2018
DOI: 10.1101/371815
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Identification of salivary and plasma biomarkers for obesity in children by non-targeted metabolomic analysis

Abstract: Chemical compounds in the saliva most likely to be associated with obesity are identified in a metabolomic analysis of paired whole saliva and plasma samples from 68 children (10-year old) who have also been evaluated for their gingival redness.Results: Through metabolomic analysis119 compounds were found only in saliva, 210 only in plasma and 126 in both. The most common plasma metabolites were lipids. The most common saliva metabolites were peptides. Amino acids and their metabolites were common in both samp… Show more

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Cited by 3 publications
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“…Identification of diaminoheptanedioate, a molecule in the cell wall of Gram-negative bacteria, as a discriminant metabolite found in the metavariable PlasmaLD2 suggested that obesity and its associated metabolic disorders are correlated to a high LPS level. Furthermore, hydroxyproline, a possible stress marker but also an obesity marker [59], was also a discriminant metabolite in our metavariable PlasmaLD2, while our metavariable GenusD1 including Escherichia-Shigella was positively correlated with blood haptoglobin, another inflammatory marker. These findings support the recent results obtained by Jergens et al (2019;[10]) using both type 2 diabetes mellitus dogs and healthy dogs.…”
Section: Discussionmentioning
confidence: 64%
“…Identification of diaminoheptanedioate, a molecule in the cell wall of Gram-negative bacteria, as a discriminant metabolite found in the metavariable PlasmaLD2 suggested that obesity and its associated metabolic disorders are correlated to a high LPS level. Furthermore, hydroxyproline, a possible stress marker but also an obesity marker [59], was also a discriminant metabolite in our metavariable PlasmaLD2, while our metavariable GenusD1 including Escherichia-Shigella was positively correlated with blood haptoglobin, another inflammatory marker. These findings support the recent results obtained by Jergens et al (2019;[10]) using both type 2 diabetes mellitus dogs and healthy dogs.…”
Section: Discussionmentioning
confidence: 64%