Journal Article

DKFZ-2019-00766

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png An individual participant data meta-analysis on metabolomics profiles for obesity and insulin resistance in European children.

Hellmuth, C. ; Kirchberg, F. F. ; Brandt, S. ; Moß, A. ; Walter, V.DKFZ* ; Rothenbacher, D. ; Brenner, H.DKFZ* ; Grote, V. ; Gruszfeld, D. ; Socha, P. ; Closa-Monasterolo, R. ; Escribano, J. ; Luque, V. ; Verduci, E. ; Mariani, B. ; Langhendries, J.-P. ; Poncelet, P. ; Heinrich, J. ; Lehmann, I. ; Standl, M. ; Uhl, O. ; Koletzko, B. ; Thiering, E. ; Wabitsch, M.

2019
Macmillan Publishers Limited, part of Springer Nature [London]

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Please use a persistent id in citations: doi:10.1038/s41598-019-41449-x

Abstract: Childhood obesity prevalence is rising in countries worldwide. A variety of etiologic factors contribute to childhood obesity but little is known about underlying biochemical mechanisms. We performed an individual participant meta-analysis including 1,020 pre-pubertal children from three European studies and investigated the associations of 285 metabolites measured by LC/MS-MS with BMI z-score, height, weight, HOMA, and lipoprotein concentrations. Seventeen metabolites were significantly associated with BMI z-score. Sphingomyelin (SM) 32:2 showed the strongest association with BMI z-score (P = 4.68 × 10-23) and was also closely related to weight, and less strongly to height and LDL, but not to HOMA. Mass spectrometric analyses identified SM 32:2 as myristic acid containing SM d18:2/14:0. Thirty-five metabolites were significantly associated to HOMA index. Alanine showed the strongest positive association with HOMA (P = 9.77 × 10-16), while acylcarnitines and non-esterified fatty acids were negatively associated with HOMA. SM d18:2/14:0 is a powerful marker for molecular changes in childhood obesity. Tracing back the origin of SM 32:2 to dietary source in combination with genetic predisposition will path the way for early intervention programs. Metabolic profiling might facilitate risk prediction and personalized interventions in overweight children.

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Contributing Institute(s):

1. Klinische Epidemiologie und Alternsforschung (C070)
2. Präventive Onkologie (C120)

Research Program(s):

1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2019

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