Metabolic Biomarkers of Monochorionic Twins Complicated With Selective Intrauterine Growth Restriction in Cord Plasma and Placental Tissue

aut.relation.issue1en_NZ
aut.relation.journalScientific Reportsen_NZ
aut.relation.volume8en_NZ
aut.researcherYoung, Timothy
dc.contributor.authorWang, Len_NZ
dc.contributor.authorHan, TLen_NZ
dc.contributor.authorLuo, Xen_NZ
dc.contributor.authorLi, Sen_NZ
dc.contributor.authorYoung, Ten_NZ
dc.contributor.authorChen, Cen_NZ
dc.contributor.authorWen, Len_NZ
dc.contributor.authorXu, Pen_NZ
dc.contributor.authorZheng, Yen_NZ
dc.contributor.authorSaffery, Ren_NZ
dc.contributor.authorBaker, PNen_NZ
dc.contributor.authorTong, Cen_NZ
dc.contributor.authorQi, Hen_NZ
dc.date.accessioned2019-04-30T02:36:12Z
dc.date.available2019-04-30T02:36:12Z
dc.date.copyright2018-12-01en_NZ
dc.date.issued2018-12-01en_NZ
dc.description.abstractThe selective intrauterine growth restriction (sIUGR) of monochorionic diamniotic (MCDC) twins causes phenotypic growth discordance, which is correlated with metabolomic pertubations. A global, untargeted identification of the metabolic fingerprint may help elucidate the etiology of sIUGR. Umbilical cord blood and placentas collected from 15 pairs of sIUGR monochorionic twins, 24 pairs of uncomplicated twins, and 14 singletons diagnosed with intrauterine growth restriction (IUGR) were subjected to gas chromatography-mass spectrometry based metabolomic analyses. Supervised multivariate regression analysis and pathway analysis were performed to compare control twins with sIUGR twins. A generalized estimating equation (GEE) model was utilized to explore metabolic differences within sIUGR co-twins. Linear logistic regression was applied to screen metabolites that significantly differed in concentration between control twins and sIUGR twins or IUGR singletons. Umbilical cord blood demonstrated better global metabolomic separation of sIUGR and control twins compared to the placenta. Disrupted amino acid and fatty acid metabolism as well as high levels of exposure to environmental xenobiotics were associated with sIUGR. The metabolic abnormalities in MCDA twins suggested that in utero growth discordance is caused by intrauterine and extrauterine environmental factors, rather than genetics. Thus, this study provides new therapeutic targets and strategies for sIUGR management and prevention.en_NZ
dc.identifier.citationScientific Reports, Volume 8, Article number: 15914 (2018)
dc.identifier.doi10.1038/s41598-018-33788-yen_NZ
dc.identifier.issn2045-2322en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/12475
dc.publisherSpringer Nature
dc.relation.urihttps://www.nature.com/articles/s41598-018-33788-y
dc.rights© The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre-ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per-mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.accessrightsOpenAccessen_NZ
dc.titleMetabolic Biomarkers of Monochorionic Twins Complicated With Selective Intrauterine Growth Restriction in Cord Plasma and Placental Tissueen_NZ
dc.typeJournal Article
pubs.elements-id348609
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Health & Environmental Science
pubs.organisational-data/AUT/Health & Environmental Science/Applied Science
pubs.organisational-data/AUT/Health & Environmental Science/School of Science
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Health and Environmental Sciences
pubs.organisational-data/AUT/PBRF/PBRF Health and Environmental Sciences/HA Science 2018 PBRF
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