Assessing individual metabolic responsiveness to a lipid challenge using a targeted metabolomic approach View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-06

AUTHORS

Angela M. Zivkovic, Michelle M. Wiest, UyenThao Nguyen, Malin L. Nording, Steven M. Watkins, J. Bruce German

ABSTRACT

The development of assessment techniques with immediate clinical applicability is a priority for resolving the growing epidemic in metabolic disease. Many imbalances in diet-dependent metabolism are not detectable in the fasted state. Resolving the high inter-individual variability in response to diet requires the development of techniques that can detect metabolic dysfunction at the level of the individual. The intra- and inter-individual variation in lipid metabolism in response to a standardized test meal was determined. Following an overnight fast on three different days, three healthy subjects consumed a test meal containing 40% of their daily calories. Plasma samples were collected at fasting, and 1, 3, 6, and 8 h after the test meal. Plasma fatty acid (FA) concentrations within separated lipid classes and lipoprotein fractions were measured at each time point. The intra-individual variation within each subject across three days was lower than the inter-individual differences among the three subjects for over 50% of metabolites in the triacylglycerol (TG), FA, and phosphatidylcholine (PC) lipid classes at 6 h, and for 25-50% of metabolites across lipid classes at 0, 1, 3, and 8 h. The consistency of response within individuals was visualized by principal component analysis (PCA) and confirmed by ANOVA. Three representative metabolites that discriminated among the three individuals in the apolipoprotein B (ApoB) fraction, TG16:1n7, TG18:2n6, and PC18:3n3, are discussed in detail. The postprandial responses of individuals were unique within metabolites that were individual discriminators (ID) of metabolic phenotype. This study shows that the targeted metabolomic measurement of individual metabolic phenotype in response to a specially formulated lipid challenge is possible even without lead-in periods, dietary and lifestyle control, or intervention over a 3-month period in healthy free-living individuals. More... »

PAGES

209

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11306-008-0136-0

DOI

http://dx.doi.org/10.1007/s11306-008-0136-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008981532

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20442800


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11306-008-0136-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11306-008-0136-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11306-008-0136-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11306-008-0136-0'


 

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