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Blood Metabolic Signatures of Body Mass Index: A Targeted Metabolomics Study in the EPIC Cohort.

Marion CarayolMichael F LeitzmannPietro FerrariRaul Zamora-RosDavid AchaintreMagdalena StepienJulie A SchmidtRuth C TravisKim OvervadAnne TjønnelandLouise HansenRudolf KaaksTilman KühnHeiner BoeingUrsula BachlechnerAntonia TrichopoulouChristina BamiaDomenico PalliClaudia AgnoliRosario TuminoPaolo VineisSalvatore PanicoJ Ramón QuirósEmilio Sánchez-CantalejoJosé María HuertaEva ArdanazLarraitz ArriolaAntonio AgudoJan NilssonOlle MelanderBas Bueno-de-MesquitaPetra H PeetersNick WarehamKay-Tee KhawMazda JenabTimothy J KeyAugustin ScalbertSabina Rinaldi
Published in: Journal of proteome research (2017)
Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases.
Keyphrases
  • body mass index
  • weight gain
  • ms ms
  • physical activity
  • metabolic syndrome
  • risk factors
  • type diabetes
  • weight loss
  • healthcare
  • cardiovascular disease
  • adipose tissue
  • risk assessment
  • genome wide
  • young adults