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.Functional Genomics of Systemic Disorder

Войтенко Анатолію Михайловичу — 75 років!

22 липня 2010 року виповнюється 75 років з дня народження Войтенка Анатолія Михайловича і 51 рік трудової і громадської діяльності. Він заслужений діяч науки і техніки України, доктор медичних наук, професор, академік Української академії екологічних наук, академік Міжнародної академії безпеки життєдіяльності

Microbiome in blood samples from the general population recruited in the MARK-AGE project: a pilot study

The presence of circulating microbiome in blood has been reported in both physiological and pathological conditions, although its origins, identities and function remain to be elucidated. This study aimed to investigate the presence of blood microbiome by quantitative real-time PCRs targeting the 16S rRNA gene. To our knowledge, this is the first study in which the circulating microbiome has been analyzed in such a large sample of individuals since the study was carried out on 1285 Randomly recruited Age-Stratified Individuals from the General population (RASIG). The samples came from several different European countries recruited within the EU Project MARK-AGE in which a series of clinical biochemical parameters were determined. The results obtained reveal an association between microbial DNA copy number and geographic origin. By contrast, no gender and age-related difference emerged, thus demonstrating the role of the environment in influencing the above levels independent of age and gender at least until the age of 75. In addition, a significant positive association was found with Free Fatty Acids (FFA) levels, leukocyte count, insulin, and glucose levels. Since these factors play an essential role in both health and disease conditions, their association with the extent of the blood microbiome leads us to consider the blood microbiome as a potential biomarker of human health.Molecular Epidemiolog

Ageing affects subtelomeric DNA methylation in blood cells from a large European population enrolled in the MARK-AGE study

Ageing leaves characteristic traces in the DNA methylation make-up of the genome. However, the importance of DNA methylation in ageing remains unclear. The study of subtelomeric regions could give promising insights into this issue. Previously reported associations between susceptibility to age-related diseases and epigenetic instability at subtelomeres suggest that the DNA methylation profile of subtelomeres undergoes remodelling during ageing. In the present work, this hypothesis has been tested in the context of the European large-scale project MARK-AGE. In this cross-sectional study, we profiled the DNA methylation of chromosomes 5 and 21 subtelomeres, in more than 2000 age-stratified women and men recruited in eight European countries. The study included individuals from the general population as well as the offspring of nonagenarians and Down syndrome subjects, who served as putative models of delayed and accelerated ageing, respectively. Significant linear changes of subtelomeric DNA methylation with increasing age were detected in the general population, indicating that subtelomeric DNA methylation changes are typical signs of ageing. Data also show that, compared to the general population, the dynamics of age-related DNA methylation changes are attenuated in the offspring of centenarian, while they accelerate in Down syndrome individuals. This result suggests that subtelomeric DNA methylation changes reflect the rate of ageing progression. We next attempted to trace the age-related changes of subtelomeric methylation back to the influence of diverse variables associated with methylation variations in the population, including demographics, dietary/health habits and clinical parameters. Results indicate that the effects of age on subtelomeric DNA methylation are mostly independent of all other variables evaluated.Molecular Epidemiolog

GlycA, a Biomarker of Low-Grade Inflammation, Is Increased in Male Night Shift Workers

Sustained night shift work is associated with various adverse health risks, including an increased risk of cardiovascular disease, type II diabetes, and susceptibility to infectious respiratory diseases. The extent of these adverse health effects, however, seems to greatly vary between night shift workers, yet the underlying reasons and the mechanisms underlying these interindividual differences remain poorly understood. Metabolomics assays in the blood have recently gained much attention as a minimally invasive biomarker platform capturing information predictive of metabolic and cardiovascular diseases. In this cross-sectional study, we explored and compared the metabolic profiles of 1010 night shift workers and 1010 age- and sex-matched day workers (non-shift workers) from the Lifelines Cohort Study. The metabolic profiles were determined using the H-1-NMR Nightingale platform for the quantification of 250 parameters of metabolism, including routine lipids, extensive lipoprotein subclasses, fatty acid composition, and various low-molecular metabolites, including amino acids, ketone bodies, and gluconeogenesis-related metabolites. Night shift workers had an increased BMI (26.6 vs. 25.9 kg/m(2)) compared with day workers (non-shift workers) in both sexes, were slightly more likely to be ever smokers (only in males) (54% vs. 46%), worked on average 5.9 +/- 3.7 night shifts per month, and had been working in night shifts for 18.3 +/- 10.5 years on average. We observed changes in several metabolic markers in male night shift workers compared with non-shift workers, but no changes were observed in women. In men, we observed higher levels of glycoprotein acetyls (GlycA), triglycerides, and fatty acids compared with non-shift workers. The changes were seen in the ratio of triglycerides and cholesterol(esters) to total lipids in different sizes of VLDL particles. Glycoprotein acetyls (GlycAs) are of particular interest as markers since they are known as biomarkers for low-grade chronic inflammation. When the analyses were adjusted for BMI, no significant associations were observed. Further studies are needed to better understand the relationship between night shift work and metabolic profiles, particularly with respect to the role of sex and BMI in this relationship.Molecular Epidemiolog

GlycA, a Biomarker of Low-Grade Inflammation, Is Increased in Male Night Shift Workers

Sustained night shift work is associated with various adverse health risks, including an increased risk of cardiovascular disease, type II diabetes, and susceptibility to infectious respiratory diseases. The extent of these adverse health effects, however, seems to greatly vary between night shift workers, yet the underlying reasons and the mechanisms underlying these interindividual differences remain poorly understood. Metabolomics assays in the blood have recently gained much attention as a minimally invasive biomarker platform capturing information predictive of metabolic and cardiovascular diseases. In this cross-sectional study, we explored and compared the metabolic profiles of 1010 night shift workers and 1010 age- and sex-matched day workers (non-shift workers) from the Lifelines Cohort Study. The metabolic profiles were determined using the H-1-NMR Nightingale platform for the quantification of 250 parameters of metabolism, including routine lipids, extensive lipoprotein subclasses, fatty acid composition, and various low-molecular metabolites, including amino acids, ketone bodies, and gluconeogenesis-related metabolites. Night shift workers had an increased BMI (26.6 vs. 25.9 kg/m(2)) compared with day workers (non-shift workers) in both sexes, were slightly more likely to be ever smokers (only in males) (54% vs. 46%), worked on average 5.9 +/- 3.7 night shifts per month, and had been working in night shifts for 18.3 +/- 10.5 years on average. We observed changes in several metabolic markers in male night shift workers compared with non-shift workers, but no changes were observed in women. In men, we observed higher levels of glycoprotein acetyls (GlycA), triglycerides, and fatty acids compared with non-shift workers. The changes were seen in the ratio of triglycerides and cholesterol(esters) to total lipids in different sizes of VLDL particles. Glycoprotein acetyls (GlycAs) are of particular interest as markers since they are known as biomarkers for low-grade chronic inflammation. When the analyses were adjusted for BMI, no significant associations were observed. Further studies are needed to better understand the relationship between night shift work and metabolic profiles, particularly with respect to the role of sex and BMI in this relationship

Metabolic syndrome model definitions predicting type 2 diabetes and cardiovascular disease

OBJECTIVE-Metabolic syndrome (MetS) is a cluster of abdominal obesity, hyperglycemia, hypertension, and dyslipidemia, which increases the risk for type 2 diabetes and cardiovascular diseases (CVDs). Some argue that MetS is not a single disorder because the traditional MetS features do not represent one entity, and they would like to exclude features from MetS. Others would like to add additional features in order to increase predictive ability of MetS. The aim of this study was to identify a MetS model that optimally predicts type 2 diabetes and CVD while still representing a single entity. RESEARCH DESIGN AND METHODS-In a random sample (n = 1,928) of the EPIC-NL cohort and a subset of the EPIC-NL MORGEN study (n = 1,333), we tested the model fit of several one-factor MetS models using confirmatory factor analysis. We compared predictive ability for type 2 diabetes and CVD of these models within the EPIC-NL case-cohort study of 545 incident type 2 diabetic subjects, 1,312 incident CVD case subjects, and the random sample, using survival analyses and reclassification. RESULTS-The standard model, representing the current MetS definition (EPIC-NL comparative fit index [CFI] = 0.95; MORGEN CFI = 0.98); the standard model excluding blood pressure (EPIC-NL CFI = 0.95; MORGEN CFI = 1.00); and the standard model extended with hsCRP (EPIC-NL CFI = 0.95) had an acceptable model fit. The model extended with hsCRP predicted type 2 diabetes (integral discrimination index [IDI]: 0.34) and CVD (IDI: 0.07) slightly better than did the standard model. CONCLUSIONS-It seems valid to represent the traditional MetS features by a single entity. Extension of this entity with hsCRP slightly improves predictive ability for type 2 diabetes and CVD. Diabetes Care 36:362-368, 201

The APOE locus is linked to decline in general cognitive function: 20-years follow-up in the Doetinchem Cohort Study

Cognitive decline is part of the normal aging process. However, some people experience a more rapid decline than others due to environmental and genetic factors. Numerous single nucleotide polymorphisms (SNPs) have been linked to cognitive function, but only a few to cognitive decline. To understand whether cognitive function and cognitive decline are driven by the same mechanisms, we investigated whether 433 SNPs previously linked to cognitive function and 2 SNPs previously linked to cognitive decline are associated with both general cognitive functioning at baseline and general cognitive decline up to 20-years follow-up in the Doetinchem Cohort Study (DCS). The DCS is a longitudinal population-based study that enrolled men and women aged 20-59 years between 1987-1991, with follow-up examinations every 5 years. We used data of rounds 2-6 (1993-2017, n = 2559). General cognitive function was assessed using four cognition tests measuring memory, speed, fluency and flexibility. With these test scores, standardized residuals (adjusted for sex, age and examination round) were calculated for each cognition test at each round and subsequently combined into one general cognitive function measure using principal component analyses. None of the 435 previously identified variants were associated with baseline general cognitive function in the DCS. But rs429358-C, a coding apolipoprotein E (APOE) SNP and one of the variants previously associated with cognitive decline, was associated with general cognitive decline in our study as well (p-value = 1 x 10(-5), Beta = -0.013). These findings suggest that decline of general cognitive function is influenced by other mechanisms than those that are involved in the regulation of general cognitive function.Metabolic health: pathophysiological trajectories and therap

The APOE locus is linked to decline in general cognitive function: 20-years follow-up in the Doetinchem Cohort Study

Cognitive decline is part of the normal aging process. However, some people experience a more rapid decline than others due to environmental and genetic factors. Numerous single nucleotide polymorphisms (SNPs) have been linked to cognitive function, but only a few to cognitive decline. To understand whether cognitive function and cognitive decline are driven by the same mechanisms, we investigated whether 433 SNPs previously linked to cognitive function and 2 SNPs previously linked to cognitive decline are associated with both general cognitive functioning at baseline and general cognitive decline up to 20-years follow-up in the Doetinchem Cohort Study (DCS). The DCS is a longitudinal population-based study that enrolled men and women aged 20-59 years between 1987-1991, with follow-up examinations every 5 years. We used data of rounds 2-6 (1993-2017, n = 2559). General cognitive function was assessed using four cognition tests measuring memory, speed, fluency and flexibility. With these test scores, standardized residuals (adjusted for sex, age and examination round) were calculated for each cognition test at each round and subsequently combined into one general cognitive function measure using principal component analyses. None of the 435 previously identified variants were associated with baseline general cognitive function in the DCS. But rs429358-C, a coding apolipoprotein E (APOE) SNP and one of the variants previously associated with cognitive decline, was associated with general cognitive decline in our study as well (p-value = 1 x 10(-5), Beta = -0.013). These findings suggest that decline of general cognitive function is influenced by other mechanisms than those that are involved in the regulation of general cognitive function