Details zur Publikation

Referenztyp Zeitschriften
DOI / URL Link
Titel (primär) An individual participant data meta-analysis on metabolomics profiles for obesity and insulin resistance in European children
Autor 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.;
Journal / Serie Scientific Reports
Erscheinungsjahr 2019
Department IMMU;
Band/Volume 9
Sprache englisch;
POF III (gesamt) F11;
Supplements https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-019-41449-x/MediaObjects/41598_2019_41449_MOESM1_ESM.pdf
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.
ID 21750
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=21750
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. (2019):
An individual participant data meta-analysis on metabolomics profiles for obesity and insulin resistance in European children
Sci. Rep. 9 , art. 5053