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Maternal Plasma Metabolomic Profiles in Spontaneous Preterm Birth: Preliminary Results
B. Lizewska, J. Teul, P. Kuc, A. Lemancewicz, K. Charkiewicz, J. Goscik, M. Kacerovsky, R. Menon, W. Miltyk, P. Laudanski,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 1992
Free Medical Journals
od 1992
PubMed Central
od 1992
Europe PubMed Central
od 1992
ProQuest Central
od 2014-01-01
Open Access Digital Library
od 1992-01-01
Open Access Digital Library
od 1992-01-01
Open Access Digital Library
od 1992-01-01
Medline Complete (EBSCOhost)
od 1997-02-01
Health & Medicine (ProQuest)
od 2014-01-01
Wiley-Blackwell Open Access Titles
od 1992
ROAD: Directory of Open Access Scholarly Resources
od 1992
PubMed
29670470
DOI
10.1155/2018/9362820
Knihovny.cz E-zdroje
- MeSH
- dospělí MeSH
- gestační stáří MeSH
- lidé MeSH
- mladý dospělý MeSH
- multivariační analýza MeSH
- předčasná porodní činnost krev MeSH
- předčasný porod krev MeSH
- retrospektivní studie MeSH
- studie případů a kontrol MeSH
- těhotenství MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- těhotenství MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Objective: To profile maternal plasma metabolome in spontaneous preterm birth. Method: In this retrospective case-control study, we have examined plasma of patient with preterm birth (between 22 and 36 weeks of pregnancy (n = 57)), with threatened preterm labor (between 23 and 36 weeks of pregnancy (n = 49)), and with term delivery (n = 25). Plasma samples were analysed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) in positive and negative polarity modes. Results: We found 168 differentially expressed metabolites that were significantly distinct between study groups. We determined 51 metabolites using publicly available databases that could be subdivided into one of the five groups: amino acids, fatty acids, lipids, hormones, and bile acids. PLS-DA models, verified by SVM classification accuracy, differentiated preterm birth and term delivery groups. Conclusions: Maternal plasma metabolites are different between term and preterm parturitions. Part of them may be related with preterm labor, while others may be affected by gestational age or the beginning of labor. Metabolite profile can classify preterm or term delivery groups raising the potential of metabolome as a biomarker to identify high-risk pregnancies. Metabolomic studies are also a tool to detect individual compounds that may be further tested in targeted researches.
Department of Perinatology Medical University of Bialystok Bialystok Poland
Department of Pharmaceutical Analysis Medical University of Bialystok Bialystok Poland
Faculty of Computer Science Bialystok University of Technology Bialystok Poland
Citace poskytuje Crossref.org
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- $a Objective: To profile maternal plasma metabolome in spontaneous preterm birth. Method: In this retrospective case-control study, we have examined plasma of patient with preterm birth (between 22 and 36 weeks of pregnancy (n = 57)), with threatened preterm labor (between 23 and 36 weeks of pregnancy (n = 49)), and with term delivery (n = 25). Plasma samples were analysed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) in positive and negative polarity modes. Results: We found 168 differentially expressed metabolites that were significantly distinct between study groups. We determined 51 metabolites using publicly available databases that could be subdivided into one of the five groups: amino acids, fatty acids, lipids, hormones, and bile acids. PLS-DA models, verified by SVM classification accuracy, differentiated preterm birth and term delivery groups. Conclusions: Maternal plasma metabolites are different between term and preterm parturitions. Part of them may be related with preterm labor, while others may be affected by gestational age or the beginning of labor. Metabolite profile can classify preterm or term delivery groups raising the potential of metabolome as a biomarker to identify high-risk pregnancies. Metabolomic studies are also a tool to detect individual compounds that may be further tested in targeted researches.
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