Dataset Information

Metabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation.

ABSTRACT: Background:Visceral adipose tissue (VAT) assessment is limited in clinical practice due to expensive, time consuming and limited availability of MRI and DXA machines. We explored the utility of a recently developed Metabolic Score for Visceral Fat (METS-VF) to assess VAT in south Asian individuals with morbid obesity. Patients and Methods:Individuals with BMI ?35 kg/m2 aged between 30 and 60 years were randomly selected from a database of individuals with morbid obesity, attending a multi-disciplinary bariatric clinic in a tertiary care teaching hospital in southern India. Body composition was assessed by using a Hologic Discovery A dual-energy X-ray absorptiometry (DXA) machine. METS-VF was used to estimate VAT by using a previously published algorithm. Results:The mean age and body mass index of the study subjects (N=350) were 38.2 years and 40.1 kg/m2. The MET-VF score performed satisfactorily (AUC of 0.78 (95% CI 0.72-0.85)) for predicting an increased visceral adipose tissue (VAT area ? 163 cm2) as detected by DXA. A METS-VF value of 7.3 was found to have a good sensitivity and reasonable specificity in predicting elevated VAT in this population. Conclusion:This is the first study to validate the utility of METS-VF as a surrogate measure of visceral adiposity in south Indian individuals with morbid obesity. Given the simplicity, easy availability, reliability and inexpensive nature of this obesity indicator, it may find its widespread use in lower middle-income countries.

SUBMITTER: Kapoor N

PROVIDER: S-EPMC7507406 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Metabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation.

Kapoor Nitin N Jiwanmall Stephen A SA Nandyal Munaf B MB Kattula Dheeraj D Paravathareddy Sandhiya S Paul Thomas V TV Furler John J Oldenburg Brian B Thomas Nihal N

Diabetes, metabolic syndrome and obesity : targets and therapy 20200916

<h4>Background</h4>Visceral adipose tissue (VAT) assessment is limited in clinical practice due to expensive, time consuming and limited availability of MRI and DXA machines. We explored the utility of a recently developed Metabolic Score for Visceral Fat (METS-VF) to assess VAT in south Asian individuals with morbid obesity.<h4>Patients and methods</h4>Individuals with BMI ≥35 kg/m<sup>2</sup> aged between 30 and 60 years were randomly selected from a database of individuals with morbid obesity ...[more]

PMID: 32982356

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Project description:Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09), previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not previously uncovered in large-scale GWAS of anthropometric traits.

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

Metabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation.

Publications

Metabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation.

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