Mixtures of long-term exposure to ambient air pollution, built environment and temperature and stroke incidence across Europe

Introduction: The complex interplay of multiple environmental factors and cardiovascular has scarcely been studied. Within the EXPANSE project, we evaluated the association between long-term exposure to multiple environmental indices and stroke incidence across Europe. Methods: Participants from three traditional adult cohorts (Germany, Netherlands and Sweden) and four administrative cohorts (Catalonia [region Spain], Rome [city-wide], Greece and Sweden [nationwide]) were followed until incident stroke, death, migration, loss of follow-up or study end. We estimated exposures at residential addresses from different exposure domains: air pollution (nitrogen dioxide (NO2), particulate matter < 2.5 μm (PM2.5), black carbon (BC), ozone), built environment (green/blue spaces, impervious surfaces) and meteorology (seasonal mean and standard deviation of temperatures). Associations between environmental exposures and stroke were estimated in single and multiple-exposure Cox proportional hazard models, and Principal Component (PC) Analyses derived prototypes for specific exposures domains. We carried out random effects meta-analyses by cohort type. Results: In over 15 million participants, increased levels of NO2 and BC were associated with increased higher stroke incidence in both cohort types. Increased Normalized Difference Vegetation Index (NDVI) was associated with a lower stroke incidence in both cohort types, whereas an increase in impervious surface was associated with an increase in stroke incidence. The first PC of the air pollution domain (PM2.5, NO2 and BC) was associated with an increase in stroke incidence. For the built environment, higher levels of NDVI and lower levels of impervious surfaces were associated with a protective effect [%change in HR per 1 unit = −2.0 (95 %CI, −5.9;2.0) and −1.1(95 %CI, −2.0; −0.3) for traditional adult and administrative cohorts, respectively]. No clear patterns were observed for distance to blue spaces or temperature parameters. Conclusions: We observed increased HRs for stroke with exposure to PM2.5, NO2 and BC, lower levels of greenness and higher impervious surface in single and combined exposure models

Variability of the Human Serum Metabolome over 3 Months in the EXPOsOMICS Personal Exposure Monitoring Study

Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and untargeted metabolomics are increasingly used in exposome studies to study the interactions between nongenetic factors and the blood metabolome. To reliably and efficiently link detected compounds to exposures and health phenotypes in such studies, it is important to understand the variability in metabolome measures. We assessed the within- and between-subject variability of untargeted LC-HRMS measurements in 298 nonfasting human serum samples collected on two occasions from 157 subjects. Samples were collected ca. 107 (IQR: 34) days apart as part of the multicenter EXPOsOMICS Personal Exposure Monitoring study. In total, 4294 metabolic features were detected, and 184 unique compounds could be identified with high confidence. The median intraclass correlation coefficient (ICC) across all metabolic features was 0.51 (IQR: 0.29) and 0.64 (IQR: 0.25) for the 184 uniquely identified compounds. For this group, the median ICC marginally changed (0.63) when we included common confounders (age, sex, and body mass index) in the regression model. When grouping compounds by compound class, the ICC was largest among glycerophospholipids (median ICC 0.70) and steroids (0.67), and lowest for amino acids (0.61) and the O-acylcarnitine class (0.44). ICCs varied substantially within chemical classes. Our results suggest that the metabolome as measured with untargeted LC-HRMS is fairly stable (ICC > 0.5) over 100 days for more than half of the features monitored in our study, to reflect average levels across this time period. Variance across the metabolome will result in differential measurement error across the metabolome, which needs to be considered in the interpretation of metabolome results

Withaferin A is a Leptin Sensitizer with Strong Anti-Diabetic Properties in Mice

The increasing global prevalence of obesity and its associated disorders point to an urgent need for the development of novel and effective therapeutic strategies that induce healthy weight loss. Obesity is characterized by hyperleptinemia and central leptin resistance. In an attempt to identify compounds that could reverse leptin resistance and thus promote weight loss, we analyzed a library of small molecules with mRNA expression profiles similar to that of celastrol, a naturally-occurring compound we previously identified as a leptin sensitizer. By this process we identified another natural compound, withaferin A, that also acts as a leptin sensitizer. We found that withaferin A treatment of diet-induced obese mice resulted in a 20-25% reduction of body weight, while also decreasing obesity-associated abnormalities including hepatic steatosis. Withaferin A marginally affects the body weight of ob/ob and db/db mice, which are both deficient in leptin signaling. In addition, withaferin A, unlike celastrol, has beneficial effects on glucose metabolism independently from its leptin-sensitizing effect. Our results show that the metabolic abnormalities of diet-induced obesity can be mitigated by sensitizing animals to endogenous leptin, and indicate that withaferin A is a potential leptin sensitizer with additional anti-diabetic actions

Adverse generational changes in obesity development converge at midlife without increased cardiometabolic risk.

OBJECTIVE: Obesity is becoming a global public health problem, but it is unclear how it impacts different generations over the life course. Here, a descriptive analysis of the age‐related changes in anthropometric measures and related cardiometabolic risk factors across different generations was performed. METHODS: The development of anthropometric measures and related cardiometabolic risk factors was studied during 26 years of follow‐up in the Doetinchem Cohort Study (N = 6,314 at baseline). All analyses were stratified by sex and generation, i.e., 10‐year age groups (20‐29, 30‐39, 40‐49, and 50‐59 years) at baseline. Generalized estimating equations were used to test for generational differences. RESULTS: Weight, BMI, waist circumference, and prevalence of overweight and obesity were higher, in general, in the younger generations during the first 10 to 15 years of follow‐up. From age 50 to 59 years onward, these measures converged in all generations of men and women. Among cardiometabolic risk factors, only type 2 diabetes showed an unfavorable shift between the two oldest generations of men. CONCLUSIONS: It was observed that, compared with the older generations, the younger generations had obesity at an earlier age but did not reach higher levels at midlife and beyond. This increased exposure to obesity was not (yet) associated with increased prevalence of cardiometabolic risk factors

Adverse generational changes in obesity development converge at midlife without increased cardiometabolic risk

Objective: Obesity is becoming a global public health problem, but it is unclear how it impacts different generations over the life course. Here, a descriptive analysis of the age-related changes in anthropometric measures and related cardiometabolic risk factors across different generations was performed. Methods: The development of anthropometric measures and related cardiometabolic risk factors was studied during 26 years of follow-up in the Doetinchem Cohort Study (N = 6,314 at baseline). All analyses were stratified by sex and generation, i.e., 10-year age groups (20-29, 30-39, 40-49, and 50-59 years) at baseline. Generalized estimating equations were used to test for generational differences. Results: Weight, BMI, waist circumference, and prevalence of overweight and obesity were higher, in general, in the younger generations during the first 10 to 15 years of follow-up. From age 50 to 59 years onward, these measures converged in all generations of men and women. Among cardiometabolic risk factors, only type 2 diabetes showed an unfavorable shift between the two oldest generations of men. Conclusions: It was observed that, compared with the older generations, the younger generations had obesity at an earlier age but did not reach higher levels at midlife and beyond. This increased exposure to obesity was not (yet) associated with increased prevalence of cardiometabolic risk factors

Inflammation Improves Glucose Homeostasis through IKKβ-XBP1s Interaction

It is widely believed that inflammation associated with obesity has an important role in the development of type 2 diabetes. IκB kinase beta (IKKβ) is a crucial kinase that responds to inflammatory stimuli such as tumor necrosis factor α (TNF-α) by initiating a variety of intracellular signaling cascades and is considered to be a key element in the inflammation-mediated development of insulin resistance. We show here, contrary to expectation, that IKKβ-mediated inflammation is a positive regulator of hepatic glucose homeostasis. IKKβ phosphorylates the spliced form of X-Box Binding Protein 1 (XBP1s) and increases the activity of XBP1s. We have used three experimental approaches to enhance the IKKβ activity in the liver of obese mice and observed increased XBP1s activity, reduced ER stress, and a significant improvement in insulin sensitivity and consequently in glucose homeostasis. Our results reveal a beneficial role of IKKβ-mediated hepatic inflammation in glucose homeostasis

Apolipoprotein A-V is a potential target for treating coronary artery disease: evidence from genetic and metabolomic analyses.

Triglyceride (TG)-lowering LPL variants in combination with genetic LDL-C-lowering variants are associated with reduced risk of coronary artery disease (CAD). Genetic variation in the APOA5 gene encoding apolipoprotein A-V also strongly affects TG levels, but the potential clinical impact and underlying mechanisms are yet to be resolved. Here, we aimed to study the effects of APOA5 genetic variation on CAD risk and plasma lipoproteins through factorial genetic association analyses. Using data from 309,780 European-ancestry participants from the UK Biobank, we evaluated the effects of lower TG levels as a result of genetic variation in APOA5 and/or LPL on CAD risk with or without a background of reduced LDL-C. Next, we compared lower TG levels via APOA5 and LPL variation with over 100 lipoprotein measurements in a combined sample from the Netherlands Epidemiology of Obesity study (N = 4,838) and the Oxford Biobank (N = 6,999). We found that lower TG levels due to combined APOA5 and LPL variation and genetically-influenced lower LDL-C levels afforded the largest reduction in CAD risk (odds ratio: 0.78 (0.73-0.82)). Compared to patients with genetically-influenced lower TG via LPL, genetically-influenced lower TG via APOA5 had similar and independent, but notably larger, effects on the lipoprotein profile. Our results suggest that lower TG levels as a result of APOA5 variation have strong beneficial effects on CAD risk and the lipoprotein profile, which suggest apo A-V may be a potential novel therapeutic target for CAD prevention.Diabetes mellitus: pathophysiological changes and therap

Triglyceride-lowering LPL alleles combined with LDL-C-lowering alleles are associated with an additively improved lipoprotein profile.

Compared to the individual groups with genetically-influenced lower TG or lower LDL-C only, the group with combined genetically-influenced lower TG and LDL-C showed an overall independent and additive pattern of changes in metabolomic measures. Over 100 measures were different (p < 1.35 × 10-3) compared to the reference, with effect sizes and directionality being similar in NEO and OBB. Most notably, levels of all very-low density lipoprotein (VLDL) and LDL sub-particles were lower

Adherence to a food group-based dietary guideline and incidence of prediabetes and type 2 diabetes

Purpose: In this study, we investigated the association between adherence to the Dutch Healthy Diet index 2015 (DHD15-index) and incidence of prediabetes (preT2D) and Type 2 Diabetes (T2D) in a representative sample for the general Dutch population. Methods: Two prospective cohort studies, The Hoorn and The New Hoorn Study, were used for data analyses. In total, data from 2951 participants without diabetes at baseline (mean age 56.5 ± 7.5 years; 49.6% male) were harmonized. Baseline dietary intake was assessed with validated Food Frequency Questionnaires and adherence to the DHD15-index was calculated (range 0–130). PreT2D and T2D were classified according to the WHO criteria 2011. Poisson regression was used to estimate prevalence ratios between participant scores on the DHD15-index and preT2D and T2D, adjusted for follow-up duration, energy intake, socio-demographic, and lifestyle factors. Change in fasting plasma glucose levels (mmol/L) over follow-up was analysed using linear regression analyses, additionally adjusted for baseline value. Results: During a mean follow-up of 6.3 ± 0.7 years, 837 participants developed preT2D and 321 participants developed T2D. The highest adherence to the DHD15-index was significantly associated with lower T2D incidence [model 3, PRT3vsT1: 0.70 (0.53; 0.92), ptrend = 0.01]. The highest adherence to the DHD15-index pointed towards a lower incidence of preT2D [PRT3vsT1: 0.87 (0.74; 1.03), ptrend = 0.11]. Higher adherence to the DHD15-index was not associated with change in fasting plasma glucose levels [β10point: − 0.012 (− 0.034; 0.009)mmol/L]. Conclusion: The present study showed that the highest compared to the lowest adherence to the DHD15-index was associated with a lower T2D incidence, and pointed towards a lower incidence of preT2D. These results support the benefits of adhering to the guidelines in T2D prevention.</p

Correction to: Adherence to a food group-based dietary guideline and incidence of prediabetes and type 2 diabetes.

The original version of this article unfortunately contained a mistake in Table 4.</p