Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: Towards metabolomics diagnostics

E. Szymanska, J. Bouwman, K. Strassburg, J.J.M. Vervoort, A.J. Kangas, P. Soininen, M. Ala-Korpela, J.A. Westerhuis, J.P.M. van Duynhoven, D.J. Mela, I.A. Macdonald, R.J. Vreeken, A.K. Smilde, D.M. Jacobs

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Abstract

Abstract Obesity 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 potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders
Original languageEnglish
Pages (from-to)652-667
JournalOMICS - A Journal of Integrative Biology
Volume16
Issue number12
DOIs
Publication statusPublished - 2012

Fingerprint

Body Fat Distribution
Metabolomics
Abdominal Obesity
Metabolites
Obesity
Fats
Biomarkers
Regression analysis
Population
Regression Analysis
Plasmas
VLDL Cholesterol
Subcutaneous Fat
Waist Circumference
Medical problems
Least-Squares Analysis
Phosphatidylcholines
Type 2 Diabetes Mellitus
Lipoproteins
Triglycerides

Keywords

  • lecithin-cholesterol acyltransferase
  • performance liquid-chromatography
  • hormone-sensitive lipase
  • visceral adipose-tissue
  • cardiovascular-disease
  • insulin sensitivity
  • human-plasma
  • risk-factors
  • abdominal adiposity
  • magnetic-resonance

Cite this

Szymanska, E. ; Bouwman, J. ; Strassburg, K. ; Vervoort, J.J.M. ; Kangas, A.J. ; Soininen, P. ; Ala-Korpela, M. ; Westerhuis, J.A. ; van Duynhoven, J.P.M. ; Mela, D.J. ; Macdonald, I.A. ; Vreeken, R.J. ; Smilde, A.K. ; Jacobs, D.M. / Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: Towards metabolomics diagnostics. In: OMICS - A Journal of Integrative Biology. 2012 ; Vol. 16, No. 12. pp. 652-667.
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abstract = "Abstract Obesity 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 potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders",
keywords = "lecithin-cholesterol acyltransferase, performance liquid-chromatography, hormone-sensitive lipase, visceral adipose-tissue, cardiovascular-disease, insulin sensitivity, human-plasma, risk-factors, abdominal adiposity, magnetic-resonance",
author = "E. Szymanska and J. Bouwman and K. Strassburg and J.J.M. Vervoort and A.J. Kangas and P. Soininen and M. Ala-Korpela and J.A. Westerhuis and {van Duynhoven}, J.P.M. and D.J. Mela and I.A. Macdonald and R.J. Vreeken and A.K. Smilde and D.M. Jacobs",
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Szymanska, E, Bouwman, J, Strassburg, K, Vervoort, JJM, Kangas, AJ, Soininen, P, Ala-Korpela, M, Westerhuis, JA, van Duynhoven, JPM, Mela, DJ, Macdonald, IA, Vreeken, RJ, Smilde, AK & Jacobs, DM 2012, 'Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: Towards metabolomics diagnostics', OMICS - A Journal of Integrative Biology, vol. 16, no. 12, pp. 652-667. https://doi.org/10.1089/omi.2012.0062

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.J.M.; Kangas, A.J.; Soininen, P.; Ala-Korpela, M.; Westerhuis, J.A.; van Duynhoven, J.P.M.; Mela, D.J.; Macdonald, I.A.; Vreeken, R.J.; Smilde, A.K.; Jacobs, D.M.

In: OMICS - A Journal of Integrative Biology, Vol. 16, No. 12, 2012, p. 652-667.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: Towards metabolomics diagnostics

AU - Szymanska, E.

AU - Bouwman, J.

AU - Strassburg, K.

AU - Vervoort, J.J.M.

AU - Kangas, A.J.

AU - Soininen, P.

AU - Ala-Korpela, M.

AU - Westerhuis, J.A.

AU - van Duynhoven, J.P.M.

AU - Mela, D.J.

AU - Macdonald, I.A.

AU - Vreeken, R.J.

AU - Smilde, A.K.

AU - Jacobs, D.M.

PY - 2012

Y1 - 2012

N2 - Abstract Obesity 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 potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders

AB - Abstract Obesity 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 potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders

KW - lecithin-cholesterol acyltransferase

KW - performance liquid-chromatography

KW - hormone-sensitive lipase

KW - visceral adipose-tissue

KW - cardiovascular-disease

KW - insulin sensitivity

KW - human-plasma

KW - risk-factors

KW - abdominal adiposity

KW - magnetic-resonance

U2 - 10.1089/omi.2012.0062

DO - 10.1089/omi.2012.0062

M3 - Article

VL - 16

SP - 652

EP - 667

JO - OMICS - A Journal of Integrative Biology

JF - OMICS - A Journal of Integrative Biology

SN - 1536-2310

IS - 12

ER -