The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study.

CONTEXT: The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHOD: We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.

OBJECTIVE: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), ß-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS: Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R 2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS: Deteriorating insulin sensitivity and ß-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, ß-cell function, and insulin clearance may be relevant to prevent progression.

Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study.

BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. FINDINGS: A higher Tpred score was associated with healthier diets high in wholegrain (ß=3.36 g, 95% CI 0.31, 6.40 and ß=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (ß=-75.53 kcal, 95% CI -144.71, -2.35 and ß=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (ß=-0.92 g, 95% CI -1.56, -0.28 and ß=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (ß=0.07 mmol/L, 95% CI 0.03, 0.1), (ß=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (ß=-0.1 mmol/L, 95% CI -0.2, -0.03), (ß=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (ß=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (ß=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (ß=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (ß=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (ß=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (ß=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. INTERPRETATION: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. FUNDING: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies.

Gene-diet quality interactions on haemoglobin A1c and type 2 diabetes risk: The Airwave Health Monitoring Study.

INTRODUCTION: Type 2 diabetes (T2D) is multifactorial involving lifestyle, environmental and genetic risk factors. This study aims to investigate the impact of genetic interactions with alcohol and diet quality on glycated haemoglobin A1c (HbA1c) independent of obesity, in a British population. METHODS: Cross-sectional study of 14 089 white British participants from Airwave Health Monitoring Study and a subsample of 3733 participants with dietary data. A T2D genetic risk score (GRS) was constructed, and its interactions with diet on HbA1c were assessed. RESULTS: GRS was associated with a higher HbA1c% (ß = 0.03, P < 0.0001) and a higher risk of prediabetes (OR = 1.09, P < 0.0001) and T2D (OR = 1.14, P = 0.006). The genetic effect on HbA1c% was significantly higher in obese participants (ß = 1.88, P interaction = 0.03). A high intake of wholegrain attenuated the effect on HbA1c% in high-risk individuals P interaction = 0.04. CONCLUSION: The genetic effect on HbA1c was almost doubled in obese individuals, compared with those with a healthy weight, and independent of weight, there was a modest offset on HbA1c in high-genetic-risk individuals consuming a diet high in wholegrain. This supports the importance of a healthy diet high in wholegrains and along with maintaining a healthy weight in controlling HbA1c among high-genetic-risk groups.

Intakes and Food Sources of Dietary Fibre and Their Associations with Measures of Body Composition and Inflammation in UK Adults: Cross-Sectional Analysis of the Airwave Health Monitoring Study.

The purpose of this study was to investigate the associations between intakes of fibre from the main food sources of fibre in the UK diet with body mass index (BMI), percentage body fat (%BF), waist circumference (WC) and C-reactive protein (CRP). Participants enrolled in the Airwave Health Monitoring Study (2007-2012) with 7-day food records (n = 6898; 61% men) were included for cross-sectional analyses. General linear models evaluated associations across fifths of fibre intakes (total, vegetable, fruit, potato, whole grain and non-whole grain cereal) with BMI, %BF, WC and CRP. Fully adjusted analyses showed inverse linear trends across fifths of total fibre and fibre from fruit with all outcome measures (ptrend < 0.0001). Vegetable fibre intake showed an inverse association with WC (ptrend 0.0156) and CRP (ptrend 0.0005). Fibre from whole grain sources showed an inverse association with BMI (ptrend 0.0002), %BF (ptrend 0.0007) and WC (ptrend 0.0004). Non-whole grain cereal fibre showed an inverse association with BMI (Ptrend 0.0095). Direct associations observed between potato fibre intake and measures of body composition and inflammation were attenuated in fully adjusted analyses controlling for fried potato intake. Higher fibre intake has a beneficial association on body composition, however, there are differential associations based on the food source.

Nutrient profiling and adherence to components of the UK national dietary guidelines association with metabolic risk factors for CVD and diabetes: Airwave Health Monitoring Study.

CVD is the leading cause of death worldwide. Diet is a key modifiable component in the development of CVD. No official UK diet quality index exists for use in UK nutritional epidemiological studies. The aims of this study are to: (i) develop a diet quality index based on components of UK dietary reference values (DRV) and (ii) determine the association between the index, the existing UK nutrient profile (NP) model and a comprehensive range of cardiometabolic risk markers among a British adult population. A cross-sectional analysis was conducted using data from the Airwave Health Monitoring Study (n 5848). Dietary intake was measured by 7-d food diary and metabolic risk using waist circumference, BMI, blood lipid profile, glycated Hb (HbA1c) and blood pressure measurements. Diet quality was assessed using the novel DRV index and NP model. Associations between diet and cardiometabolic risk were analysed via multivariate linear models and logistic regression. A two-point increase in NP score was associated with total cholesterol (ß -0·33 mmol/l, P<0·0001) and HbA1c (ß -0·01 %, P<0·0001). A two-point increase in DRV score was associated with waist circumference (ß -0·56 cm, P<0·0001), BMI (ß -0·15 kg/m2, P<0·0001), total cholesterol (ß -0·06 mmol/l, P<0·0001) and HbA1c (ß -0·02 %, P=0·002). A one-point increase in DRV score was associated with type 2 diabetes (T2D) (OR 0·94, P=0·01) and obesity (OR 0·95, P<0·0001). The DRV index is associated with overall diet quality and risk factors for CVD and T2D, supporting its application in nutritional epidemiological studies investigating CVD risk in a UK population.

A cross-sectional investigation into the occupational and socio-demographic characteristics of British police force employees reporting a dietary pattern associated with cardiometabolic risk: findings from the Airwave Health Monitoring Study.

PURPOSE: The aims of this study were to (1) determine the association between diet quality using the Dietary Approaches to Stop Hypertension (DASH) score and cardiometabolic risk in a British working population and (2) identify employee characteristics associated with reporting a poorer quality dietary pattern. METHODS: British police employees enrolled (2007-2012) into the Airwave Health Monitoring Study (n = 5527) were included for sex-specific cross-sectional analyses. Dietary intakes were measured using 7-day food records. DASH score was calculated to determine diet quality. Logistic regression evaluated associations between (1) diet quality and increased cardiometabolic risk (defined as ≥ 3 risk markers: dyslipidaemia, elevated blood pressure, waist circumference, CRP or HbA1c), and (2) poor diet quality (lowest fifth of DASH score distribution) and employee characteristics. RESULTS: Employees recording a poor diet quality had greater odds (OR) of increased cardiometabolic risk independent of established risk factors (demographic, lifestyle and occupational) and BMI: men OR 1.50 (95% CI 1.12-2.00), women: OR 1.84 (95% CI 1.19-2.97) compared to the healthiest diet group. Characteristics associated with reporting a poor quality diet were employment in Scotland vs. England: men OR 1.88 (95% CI 1.53-2.32), women: OR 1.49 (95% CI 1.11-2.00), longer working hours (≥ 49 vs. ≤40 h) men: OR 1.53 (95% CI 1.21-1.92) women: OR 1.53 (95% CI 1.12-2.09). For men, job strain (high vs. low) was associated with reporting a poor diet quality OR 1.66 (95% CI 1.30-2.12). CONCLUSIONS: The general population disparities in diet quality between England and Scotland were reflected in British police employees. The association of longer working hours and job strain with diet quality supports the targeting of workplace nutritional interventions.

Dietary assessment of British police force employees: a description of diet record coding procedures and cross-sectional evaluation of dietary energy intake reporting (The Airwave Health Monitoring Study).

OBJECTIVES: Dietary intake is a key aspect of occupational health. To capture the characteristics of dietary behaviour that is affected by occupational environment that may affect disease risk, a collection of prospective multiday dietary records is required. The aims of this paper are to: (1) collect multiday dietary data in the Airwave Health Monitoring Study, (2) describe the dietary coding procedures applied and (3) investigate the plausibility of dietary reporting in this occupational cohort. DESIGN: A dietary coding protocol for this large-scale study was developed to minimise coding error rate. Participants (n 4412) who completed 7-day food records were included for cross-sectional analyses. Energy intake (EI) misreporting was estimated using the Goldberg method. Multivariate logistic regression models were applied to determine participant characteristics associated with EI misreporting. SETTING: British police force employees enrolled (2007-2012) into the Airwave Health Monitoring Study. RESULTS: The mean code error rate per food diary was 3.7% (SD 3.2%). The strongest predictors of EI under-reporting were body mass index (BMI) and physical activity. Compared with participants with BMI<25 kg/m2, those with BMI>30 kg/m2 had increased odds of being classified as under-reporting EI (men OR 5.20 95% CI 3.92 to 6.89; women OR 2.66 95% CI 1.85 to 3.83). Men and women in the highest physical activity category compared with the lowest were also more likely to be classified as under-reporting (men OR 3.33 95% CI 2.46 to 4.50; women OR 4.34 95% CI 2.91 to 6.55). CONCLUSIONS: A reproducible dietary record coding procedure has been developed to minimise coding error in complex 7-day diet diaries. The prevalence of EI under-reporting is comparable with existing national UK cohorts and, in agreement with previous studies, classification of under-reporting was biased towards specific subgroups of participants.