Precision nutrition in diabetes: when population-based dietary advice gets personal

Towards nutrition with precision: unlocking biomarkers as dietary assessment tools

Precision nutrition requires precise tools to monitor dietary habits. Yet current dietary assessment instruments are subjective, limiting our understanding of the causal relationships between diet and health. Biomarkers of food intake (BFIs) hold promise to increase the objectivity and accuracy of dietary assessment, enabling adjustment for compliance and misreporting. Here, we update current concepts and provide a comprehensive overview of BFIs measured in urine and blood. We rank BFIs based on a four-level utility scale to guide selection and identify combinations of BFIs that specifically reflect complex food intakes, making them applicable as dietary instruments. We discuss the main challenges in biomarker development and illustrate key solutions for the application of BFIs in human studies, highlighting different strategies for selecting and combining BFIs to support specific study designs. Finally, we present a roadmap for BFI development and implementation to leverage current knowledge and enable precision in nutrition research.

Glucagon kinetics assessed by mathematical modelling during oral glucose administration in people spanning from normal glucose tolerance to type 2 diabetes

Background/Objectives

Glucagon is important in the maintenance of glucose homeostasis, with also effects on lipids. In this study, we aimed to apply a recently developed model of glucagon kinetics to determine the sensitivity of glucagon variations (especially, glucagon inhibition) to insulin levels ("alpha-cell insulin sensitivity"), during oral glucose administration.

Subjects/Methods

We studied 50 participants (spanning from normal glucose tolerance to type 2 diabetes) undergoing frequently sampled 5-hr oral glucose tolerance test (OGTT). The alpha-cell insulin sensitivity and the glucagon kinetics were assessed by a mathematical model that we developed previously.

Results

The alpha-cell insulin sensitivity parameter (named SGLUCA; "GLUCA": "glucagon") was remarkably variable among participants (CV=221%). SGLUCA was found inversely correlated with the mean glycemic values, as well as with 2-hr glycemia of the OGTT. When stratifying participants into two groups (normal glucose tolerance, NGT, N=28, and impaired glucose regulation/type 2 diabetes, IGR_T2D, N=22), we found that SGLUCA was lower in the latter (1.50 ± 0.50·10-2 vs. 0.26 ± 0.14·10-2 ng·L-1 GLUCA/pmol·L-1 INS, in NGT and IGR_T2D, respectively, p=0.009; "INS": "insulin").

Conclusions

The alpha-cell insulin sensitivity is highly variable among subjects, and it is different in groups at different glucose tolerance. This may be relevant for defining personalized treatment schemes, in terms of dietary prescriptions but also for treatments with glucagon-related agents.

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

Background and Objectives: Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.

Association of dietary patterns with diabetes-related comorbidities varies among diabetes endotypes

BACKGROUND AND AIMS

Differences of dietary pattern adherence across the novel diabetes endotypes are unknown. This study assessed adherence to pre-specified dietary patterns and their associations with cardiovascular risk factors, kidney function, and neuropathy among diabetes endotypes.

METHODS AND RESULTS

The cross-sectional analysis included 765 individuals with recent-onset (67 %) and prevalent diabetes (33 %) from the German Diabetes Study (GDS) allocated into severe autoimmune diabetes (SAID, 35 %), severe insulin-deficient diabetes (SIDD, 3 %), severe insulin-resistant diabetes (SIRD, 5 %), mild obesity-related diabetes (MOD, 28 %), and mild age-related diabetes (MARD, 29 %). Adherence to a Mediterranean diet score (MDS), Dietary Approaches to Stop Hypertension (DASH) score, overall plant-based diet (PDI), healthful (hPDI) and unhealthful plant-based diet index (uPDI) was derived from a food frequency questionnaire and associated with cardiovascular risk factors, kidney function, and neuropathy using multivariable linear regression analysis. Differences in dietary pattern adherence between endotypes were assessed using generalized mixed models. People with MARD showed the highest, those with SIDD and MOD the lowest adherence to the hPDI. Adherence to the MDS, DASH, overall PDI, and hPDI was inversely associated with high-sensitivity C-reactive protein (hsCRP) among people with MARD (β (95%CI): -9.18 % (-15.61; -2.26); -13.61 % (-24.17; -1.58); -19.15 % (-34.28; -0.53); -16.10 % (-28.81; -1.12), respectively). Adherence to the PDIs was associated with LDL cholesterol among people with SAID, SIRD, and MOD.

CONCLUSIONS

Minor differences in dietary pattern adherence (in particular for hPDI) and associations with markers of diabetes-related complications (e.g. hsCRP) were observed between endotypes. So far, evidence is insufficient to derive endotype-specific dietary recommendations.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT01055093.

Personalized Versus Non-personalized Nutritional Recommendations/Interventions for Type 2 Diabetes Mellitus Remission: A Narrative Review

It is a well-evidenced fact that diet significantly impacts type 2 diabetes mellitus (T2DM) prevention and management. However, dietary responses vary among different populations, necessitating personalized recommendations. Substantial evidence supports the role of diet in T2DM remission, particularly low-energy or low-carbohydrate diets that facilitate weight loss, enhance glycemic control, and achieve remission. This review aims to comprehensively analyze and compare personalized nutritional interventions with non-personalized approaches in T2DM remission. We conducted a literature search using the Academy of Nutrition and Dietetics guidelines, focusing on clinical and observational trials published within the past decade. We present the strengths and drawbacks of incorporating personalized nutrition into practice, along with the areas for research in implementing personalized interventions, such as cost-effectiveness and accessibility. The findings reveal consistently higher diabetes remission rates in personalized nutrition studies compared to non-personalized interventions.

Assessment of the impact of a personalised nutrition intervention in impaired glucose regulation over 26 weeks: a randomised controlled trial

Dietary interventions can reduce progression to type 2 diabetes mellitus (T2DM) in people with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA-personalised nutrition intervention in people with non-diabetic hyperglycaemia over 26 weeks. ASPIRE-DNA was a pilot study. Participants were randomised into three arms to receive either (i) Control arm: standard care (NICE guidelines) (n = 51), (ii) Intervention arm: DNA-personalised dietary advice (n = 50), or (iii) Exploratory arm: DNA-personalised dietary advice via a self-guided app and wearable device (n = 46). The primary outcome was the difference in fasting plasma glucose (FPG) between the Control and Intervention arms after 6 weeks. 180 people were recruited, of whom 148 people were randomised, mean age of 59 years (SD = 11), 69% of whom were female. There was no significant difference in the FPG change between the Control and Intervention arms at 6 weeks (- 0.13 mmol/L (95% CI [- 0.37, 0.11]), p = 0.29), however, we found that a DNA-personalised dietary intervention led to a significant reduction of FPG at 26 weeks in the Intervention arm when compared to standard care (- 0.019 (SD = 0.008), p = 0.01), as did the Exploratory arm (- 0.021 (SD = 0.008), p = 0.006). HbA1c at 26 weeks was significantly reduced in the Intervention arm when compared to standard care (- 0.038 (SD = 0.018), p = 0.04). There was some evidence suggesting prevention of progression to T2DM across the groups that received a DNA-based intervention (p = 0.06). Personalisation of dietary advice based on DNA did not result in glucose changes within the first 6 weeks but was associated with significant reduction of FPG and HbA1c at 26 weeks when compared to standard care. The DNA-based diet was effective regardless of intervention type, though results should be interpreted with caution due to the low sample size. These findings suggest that DNA-based dietary guidance is an effective intervention compared to standard care, but there is still a minimum timeframe of adherence to the intervention before changes in clinical outcomes become apparent.Trial Registration: www.clinicaltrials.gov.uk Ref: NCT03702465.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATIONS

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

Dietary intervention improves metabolic levels in patients with type 2 diabetes through the gut microbiota: a systematic review and meta-analysis

Background

Poor dietary structure plays a pivotal role in the development and progression of type 2 diabetes and is closely associated with dysbiosis of the gut microbiota. Thus, the objective of this systematic review was to assess the impact of dietary interventions on improving gut microbiota and metabolic levels in patients with type 2 diabetes.

Methods

We conducted a systematic review and meta-analysis following the PRISMA 2020 guidelines.

Results

Twelve studies met the inclusion criteria. In comparison to baseline measurements, the high-fiber diet produced substantial reductions in FBG (mean difference -1.15 mmol/L; 95% CI, -2.24 to -0.05; I2 = 94%; P = 0.04), HbA1c (mean difference -0.99%; 95% CI, -1.93 to -0.03; I2 = 89%; P = 0.04), and total cholesterol (mean difference -0.95 mmol/L; 95% CI, -1.57 to -0.33; I2 = 77%; P = 0.003); the high-fat and low-carbohydrate diet led to a significant reduction in HbA1c (mean difference -0.98; 95% CI, -1.50 to -0.46; I2 = 0%; P = 0.0002). Within the experimental group (intervention diets), total cholesterol (mean difference -0.69 mmol/L; 95% CI, -1.27 to -0.10; I2 = 52%; P = 0.02) and LDL-C (mean difference -0.45 mmol/L; 95% CI, -0.68 to -0.22; I2 = 0%; P < 0.0001) experienced significant reductions in comparison to the control group (recommended diets for type 2 diabetes). However, no statistically significant differences emerged in the case of FBG, HbA1c, HOMA-IR, and HDL-C between the experimental and control groups. The high dietary fiber diet triggered an augmented presence of short-chain fatty acid-producing bacteria in the intestines of individuals with T2DM. In addition, the high-fat and low-carbohydrate diet resulted in a notable decrease in Bacteroides abundance while simultaneously increasing the relative abundance of Eubacterium. Compared to a specific dietary pattern, personalized diets appear to result in the production of a greater variety of beneficial bacteria in the gut, leading to more effective blood glucose control in T2D patients.

Conclusion

Dietary interventions hold promise for enhancing metabolic profiles in individuals with T2D through modulation of the gut microbiota. Tailored dietary regimens appear to be more effective than standard diets in improving glucose metabolism. However, given the limited and highly heterogeneous nature of the current sample size, further well-designed and controlled intervention studies are warranted in the future.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Embracing complexity: making sense of diet, nutrition, obesity and type 2 diabetes

Nutrition therapy has been emphasised for decades for people with type 2 diabetes, and the vital importance of diet and nutrition is now also recognised for type 2 diabetes prevention. However, the complexity of diet and mixed messages on what is unhealthy, healthy or optimal have led to confusion among people with diabetes and their physicians as well as the general public. What should people eat for the prevention, management and remission of type 2 diabetes? Recently, progress has been made in research evidence that has advanced our understanding in several areas of past uncertainty. This article examines some of these issues, focusing on the role of diet in weight management and in the prevention and management of type 2 diabetes. It considers nutritional strategies including low-energy, low-fat and low-carbohydrate diets, discusses inter-relationships between nutrients, foods and dietary patterns, and examines aspects of quantity and quality together with new developments, challenges and future directions.

Using Continuous Glucose Monitoring to Prescribe a Time to Exercise for Individuals with Type 2 Diabetes

This study examines the potential utility of using continuous glucose monitoring (CGM) to prescribe an exercise time to target peak hyperglycaemia in people with type 2 diabetes (T2D). The main aim is to test the feasibility of prescribing an individualised daily exercise time, based on the time of CGM-derived peak glucose, for people with T2D. Thirty-five individuals with T2D (HbA1c: 7.2 ± 0.8%; age: 64 ± 7 y; BMI: 29.2 ± 5.2 kg/m²) were recruited and randomised to one of two 14 d exercise interventions: i) ExPeak (daily exercise starting 30 min before peak hyperglycaemia) or placebo active control NonPeak (daily exercise starting 90 min after peak hyperglycaemia). The time of peak hyperglycaemia was determined via a two-week baseline CGM. A CGM, accelerometer, and heart rate monitor were worn during the free-living interventions to objectively measure glycaemic control outcomes, moderate-to-vigorous intensity physical activity (MVPA), and exercise adherence for future translation in a clinical trial. Participation in MVPA increased 26% when an exercise time was prescribed compared to habitual baseline (p < 0.01), with no difference between intervention groups (p > 0.26). The total MVPA increased by 10 min/day during the intervention compared to the baseline (baseline: 23 ± 14 min/d vs. intervention: 33 ± 16 min/d, main effect of time p = 0.03, no interaction). The change in peak blood glucose (mmol/L) was similar between the ExPeak (-0.44 ± 1.6 mmol/L, d = 0.21) and the NonPeak (-0.39 ± 1.5 mmol/L, d = 0.16) intervention groups (p = 0.92). Prescribing an exercise time based on CGM may increase daily participation in physical activity in people with type 2 diabetes; however, further studies are needed to test the long-term impact of this approach.

Probiotics and Prebiotics as Dietary Supplements for the Adjunctive Treatment of Type 2 Diabetes

In modern lifestyles, high-fat diets and prolonged inactivity lead to more people developing type 2 diabetes (T2D). Based on the modern pathogenesis of T2D, food, and its components have become one of the top concerns for patients. Recent studies have found that dysbiosis and gut-related inflammation are more common in T2D patients. Probiotics and prebiotics play complementary roles in the gut as dietary supplements. Together, they may help improve dysbiosis and intestinal inflammation in people with T2D, increase the production of blood glucose-lowering hormones such as incretin, and help reduce insulin resistance and lower blood glucose. Therefore, changing the dietary structure and increasing the intake of probiotics and prebiotics is expected to become a new strategy for the adjuvant treatment of T2D.

Prognostic nutritional index as a risk factor for diabetic kidney disease and mortality in patients with type 2 diabetes mellitus

AIMS

Microinflammation and malnutrition are common in individuals with type 2 diabetes mellitus (T2DM). We aimed to validate whether prognostic nutritional index (PNI) may increase the risk of diabetic kidney disease (DKD) and all-cause mortality in T2DM patients.

METHODS

This retrospective cohort study was based on the National Health and Nutrition Examination Survey (NHANES) and National Death Index (NDI) 2013-2018 database. A total of 14,349 eligible subjects were included, and 2720 of them were with T2DM. PNI was assessed by the 5 × lymphocyte count (10⁹/L) + serum albumin (g/L). The Logistic and Cox regression analyses were conducted to investigate the risk factors of DKD and mortality in T2DM patients.

RESULTS

For 14,349 participants represented 224.7 million noninstitutionalized residents of the United State, the average PNI was 53.72 ± 0.12, and the prevalence of T2DM was 14.89%. T2DM patients had a lower level of PNI and dietary protein intake, a higher risk of mortality, kidney injury, anemia, arterial hypertension and hyperuricemia, compared with non-T2DM subjects. DKD occurred in 35.06% of diabetic participants and a higher PNI was independently related with a lower risk of DKD (OR 0.64, 95% CI 0.459-0.892, p = 0.01) in T2DM after multivariate adjustment. During a median follow-up of 46 person-months (29-66 months), a total of 233 T2DM individuals died from all causes (mortality rate = 8.17%). Subjects with T2DM who had a higher PNI showed a lower risk of all-cause mortality (HR 0.60, 95% CI 0.37-0.97, p = 0.036).

CONCLUSIONS

PNI, as a marker of immunonutrition, correlated with the incidence of DKD, and was an independent predictor for all-cause mortality in participants with T2DM. Thus, PNI may conduce to the risk stratification and timely intervention of T2DM patients.

MetaboVariation: Exploring Individual Variation in Metabolite Levels

To date, most metabolomics biomarker research has focused on identifying disease biomarkers. However, there is a need for biomarkers of early metabolic dysfunction to identify individuals who would benefit from lifestyle interventions. Concomitantly, there is a need to develop strategies to analyse metabolomics data at an individual level. We propose "MetaboVariation", a method that models repeated measurements on individuals to explore fluctuations in metabolite levels at an individual level. MetaboVariation employs a Bayesian generalised linear model to flag individuals with intra-individual variations in their metabolite levels across multiple measurements. MetaboVariation models repeated metabolite levels as a function of explanatory variables while accounting for intra-individual variation. The posterior predictive distribution of metabolite levels at the individual level is available, and is used to flag individuals with observed metabolite levels outside the 95% highest posterior density prediction interval at a given time point. MetaboVariation was applied to a dataset containing metabolite levels for 20 metabolites, measured once every four months, in 164 individuals. A total of 28% of individuals with intra-individual variations in three or more metabolites were flagged. An R package for MetaboVariation was developed with an embedded R Shiny web application. To summarize, MetaboVariation has made considerable progress in developing strategies for analysing metabolomics data at the individual level, thus paving the way toward personalised healthcare.

Selenium in Bodily Homeostasis: Hypothalamus, Hormones, and Highways of Communication

The ability of the body to maintain homeostasis requires constant communication between the brain and peripheral tissues. Different organs produce signals, often in the form of hormones, which are detected by the hypothalamus. In response, the hypothalamus alters its regulation of bodily processes, which is achieved through its own pathways of hormonal communication. The generation and transmission of the molecules involved in these bi-directional axes can be affected by redox balance. The essential trace element selenium is known to influence numerous physiological processes, including energy homeostasis, through its various redox functions. Selenium must be obtained through the diet and is used to synthesize selenoproteins, a family of proteins with mainly antioxidant functions. Alterations in selenium status have been correlated with homeostatic disturbances in humans and studies with animal models of selenoprotein dysfunction indicate a strong influence on energy balance. The relationship between selenium and energy metabolism is complicated, however, as selenium has been shown to participate in multiple levels of homeostatic communication. This review discusses the role of selenium in the various pathways of communication between the body and the brain that are essential for maintaining homeostasis.

Level of dietary adherence and determinants among type 2 diabetes population in Ethiopian: A systemic review with meta-analysis

BACKGROUND

The beneficial effect of the dietary practice is significant reduction in the risk of developing diabetes related complication. Dietary practice among type 2 diabetes is not well-implemented in Ethiopia. Up to now, in the nation, several primary observational studies have been done on dietary adherence level and its determinants among type 2 diabetes. However, a comprehensive review that would have a lot of strong evidence for designing intervention is lacking. So, this review with a meta-analysis was conducted to bridge this gap.

METHODS

A systematic review of an observational study is conducted following the PRISMA checklist. Three reviewers have been searched and extracted from the World Health Organization- Hinari portal (SCOPUS, African Index Medicus, and African Journals Online databases), PubMed, Google Scholar and EMBASE. Articles' quality was assessed using the Newcastle-Ottawa Scale by two independent reviewers, and only studies with low and moderate risk were included in the final analysis. The review presented the pooled proportion dietary adherence among type2 diabetes and the odds ratios of risk factors favor to dietary adherence after checking for heterogeneity and publication bias. The review has been registered in PROSPERO with protocol number CRD42020149475.

RESULTS

We included 19 primary studies (with 6, 308 participants) in this meta-analysis. The pooled proportion of dietary adherence in the type 2 diabetes population was 41.05% (95% CI: 34.86-47.24, I2 = 93.1%). Educational level (Pooled Odds Ratio (POR): 3.29; 95%CI: 1.41-5.16; I2 = 91.1%), monthly income (POR: 2.50; 95%CI: 1.41-3.52; I2 = 0.0%), and who had dietary knowledge (POR: 2.19; 95%CI: 1.59-2.79; I2 = 0.0%) were statistically significant factors of dietary adherence.

CONCLUSION

The overall pooled proportion of dietary adherence among type 2 diabetes in Ethiopia was below half. Further works would be needed to improve dietary adherence in the type 2 diabetes population. So, factors that were identified might help to revise the plan set by the country, and further research might be required to health facility fidelity and dietary education according to diabetes recommended dietary guideline.

Distinct impacts of fat and fructose on the liver, muscle, and adipose tissue metabolome: An integrated view

OBJECTIVE

In the last years, changes in dietary habits have contributed to the increasing prevalence of metabolic disorders, such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). The differential burden of lipids and fructose on distinct organs needs to be unveiled. Herein, we hypothesized that high-fat and high-fructose diets differentially affect the metabolome of insulin-sensitive organs such as the liver, muscle, and different adipose tissue depots.

METHODS

We have studied the impact of 12 weeks of a control (11.50% calories from fat, 26.93% from protein, and 61.57% from carbohydrates), high-fat/sucrose (HFat), or high-fructose (HFruct) feeding on C57Bl/6J male mice. Besides glucose homeostasis, we analyzed the hepatic levels of glucose and lipid-metabolism-related genes and the metabolome of the liver, the muscle, and white (WAT) and brown adipose tissue (BAT) depots.

RESULTS

HFat diet led to a more profound impact on hepatic glucose and lipid metabolism than HFruct, with mice presenting glucose intolerance, increased saturated fatty acids, and no glycogen pool, yet both HFat and HFruct presented hepatic insulin resistance. HFat diet promoted a decrease in glucose and lactate pools in the muscle and an increase in glutamate levels. While HFat had alterations in BAT metabolites that indicate increased thermogenesis, HFruct led to an increase in betaine, a protective metabolite against fructose-induced inflammation.

CONCLUSIONS

Our data illustrate that HFat and HFruct have a negative but distinct impact on the metabolome of the liver, muscle, WAT, and BAT.