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Influence of Biological and Technical Covariates on Non-targeted Metabolite Profiling in a Large-scale Epidemiological Study

Kumar, Jitender (author)
Broeckling, Corey D. (author)
Wiklund, Fredrik (author)
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Ingelsson, Erik (author)
Uppsala universitet,Science for Life Laboratory, SciLifeLab,Molekylär epidemiologi
Prenni, Jessica E. (author)
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 (creator_code:org_t)
2013
2013
English.
In: Current Metabolomics. - 2213-235X. ; 1:3, s. 220-226-
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Non-targeted metabolite profiling using ultra performance liquid chromatography-mass spectrometry (UPLCMS) was performed as part of a large-scale epidemiological study involving biobanked serum samples. The influence of both biological (age and body mass index) and technical (season of sample collection, fasting time, handling time, and storage time) covariates on the analysis was assessed. Statistical models including different sets of these covariates were compared and the results illustrate that variation in which covariates were included did not have an appreciable effect on the number or composition of biologically significant metabolite features associated with body mass index or age. Furthermore, when all covariates were included in the model, there was little overlap of metabolite features significantly associated with the different covariates. Thus, the results of this study illustrate that while some of the observed quantitative variance of metabolite features can be explained by biological and technical covariates, the use of non-targeted metabolite profiling of serum by UPLC-MS is valid for studies of biological outcomes in biobanked clinical samples from large-scale studies. - See more at: http://www.eurekaselect.com/115259/article#sthash.BOvtwWe7.dpuf

Keyword

Biobanked clinical samples
biomarker discovery
covariates
Non-targeted metabolomics
statistical models
ultra performance liquid chromatography-mass spectrometry

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