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

Fasting and postprandial plasma metabolite responses to a 12-wk dietary intervention in tissue-specific insulin resistance: a secondary analysis of the PERSonalized glucose Optimization through Nutritional intervention (PERSON) randomized trial

BACKGROUND

We previously showed that dietary intervention effects on cardiometabolic health were driven by tissue-specific insulin resistance (IR) phenotype: individuals with predominant muscle IR (MIR) benefited more from a low-fat, high-protein, and high-fiber (LFHP) diet, whereas individuals with predominant liver insulin resistance (LIR) benefited more from a high-monounsaturated fatty acid (HMUFA) diet.

OBJECTIVES

To further characterize the effects of LFHP and HMUFA diets and their interaction with tissue-specific IR, we investigated dietary intervention effects on fasting and postprandial plasma metabolite profile.

METHODS

Adults with MIR or LIR (40-75 y, BMI 25-40 kg/m2) were randomly assigned to a 12-wk HMUFA or LFHP diet (n = 242). After the exclusion of statin use, 214 participants were included in this prespecified secondary analysis. Plasma samples were collected before (T = 0) and after (T = 30, 60, 120, and 240 min) a high-fat mixed meal for quantification of 247 metabolite measures using nuclear magnetic resonance spectroscopy.

RESULTS

A larger reduction in fasting VLDL-triacylglycerol (TAG) and VLDL particle size was observed in individuals with MIR following the LFHP diet and those with LIR following the HMUFA diet, although no longer statistically significant after false discovery rate (FDR) adjustment. No IR phenotype-by-diet interactions were found for postprandial plasma metabolites assessed as total area under the curve (tAUC). Irrespective of IR phenotype, the LFHP diet induced greater reductions in postprandial plasma tAUC of the larger VLDL particles and small HDL particles, and TAG content in most VLDL subclasses and the smaller LDL and HDL subclasses (for example, VLDL-TAG tAUC standardized mean change [95% CI] LFHP = -0.29 [-0.43, -0.16] compared with HMUFA = -0.04 [-0.16, 0.09]; FDR-adjusted P for diet × time = 0.041).

CONCLUSIONS

Diet effects on plasma metabolite profiles were more pronounced than phenotype-by-diet interactions. An LFHP diet may be more effective than an HMUFA diet for reducing cardiometabolic risk in individuals with tissue-specific IR, irrespective of IR phenotype. Am J Clin Nutr 20xx;x:xx. This trial was registered at the clinicaltrials.gov registration (https://clinicaltrials.gov/study/NCT03708419?term=NCT03708419&rank=1) as NCT03708419 and CCMO registration (https://www.toetsingonline.nl/to/ccmo_search.nsf/fABRpop?readform&unids=3969AABCD9BA27FEC12587F1001BCC65) as NL63768.068.17.

Effects of dietary fibre on metabolic health and obesity

Obesity and metabolic syndrome represent a growing epidemic worldwide. Body weight is regulated through complex interactions between hormonal, neural and metabolic pathways and is influenced by numerous environmental factors. Imbalances between energy intake and expenditure can occur due to several factors, including alterations in eating behaviours, abnormal satiation and satiety, and low energy expenditure. The gut microbiota profoundly affects all aspects of energy homeostasis through diverse mechanisms involving effects on mucosal and systemic immune, hormonal and neural systems. The benefits of dietary fibre on metabolism and obesity have been demonstrated through mechanistic studies and clinical trials, but many questions remain as to how different fibres are best utilized in managing obesity. In this Review, we discuss the physiochemical properties of different fibres, current findings on how fibre and the gut microbiota interact to regulate body weight homeostasis, and knowledge gaps related to using dietary fibres as a complementary strategy. Precision medicine approaches that utilize baseline microbiota and clinical characteristics to predict individual responses to fibre supplementation represent a new paradigm with great potential to enhance weight management efficacy, but many challenges remain before these approaches can be fully implemented.

Association between Diet Quality and Risk of Type 2 Diabetes Mellitus in Patients with Coronary Heart Disease: Findings from the CORDIOPREV Study

The incidence of type 2 diabetes mellitus (T2DM) is growing in Western countries. Nutritional interventions that promote high-quality dietary patterns could help reverse this trend. We aimed to evaluate whether changes in Nutrient-Rich Food Index 9.3 (NRF9.3) were related to the risk of developing T2DM in patients with coronary heart disease (CHD). The study was carried out in the context of two healthy dietary interventions (a Mediterranean and a low-fat diet). For this purpose, we evaluated all the patients in the CORDIOPREV study without T2DM at baseline. Data were obtained during the first 5 years of dietary intervention. The score was calculated using the Food Frequency Questionnaires at baseline and after 1 year of intervention. After 5 years of follow-up, 106 patients developed T2DM (incident-T2DM), while 316 subjects did not (non-T2DM). Total NRF9.3 score and changes during the first year of intervention were compared between incident-T2DM and non-T2DM. Incident-T2DM showed less improvement in NRF9.3 than non-T2DM (p = 0.010). In the multi-adjusted Cox proportional hazard study, patients with greater improvement in NRF9.3 had over 50% less risk of developing T2DM compared with the lowest tertile (HR 2.10, 95%, CI = 1.12-3.56). In conclusion, improved diet quality in terms of nutrient density after the dietary intervention was associated with a lower risk of T2DM in patients with CHD.

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.

Body composition and body fat distribution in tissue-specific insulin resistance and in response to a 12-week isocaloric dietary macronutrient intervention

BACKGROUND

Body composition and body fat distribution are important predictors of cardiometabolic diseases. The etiology of cardiometabolic diseases is heterogenous, and partly driven by inter-individual differences in tissue-specific insulin sensitivity.

OBJECTIVES

To investigate (1) the associations between body composition and whole-body, liver and muscle insulin sensitivity, and (2) changes in body composition and insulin sensitivity and their relationship after a 12-week isocaloric diet high in mono-unsaturated fatty acids (HMUFA) or a low-fat, high-protein, high-fiber (LFHP) diet.

METHODS

This subcohort analysis of the PERSON study includes 93 individuals (53% women, BMI 25-40 kg/m2, 40-75 years) who participated in this randomized intervention study. At baseline and after 12 weeks of following the LFHP, or HMUFA diet, we performed a 7-point oral glucose tolerance test to assess whole-body, liver, and muscle insulin sensitivity, and whole-body magnetic resonance imaging to determine body composition and body fat distribution. Both diets are within the guidelines of healthy nutrition.

RESULTS

At baseline, liver fat content was associated with worse liver insulin sensitivity (β [95%CI]; 0.12 [0.01; 0.22]). Only in women, thigh muscle fat content was inversely related to muscle insulin sensitivity (-0.27 [-0.48; -0.05]). Visceral adipose tissue (VAT) was inversely associated with whole-body, liver, and muscle insulin sensitivity. Both diets decreased VAT, abdominal subcutaneous adipose tissue (aSAT), and liver fat, but not whole-body and tissue-specific insulin sensitivity with no differences between diets. Waist circumference, however, decreased more following the LFHP diet as compared to the HMUFA diet (-3.0 vs. -0.5 cm, respectively). After the LFHP but not HMUFA diet, improvements in body composition were positively associated with improvements in whole-body and liver insulin sensitivity.

CONCLUSIONS

Liver and muscle insulin sensitivity are distinctly associated with liver and muscle fat accumulation. Although both LFHP and HMUFA diets improved in body fat, VAT, aSAT, and liver fat, only LFHP-induced improvements in body composition are associated with improved insulin sensitivity.

TRIAL REGISTRATION

NCT03708419 (clinicaltrials.gov).

Metabolic phenotyping in people living with obesity: Implications for dietary prevention

Given the increasing number of people living with obesity and related chronic metabolic disease, precision nutrition approaches are required to increase the effectiveness of prevention strategies. This review addresses these approaches in different metabolic phenotypes (metabotypes) in obesity. Although obesity is typically associated with an increased cardiometabolic disease risk, some people with obesity are relatively protected against the detrimental effects of excess adiposity on cardiometabolic health, also referred to as 'metabolically healthy obesity' (MHO). Underlying mechanisms, the extent to which MHO is a transient state as well as lifestyle strategies to counteract the transition from MHO to metabolically unhealthy obesity (MUO) are discussed. Based on the limited resources that are available for dietary lifestyle interventions, it may be reasonable to prioritize interventions for people with MUO, since targeting high-risk patients for specific nutritional, lifestyle or weight-loss strategies may enhance the cost-effectiveness of these interventions. Additionally, the concept of tissue insulin resistant (IR) metabotypes is discussed, representing distinct etiologies towards type 2 diabetes (T2D) as well as cardiovascular disease (CVD). Recent evidence indicates that these tissue IR metabotypes, already present in individuals with obesity with a normal glucose homeostasis, respond differentially to diet. Modulation of dietary macronutrient composition according to these metabotypes may considerably improve cardiometabolic health benefits. Thus, nutritional or lifestyle intervention may improve cardiometabolic health, even with only minor or no weight loss, which stresses the importance of focusing on a healthy lifestyle and not on weight loss only. Targeting different metabotypes towards T2D and cardiometabolic diseases may lead to more effective lifestyle prevention and treatment strategies. Age and sex-related differences in tissue metabotypes and related microbial composition and functionality (fermentation), as important drivers and/or mediators of dietary intervention response, have to be taken into account. For the implementation of these approaches, more prospective trials are required to provide the knowledge base for precision nutrition in the prevention of chronic metabolic diseases.

Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study

OBJECTIVE

We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk.

METHODS

This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out.

RESULTS

LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%.

CONCLUSION

Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937.

Physical activity and sedentary behavior show distinct associations with tissue-specific insulin sensitivity in adults with overweight

AIM

The aim of this study is to investigate associations between the physical activity (PA) spectrum (sedentary behavior to exercise) and tissue-specific insulin resistance (IR).

METHODS

We included 219 participants for analysis (median [IQR]: 61 [55; 67] years, BMI 29.6 [26.9; 32.0] kg/m² ; 60% female) with predominant muscle or liver IR, as determined using a 7-point oral glucose tolerance test (OGTT). PA and sedentary behavior were measured objectively (ActivPAL) across 7 days. Context-specific PA was assessed with the Baecke questionnaire. Multiple linear regression models (adjustments include age, sex, BMI, site, season, retirement, and dietary intake) were used to determine associations between the PA spectrum and hepatic insulin resistance index (HIRI), muscle insulin sensitivity index (MISI) and whole-body IR (HOMA-IR, Matsuda index).

RESULTS

In fully adjusted models, objectively measured total PA (standardized regression coefficient β = 0.17, p = 0.020), light-intensity PA (β = 0.15, p = 0.045) and moderate-to-vigorous intensity PA (β = 0.13, p = 0.048) were independently associated with Matsuda index, but not HOMA-IR (p > 0.05). A higher questionnaire-derived sport index and leisure index were associated with significantly lower whole-body IR (Matsuda, HOMA-IR) in men but not in women. Results varied across tissues: more time spent sedentary (β = -0.24, p = 0.045) and a higher leisure index (β = 0.14, p = 0.034) were respectively negatively and positively associated with MISI, but not HIRI. A higher sport index was associated with lower HIRI (β = -0.30, p = 0.007, in men only).

CONCLUSION

While we confirm a beneficial association between PA and whole-body IR, our findings indicate that associations between the PA spectrum and IR seem distinct depending on the primary site of insulin resistance (muscle or liver).

Cardiometabolic health improvements upon dietary intervention are driven by tissue-specific insulin resistance phenotype: A precision nutrition trial

Precision nutrition based on metabolic phenotype may increase the effectiveness of interventions. In this proof-of-concept study, we investigated the effect of modulating dietary macronutrient composition according to muscle insulin-resistant (MIR) or liver insulin-resistant (LIR) phenotypes on cardiometabolic health. Women and men with MIR or LIR (n = 242, body mass index [BMI] 25-40 kg/m², 40-75 years) were randomized to phenotype diet (PhenoDiet) group A or B and followed a 12-week high-monounsaturated fatty acid (HMUFA) diet or low-fat, high-protein, and high-fiber diet (LFHP) (PhenoDiet group A, MIR/HMUFA and LIR/LFHP; PhenoDiet group B, MIR/LFHP and LIR/HMUFA). PhenoDiet group B showed no significant improvements in the primary outcome disposition index, but greater improvements in insulin sensitivity, glucose homeostasis, serum triacylglycerol, and C-reactive protein compared with PhenoDiet group A were observed. We demonstrate that modulating macronutrient composition within the dietary guidelines based on tissue-specific insulin resistance (IR) phenotype enhances cardiometabolic health improvements. Clinicaltrials.gov registration: NCT03708419, CCMO registration NL63768.068.17.

Metabolomics and Lipidomics Signatures of Insulin Resistance and Abdominal Fat Depots in People Living with Obesity

The liver, skeletal muscle, and adipose tissue are major insulin target tissues and key players in glucose homeostasis. We and others have described diverse insulin resistance (IR) phenotypes in people at risk of developing type 2 diabetes. It is postulated that identifying the IR phenotype in a patient may guide the treatment or the prevention strategy for better health outcomes in populations at risk. Here, we performed plasma metabolomics and lipidomics in a cohort of men and women living with obesity not complicated by diabetes (mean [SD] BMI 36.0 [4.5] kg/m2, n = 62) to identify plasma signatures of metabolites and lipids that align with phenotypes of IR (muscle, liver, or adipose tissue) and abdominal fat depots. We used 2-step hyperinsulinemic-euglycemic clamp with deuterated glucose, oral glucose tolerance test, dual-energy X-ray absorptiometry and abdominal magnetic resonance imaging to assess muscle-, liver- and adipose tissue- IR, beta cell function, body composition, abdominal fat distribution and liver fat, respectively. Spearman’s rank correlation analyses that passed the Benjamini−Hochberg statistical correction revealed that cytidine, gamma-aminobutyric acid, anandamide, and citrate corresponded uniquely with muscle IR, tryptophan, cAMP and phosphocholine corresponded uniquely with liver IR and phenylpyruvate and hydroxy-isocaproic acid corresponded uniquely with adipose tissue IR (p < 7.2 × 10−4). Plasma cholesteryl sulfate (p = 0.00029) and guanidinoacetic acid (p = 0.0001) differentiated between visceral and subcutaneous adiposity, while homogentisate correlated uniquely with liver fat (p = 0.00035). Our findings may help identify diverse insulin resistance and adiposity phenotypes and enable targeted treatments in people living with obesity.

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.

Link between Insulin Resistance and Obesity—From Diagnosis to Treatment

Insulin resistance (IR) has become a common health issue in medical practice. There are no detailed data on IR prevalence, but it is an increasing problem due to its close association with obesity. However, IR is not considered as a separate nosological entity and the diagnostic criteria are not well defined, which leads to overdiagnosis of IR and an inappropriate approach. This review aims to summarize the available literature on IR pathophysiology, its relationship with obesity, as well as diagnostic methods, clinical presentation and treatment. Excessive energy intake results in cell overload that triggers mechanisms to protect cells from further energy accumulation by reducing insulin sensitivity. Additionally, hypertrophied adipocytes and macrophage infiltration causes local inflammation that may result in general inflammation that induces IR. The clinical picture varies from skin lesions (e.g., acanthosis nigricans) to metabolic disorders such as diabetes mellitus or metabolic-associated fatty liver disease. There are numerous IR laboratory markers with varying sensitivities and specificities. Nutrition changes and regular physical activity are crucial for IR management because a reduction in adipose tissue may reverse the inflammatory state and consequently reduce the severity of insulin resistance. In cases of obesity, anti-obesity medications can be used.

Dietary macronutrients and the gut microbiome: a precision nutrition approach to improve cardiometabolic health

Accumulating evidence indicates that the gut microbiome is an important regulator of body weight, glucose and lipid metabolism, and inflammatory processes, and may thereby play a key role in the aetiology of obesity, insulin resistance and type 2 diabetes. Interindividual responsiveness to specific dietary interventions may be partially determined by differences in baseline gut microbiota composition and functionality between individuals with distinct metabolic phenotypes. However, the relationship between an individual's diet, gut microbiome and host metabolic phenotype is multidirectional and complex, yielding a challenge for practical implementation of targeted dietary guidelines. In this review, we discuss the latest research describing interactions between dietary composition, the gut microbiome and host metabolism. Furthermore, we describe how this knowledge can be integrated to develop precision-based nutritional strategies to improve bodyweight control and metabolic health in humans. Specifically, we will address that (1) insight in the role of the baseline gut microbial and metabolic phenotype in dietary intervention response may provide leads for precision-based nutritional strategies; that (2) the balance between carbohydrate and protein fermentation by the gut microbiota, as well as the site of fermentation in the colon, seems important determinants of host metabolism; and that (3) 'big data', including multiple omics and advanced modelling, are of undeniable importance in predicting (non-)response to dietary interventions. Clearly, detailed metabolic and microbial phenotyping in humans is necessary to better understand the link between diet, the gut microbiome and host metabolism, which is required to develop targeted dietary strategies and guidelines for different subgroups of the population.

The Role of Dietary Intake in Type 2 Diabetes Mellitus: Importance of Macro and Micronutrients in Glucose Homeostasis

The prevalence of Type 2 diabetes (T2D) is increasing worldwide. Genetics and lifestyle, especially diet, are contributing factors. Analyses of macro- and micronutrient intake across global populations may help to explain their impact on glucose homeostasis and disease development. To this end, 420 Tunisians were enrolled in a prospective cross-sectional study of daily food consumption. Various data were collected and blood samples were drawn for biochemical assay. A 24-h recall questionnaire was obtained from participants to evaluate dietary intake. Statistical analyses were conducted using Nutrilog and R software. Biochemical analyses stratified the studied population (n = 371) into three groups: diabetics (n = 106), prediabetics (n = 192) and controls (n = 73); 49 subjects were excluded. Our results showed that Tunisians had hypercaloric diets high in carbohydrates and fat with variability in the levels of some vitamins and minerals, including riboflavin and niacin, that were statistically different among groups. The lower intake of vitamin D was associated with a greater risk of T2D. Higher vitamin A and sodium intake were associated with poor glucose homeostasis, although protein intake may improve it. In perspective, nutrigenomic studies can provide insight into problematic diets and poor eating habits and offer opportunities to analyze the effects of behavioral changes that can mitigate T2D development and progression.

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 β-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.

An altered microbiota pattern precedes Type 2 diabetes mellitus development: From the CORDIOPREV study

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Type 2 diabetes (T2DM) increases the risk of recurrence in myocardial infarction patients.

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A gut microbiota profile is associated to the further T2DM development.

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Microbiome data improved the prediction of T2DM development when added to clinical parameters.

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A risk score including the most predictive genera was associated with the probability of T2DM.

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A high risk score was associated with a higher hepatic insulin resistance and β-cell dysfunction.

Introduction

A distinctive gut microbiome have been linked to type 2 diabetes mellitus (T2DM).

Objectives

We aimed to evaluate whether gut microbiota composition, in addition to clinical biomarkers, could improve the prediction of new incident cases of diabetes in patients with coronary heart disease.

Methods

All the patients from the CORDIOPREV (Clinical Trials.gov.Identifier: NCT00924937) study without T2DM at baseline were included (n = 462). Overall, 107 patients developed it after a median of 60 months. The gut microbiota composition was determined by 16S rRNA gene sequencing and predictive models were created using hold-out method.

Results

A gut microbiota profile associated with T2DM development was determined through a microbiome-based predictive model. The addition of microbiome data to clinical parameters (variables included in FINDRISC risk score and the diabetes risk score of the American Diabetes Association, HDL, triglycerides and HbA1c) improved the prediction increasing the area under the curve from 0.632 to 0.946. Furthermore, a microbiome-based risk score including the ten most discriminant genera, was associated with the probability of develop T2DM.

Conclusion

These results suggest that a microbiota profile is associated to the T2DM development. An integrate predictive model of microbiome and clinical data that can improve the prediction of T2DM is also proposed, if is validated in independent populations to prevent this disease.

Diabetes remission is modulated by branched chain amino acids according to the diet consumed: from the CORDIOPREV study

SCOPE

BCAA plasma levels may be differentially associated with type 2 diabetes mellitus (T2DM) remission through the consumption of the Mediterranean diet (Med) and a low-fat (LF) diet.

METHODS

183 newly-diagnosed T2DM patients within the CORDIOPREV study were randomized to consume the Med or a LF diet. BCAA plasma levels (isoleucine, leucine and valine) were measured at fasting and after 120 min of an oral glucose tolerance test (OGTT) at the baseline of the study and after 5 y of the dietary intervention.

RESULTS

Isoleucine, leucine and valine plasma levels after 120 min of an OGTT in the Med diet (N = 80) were associated by COX analysis with T2DM remission: HR per SD (95%CI): 0.53 (0.37-0.77), 0.75 (0.52-1.08) and 0.61 (0.45-0.82), respectively; no association was found in patients who consumed a LF diet (N = 103). BCAA plasma levels combined in a score showed a HR of 3.33 (1.55-7.19) of T2DM remission for patients with a high score values in the Med diet, while in those with a LF diet no association was found.

CONCLUSION

Our study suggests that BCAA measurements potentially be used as a tool to select the most suitable diet to induce T2DM remission by nutritional strategies. This article is protected by copyright. All rights reserved.

Digital Resilience Biomarkers for Personalized Health Maintenance and Disease Prevention

Health maintenance and disease prevention strategies become increasingly prioritized with increasing health and economic burden of chronic, lifestyle-related diseases. A key element in these strategies is the empowerment of individuals to control their health. Self-measurement plays an essential role in achieving such empowerment. Digital measurements have the advantage of being measured non-invasively, passively, continuously, and in a real-world context. An important question is whether such measurement can sensitively measure subtle disbalances in the progression toward disease, as well as the subtle effects of, for example, nutritional improvement. The concept of resilience biomarkers, defined as the dynamic evaluation of the biological response to an external challenge, has been identified as a viable strategy to measure these subtle effects. In this review, we explore the potential of integrating this concept with digital physiological measurements to come to digital resilience biomarkers. Additionally, we discuss the potential of wearable, non-invasive, and continuous measurement of molecular biomarkers. These types of innovative measurements may, in the future, also serve as a digital resilience biomarker to provide even more insight into the personal biological dynamics of an individual. Altogether, digital resilience biomarkers are envisioned to allow for the measurement of subtle effects of health maintenance and disease prevention strategies in a real-world context and thereby give personalized feedback to improve health.

A plasma fatty acid profile associated to type 2 diabetes development: from the CORDIOPREV study

Purpose

The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide. For this reason, it is essential to identify biomarkers for the early detection of T2DM risk and/or for a better prognosis of T2DM. We aimed to identify a plasma fatty acid (FA) profile associated with T2DM development.

Methods

We included 462 coronary heart disease patients from the CORDIOPREV study without T2DM at baseline. Of these, 107 patients developed T2DM according to the American Diabetes Association (ADA) diagnosis criteria after a median follow-up of 60 months. We performed a random classification of patients in a training set, used to build a FA Score, and a Validation set, in which we tested the FA Score.

Results

FA selection with the highest prediction power was performed by random survival forest in the Training set, which yielded 4 out of the 24 FA: myristic, petroselinic, α-linolenic and arachidonic acids. We built a FA Score with the selected FA and observed that patients with a higher score presented a greater risk of T2DM development, with an HR of 3.15 (95% CI 2.04–3.37) in the Training set, and an HR of 2.14 (95% CI 1.50–2.84) in the Validation set, per standard deviation (SD) increase. Moreover, patients with a higher FA Score presented lower insulin sensitivity and higher hepatic insulin resistance (p < 0.05).

Conclusion

Our results suggest that a detrimental FA plasma profile precedes the development of T2DM in patients with coronary heart disease, and that this FA profile can, therefore, be used as a predictive biomarker.

Clinical Trials.gov.Identifier

NCT00924937.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-021-02676-z.

The PERSonalized Glucose Optimization Through Nutritional Intervention (PERSON) Study: Rationale, Design and Preliminary Screening Results

Background: It is well-established that the etiology of type 2 diabetes differs between individuals. Insulin resistance (IR) may develop in different tissues, but the severity of IR may differ in key metabolic organs such as the liver and skeletal muscle. Recent evidence suggests that these distinct tissue-specific IR phenotypes may also respond differentially to dietary macronutrient composition with respect to improvements in glucose metabolism.

Objective: The main objective of the PERSON study is to investigate the effects of an optimal vs. suboptimal dietary macronutrient intervention according to tissue-specific IR phenotype on glucose metabolism and other health outcomes.

Methods: In total, 240 overweight/obese (BMI 25 – 40 kg/m²) men and women (age 40 – 75 years) with either skeletal muscle insulin resistance (MIR) or liver insulin resistance (LIR) will participate in a two-center, randomized, double-blind, parallel, 12-week dietary intervention study. At screening, participants undergo a 7-point oral glucose tolerance test (OGTT) to determine the hepatic insulin resistance index (HIRI) and muscle insulin sensitivity index (MISI), classifying each participant as either “No MIR/LIR,” “MIR,” “LIR,” or “combined MIR/LIR.” Individuals with MIR or LIR are randomized to follow one of two isocaloric diets varying in macronutrient content and quality, that is hypothesized to be either an optimal or suboptimal diet, depending on their tissue-specific IR phenotype (MIR/LIR). Extensive measurements in a controlled laboratory setting as well as phenotyping in daily life are performed before and after the intervention. The primary study outcome is the difference in change in disposition index, which is the product of insulin sensitivity and first-phase insulin secretion, between participants who received their hypothesized optimal or suboptimal diet.

Discussion: The PERSON study is one of the first randomized clinical trials in the field of precision nutrition to test effects of a more personalized dietary intervention based on IR phenotype. The results of the PERSON study will contribute knowledge on the effectiveness of targeted nutritional strategies to the emerging field of precision nutrition, and improve our understanding of the complex pathophysiology of whole body and tissue-specific IR.

Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT03708419, clinicaltrials.gov as NCT03708419.

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.

Effects of Low-Carbohydrate versus Mediterranean Diets on Weight Loss, Glucose Metabolism, Insulin Kinetics and β-Cell Function in Morbidly Obese Individuals

Low-calorie Mediterranean-style or low-carbohydrate dietary regimens are widely used nutritional strategies against obesity and associated metabolic diseases, including type 2 diabetes. The aim of this study was to compare the effectiveness of a balanced Mediterranean diet with a low-carbohydrate diet on weight loss and glucose homeostasis in morbidly obese individuals at high risk to develop diabetes. Insulin secretion, insulin clearance, and different β-cell function components were estimated by modeling plasma glucose, insulin and C-peptide profiles during 75-g oral glucose tolerance tests (OGTTs) performed at baseline and after 4 weeks of each dietary intervention. The average weight loss was 5%, being 58% greater in the low-carbohydrate-group than Mediterranean-group. Fasting plasma glucose and glucose tolerance were not affected by the diets. The two dietary regimens proved similarly effective in improving insulin resistance and fasting hyperinsulinemia, while enhancing endogenous insulin clearance and β-cell glucose sensitivity. In summary, we demonstrated that a low-carbohydrate diet is a successful short-term approach for weight loss in morbidly obese patients and a feasible alternative to the Mediterranean diet for its glucometabolic benefits, including improvements in insulin resistance, insulin clearance and β-cell function. Further studies are needed to compare the long-term efficacy and safety of the two diets.

Nutrigenomics: lessons learned and future perspectives

The omics technologies of metabolomics, transcriptomics, proteomics, and metagenomics are playing an increasingly important role in nutrition science. With the emergence of the concept of precision nutrition and the need to understand individual responses to dietary interventions, it is an opportune time to examine the impact of these tools to date in human nutrition studies. Advances in our mechanistic understanding of dietary interventions were realized through incorporation of metabolomics, proteomics, and, more recently, metagenomics. A common observation across the studies was the low intra-individual variability of the omics measurements and the high inter-individual variation. Harnessing this data for use in the development of precision nutrition will be important. Metabolomics in particular has played a key role in the development of biomarkers of food intake in an effort to enhance the accuracy of dietary assessments. Further work is needed to realize the full potential of such biomarkers and to demonstrate integration with current strategies, with the goal of overcoming the well-established limitations of self-reported approaches. Although many of the nutrigenomic studies performed to date were labelled as proof-of-concept or pilot studies, there is ample evidence to support the use of these technologies in nutrition science. Incorporating omic technologies from the start of study designs will ensure that studies are sufficiently powered for such data. Furthermore, multi-disciplinary collaborations are likely to become even more important to aid analyses and interpretation of the data.

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.

miR-223-3p as a potential biomarker and player for adipose tissue dysfunction preceding type 2 diabetes onset

Circulating microRNAs (miRNAs) have been proposed as biomarkers for type 2 diabetes (T2D). Adipose tissue (AT), for which dysfunction is widely associated with T2D development, has been reported as a major source of circulating miRNAs. However, the role of dysfunctional AT in the altered pattern of circulating miRNAs associated with T2D onset remains unexplored. Herein, we investigated the relationship between T2D-associated circulating miRNAs and AT function, as well as the role of preadipocytes and adipocytes as secreting cells of candidate circulating miRNAs. Among the plasma miRNAs related to T2D onset in the CORonary Diet Intervention with Olive oil and cardiovascular PREVention (CORDIOPREV) cohort, baseline miR-223-3p levels (diminished in patients who next developed T2D [incident-T2D]) were significantly related to AT insulin resistance (IR). Baseline serum from incident-T2D participants induced inflammation and IR in 3T3-L1 adipocytes. We demonstrated that tumor necrosis factor (TNF)-α inhibited miR-223-3p secretion while enhancing miR-223-3p intracellular accumulation in 3T3-L1 (pre)adipocytes. Overexpression studies showed that an intracellular increase of miR-223-3p impaired glucose and lipid metabolism in these cells. Our findings provide mechanistic insights into the alteration of circulating miRNAs preceding T2D, unveiling both preadipocytes and adipocytes as miR-223-3p-secreting cells and suggesting that inflammation promotes miR-223-3p intracellular accumulation, which might contribute to (pre)adipocyte dysfunction and body metabolic dysregulation.

Sexual dimorphism in cardiometabolic health: the role of adipose tissue, muscle and liver

Obesity is associated with many adverse health effects, such as an increased cardiometabolic risk. Despite higher adiposity for a given BMI, premenopausal women are at lower risk of cardiometabolic disease than men of the same age. This cardiometabolic advantage in women seems to disappear after the menopause or when type 2 diabetes mellitus develops. Sexual dimorphism in substrate supply and utilization, deposition of excess lipids and mobilization of stored lipids in various key metabolic organs (such as adipose tissue, skeletal muscle and the liver) are associated with differences in tissue-specific insulin sensitivity and cardiometabolic risk profiles between men and women. Moreover, lifestyle-related factors and epigenetic and genetic mechanisms seem to affect metabolic complications and disease risk in a sex-specific manner. This Review provides insight into sexual dimorphism in adipose tissue distribution, adipose tissue, skeletal muscle and liver substrate metabolism and tissue-specific insulin sensitivity in humans, as well as the underlying mechanisms, and addresses the effect of these sex differences on cardiometabolic health. Additionally, this Review highlights the implications of sexual dimorphism in the pathophysiology of obesity-related cardiometabolic risk for the development of sex-specific prevention and treatment strategies.

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.

A Diet-Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study

SCOPE

The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low-fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet.

METHODS AND RESULTS

All the patients from the CORDIOPREV study without T2D at baseline (n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow-up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella, and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria, Betaproteobacteria, and Prevotella are associated with T2D risk when a Med diet is consumed.

CONCLUSION

The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.

Dietary Intervention Modulates the Expression of Splicing Machinery in Cardiovascular Patients at High Risk of Type 2 Diabetes Development: From the CORDIOPREV Study

Type-2 diabetes mellitus (T2DM) has become a major health problem worldwide. T2DM risk can be reduced with healthy dietary interventions, but the precise molecular underpinnings behind this association are still incompletely understood. We recently discovered that the expression profile of the splicing machinery is associated with the risk of T2DM development. Thus, the aim of this work was to evaluate the influence of 3-year dietary intervention in the expression pattern of the splicing machinery components in peripheral blood mononuclear cells (PBMCs) from patients within the CORDIOPREV study. Expression of splicing machinery components was determined in PBMCs, at baseline and after 3 years of follow-up, from all patients who developed T2DM (Incident-T2DM, n = 107) and 108 randomly selected non-T2DM subjects, who were randomly enrolled in two healthy dietary patterns (Mediterranean or low-fat diets). Dietary intervention modulated the expression of key splicing machinery components (i.e., up-regulation of SPFQ/RMB45/RNU6, etc., down-regulation of RNU2/SRSF6) after three years, independently of the type of healthy diet. Some of these changes (SPFQ/RMB45/SRSF6) were associated with key clinical features and were differentially induced in Incident-T2DM patients and non-T2DM subjects. This study reveals that splicing machinery can be modulated by long-term dietary intervention, and could become a valuable tool to screen the progression of T2DM.

A set of miRNAs predicts T2DM remission in patients with coronary heart disease: from the CORDIOPREV study

MicroRNAs (miRNAs) regulate the expression of genes associated with the development of diseases, including type 2 diabetes mellitus (T2DM). However, the use of miRNAs to predict T2DM remission has been poorly studied. Therefore, we aimed to investigate whether circulating miRNAs could be used to predict the probability of T2DM remission in patients with coronary heart disease. We included the newly diagnosed T2DM (n = 190) of the 1,002 patients from the CORDIOPREV study. Seventy-three patients reverted from T2DM after 5 years of dietary intervention with a low-fat or Mediterranean diet. Plasma levels of 56 miRNAs were measured by OpenArray. Generalized linear model, receiver operating characteristic (ROC), Cox regression, and pathway analyses were performed. ROC analysis based on clinical variables showed an area under the curve (AUC) of 0.66. After a linear regression analysis, seven miRNAs were identified as the most important variables in the group’s differentiation. The addition of these miRNAs to clinical variables showed an AUC of 0.79. Cox regression analysis using a T2DM remission score including miRNAs showed that high-score patients have a higher probability of T2DM remission (hazard ratio [HR]_{low versus high}, 4.44). Finally, 26 genes involved in 10 pathways were related to the miRNAs. We have identified miRNAs (hsa-let-7b, hsa-miR-101, hsa-miR-130b-3p, hsa-miR-27a, hsa-miR-30a-5p, hsa-miR-375, and hsa-miR-486) that contribute to the prediction of T2DM remission in patients with coronary heart disease.

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 β-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.

Extra virgin olive oil: More than a healthy fat

The beneficial effects of a Mediterranean diet on human health and, in particular, on lowering risk of cardiovascular disease, has been mainly attributed to its high content to extra virgin olive oil (EVOO). While its main fatty acid, oleic acid, is considered important to these effects, EVOO has other biological properties that depend on, or are potentiated by other minor components of this oil. Initially, the mechanisms considered as possible causes of this cardioprotective effect of EVOO were based on the incidence on the so-called traditional risk factors (especially lipids and blood pressure). However, the high relative reduction in the prevalence of cardiovascular morbidity and mortality were not proportional to the limited findings about regulation of those traditional risk factors. In addition to several studies confirming the above effects, current research on beneficial effect of EVOO, and in particular in conjunction with Mediterranean style diets, is being focused on defining its effects on newer cardiovascular risk factors, such as inflammation, oxidative stress, coagulation, platelet aggregation, fibrinolysis, endothelial function or lipids or on the modulation of the conditions which predispose people to cardiovascular events, such as obesity, metabolic syndrome or type 2 diabetes mellitus. In the current review, we will mainly focus on reviewing the current evidence about the effects that EVOO exerts on alternative factors, including postprandial lipemia or coagulation, among others, discussing the underlying mechanism by which it exerts its effect, as well as providing a short review on future directions.

Reduction in Circulating Advanced Glycation End Products by Mediterranean Diet Is Associated with Increased Likelihood of Type 2 Diabetes Remission in Patients with Coronary Heart Disease: From the Cordioprev Study

SCOPE

It is hypothesized that decreased advanced glycation end products (AGEs) levels could affect type 2 diabetes mellitus (T2DM) remission in newly diagnosed patients through the consumption of two healthy diets.

METHODS AND RESULTS

Patients from CORDIOPREV study, all with previous cardiovascular events, with T2DM at the beginning of the study are included. Patients are randomized to a Mediterranean or a low-fat diet for five years. No different diabetes remission rates are found among diets. Serum methylglioxal (MG) and carboximethyllysine (CML), levels dietary AGE, as well as gene expression of AGER1 and RAGE are measured. Serum MG decreases only after the consumption of the Mediterranean diet. Moreover, a COX regression analysis shows that each SD decrease in the MG, occurring after the Mediterranean diet, increases the probability of T2DM remission with HR:2.56(1.02-6.25) and p = 0.046 and each SD increase in disposition index at baseline increases the probability of remission with HR:1.94(1.32-2.87) and p = 0.001.

CONCLUSIONS

It is demonstrated that the reduction of serum AGEs levels and the modulation of its metabolism, occurring after the consumption of a Mediterranean diet, might be involved in the molecular mechanism underlying the T2DM remission of newly diagnosed patients with coronary heart disease.

Effects of total fat intake on body fatness in adults

BACKGROUND

The ideal proportion of energy from fat in our food and its relation to body weight is not clear. In order to prevent overweight and obesity in the general population, we need to understand the relationship between the proportion of energy from fat and resulting weight and body fatness in the general population.

OBJECTIVES

To assess the effects of proportion of energy intake from fat on measures of body fatness (including body weight, waist circumference, percentage body fat and body mass index) in people not aiming to lose weight, using all appropriate randomised controlled trials (RCTs) of at least six months duration.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, Clinicaltrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) to October 2019. We did not limit the search by language.

SELECTION CRITERIA

Trials fulfilled the following criteria: 1) randomised intervention trial, 2) included adults aged at least 18 years, 3) randomised to a lower fat versus higher fat diet, without the intention to reduce weight in any participants, 4) not multifactorial and 5) assessed a measure of weight or body fatness after at least six months. We duplicated inclusion decisions and resolved disagreement by discussion or referral to a third party.

DATA COLLECTION AND ANALYSIS

We extracted data on the population, intervention, control and outcome measures in duplicate. We extracted measures of body fatness (body weight, BMI, percentage body fat and waist circumference) independently in duplicate at all available time points. We performed random-effects meta-analyses, meta-regression, subgrouping, sensitivity, funnel plot analyses and GRADE assessment.

MAIN RESULTS

We included 37 RCTs (57,079 participants). There is consistent high-quality evidence from RCTs that reducing total fat intake results in small reductions in body fatness; this was seen in almost all included studies and was highly resistant to sensitivity analyses (GRADE high-consistency evidence, not downgraded). The effect of eating less fat (compared with higher fat intake) is a mean body weight reduction of 1.4 kg (95% confidence interval (CI) -1.7 to -1.1 kg, in 53,875 participants from 26 RCTs, I² = 75%). The heterogeneity was explained in subgrouping and meta-regression. These suggested that greater weight loss results from greater fat reductions in people with lower fat intake at baseline, and people with higher body mass index (BMI) at baseline. The size of the effect on weight does not alter over time and is mirrored by reductions in BMI (MD -0.5 kg/m², 95% CI -0.6 to -0.3, 46,539 participants in 14 trials, I² = 21%), waist circumference (MD -0.5 cm, 95% CI -0.7 to -0.2, 16,620 participants in 3 trials; I² = 21%), and percentage body fat (MD -0.3% body fat, 95% CI -0.6 to 0.00, P = 0.05, in 2350 participants in 2 trials; I² = 0%). There was no suggestion of harms associated with low fat diets that might mitigate any benefits on body fatness. The reduction in body weight was reflected in small reductions in LDL (-0.13 mmol/L, 95% CI -0.21 to -0.05), and total cholesterol (-0.23 mmol/L, 95% CI -0.32 to -0.14), with little or no effect on HDL cholesterol (-0.02 mmol/L, 95% CI -0.03 to 0.00), triglycerides (0.01 mmol/L, 95% CI -0.05 to 0.07), systolic (-0.75 mmHg, 95% CI -1.42 to -0.07) or diastolic blood pressure(-0.52 mmHg, 95% CI -0.95 to -0.09), all GRADE high-consistency evidence or quality of life (0.04, 95% CI 0.01 to 0.07, on a scale of 0 to 10, GRADE low-consistency evidence).

AUTHORS' CONCLUSIONS

Trials where participants were randomised to a lower fat intake versus a higher fat intake, but with no intention to reduce weight, showed a consistent, stable but small effect of low fat intake on body fatness: slightly lower weight, BMI, waist circumference and percentage body fat compared with higher fat arms. Greater fat reduction, lower baseline fat intake and higher baseline BMI were all associated with greater reductions in weight. There was no evidence of harm to serum lipids, blood pressure or quality of life, but rather of small benefits or no effect.

Metabolic profiling of tissue-specific insulin resistance in human obesity: results from the Diogenes study and the Maastricht Study

BACKGROUND

Recent evidence indicates that insulin resistance (IR) in obesity may develop independently in different organs, representing different etiologies toward type 2 diabetes and other cardiometabolic diseases. The aim of this study was to investigate whether IR in the liver and IR in skeletal muscle are associated with distinct metabolic profiles.

METHODS

This study includes baseline data from 634 adults with overweight or obesity (BMI ≥ 27 kg/m²) (≤65 years; 63% women) without diabetes of the European Diogenes Study. Hepatic insulin resistance index (HIRI) and muscle insulin sensitivity index (MISI), were derived from a five-point OGTT. At baseline 17 serum metabolites were identified and quantified by nuclear-magnetic-resonance spectroscopy. Linear mixed model analyses (adjusting for center, sex, body mass index (BMI), waist-to-hip ratio) were used to associate HIRI and MISI with these metabolites. In an independent sample of 540 participants without diabetes (BMI ≥ 27 kg/m²; 40-65 years; 46% women) of the Maastricht Study, an observational prospective population-based cohort study, 11 plasma metabolites and a seven-point OGTT were available for validation.

RESULTS

Both HIRI and MISI were associated with higher levels of valine, isoleucine, oxo-isovaleric acid, alanine, lactate, and triglycerides, and lower levels of glycine (all p < 0.05). HIRI was also associated with higher levels of leucine, hydroxyisobutyrate, tyrosine, proline, creatine, and n-acetyl and lower levels of acetoacetate and 3-OH-butyrate (all p < 0.05). Except for valine, these results were replicated for all available metabolites in the Maastricht Study.

CONCLUSIONS

In persons with obesity without diabetes, both liver and muscle IR show a circulating metabolic profile of elevated (branched-chain) amino acids, lactate, and triglycerides, and lower glycine levels, but only liver IR associates with lower ketone body levels and elevated ketogenic amino acids in circulation, suggestive of decreased ketogenesis. This knowledge might enhance developments of more targeted tissue-specific interventions to prevent progression to more severe disease stages.

Current metabolic perspective on malnutrition in obesity: towards more subgroup-based nutritional approaches?

Lifestyle intervention may be effective in reducing type 2 diabetes mellitus incidence and cardiometabolic risk. A more personalised nutritional approach based on an individual or subgroup-based metabolic profile may optimise intervention outcome. Whole body insulin resistance (IR) reflects defective insulin action in tissues such as muscle, liver, adipose tissue, gut and brain, which may precede the development of cardiometabolic diseases. IR may develop in different organs but the severity may vary between organs. Individuals with more pronounced hepatic IR have a distinct plasma metabolome and lipidome profile as compared with individuals with more pronounced muscle IR. Additionally, genes related to extracellular modelling were upregulated in abdominal subcutaneous adipose tissue in individuals with more pronounced hepatic IR, whilst genes related to inflammation as well as systemic low-grade inflammation were upregulated in individuals with primarily muscle IR. There are indications that these distinct IR phenotypes may also respond differentially to dietary macronutrient composition. Besides metabolic phenotype, microbial phenotype may be of importance in personalising the response to diet. In particular fibres or fibre mixtures, leading to a high distal acetate and SCFA production may have more pronounced effects on metabolic health. Notably, individuals with prediabetes may have a reduced response to diet-induced microbiota modulation with respect to host insulin sensitivity and metabolic health outcomes. Overall, we need more research to relate metabolic subphenotypes to intervention outcomes to define more optimal diets for individuals with or predisposed to chronic metabolic diseases.

Plasma cathepsin D activity is negatively associated with hepatic insulin sensitivity in overweight and obese humans

AIMS/HYPOTHESIS

Insulin resistance in skeletal muscle and liver plays a major role in the pathophysiology of type 2 diabetes. The hyperinsulinaemic-euglycaemic clamp is considered the gold standard for assessing peripheral and hepatic insulin sensitivity, yet it is a costly and labour-intensive procedure. Therefore, easy-to-measure, cost-effective approaches to determine insulin sensitivity are needed to enable organ-specific interventions. Recently, evidence emerged that plasma cathepsin D (CTSD) is associated with insulin sensitivity and hepatic inflammation. Here, we aimed to investigate whether plasma CTSD is associated with hepatic and/or peripheral insulin sensitivity in humans.

METHODS

As part of two large clinical trials (one designed to investigate the effects of antibiotics, and the other to investigate polyphenol supplementation, on insulin sensitivity), 94 overweight and obese adults (BMI 25-35 kg/m²) previously underwent a two-step hyperinsulinaemic-euglycaemic clamp (using [6,6-²H₂]glucose) to assess hepatic and peripheral insulin sensitivity (per cent suppression of endogenous glucose output during the low-insulin-infusion step, and the rate of glucose disappearance during high-insulin infusion [40 mU/(m² × min)], respectively). In this secondary analysis, plasma CTSD levels, CTSD activity and plasma inflammatory cytokines were measured.

RESULTS

Plasma CTSD levels were positively associated with the proinflammatory cytokines IL-8 and TNF-α (IL-8: standardised β = 0.495, p < 0.001; TNF-α: standardised β = 0.264, p = 0.012). Plasma CTSD activity was negatively associated with hepatic insulin sensitivity (standardised β = -0.206, p = 0.043), independent of age, sex, BMI and waist circumference, but it was not associated with peripheral insulin sensitivity. However, plasma IL-8 and TNF-α were not significantly correlated with hepatic insulin sensitivity.

CONCLUSIONS/INTERPRETATION

We demonstrate that plasma CTSD activity, but not systemic inflammation, is inversely related to hepatic insulin sensitivity, suggesting that plasma CTSD activity may be used as a non-invasive marker for hepatic insulin sensitivity in humans.

Nutrition interventions for healthy ageing across the lifespan: a conference report

Thanks to advances in modern medicine over the past century, the world’s population has experienced a marked increase in longevity. However, disparities exist that lead to groups with both shorter lifespan and significantly diminished health, especially in the aged. Unequal access to proper nutrition, healthcare services, and information to make informed health and nutrition decisions all contribute to these concerns. This in turn has hastened the ageing process in some and adversely affected others’ ability to age healthfully. Many in developing as well as developed societies are plagued with the dichotomy of simultaneous calorie excess and nutrient inadequacy. This has resulted in mental and physical deterioration, increased non-communicable disease rates, lost productivity and quality of life, and increased medical costs. While adequate nutrition is fundamental to good health, it remains unclear what impact various dietary interventions may have on improving healthspan and quality of life with age. With a rapidly ageing global population, there is an urgent need for innovative approaches to health promotion as individual’s age. Successful research, education, and interventions should include the development of both qualitative and quantitative biomarkers and other tools which can measure improvements in physiological integrity throughout life. Data-driven health policy shifts should be aimed at reducing the socio-economic inequalities that lead to premature ageing. A framework for progress has been proposed and published by the World Health Organization in its Global Strategy and Action Plan on Ageing and Health. This symposium focused on the impact of nutrition on this framework, stressing the need to better understand an individual’s balance of intrinsic capacity and functional abilities at various life stages, and the impact this balance has on their mental and physical health in the environments they inhabit.

Subcutaneous Adipose Tissue and Systemic Inflammation Are Associated With Peripheral but Not Hepatic Insulin Resistance in Humans

Obesity-related insulin resistance (IR) may develop in multiple organs, representing various etiologies for cardiometabolic diseases. We identified abdominal subcutaneous adipose tissue (ScAT) transcriptome profiles in liver or muscle IR by means of RNA sequencing in overweight or obese participants of the Diet, Obesity, and Genes (DiOGenes) (NCT00390637, ClinicalTrials.gov) cohort (n = 368). Tissue-specific IR phenotypes were derived from a 5-point oral glucose tolerance test. Hepatic and muscle IR were characterized by distinct abdominal ScAT transcriptome profiles. Genes related to extracellular remodeling were upregulated in individuals with primarily hepatic IR, while genes related to inflammation were upregulated in individuals with primarily muscle IR. In line with this, in two independent cohorts, the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) (n = 325) and the Maastricht Study (n = 685), an increased systemic low-grade inflammation profile was specifically related to muscle IR but not to liver IR. We propose that increased ScAT inflammatory gene expression may translate into an increased systemic inflammatory profile, linking ScAT inflammation to the muscle IR phenotype. These distinct IR phenotypes may provide leads for more personalized prevention of cardiometabolic diseases.

The Impact of Dairy Products in the Development of Type 2 Diabetes: Where Does the Evidence Stand in 2019?

The prevalence of type 2 diabetes (T2D) has increased rapidly. Adopting a heathy diet is suggested as one of the effective behaviors to prevent or delay onset of T2D. Dairy consumption has been recommended as part of a healthy diet, but there remains uncertainty in both the scientific community and the public about the effect of different dairy products on T2D risk. In a recent workshop, the evidence on dairy products and T2D risk was presented and discussed by a group of experts. The main conclusions from the workshop are presented in this position paper and are as follows. 1) Available evidence from large prospective cohort studies and limited randomized controlled trials (RCTs) suggests that total dairy consumption has a neutral or moderately beneficial effect on T2D risk. 2) Increasing evidence from prospective cohort studies indicates that yogurt is most strongly associated with a lower T2D risk, but evidence from RCTs is scarce. 3) Fatty acids from dairy (medium-chain, odd, and very long-chain SFAs as well as trans-palmitoleic acid) are associated with lower T2D risk and improved metabolic health, but more research is needed on studies that explore cause and effect relations to exclude the possibility that the dairy fatty acids simply serve as markers of overall dairy consumption. 4) The food matrix can be a stronger determinant of health effects than SFA content. This review further identifies research gaps in the existing knowledge and highlights key research questions that need to be addressed to better understand the impact of dairy consumption on future T2D risk.

Improved quantification of muscle insulin sensitivity using oral glucose tolerance test data: the MISI Calculator

The Muscle Insulin Sensitivity Index (MISI) has been developed to estimate muscle-specific insulin sensitivity based on oral glucose tolerance test (OGTT) data. To date, the score has been implemented with considerable variation in literature and initial positive evaluations were not reproduced in subsequent studies. In this study, we investigate the computation of MISI on oral OGTT data with differing sampling schedules and aim to standardise and improve its calculation. Seven time point OGTT data for 2631 individuals from the Maastricht Study and seven time point OGTT data combined with a hyperinsulinemic-euglycaemic clamp for 71 individuals from the PRESERVE Study were used to evaluate the performance of MISI. MISI was computed on subsets of OGTT data representing four and five time point sampling schedules to determine minimal requirements for accurate computation of the score. A modified MISI computed on cubic splines of the measured data, resulting in improved identification of glucose peak and nadir, was compared with the original method yielding an increased correlation (ρ = 0.576) with the clamp measurement of peripheral insulin sensitivity as compared to the original method (ρ = 0.513). Finally, a standalone MISI calculator was developed allowing for a standardised method of calculation using both the original and improved methods.

Indirect insulin resistance detection: Current clinical trends and laboratory limitations

There is a steady increase in the number of overweight and obese people worldwide and increasingly, younger people. Excess adipose tissue impairs the action of insulin, leading to insulin resistance (IR). Tissue IR is a major factor in relation to cardiovascular disease, metabolic syndrome and diabetes. Thus, it is important to recognize at the pre-disease stage with the possibility of therapeutic intervention. IR is assessed using indicators of epidemiological significance, most often calculated from fasting and postprandial glucose and insulin values, so-called indirect indicators of insulin resistance. The most commonly used parameter is the Homeostatic Model Assessment (HOMA). Although the Quantitative Insulin Sensitivity Check Index (QUICKI), Matsuda Index and the Insulin Secretion-Sensitivity Index-2 (ISSI-2) are also used, the values of these indices established for IR vary for different age, sex, populations and ethnic groups. Thus, appropriate reference values of indirect indices should be determined for such groups, and when this is precluded, data from published studies carried out on the most ethnically, socio-economically and age-matched populations should be applied.

A plasma circulating miRNAs profile predicts type 2 diabetes mellitus and prediabetes: from the CORDIOPREV study

We aimed to explore whether changes in circulating levels of miRNAs according to type 2 diabetes mellitus (T2DM) or prediabetes status could be used as biomarkers to evaluate the risk of developing the disease. The study included 462 patients without T2DM at baseline from the CORDIOPREV trial. After a median follow-up of 60 months, 107 of the subjects developed T2DM, 30 developed prediabetes, 223 maintained prediabetes and 78 remained disease-free. Plasma levels of four miRNAs related to insulin signaling and beta-cell function were measured by RT-PCR. We analyzed the relationship between miRNAs levels and insulin signaling and release indexes at baseline and after the follow-up period. The risk of developing disease based on tertiles (T1-T2-T3) of baseline miRNAs levels was evaluated by COX analysis. Thus, we observed higher miR-150 and miR-30a-5p and lower miR-15a and miR-375 baseline levels in subjects with T2DM than in disease-free subjects. Patients with high miR-150 and miR-30a-5p baseline levels had lower disposition index (p = 0.047 and p = 0.007, respectively). The higher risk of disease was associated with high levels (T3) of miR-150 and miR-30a-5p (HR_T3-T1 = 4.218 and HR_T3-T1 = 2.527, respectively) and low levels (T1) of miR-15a and miR-375 (HR_T1-T3 = 3.269 and HR_T1-T3 = 1.604, respectively). In conclusion, our study showed that deregulated plasma levels of miR-150, miR-30a-5p, miR-15a, and miR-375 were observed years before the onset of T2DM and pre-DM and could be used to evaluate the risk of developing the disease, which may improve prediction and prevention among individuals at high risk for T2DM.

Tiny RNA molecules circulating in the blood could give early warning of type 2 diabetes risk. MicroRNAs help regulate the expression of other genes, and recent research has linked irregularities in these molecules to many different diseases. Researchers led by José López Miranda of the University of Córdoba in Spain monitored a cohort of 462 patients for several years to assess how plasma levels of certain microRNAs are deregulated before the onset and progression of diabetes. They observed a striking ‘signature’ of altered expression in four microRNAs for patients who developed diabetes over the course of the study. Intriguingly, patients with markedly elevated blood sugar—state known as prediabetes—exhibited a similar signature, but with more modest alteration in the gene expression levels, indicating that these microRNAs could help clinicians track and prevent disease onset.

Changes in Splicing Machinery Components Influence, Precede, and Early Predict the Development of Type 2 Diabetes: From the CORDIOPREV Study

Background

Type-2 diabetes mellitus (T2DM) is a major health problem with increasing incidence, which severely impacts cardiovascular disease. Because T2DM is associated with altered gene expression and aberrant splicing, we hypothesized that dysregulations in splicing machinery could precede, contribute to, and predict T2DM development.

Methods

A cohort of patients with cardiovascular disease (CORDIOPREV study) and without T2DM at baseline (at the inclusion of the study) was used (n = 215). We determined the expression of selected splicing machinery components in fasting and 4 h-postprandial peripheral blood mononuclear cells (PBMCs, obtained at baseline) from all the patients who developed T2DM during 5-years of follow-up (n = 107 incident-T2DM cases) and 108 randomly selected non-T2DM patients (controls). Serum from incident-T2DM and control patients was used to analyze in vitro the modulation of splicing machinery expression in control PBMCs from an independent cohort of healthy subjects.

Findings

Expression of key splicing machinery components (e.g. RNU2, RNU4 or RNU12) from fasting and 4 h-postprandial PBMCs of incident-T2DM patients was markedly altered compared to non-T2DM controls. Moreover, in vitro treatment of healthy individuals PBMCs with serum from incident-T2DM patients (compared to non-T2DM controls) reduced the expression of splicing machinery elements found down-regulated in incident-T2DM patients PBMCs. Finally, fasting/postprandial levels of several splicing machinery components in the PBMCs of CORDIOPREV patients were associated to higher risk of T2DM (Odds Ratio > 4) and could accurately predict (AUC > 0.85) T2DM development.

Interpretation

Our results reveal the existence of splicing machinery alterations that precede and predict T2DM development in patients with cardiovascular disease.

Fund

ISCIII, MINECO, CIBERObn.

Predictive Accuracy of Surrogate Indices for Hepatic and Skeletal Muscle Insulin Sensitivity

Context

Surrogate indices of muscle and hepatic insulin sensitivity derived from an oral glucose tolerance test (OGTT) are frequently used in clinical studies. However, the predictive accuracy of these indices has not been validated.

Design

In this cross-sectional study, hyperinsulinemic-euglycemic glucose clamp with tritiated glucose infusion and a 75-g OGTT were performed in individuals (n = 659, aged 18 to 49 years, body mass index of 16 to 64 kg/m²) with varying degrees of glucose tolerance. A calibration model was used to assess the ability of OGTT-derived, tissue-specific surrogate indices [hepatic insulin resistance index (HIRI) and muscle insulin sensitivity index (MISI)] to predict insulin sensitivity/resistance indices derived from the reference glucose clamp [Hepatic-IR_basal, a product of fasting plasma insulin and hepatic glucose production (HGP), Hepatic-IR_clamp, reciprocal of the percent suppression of HGP during the insulin clamp corrected for plasma insulin concentration, and Muscle-IS_clamp, a measure of peripheral glucose disposal]. Predictive accuracy was assessed by root mean squared error of prediction and leave-one-out, cross-validation-type square root of the mean squared error of prediction.

Results

HIRI and MISI were correlated with their respective clamp-derived indices. HIRI was negatively related to Muscle-IS_clamp (r = -0.62, P < 0.0001) and MISI correlated with Hepatic-IR derived from the clamp (Hepatic-IR_basal: r = -0.48, P < 0.0001 and Hepatic-IR_clamp: r = -0.41, P < 0.0001). However, the accuracy of HIRI and MISI to predict Hepatic-IR (basal or during clamp) was not significantly different. Likewise, the ability of HIRI and MISI to predict Muscle-IS_clamp was also similar.

Conclusion

Our findings indicate that the surrogate indices derived from an OGTT are accurate in predicting insulin sensitivity but are not tissue specific.

Plasma lipid profiling of tissue-specific insulin resistance in human obesity

BACKGROUND/OBJECTIVES

Obesity-associated insulin resistance (IR) may develop in multiple organs, representing different aetiologies towards cardiometabolic diseases. This study aimed to identify distinct plasma lipid profiles in overweight/obese individuals who show muscle-IR and/or liver-IR.

SUBJECTS/METHODS

Baseline data of the European multicenter DiOGenes project were used (n = 640; 401 women, nondiabetic BMI: 27-45 kg/m²). Muscle insulin sensitivity index (MISI) and hepatic insulin resistance index (HIRI) were derived from a 5-point oral glucose tolerance test. The 140 plasma lipids were quantified by liquid chromatography-mass spectrometry. Linear mixed models were used to evaluate associations between MISI, HIRI and plasma lipids.

RESULTS

MISI was comparable between sexes while HIRI and triacylglycerol (TAG) levels were lower in women than in men. MISI was associated with higher lysophosphatidylcholine (LPC) levels (standardized (std)β = 0.126; FDR-p = 0.032). Sex interactions were observed for associations between HIRI, TAG and diacylglycerol (DAG) lipid classes. In women, but not in men, HIRI was associated with higher levels of TAG (44 out of 55 species) and both DAG species (stdβ: 0.139-0.313; FDR-p < 0.05), a lower odd-chain/even-chain TAG ratio (stdβ = -0.182; FDR-p = 0.005) and a lower very-long-chain/long-chain TAG ratio (stdβ = -0.156; FDR-p = 0.037).

CONCLUSIONS

In overweight/obese individuals, muscle insulin sensitivity is associated with higher plasma LPC concentrations. Women have less hepatic IR and lower TAG than men. Nevertheless, hepatic IR is associated with higher plasma TAG and DAG concentrations and a lower abundance of odd-chain and very-long-chain TAG in women, but not in men. This suggests a more pronounced worsening of plasma lipid profile in women with the progression of hepatic IR.

Circulating miRNAs as Predictive Biomarkers of Type 2 Diabetes Mellitus Development in Coronary Heart Disease Patients from the CORDIOPREV Study

Circulating microRNAs (miRNAs) have been proposed as type 2 diabetes biomarkers, and they may be a more sensitive way to predict development of the disease than the currently used tools. Our aim was to identify whether circulating miRNAs, added to clinical and biochemical markers, yielded better potential for predicting type 2 diabetes. The study included 462 non-diabetic patients at baseline in the CORDIOPREV study. After a median follow-up of 60 months, 107 of them developed type 2 diabetes. Plasma levels of 24 miRNAs were measured at baseline by qRT-PCR, and other strong biomarkers to predict diabetes were determined. The ROC analysis identified 9 miRNAs, which, added to HbA1c, have a greater predictive value in early diagnosis of type 2 diabetes (AUC = 0.8342) than HbA1c alone (AUC = 0.6950). The miRNA and HbA1c-based model did not improve when the FINDRISC was included (AUC = 0.8293). Cox regression analyses showed that patients with low miR-103, miR-28-3p, miR-29a, and miR-9 and high miR-30a-5p and miR-150 circulating levels have a higher risk of disease (HR = 11.27; 95% CI = 2.61-48.65). Our results suggest that circulating miRNAs could potentially be used as a new tool for predicting the development of type 2 diabetes in clinical practice.

Ectopic Fat Accumulation in Distinct Insulin Resistant Phenotypes; Targets for Personalized Nutritional Interventions

Cardiometabolic diseases are one of the leading causes for disability and mortality in the Western world. The prevalence of these chronic diseases is expected to rise even further in the next decades. Insulin resistance (IR) and related metabolic disturbances are linked to ectopic fat deposition, which is the storage of excess lipids in metabolic organs such as liver and muscle. Notably, a vicious circle exists between IR and ectopic fat, together increasing the risk for the development of cardiometabolic diseases. Nutrition is a key-determining factor for both IR and ectopic fat deposition. The macronutrient composition of the diet may impact metabolic processes related to ectopic fat accumulation and IR. Interestingly, however, the metabolic phenotype of an individual may determine the response to a certain diet. Therefore, population-based nutritional interventions may not always lead to the most optimal (cardiometabolic) outcomes at the individual level, and differences in the metabolic phenotype may underlie conflicting findings related to IR and ectopic fat in dietary intervention studies. Detailed metabolic phenotyping will help to better understand the complex relationship between diet and metabolic regulation, and to optimize intervention outcomes. A subgroup-based approach that integrates, among others, tissue-specific IR, cardiometabolic parameters, anthropometrics, gut microbiota, age, sex, ethnicity, and psychological factors may thereby increase the efficacy of dietary interventions. Nevertheless, the implementation of more personalized nutrition may be complex, costly, and time consuming. Future studies are urgently warranted to obtain insight into a more personalized approach to nutritional interventions, taking into account the metabolic phenotype to ultimately improve insulin sensitivity and reduce the risk for cardiometabolic diseases.