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Prediction of Circulating Adipokine Levels Based on Body Fat Compartments and Adipose Tissue Gene Expression.

ABSTRACT: BACKGROUND:Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels. OBJECTIVES:To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine plasma concentrations of the adipokines adiponectin, leptin, soluble leptin receptor, resistin, interleukin 6, and fatty acid-binding protein 4 (FABP4). METHODS:We performed a cross-sectional analysis of 156 participants from the EPIC Potsdam cohort study and analyzed multiple regression models and partial correlation coefficients. RESULTS:For leptin and FABP4 concentrations, 81 and 45% variance were explained by SAT mass, VAT mass, and gene expression in SAT in multivariable regression models. For the remaining adipokines, AT mass and gene expression explained <16% variance of plasma concentrations. Gene expression in SAT was a less important predictor compared to AT mass. SAT mass was a better predictor than VAT mass for leptin (partial correlation r = 0.81, 95% confidence interval 0.75-0.86, vs. r = 0.58, 95% confidence interval 0.46-0.67), while differences between AT compartments were small for the other adipokines. CONCLUSIONS:While plasma levels of leptin and FABP4 can be explained in a large and medium part by the amount of AT and SAT gene expression, surprisingly, these predictors explained only little variance for all other investigated adipokines.

SUBMITTER: Konigorski S

PROVIDER: S-EPMC6940469 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Prediction of Circulating Adipokine Levels Based on Body Fat Compartments and Adipose Tissue Gene Expression.

Konigorski Stefan S Janke Jürgen J Drogan Dagmar D Bergmann Manuela M MM Hierholzer Johannes J Kaaks Rudolf R Boeing Heiner H Pischon Tobias T

Obesity facts 20191107 6

<h4>Background</h4>Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels.<h4>Objectives</h4>To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine pl ...[more]

PMID: 31698359

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Project description:BackgroundThe conventional measurement of obesity utilises the body mass index (BMI) criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM), and specifically visceral adipose tissue (VAT) mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a) to compare five anthropometric predictors of %FM and VAT mass, and (b) to explore new cut-points for the best of these predictors to improve the characterisation of obesity.MethodsBMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and waist/height0.5 (WHT.5R) were measured and calculated for 81 adults (40 women, 41 men; mean (SD) age: 38.4 (17.5) years; 94% Caucasian). Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0) was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC) to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass).ResultsThe best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes.ConclusionsIn the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals who would most benefit from therapeutic intervention.

Dataset Information

Prediction of Circulating Adipokine Levels Based on Body Fat Compartments and Adipose Tissue Gene Expression.

Publications

Prediction of Circulating Adipokine Levels Based on Body Fat Compartments and Adipose Tissue Gene Expression.

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