Metabolomic Biomarkers for Obesity in Humans: A Short Review

Rauschert, Sebastian; Uhl, Olaf; Koletzko, Berthold; Hellmuth, Christian

doi:10.1159/000365040

Cited by 109 publications

(101 citation statements)

References 46 publications

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“…6,47 Although the usual relation of AA to obesity or insulin resistance is not seen in the present 302 study, these results are in agreement with stable levels of these AA observed across pregnancy trimesters 303 despite the normal gestation-induced progressive insulin resistance. 18 A possible explanation is placental 304 uptake of AA and transfer to the fetus for protein synthesis, 48 particularly in the case of BCAA which are 305 used for placental nitrogen supply.…”

supporting

confidence: 82%

“…6 However, significant alterations in maternal metabolism 69 occur during pregnancy and even between pregnancy trimesters, 7 making comparisons to the non-70 pregnant state difficult or invalid. While the impact of maternal obesity on adverse pregnancy and 71 offspring outcomes is well documented, a more in depth study of the maternal metabolome may highlight 72 biomarkers of gestational metabolic disturbances and potential causal pathways for fetal programming of 73 adult disease risks.…”

Section: Introduction 57mentioning

confidence: 99%

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Association of maternal prepregnancy BMI with metabolomic profile across gestation

et al. 2016

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supporting

confidence: 82%

Section: Introduction 57mentioning

confidence: 99%

Association of maternal prepregnancy BMI with metabolomic profile across gestation

et al. 2016

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“…Thus, there is great need for reliable and convenient measures of compliance in nutrition research. Newly developed methods for determination of multiple serum metabolites, termed metabolomics, offer promise in this regard (7)(8)(9)(10)(11).…”

Section: Introductionmentioning

confidence: 99%

Metabolomic profiles as reliable biomarkers of dietary composition

Esko¹,

Hirschhorn

Feldman

et al. 2017

The American Journal of Clinical Nutrition

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Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Design: Twenty-one adults with a high body mass index (in kg/m 2 ; mean 6 SD: 34.4 6 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Results: Of 333 metabolites, we identified 152 whose concentrations differed for $1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (.95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.Am J Clin Nutr 2017;105:547-54.

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“…BCAA, non-esterified fatty acids, organic acids, acylcarnitines and phospholipids were identified as potential biomarkers for obesity in a recent review [29]. This indicates a relation of elevated BCAA by HP diet to the obese state [21,23].…”

Section: One Step Further -The Link To Early Weight Gain and Obesity mentioning

confidence: 99%