personalised nutrition?

Personalised nutrition (PN) is an emerging field that bears great promise. Several definitions of PN have been proposed and different modelling approaches have been used to claim PN effects. We tentatively propose to group these approaches into two categories, which we term outcome-based and population reference approaches, respectively. Understanding the fundamental differences between these two types of modelling approaches may allow a more realistic appreciation of what to expect from PN interventions presently and may be helpful for designing and planning future studies investigating PN interventions.

Evidence-based weight loss interventions: Individualized treatment options to maximize patient outcomes

Against the backdrop of obesity as a major public health problem, we examined three questions: How much weight loss is needed to benefit patients with obesity? How well do current therapies do in producing weight loss? What strategies can be used to improve patient outcomes using evidence-based studies. This paper reviews literature on the outcomes of lifestyle, diet, medications and surgical treatments for obesity using literature searches for obesity treatments. Current treatments, including lifestyle, diet and exercise, produce a weight loss of 5% to 7% on average. Despite continued attempts to identify superior dietary approaches, most careful comparisons find that low carbohydrate diets are not significantly better than low fat diets for weight loss. The four medications currently approved by the US Food and Drug Administration for long-term management of obesity are not as effective as surgery, adding about 5% on average to lifestyle approaches to weight loss. Two new medications that are under investigation, semaglutide and tirzepatide, significantly improve on this. For all treatments for weight loss, including lifestyle, medications and surgery, there is enormous variability in the amount of weight lost. Examination of this literature has yielded evidence supporting baseline and process predictors, but the effect sizes associated with these predictors are small and there are no prospective studies showing that a personalized approach based on genotype or phenotype will yield uniform success. Because obesity is a chronic disease it requires a 'continuous treatment model' across the lifespan.

Data integration for prediction of weight loss in randomized controlled dietary trials

Diet is an important component in weight management strategies, but heterogeneous responses to the same diet make it difficult to foresee individual weight-loss outcomes. Omics-based technologies now allow for analysis of multiple factors for weight loss prediction at the individual level. Here, we classify weight loss responders (N = 106) and non-responders (N = 97) of overweight non-diabetic middle-aged Danes to two earlier reported dietary trials over 8 weeks. Random forest models integrated gut microbiome, host genetics, urine metabolome, measures of physiology and anthropometrics measured prior to any dietary intervention to identify individual predisposing features of weight loss in combination with diet. The most predictive models for weight loss included features of diet, gut bacterial species and urine metabolites (ROC-AUC: 0.84-0.88) compared to a diet-only model (ROC-AUC: 0.62). A model ensemble integrating multi-omics identified 64% of the non-responders with 80% confidence. Such models will be useful to assist in selecting appropriate weight management strategies, as individual predisposition to diet response varies.

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.

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.

The role of dietary protein in obesity

Protein-rich diets are surging in popularity for weight loss. An increase in diet-induced thermogenesis, better preservation of fat-free mass, and enhanced satiety with greater dietary protein intakes may lead to increased energy expenditure and decreased energy intake; and thus promote a more negative energy balance that facilitates weight loss. Results from large randomized trials and meta-analyses of many smaller trials indicate that high-protein diets typically induce significantly greater amounts of weight loss than conventional low-fat or high-carbohydrate diets during the early, rapid weight loss phase (3-6 months), but differences between diets are attenuated and no longer significant during the late, slow weight loss phase (12-24 months). Gradually decreasing adherence may be responsible for this observation; in fact, dietary adherence, rather than macronutrient composition, is likely the major predictor of long-term weight loss success. Recently, some randomized trials evaluated the efficacy of high-protein (vs. normal-protein) diets consumed ad libitum during weight loss maintenance, i.e. after clinically significant weight loss. Weight regain may be smaller with high-protein diets in the short-term (3-12 months), but longer studies are needed to confirm this. Given the lack of conclusive evidence in favor of high-protein diets, or any other dietary pattern, it is reasonable to conclude that no individual nutrient is a friend or a foe when it comes to weight loss and its maintenance. Therefore, any diet that best suits one's dietary habits and food preferences is likely to be better adhered to, and thus lead to more successful long-term weight loss.

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.

Pretreatment Prevotella-to-Bacteroides ratio and salivary amylase gene copy number as prognostic markers for dietary weight loss

BACKGROUND

The inconsistent link observed between salivary amylase gene copy number (AMY1 CN) and weight management is likely modified by diet and microbiome.

OBJECTIVE

Based on analysis of a previously published study, we investigated the hypothesis that interaction between diet, Prevotella-to-Bacteriodes ratio (P/B ratio), and AMY1 CN influence weight change.

METHODS

Sixty-two people with increased waist circumference were randomly assigned to receive an ad libitum New Nordic Diet (NND) high in dietary fiber, whole grain, intrinsic sugars, and starch or an Average Danish (Western) Diet (ADD) for 26 weeks. All foods were provided free of charge. Before subjects were randomly assigned to receive the NND or ADD diet, blood and fecal samples were collected, from which AMY1 CN and P/B ratio, respectively, were determined. Body weight change was described by using linear mixed models, including biomarker [log10(P/B ratio) and/or AMY1 CN] diet-group interactions.

RESULTS

Baseline means ± SDs of log10(P/B ratio) and AMY1 CN were -2.1 ± 1.8 and 6.6 ± 2.4, respectively. Baseline P/B ratio predicted a 0.99-kg/unit (95% CI: 0.40, 1.57; n = 54; P < 0.001) higher weight loss for those subjects on the NND compared with those on the ADD diet, whereas AMY1 CN was not found to predict weight loss differences between the NND and ADD groups [0.05 kg/CN (95% CI: -0.40, 0.51; n = 54; P = 0.83)]. However, among subjects with low AMY1 CN (<6.5 copies), baseline P/B ratio predicted a 2.12-kg/unit (95% CI: 1.37, 2.88; n = 30; P < 0.001) higher weight loss for the NND group than the ADD group. No such differences in weight loss were found among subjects in both groups with high AMY1 CN [-0.17 kg/unit (95% CI: -1.01, 0.66; n = 24; P = 0.68)].

CONCLUSIONS

The combined use of low AMY1 CN and pretreatment P/B ratio for weight loss prediction led to highly individualized weight loss results with the introduction of more fiber, whole grain, intrinsic sugars, and starch in the diet. These preliminary observations suggest that more undigested starch reaches the colon in individuals with low AMY1 CN, and that the fate of this starch depends on the gut microbiota composition. This trial was registered at clinicaltrials.gov as NCT01195610.

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.