Body Size Measurements as Predictors of Type 2 Diabetes in Aboriginal People

OBJECTIVE: To investigate waist circumference, waist-to-hip ratio, body mass index (BMI), weight and hip circumference as risk factors for type 2 diabetes in Aboriginal Australians. DESIGN: Community-based cross-sectional study. SUBJECTS: In total, 915 Australian Aboriginal adults (age: 18-74 y) from a remote Aboriginal community in the Northern Territory of Australia. MEASUREMENTS: Body size measurements included waist circumference, waist-to-hip ratio, BMI, weight and hip circumference. Diabetes status was determined according to medical history and fasting and 2-h postload plasma glucose values. Logistic regression was used to calculate odds ratio for diabetes associated with 1 standard deviation (s.d.) increase in a body size measurement. The areas under the ROC curves of five body size measurements were calculated and compared. RESULTS: Risk of diabetes increased with increasing levels of body size. ORs (95% CI) for diabetes with adjustment for age and sex were 2.16 (1.75, 2.66), 1.80 (1.49, 2.17), 1.41 (1.17, 1.71), 1.81 (1.51, 2.19) and 1.84 (1.50, 2.24) associated with 1 s.d. increase in waist circumference, BMI, weight, waist-to-hip ratio, and hip circumference, respectively. The area under the ROC curve for waist circumference was significantly higher than those for other measurements. CONCLUSION: Waist circumference is the best body size measurement in predicting diabetes in Aboriginal people

Body composition and body fat distribution are related to cardiac autonomic control in non-alcoholic fatty liver disease patients

BACKGROUND/OBJECTIVES: Heart rate recovery (HRR), a cardiac autonomic control marker, was shown to be related to body composition (BC), yet this was not tested in non-alcoholic fatty liver disease (NAFLD) patients. The aim of this study was to determine if, and to what extent, markers of BC and body fat (BF) distribution are related to cardiac autonomic control in NAFLD patients. SUBJECTS/METHODS: BC was assessed with dual-energy X-ray absorptiometry in 28 NAFLD patients (19 men, 51±13 years, and 9 women, 47±13 years). BF depots ratios were calculated to assess BF distribution. Subjects’ HRR was recorded 1 (HRR1) and 2 min (HRR2) immediately after a maximum graded exercise test. RESULTS: BC and BF distribution were related to HRR; particularly weight, trunk BF and trunk BF-to-appendicular BF ratio showed a negative relation with HRR1 (r 1⁄4 0.613, r 1⁄4 0.597 and r 1⁄4 0.547, respectively, Po0.01) and HRR2 (r 1⁄4 0.484, r 1⁄4 0.446, Po0.05, and r 1⁄4 0.590, Po0.01, respectively). Age seems to be related to both HRR1 and HRR2 except when controlled for BF distribution. The preferred model in multiple regression should include trunk BF-to-appendicular BF ratio and BF to predict HRR1 (r2 1⁄4 0.549; Po0.05), and trunk BF-to-appendicular BF ratio alone to predict HRR2 (r2 1⁄4 0.430; Po0.001). CONCLUSIONS: BC and BF distribution were related to HRR in NAFLD patients. Trunk BF-to-appendicular BF ratio was the best independent predictor of HRR and therefore may be best related to cardiovascular increased risk, and possibly act as a mediator in age-related cardiac autonomic control variation.info:eu-repo/semantics/publishedVersio

Feasibility of MR-Based Body Composition Analysis in Large Scale Population Studies

Introduction Quantitative and accurate measurements of fat and muscle in the body are important for prevention and diagnosis of diseases related to obesity and muscle degeneration. Manually segmenting muscle and fat compartments in MR body-images is laborious and time-consuming, hindering implementation in large cohorts. In the present study, the feasibility and success-rate of a Dixon-based MR scan followed by an intensity-normalised, non-rigid, multi-atlas based segmentation was investigated in a cohort of 3,000 subjects. Materials and Methods 3,000 participants in the in-depth phenotyping arm of the UK Biobank imaging study underwent a comprehensive MR examination. All subjects were scanned using a 1.5 T MR-scanner with the dual-echo Dixon Vibe protocol, covering neck to knees. Subjects were scanned with six slabs in supine position, without localizer. Automated body composition analysis was performed using the AMRA Profiler™ system, to segment and quantify visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT) and thigh muscles. Technical quality assurance was performed and a standard set of acceptance/rejection criteria was established. Descriptive statistics were calculated for all volume measurements and quality assurance metrics. Results Of the 3,000 subjects, 2,995 (99.83%) were analysable for body fat, 2,828 (94.27%) were analysable when body fat and one thigh was included, and 2,775 (92.50%) were fully analysable for body fat and both thigh muscles. Reasons for not being able to analyse datasets were mainly due to missing slabs in the acquisition, or patient positioned so that large parts of the volume was outside of the field-of-view. Discussion and Conclusions In conclusion, this study showed that the rapid UK Biobank MR-protocol was well tolerated by most subjects and sufficiently robust to achieve very high success-rate for body composition analysis. This research has been conducted using the UK Biobank Resource

Genetic influences on the insulin response of the beta cell to different secretagogues

Aims/hypothesis: The aim of the present study was to estimate the heritability of the beta cell insulin response to glucose and to glucose combined with glucagon-like peptide-1 (GLP-1) or with GLP-1 plus arginine. Methods: This was a twin-family study that included 54 families from the Netherlands Twin Register. The participants were healthy twin pairs and their siblings of the same sex, aged 20 to 50 years. Insulin response of the beta cell was assessed by a modified hyperglycaemic clamp with additional GLP-1 and arginine. Insulin sensitivity index (ISI) was assessed by the euglycaemic-hyperinsulinaemic clamp. Multivariate structural equation modelling was used to obtain heritabilities and the genetic factors underlying individual differences in BMI, ISI and secretory responses of the beta cell. Results: The heritability of insulin levels in response to glucose was 52% and 77% for the first and second phase, respectively, 53% in response to glucose+GLP-1 and 80% in response to an additional arginine bolus. Insulin responses to the administration of glucose, glucose+GLP-1 and glucose+GLP-1+arginine were highly correlated (0.62<r<0.79). Heritability of BMI and ISI was 74% and 60% respectively. The genetic factors that influenced BMI and ISI explained about half of the heritability of insulin levels in response to the three secretagogues. The other half was due to genetic factors specific to the beta cell. Conclusions/interpretation: In healthy adults, genetic factors explain most of the individual differences in the secretory capacity of the beta cell. These genetic influences are partly independent from the genes that influence BMI and ISI. © 2009 Springer-Verlag

The Role of Body Mass Index, Insulin, and Adiponectin in the Relation Between Fat Distribution and Bone Mineral Density

Despite the positive association between body mass index (BMI) and bone mineral density (BMD) and content (BMC), the role of fat distribution in BMD/BMC remains unclear. We examined relationships between BMD/BMC and various measurements of fat distribution and studied the role of BMI, insulin, and adiponectin in these relations. Using a cross-sectional investigation of 2631 participants from the Erasmus Rucphen Family study, we studied associations between BMD (using dual-energy X-ray absorptiometry (DXA]) at the hip, lumbar spine, total body (BMD and BMC), and fat distribution by the waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and DXA-based trunk-to-leg fat ratio and android-to-gynoid fat ratio. Analyses were stratified by gender and median age (48.0 years in women and 49.2 years in men) and were performed with and without adjustment for BMI, fasting insulin, and adiponectin. Using linear regression (adjusting for age, height, smoking, and use of alcohol), most relationships between fat distribution and BMD and BMC were positive, except for WTR. After BMI adjustment, most correlations were negative except for trunk-to-leg fat ratio in both genders. No consistent influence of age or menopausal status was found. Insulin and adiponectin levels did not explain either positive or negative associations. In conclusion, positive associations between android fat distribution and BMD/BMC are explained by higher BMI but not by higher insulin and/or lower adiponectin levels. Inverse associations after adjustment for BMI suggest that android fat deposition as measured by the WHR, WTR, and DXA-based android-to-gynoid fat ratio is not beneficial and possibly even deleterious for bone

Genetic association study of adiposity and melanocortin-4 receptor (MC4R) common variants: Replication and functional characterization of non-coding regions

Common genetic variants 3′ of MC4R within two large linkage disequilibrium (LD) blocks spanning 288 kb have been associated with common and rare forms of obesity. This large association region has not been refined and the relevant DNA segments within the association region have not been identified. In this study, we investigated whether common variants in the MC4R gene region were associated with adiposity-related traits in a biracial population-based study. Single nucleotide polymorphisms (SNPs) in the MC4R region were genotyped with a custom array and a genome-wide array and associations between SNPs and five adiposity-related traits were determined using race-stratified linear regression. Previously reported associations between lower BMI and the minor alleles of rs2229616/Val103Ile and rs52820871/Ile251Leu were replicated in white female participants. Among white participants, rs11152221 in a proximal 3′ LD block (closer to MC4R) was significantly associated with multiple adiposity traits, but SNPs in a distal 309 LD block (farther from MC4R ) were not. In a case-control study of severe obesity, rs11152221 was significantly associated. The association results directed our follow-up studies to the proximal LD block downstream of MC4R. By considering nucleotide conservation, the significance of association, and proximity to the MC4R gene, we identified a candidate MC4R regulatory region. This candidate region was sequenced in 20 individuals from a study of severe obesity in an attempt to identify additional variants, and the candidate region was tested for enhancer activity using in vivo enhancer assays in zebrafish and mice. Novel variants were not identified by sequencing and the candidate region did not drive reporter gene expression in zebrafish or mice. The identification of a putative insulator in this region could help to explain the challenges faced in this study and others to link SNPs associated with adiposity to altered MC4R expression. © 2014 Evans et al

Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types

Abstract Background A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16− monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Conclusions Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability

Reported food intake and distribution of body fat: a repeated cross-sectional study

BACKGROUND: Body mass, as well as distribution of body fat, are predictors of both diabetes and cardiovascular disease. In Northern Sweden, despite a marked increase in average body mass, prevalence of diabetes was stagnant and myocardial infarctions decreased. A more favourable distribution of body fat is a possible contributing factor. This study investigates the relative importance of individual food items for time trends in waist circumference (WC) and hip circumference (HC) on a population level. METHODS: Independent cross-sectional surveys conducted in 1986, 1990, 1994 and 1999 in the two northernmost counties of Sweden with a common population of 250000. Randomly selected age stratified samples, altogether 2982 men and 3087 women aged 25–64 years. Questionnaires were completed and anthropometric measurements taken. For each food item, associations between frequency of consumption and waist and hip circumferences were estimated. Partial regression coefficients for every level of reported intake were multiplied with differences in proportion of the population reporting the corresponding levels of intake in 1986 and 1999. The sum of these product terms for every food item was the respective estimated impact on mean circumference. RESULTS: Time trends in reported food consumption associated with the more favourable gynoid distribution of adipose tissue were increased use of vegetable oil, pasta and 1.5% fat milk. Trends associated with abdominal obesity were increased consumption of beer in men and higher intake of hamburgers and French fried potatoes in women. CONCLUSION: Food trends as markers of time trends in body fat distribution have been identified. The method is a complement to conventional approaches to establish associations between food intake and disease risk on a population level

Strength Training for Arthritis Trial (START): design and rationale

Background Muscle loss and fat gain contribute to the disability, pain, and morbidity associated with knee osteoarthritis (OA), and thigh muscle weakness is an independent and modifiable risk factor for it. However, while all published treatment guidelines recommend muscle strengthening exercise to combat loss of muscle mass and strength in knee OA patients, previous strength training studies either used intensities or loads below recommended levels for healthy adults or were generally short, lasting only 6 to 24 weeks. The efficacy of high-intensity strength training in improving OA symptoms, slowing progression, and affecting the underlying mechanisms has not been examined due to the unsubstantiated belief that it might exacerbate symptoms. We hypothesize that in addition to short-term clinical benefits, combining greater duration with high-intensity strength training will alter thigh composition sufficiently to attain long-term reductions in knee-joint forces, lower pain levels, decrease inflammatory cytokines, and slow OA progression. Methods/Design This is an assessor-blind, randomized controlled trial. The study population consists of 372 older (age ≥ 55 yrs) ambulatory, community-dwelling persons with: (1) mild-to-moderate medial tibiofemoral OA (Kellgren-Lawrence (KL) = 2 or 3); (2) knee neutral or varus aligned knee ( -2° valgus ≤ angle ≤ 10° varus); (3) 20 kg.m-2 ≥ BMI ≤ 45 kg.m-2; and (3) no participation in a formal strength-training program for more than 30 minutes per week within the past 6 months. Participants are randomized to one of 3 groups: high-intensity strength training (75-90% 1Repetition Maximum (1RM)); low-intensity strength training (30-40%1RM); or healthy living education. The primary clinical aim is to compare the interventions’ effects on knee pain, and the primary mechanistic aim is to compare their effects on knee-joint compressive forces during walking, a mechanism that affects the OA disease pathway. Secondary aims will compare the interventions’ effects on additional clinical measures of disease severity (e.g., function, mobility); disease progression measured by x-ray; thigh muscle and fat volume, measured by computed tomography (CT); components of thigh muscle function, including hip abductor strength and quadriceps strength, and power; additional measures of knee-joint loading; inflammatory and OA biomarkers; and health-related quality of life. Discussion Test-retest reliability for the thigh CT scan was: total thigh volume, intra-class correlation coefficients (ICC) = 0.99; total fat volume, ICC = 0.99, and total muscle volume, ICC = 0.99. ICC for both isokinetic concentric knee flexion and extension strength was 0.93, and for hip-abductor concentric strength was 0.99. The reliability of our 1RM testing was: leg press, ICC = 0.95; leg curl, ICC = 0.99; and leg extension, ICC = 0.98. Results of this trial will provide critically needed guidance for clinicians in a variety of health professions who prescribe and oversee treatment and prevention of OA-related complications. Given the prevalence and impact of OA and the widespread availability of this intervention, assessing the efficacy of optimal strength training has the potential for immediate and vital clinical impact

Obesity as Assessed by Body Adiposity Index and Multivariable Cardiovascular Disease Risk

To assess the role of body adiposity index (BAI) in predicting cardiovascular disease (CVD) and coronary heart disease (CHD) mortality, in comparison with body mass index (BMI), waist circumference (WC), and the waist circumference to hip circumference ratio (WHR). This study was a prospective 15 year mortality follow-up of 4175 Australian males, free of heart disease, diabetes and stroke. The Framingham Risk Scores (FRS) for CHD and CVD death were calculated at baseline for all subjects. Multivariable logistic regression was used to assess the effects of the measures of obesity on CVD and CHD mortality, before adjustment and after adjustment for FRS. The predictive ability of BAI, though present in the unadjusted analyses, was generally not significant after adjustment for age and FRS for both CVD and CHD mortality. BMI behaved similarly to BAI in that its predictive ability was generally not significant after adjustments. Both WC and WHR were significant predictors of CVD and CHD mortality and remained significant after adjustment for covariates. BAI appeared to be of potential interest as a measure of % body fat and of obesity, but was ineffective in predicting CVD and CHD