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Associations of anthropometric markers with serum metabolites using a targeted metabolomics approach: results of the EPIC-potsdam study

BACKGROUND/OBJECTIVES: The metabolic consequences of type of body shape need further exploration. Whereas accumulation of body mass in the abdominal area is a well-established metabolic risk factor, accumulation in the gluteofemoral area is controversially debated. We evaluated the associations of a...

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Detalles Bibliográficos
Autores principales: Bachlechner, U, Floegel, A, Steffen, A, Prehn, C, Adamski, J, Pischon, T, Boeing, H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4931315/
https://www.ncbi.nlm.nih.gov/pubmed/27348203
http://dx.doi.org/10.1038/nutd.2016.23
Descripción
Sumario:BACKGROUND/OBJECTIVES: The metabolic consequences of type of body shape need further exploration. Whereas accumulation of body mass in the abdominal area is a well-established metabolic risk factor, accumulation in the gluteofemoral area is controversially debated. We evaluated the associations of anthropometric markers of overall body mass and body shape with 127 serum metabolites within a sub-sample of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. SUBJECTS/METHODS: The cross-sectional analysis was conducted in 2270 participants, randomly drawn from the EPIC-Potsdam cohort. Metabolites were measured by targeted metabolomics. To select metabolites related with both waist circumference (WC) (abdominal subcutaneous and visceral fat) and hip circumference (HC) (gluteofemoral fat, muscles and bone structure) correlations (r) with body mass index (BMI) as aggregating marker of body mass (lean and fat mass) were calculated. Relations with body shape were assessed by median metabolite concentrations across tertiles of WC and HC, mutually adjusted to each other. RESULTS: Correlations revealed 23 metabolites related to BMI (r⩾I0.20 I). Metabolites showing relations with BMI were showing similar relations with HC adjusted WC (WC(HC)). In contrast, relations with WC adjusted HC (HC(WC)) were less concordant with relations of BMI and WC(HC). In both sexes, metabolites with concordant relations regarding WC(HC) and HC(WC) included tyrosine, diacyl-phosphatidylcholine C38:3, C38:4, lyso-phosphatidylcholine C18:1, C18:2 and sphingomyelin C18:1; metabolites with opposite relations included isoleucine, diacyl-phosphatidylcholine C42:0, acyl–alkyl-phosphatidylcholine C34:3, C42:4, C42:5, C44:4 and C44:6. Metabolites specifically related to HC(WC) included acyl–alkyl-phosphatidylcholine C34:2, C36:2, C38:2 and C40:4, and were solely observed in men. Other metabolites were related to WC(HC) only. CONCLUSIONS: The study revealed specific metabolic profiles for HC(WC) as marker of gluteofemoral body mass differing from those for BMI and WC(HC) as markers of overall body mass and abdominal fat, respectively. Thus, the study suggests that gluteofemoral mass may have less-adverse metabolic implications than abdominal fat.