Gas chromatographic profiles of plasma total lipids as indicators of dietary history

Kuksis, A.; Myher, J. J.; Geher, K.; Breckenridge, W. C.; Feather, T.; McGuire, Valerie; Little, J. A.

doi:10.1016/0378-4347(92)80358-w

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…In addition, the total level of triacylglycerols and the level of a specific triacylglycerol, TG(48:4), were negatively impacting on weight loss success. High levels of TGs in the bloodstream can be caused by an higher intake of fat or a lower fat turnover. Furthermore, phosphatidylcholines PC(O‐34:1) and PC(O‐44:5) and sphingomyelin (d18:1/16:1) also contributed positively to weight loss success.…”

Section: Discussionmentioning

confidence: 99%

Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study

Stroeve

Saccenti

Bouwman

et al. 2016

Obesity

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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 5 236) and women (N 5 431) 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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Section: Discussionmentioning

confidence: 99%