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Hellmuth, C.* ; Kirchberg, F.F.* ; Brandt, S.* ; Moß, A.* ; Walter, V.* ; Rothenbacher, D.* ; Brenner, H.* ; 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.*

An individual participant data meta-analysis on metabolomics profiles for obesity and insulin resistance in European children.

Sci. Rep. 9:5053 (2019)

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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 x 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 x 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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