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@ARTICLE{Hardikar:157074,
author = {S. Hardikar and R. D. Albrechtsen and D. Achaintre and T.
Lin and S. Pauleck and M. Playdon and A. N. Holowatyj and B.
Gigic and P. Schrotz-King$^*$ and J. Boehm and N. Habermann
and S. Brezina and A. Gsur and E. H. van Roekel and M. P.
Weijenberg and P. Keski-Rahkonen and A. Scalbert and J. Ose
and C. M. Ulrich},
title = {{I}mpact of {P}re-blood {C}ollection {F}actors on {P}lasma
{M}etabolomic {P}rofiles.},
journal = {Metabolites},
volume = {10},
number = {5},
issn = {2218-1989},
address = {Basel},
publisher = {MDPI},
reportid = {DKFZ-2020-01365},
pages = {213},
year = {2020},
abstract = {Demographic, lifestyle and biospecimen-related factors at
the time of blood collection can influence metabolite levels
in epidemiological studies. Identifying the major influences
on metabolite concentrations is critical to designing
appropriate sample collection protocols and considering
covariate adjustment in metabolomics analyses. We examined
the association of age, sex, and other short-term pre-blood
collection factors (time of day, season, fasting duration,
physical activity, NSAID use, smoking and alcohol
consumption in the days prior to collection) with 133
targeted plasma metabolites (acylcarnitines, amino acids,
biogenic amines, sphingolipids, glycerophospholipids, and
hexoses) among 108 individuals that reported exposures
within 48 h before collection. The differences in mean
metabolite concentrations were assessed between groups based
on pre-collection factors using two-sided t-tests and ANOVA
with FDR correction. Percent differences in metabolite
concentrations were negligible across season, time of day of
collection, fasting status or lifestyle behaviors at the
time of collection, including physical activity or the use
of tobacco, alcohol or NSAIDs. The metabolites differed in
concentration between the age and sex categories for
$21.8\%$ and $14.3\%$ metabolites, respectively. In
conclusion, extrinsic factors in the short period prior to
collection were not meaningfully associated with
concentrations of selected endogenous metabolites in a
cross-sectional sample, though metabolite concentrations
differed by age and sex. Larger studies with more coverage
of the human metabolome are warranted.},
cin = {C120},
ddc = {540},
cid = {I:(DE-He78)C120-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32455751},
pmc = {pmc:PMC7281389},
doi = {10.3390/metabo10050213},
url = {https://inrepo02.dkfz.de/record/157074},
}