154 research outputs found
Associations between reliable changes in depression and changes in BMI, total body fatness and visceral adiposity during a 12-month weight loss trial.
We investigated associations between changes in depression and body composition over a 12-month weight loss trial. Of the 298 adults (BMI > 27 m/kg2), 219 with complete depression and body composition data were included. A 10-item Center for Epidemiologic Studies Depression Scale measured depression; dual-energy X-ray absorptiometry measured body composition. Multinomial logistic regression predicted reliable changes in depression by BMI, body fat (BF) and visceral adiposity (VAT). Multiplicative interaction terms tested modification by sex and ethnicity. Participants with increases in body composition were less likely to experience improvements in depression (BMI: RRR = 0.79 (0.68-0.91), p < 0.01; BF: RRR = 0.97 (0.94 - 0.99), p = 0.01; VAT: RRR = 0.99 (0.98-1.00), p = 0.02), but not worsening of depression (BMI: RRR = 1.29 (0.96-1.73), p = 0.10; BF: RRR = 1.04 (0.99-1.09), p = 0.15; VAT: RRR = 1.01 (1.00-1.03), p = 0.18). Sex and ethnicity interaction terms were not significant. However, the relationship was only significant among females, among non-Latinos for BMI and BF, and among Latinos for VAT. Our study supports the association between depression and obesity and highlights the need for longitudinal studies investigating VAT and depression in diverse ethnic groups
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Metabolomics profiling of visceral adipose tissue: Results From MESA and the NEO study
Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity-related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross-sectional linear regression of individual-level data from participants in MESA (Multi-Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1H nuclear magnetic resonance spectroscopy. A total of 30Â 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid-lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P=4.88Ă—10-20-1.16Ă—10-3). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched-chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P=1.90Ă—10-35-8.46Ă—10-7), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community-based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity
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
The association of 9p21-3 locus with coronary atherosclerosis: a systematic review and meta-analysis
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