Associations of coagulation parameters and thrombin generation potential with the incidence of type 2 diabetes: mediating role of glycoprotein acetylation.

Hypercoagulability is characterized by abnormal elevations of coagulation factor levels and increased thrombin generation potential. Prior studies demonstrated links between impaired glucose metabolism, endothelial dysfunction, and hypercoagulability. However, the associations between hypercoagulability and incident type 2 diabetes as well as its underlying mechanism remain unclear. We aimed to assess the associations between coagulation parameters including coagulation factor (F) VIII, FIX, FXI, fibrinogen, thrombin generation potential (lag time, endogenous thrombin potential [ETP], peak, time-to-peak, velocity) and incident type 2 diabetes, and to study the underlying mechanism by examining the mediating role of glycoprotein acetylation (GlycA). In the Netherlands Epidemiology of Obesity study, we applied a Cox Proportional-Hazards Model in 5718 participants after adjustment for confounders. We further conducted a mediation analysis investigating the mediation effect of GlycA on the observed associations. During a median follow-up of 6.7 years, 281 incident type 2 diabetes diagnoses were reported. Compared with the lowest quartile, hazard ratio (95% confidence interval) of the highest quartile was 2.47 (1.48-4.14) for FIX, 1.37 (0.85-2.20) for FVIII, 1.11 (0.76-1.63) for FXI, 0.98 (0.65-1.48) for fibrinogen, 1.56 (1.07-2.28) for ETP, 1.84 (1.23-2.74) for peak, 1.59 (1.08-2.33) for velocity, 0.92 (0.62-1.38) for lag time, and 1.21 (0.86-1.70) for time-to-peak. GlycA mediated only a small proportion of all observed associations. In conclusion, elevated levels of coagulation factor and thrombin generation potential are associated with incident type 2 diabetes, suggesting the involvement of hypercoagulability in the pathogenesis of type 2 diabetes.

Timing of physical activity in relation to liver fat content and insulin resistance.

AIMS/HYPOTHESIS: We hypothesised that the insulin-sensitising effect of physical activity depends on the timing of the activity. Here, we examined cross-sectional associations of breaks in sedentary time and timing of physical activity with liver fat content and insulin resistance in a Dutch cohort. METHODS: In 775 participants of the Netherlands Epidemiology of Obesity (NEO) study, we assessed sedentary time, breaks in sedentary time and different intensities of physical activity using activity sensors, and liver fat content by magnetic resonance spectroscopy (n=256). Participants were categorised as being most active in the morning (06:00-12:00 hours), afternoon (12:00-18:00 hours) or evening (18:00-00:00 hours) or as engaging in moderate-to-vigorous-physical activity (MVPA) evenly distributed throughout the day. Most active in a certain time block was defined as spending the majority (%) of total daily MVPA in that block. We examined associations between sedentary time, breaks and timing of MVPA with liver fat content and HOMA-IR using linear regression analyses, adjusted for demographic and lifestyle factors including total body fat. Associations of timing of MVPA were additionally adjusted for total MVPA. RESULTS: The participants (42% men) had a mean (SD) age of 56 (4) years and a mean (SD) BMI of 26.2 (4.1) kg/m2. Total sedentary time was not associated with liver fat content or insulin resistance, whereas the amount of breaks in sedentary time was associated with higher liver fat content. Total MVPA (-5%/h [95% CI -10%/h, 0%/h]) and timing of MVPA were associated with reduced insulin resistance but not with liver fat content. Compared with participants who had an even distribution of MVPA throughout the day, insulin resistance was similar (-3% [95% CI -25%, 16%]) in those most active in morning, whereas it was reduced in participants who were most active in the afternoon (-18% [95% CI -33%, -2%]) or evening (-25% [95% CI -49%, -4%]). CONCLUSIONS/INTERPRETATION: The number of daily breaks in sedentary time was not associated with lower liver fat content or reduced insulin resistance. Moderate-to-vigorous activity in the afternoon or evening was associated with a reduction of up to 25% in insulin resistance. Further studies should assess whether timing of physical activity is also important for the occurrence of type 2 diabetes.

Adherence to dietary guidelines in relation to visceral fat and liver fat in middle-aged men and women: the NEO study.

BACKGROUND: It is unclear to what extent adherence to dietary guidelines may specifically affect visceral fat and liver fat. We aimed to study the association between the Dutch Healthy Diet Index (DHD-index) and total body fat, visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC) in middle-aged men and women. DESIGN: In this cross-sectional study, VAT was assessed by magnetic resonance imaging (MRI) in 2580 participants, and HTGC by proton-MR spectroscopy in 2083 participants. Habitual dietary intake and physical activity were estimated by questionnaire. Adherence to the current Dutch dietary guidelines was estimated by the 2015 DHD-index score based on the thirteen components (vegetables, fruit, wholegrain products, legumes, nuts, dairy, fish, tea, liquid fats, red meat, processed meat, sweetened beverages, and alcohol). The DHD-index ranges between 0 and 130 with a higher score indicating a healthier diet. We used linear regression to examine associations of the DHD-index with VAT and HTGC, adjusted for age, smoking, education, ethnicity, basal metabolic rate, energy restricted diet, menopausal state, physical activity, total energy intake, and total body fat. We additionally excluded the components one by one to examine individual contributions to the associations. RESULTS: Included participants (43% men) had a mean (SD) age of 56 (6) years and DHD-index score of 71 (15). A 10-point higher DHD-index score was associated with 2.3 cm2 less visceral fat (95% CI; -3.5; -1.0 cm2) and less liver fat (0.94 times, 95% CI; 0.90; 0.98). Of all components, exclusion of dairy attenuated the associations with TBF and VAT. CONCLUSIONS: Adherence to the dietary guidelines as estimated by the DHD-index was associated with less total body fat, and with less visceral and liver fat after adjustment for total body fat. These findings might contribute to better understanding of the mechanisms underlying associations between dietary habits and cardiometabolic diseases.

Sweet Snacks Are Positively and Fruits and Vegetables Are Negatively Associated with Visceral or Liver Fat Content in Middle-Aged Men and Women.

BACKGROUND: Visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC) are major risk factors for cardiometabolic diseases. OBJECTIVE: We aimed to investigate the association of dietary intake of the main food groups with VAT and HTGC in middle-aged men and women. METHODS: We used data from the Netherlands Epidemiology of Obesity study, a population-based study including 6671 participants aged 45-65 y at baseline. In this cross-sectional analysis, VAT and HTGC were assessed by magnetic resonance imaging and spectroscopy, respectively, as the primary outcomes. Habitual intake of main food groups (dairy, meat, fish, fruits and vegetables, sweet snacks, and fats and oils) was estimated through the use of a food-frequency questionnaire. We examined associations of intake of different food groups with VAT and HTGC by linear regression analysis stratified by sex and adjusted for age, smoking, education, ethnicity, physical activity, basal metabolic rate, energy-restricted diet, menopausal state, and total energy intake. RESULTS: In women, a 100-g/d higher intake of dairy was associated with 2.0 cm2 less VAT (95% CI: -3.4, -0.7 cm2) and a 0.95-fold lower HTGC (95% CI: 0.90-, 0.99-fold). Moreover, a 100-g/d higher intake of fruit and vegetables was associated with 1.6 cm2 less VAT (95% CI: -2.9, -0.2 cm2) in women. Fruit and vegetables were negatively associated (0.95; 95% CI: 0.91, 1.00) with HTGC, and sweet snacks were positively associated (1.29; 95% CI: 1.03, 1.63). Patterns were weaker but similar in men. Fish intake was not associated with VAT or HTGC and plant-based fat and oil intake were only associated with VAT after adjustment for total body fat. CONCLUSIONS: Despite some variation in the strength of the associations between men and women, dietary intake of sweet snacks was positively associated with HTGC, and fruit and vegetable intake were negatively associated with visceral and liver fat content. Prospective studies are needed to confirm these results. The Netherlands Epidemiology of Obesity study is registered at clinicaltrials.gov with identifier NCT03410316.

Consumption of Alcoholic and Sugar-Sweetened Beverages is Associated with Increased Liver Fat Content in Middle-Aged Men and Women.

BACKGROUND: Fatty liver is the leading cause of chronic liver diseases and increases the risk of cardiovascular disease. Besides alcohol consumption, energy-containing nonalcoholic beverages may contribute to liver fat accumulation. OBJECTIVE: We aimed to study the consumption of alcoholic and nonalcoholic beverages and their mutual replacement in relation to hepatic triglyceride content (HTGC) in middle-aged men and women. METHODS: In this cross-sectional analysis, HTGC was assessed by proton magnetic resonance spectroscopy. Habitual consumption of alcoholic and nonalcoholic beverages was assessed using a validated food-frequency questionnaire. All beverages were converted to standard servings and to percentage of total energy intake (En%). We performed linear regression to examine the association of alcoholic and nonalcoholic beverages with HTGC, adjusted for age, sex, smoking, education, ethnicity, physical activity, total energy intake, and total body fat. We studied replacement of alcoholic beverages with nonalcoholic beverages per 1 serving/d and per 5 En%/d. RESULTS: After exclusion of individuals with missing values, 1966 participants (47% men) were analyzed, with a mean ± SD age of 55 ± 6 y, BMI of 26 ± 4 kg/m2, and HTGC of 5.7% ± 7.9%. Each extra alcoholic serving per day was associated with more liver fat (1.09 times; 95% CI: 1.05, 1.12). Replacing 5 En% of alcoholic beverages with milk was associated with less liver fat (0.89 times; 95% CI: 0.81, 0.98), whereas replacement with 5 En% of sugar-sweetened beverages was associated with liver fat to an extent similar to alcoholic beverages (1.00 times; 95% CI: 0.91, 1.09). CONCLUSION: In a population-based cohort, consumption of each extra daily alcoholic beverage was associated with more liver fat. In isocaloric replacement of alcoholic beverages, milk was associated with less liver fat, whereas sugar-sweetened beverages were equally associated with liver fat. This suggests that intake of alcohol and sugars may contribute to liver fat accumulation. This trial was registered at clinicaltrials.gov as NCT03410316.

The association between low sex hormone binding globulin and increased risk of type 2 diabetes is mediated by increased visceral and liver fat: results from observational and Mendelian randomization analyses.

The aim of this study was to investigate the associations between sex hormone binding globulin (SHBG), visceral fat (VAT), liver fat content, and risk of type 2 diabetes. In the Netherlands Epidemiology of Obesity study 5690 women (53%) and men without pre-existing diabetes were included and followed for incident type 2 diabetes. SHBG concentrations were measured in all, VAT with MRI, and liver fat content with proton-MR spectroscopy in n=1822. We examined associations between SHBG and liver fat with linear regression and bidirectional Mendelian randomization analyses, and between SHBG and type 2 diabetes with Cox regression adjusted for confounding, and additionally for VAT and liver fat to examine mediation. The mean(SD) age was 56(6) years, BMI 30(4) kg/m2, median(IQR) SHBG was 47 (34,65) nmol/L in women and 34 (26,43) nmol/L in men, median(IQR) liver fat was 3.4(1.6,8.2)% in women and 6.0 (2.9,13.5)% in men. Compared with the highest SHBG quartile, liver fat was 2.9-fold (95%CI: 2.4,3.4) increased in women and 1.6-fold (95%CI: 1.3,1.8) in men, and the hazard ratio (95%CI) of type 2 diabetes was 4.9 (2.4,9.9) in women and 1.8 (1.1,2.9) in men. Genetically predicted SHBG was associated with liver fat content (women: SD (95%CI) -0.45(-0.55,-0.35), men: ln(95%CI) -0.25 (-0.34,-0.16)). VAT and liver fat together mediated 43% (women) and 60% (men) of the SHBG-type 2 diabetes association. To conclude, in a middle-aged population with overweight, the association between low SHBG and increased risk of type 2 diabetes was for a large part mediated by increased VAT and liver fat.

Objectively Measured Physical Activity and Body Fatness: Associations with Total Body Fat, Visceral Fat, and Liver Fat.

PURPOSE: It remains unclear to what extent habitual physical activity and sedentary time (ST) are associated with visceral fat and liver fat. We studied the substitution of ST with time spent physically active and total body fat (TBF), visceral adipose tissue (VAT), and hepatic triglyceride content (HTGC) in middle-age men and women. DESIGN: In this cross-sectional analysis of the Netherlands Epidemiology of Obesity study, physical activity was assessed in 228 participants using a combined accelerometer and heart rate monitor. TBF was assessed by the Tanita bioelectrical impedance, VAT by magnetic resonance imaging, and HTGC by proton-MR spectroscopy. Behavioral intensity distribution was categorized as ST, time spent in light physical activity (LPA), and moderate to vigorous physical activity (MVPA). To estimate the effect of replacing 30 min·d-1 of ST with 30 min·d-1 LPA or MVPA, we performed isotemporal substitution analyses, adjusted for sex, age, ethnicity, education, the Dutch Healthy Diet index, and smoking. RESULTS: Included participants (41% men) had a mean ± SD age of 56 ± 6 yr and spent 88 ± 56 min in MVPA and 9.0 ± 2.1 h of ST. Replacing 30 min·d-1 of ST with 30 min of MVPA was associated with 1.3% less TBF (95% confidence interval = -2.0 to -0.7), 7.8 cm2 less VAT (-11.6 to -4.0), and 0.89 times HTGC (0.82-0.97). Replacement with LPA was not associated with TBF (-0.03%; -0.5 to 0.4), VAT (-1.7 cm2; -4.4 to 0.9), or HTGC (0.98 times; 0.92-1.04). CONCLUSIONS: Reallocation of time spent sedentary with time spent in MVPA, but not LPA, was associated with less TBF, visceral fat, and liver fat. These findings contribute to the development of more specified guidelines on ST and physical activity.

Effects of dietary macronutrients on liver fat content in adults: a systematic review and meta-analysis of randomized controlled trials.

Dietary macronutrient composition may affect hepatic liver content and its associated diseases, but the results from human intervention trials have been equivocal or underpowered. We aimed to assess the effects of dietary macronutrient composition on liver fat content by conducting a systematic review and meta-analysis of randomized controlled trials in adults. Four databases (PubMed, Embase, Web of Science, and COCHRANE Library) were systematically searched for trials with isocaloric diets evaluating the effect of dietary macronutrient composition (energy percentages of fat, carbohydrates, and protein, and their specific types) on liver fat content as assessed by magnetic resonance techniques, computed tomography or liver biopsy. Data on change in liver fat content were pooled by random or fixed-effects meta-analyses and expressed as standardized mean difference (SMD). We included 26 randomized controlled trials providing data for 32 comparisons on dietary macronutrient composition. Replacing dietary fat with carbohydrates did not result in changes in liver fat (12 comparisons, SMD 0.01 (95% CI -0.36; 0.37)). Unsaturated fat as compared with saturated fat reduced liver fat content (4 comparisons, SMD -0.80 (95% CI -1.09; -0.51)). Replacing carbohydrates with protein reduced liver fat content (5 comparisons, SMD -0.33 (95% CI -0.54; -0.12)). Our meta-analyses showed that replacing carbohydrates with total fat on liver fat content was not effective, while replacing carbohydrates with proteins and saturated fat with unsaturated fat was. More well-performed and well-described studies on the effect of types of carbohydrates and proteins on liver fat content are needed, especially studies comparing proteins with fats.

Associations between Lifestyle Factors and Vitamin E Metabolites in the General Population.

The antioxidant vitamin E (α-tocopherol, α-TOH) protects lipids from oxidation by reactive oxygen species. We hypothesized that lifestyle factors associate with vitamin E metabolism marked by urinary α-tocopheronolactone hydroquinone (α-TLHQ) and α-carboxymethyl-hydroxychroman (α-CEHC levels), as potential reflection of lipid oxidation. We conducted a cross-sectional study in the Netherlands Epidemiology of Obesity Study. Serum α-TOH, and urinary α-TLHQ and α-CEHC were quantified by liquid chromatography coupled with tandem mass spectrometry. Information on the lifestyle factors (sleep, physical activity (PA), smoking and alcohol) were collected through questionnaires. Multivariable linear regression analyses were performed to assess the associations between the lifestyle factors and α-TOH measures. A total of 530 participants (46% men) were included with mean (SD) age of 56 (6) years. Of the examined lifestyle factors, only poor sleep was associated with a higher serum α-TOH (mean difference: 4% (95% CI: 1, 7%)). Current smoking was associated with higher urinary α-CEHC (32%: (14%, 53%)), with evidence of a dose-response relationship with smoking intensity (low pack years, 24% (2, 52%); high pack years, 55% (25, 93%)). Moderate physical activity was associated with a lower α-TLHQ relative to α-CEHC (-17%: (-26, -6%), compared with low PA). Only specific lifestyle factors associate with vitamin E metabolism. Examining serum α-TOH does not provide complete insight in vitamin E antioxidant capacity.

Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.

SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption. METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure. CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.