Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 498386
Title Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study
Author(s) Stroeve, Johanna H.M.; Saccenti, Edoardo; Bouwman, Jildau; Dane, Adrie; Strassburg, Katrin; Vervoort, Jacques; Hankemeier, Thomas; Astrup, Arne; Smilde, Age K.; Ommen, Ben Van; Saris, Wim H.M.
Source Obesity 24 (2016)2. - ISSN 1930-7381 - p. 379 - 388.
DOI https://doi.org/10.1002/oby.21361
Department(s) Systems and Synthetic Biology
VLAG
Biochemistry
ATV VlagVlag
Publication type Refereed Article in a scientific journal
Publication year 2016
Abstract

Objective Aim is to predict successful weight loss by metabolic signatures at baseline and to identify which differences in metabolic status may underlie variations in weight loss success. Methods In DiOGenes, a randomized, controlled trial, weight loss was induced using a low-calorie diet (800 kcal) for 8 weeks. Men (N = 236) and women (N = 431) as well as groups with overweight/obesity and morbid obesity were studied separately. The relation between the metabolic status before weight loss and weight loss was assessed by stepwise regression on multiple data sets, including anthropometric parameters, NMR-based plasma metabolites, and LC-MS-based plasma lipid species. Results Maximally, 57% of the variation in weight loss success can be predicted by baseline parameters. The most powerful predictive models were obtained in subjects with morbid obesity. In these models, the metabolites most predictive for weight loss were acetoacetate, triacylglycerols, phosphatidylcholines, specific amino acids, and creatine and creatinine. This metabolic profile suggests that high energy metabolism activity results in higher amounts of weight loss. Conclusions Possible predictive (pre-diet) markers were found for amount of weight loss for specific subgroups.

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