Abdominal and Gynoid Fat Mass Are Associated with Cardiovascular Risk Factors in Men and Women

Wiklund, Peder; Toss, Fredrik; Weinehall, Lars; Hallmans, Göran; Franks, Paul W.; Nordström, Anna; Nordström, Peter

doi:10.1210/jc.2008-0804

Cited by 181 publications

(163 citation statements)

References 25 publications

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“…Fat percentage was calculated as fat mass/(fat mass + lean mass + bone mineral content) for the total body and android and gynoid fat mass and fat percentage were determined from a total body scan as described by Wiklund et al [17]. Venous blood samples were drawn after a 12-h overnight fast for the measurement of serum metabolites (NMR), glucose (measured using the spectrophotometric hexokinase and glucose-6-phosphate dehydrogenase; Roche Diagnostics, Basel, Switzerland), serum insulin (timeresolved immunofluorometric assay; Perkin Elmer, Waltham, MA, USA) and high sensitivity C-reactive protein (CRP) (Cobas CRP (Latex)HS, Roche Diagnostics).…”

Section: 2mentioning

confidence: 99%

Abdominal obesity and circulating metabolites: A twin study approach

et al. 2016

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Objective. To investigate how obesity, insulin resistance and low-grade inflammation link to circulating metabolites, and whether the connections are due to genetic or environmental factors.Subjects and methods. Circulating serum metabolites were determined by proton NMR spectroscopy. Data from 1368 (531 monozygotic (MZ) and 837 dizygotic (DZ)) twins were used for bivariate twin modeling to derive the genetic (r g ) and environmental (r e ) correlations between waist circumference (WC) and serum metabolites. Detailed examination of the associations between fat distribution (DEXA) and metabolic health (HOMA-IR, CRP) was performed among 286 twins including 33 BMI-discordant MZ pairs. Results. Fat, especially in the abdominal area (i.e. WC, android fat % and android to gynoid fat ratio), together with HOMA-IR and CRP correlated significantly with an atherogenic lipoprotein profile, higher levels of branched-chain (BCAA) and aromatic amino acids, higher levels of glycoprotein, and a more saturated fatty acid profile. In contrast, a higher proportion of gynoid to total fat associated with a favorable metabolite profile. There was a significant genetic overlap between WC and several metabolites, most strongly with phenylalanine (r g = 0.40), glycoprotein (r g = 0.37), serum triglycerides (r g = 0.36), BCAAs (r g = 0.30-0.40), HDL Keywords:Twin study Bivariate twin model 2 0 1 6 ) 1 1 Conclusions. A wide range of unfavorable alterations in the serum metabolome was associated with abdominal obesity, insulin resistance and low-grade inflammation. Twin modeling and obesity-discordant twin analysis suggest that these associations are partly explained by shared genes but also reflect mechanisms independent of genetic liability. Genetic correlation Serum metabolites Obesity measures M E T A B O L I S M C L I N I C A L A N D E X P E R I M E N T A L 6 5 (

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Section: 2mentioning

confidence: 99%

Abdominal obesity and circulating metabolites: A twin study approach

et al. 2016

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“…In general, men accumulate excessive fat in the abdominal region, whereas women are more susceptible to the accumulation of fat in the gynoid (gluteofemoral) region. Although increase in gynoid adipose tissue also correlates to CVD risk in obese women (mainly due to the general increase in weight), high storage of fat in the gynoid region relative to total fat is negatively related to CVD risk (Wiklund et al, 2008). Excessive accumulation of fat in the abdominal region has strongly been associated with metabolic alterations such as disturbed plasma lipoprotein profiles, hyperinsulinaemia, insulin resistance, and glucose intolerance (Lemieux et al, 1994).…”

Section: Introductionmentioning

confidence: 99%

Gender-Dependent Associations of Metabolite Profiles and Body Fat Distribution in a Healthy Population with Central Obesity: Towards Metabolomics Diagnostics

Szymańska

Bouwman

Strassburg

et al. 2012

OMICS: A Journal of Integrative Biology

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Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics Szymanska, E.; Bouwman, J.; Strassburg, K.; Vervoort, J.; Kangas, A.J.; Soininen, P.; AlaKorpela, M.; Westerhuis, J.A.; van Duynhoven, J.P.M.; Mela, D.J.; Macdonald, I.A.; Vreeken, R.J.; Smilde, A.K.; Jacobs, D.M. Published in: Omics DOI:10.1089/omi.2012.0062 Link to publication Citation for published version (APA):Szymaska, E., Bouwman, J., Strassburg, K., Vervoort, J., Kangas, A. J., Soininen, P., ... Jacobs, D. M. (2012). Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics. Omics, 16(12), 652-667. DOI: 10.1089/omi.2012.0062 General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. AbstractObesity is a risk factor for cardiovascular diseases and type 2 diabetes especially when the fat is accumulated to central depots. Novel biomarkers are crucial to develop diagnostics for obesity and related metabolic disorders. We evaluated the associations between metabolite profiles (136 lipid components, 12 lipoprotein subclasses, 17 low-molecular-weight metabolites, 12 clinical markers) and 28 phenotype parameters (including different body fat distribution parameters such as android (A), gynoid (G), abdominal visceral (VAT), subcutaneous (SAT) fat) in 215 plasma/serum samples from healthy overweight men (n = 32) and women (n = 83) with central obesity.(Partial) correlation analysis and partial least squares (PLS) regression analysis showed that only specific metabolites were associated to A:G ratio, VAT, and SAT, respectively. These association patterns were gender dependent. For example, insulin, cholesterol, VLDL, and certain triacylglycerols (TG 54:1-3) correlated to VAT in women, while in men VAT was associated with TG 50:1-5, TG 55:1, phosphatidylcholine (PC 32:0), and VLDL ((X)L). Moreover, multiple regression analysis revealed that waist circumference and total fat were sufficient to predict VAT and SAT in women. In contrast, only VAT but not SAT could be predicted in men and only when plasma metabolites were included, with PC 32:0 being most strongly associated with VAT. These findings collectively highlight the p...

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“…33 Also, abdominal fat mass has been found to be associated with traditional CVD risk factors, such as IGT, hypertriglyceridemia and hypertension. 15 This association may at least partially explain the observed association between abdominal fat mass and stroke incidence. In the present study, this hypothesis is supported by the fact that after adjustment for hypertension and diabetes, the associations between all estimates and fatness and stroke disappeared.…”

Section: Discussionmentioning

confidence: 98%

“…All lateral soft tissue was included. 15 The scaling option was used and set to 200 to maximize precision. Two investigators performed all of the analyses (FT and PW).…”

Section: Measurements Of Fat Massmentioning

confidence: 99%

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Abdominal and gynoid adiposity and the risk of stroke

et al. 2011

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Background: Previous studies have indicated that fat distribution is important in the development of cardiovascular disease (CVD). We investigated the association between fat distribution, as measured by dual energy X-ray absorptiometry (DXA), and the incidence of stroke. Methods: A cohort of 2751 men and women aged X40 years was recruited. Baseline levels of abdominal, gynoid and total body fat were measured by DXA. Body mass index (BMI, kg m À2 ) was calculated. Stroke incidence was recorded using the regional stroke registry until subjects reached 75 years of age. Results: During a mean follow-up time of 8 years and 9 months, 91 strokes occurred. Of the adiposity indices accessed abdominal fat mass was the best predictor of stroke in women (hazard ratio (HR) ¼ 1.66, 95% confidence interval (CI) ¼ 1.23-2.24 per standard deviation increase), whereas the ratio of gynoid fat to total fat mass was associated with a decreased risk of stroke (HR ¼ 0.72, 95% CI ¼ 0.54-0.96). Abdominal fat mass was the only of the adiposity indices assessed that was found to be a significant predictor of stroke in men (HR ¼ 1.49, 95% CI ¼ 1.06-2.09). The associations between abdominal fat mass and stroke remained significant in both women and men after adjustment for BMI (HR ¼ 1.80, 95% CI ¼ 1.06-3.07; HR ¼ 1.71, 95% CI ¼ 1.13-2.59, respectively). However, in a subgroup analyses abdominal fat was not a significant predictor after further adjustment for diabetes, smoking and hypertension. Conclusion: Abdominal fat mass is a risk factor for stroke independent of BMI, but not independent of diabetes, smoking and hypertension. This indicates that the excess in stroke risk associated with abdominal fat mass is at least partially mediated through traditional stroke risk factors.

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Abdominal and Gynoid Fat Mass Are Associated with Cardiovascular Risk Factors in Men and Women

Abstract: Abdominal fat mass is strongly independently associated with CVD risk factors in the present study. In contrast, gynoid fat mass was positively associated, whereas the ratio of gynoid to total fat mass was negatively associated with risk factors for CVD.

Cited by 181 publications

References 25 publications

Abdominal obesity and circulating metabolites: A twin study approach

Abdominal obesity and circulating metabolites: A twin study approach

Gender-Dependent Associations of Metabolite Profiles and Body Fat Distribution in a Healthy Population with Central Obesity: Towards Metabolomics Diagnostics

Abdominal and gynoid adiposity and the risk of stroke

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