Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women

Hemi Luan; Nan Meng; Ping Liu; Jin Fu; Xiaomin Chen; Weiqiao Rao; Hui Jiang; Xun Xu; Zongwei CAI; Jun Wang

doi:10.1186/s13742-015-0054-9

Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women

Hemi Luan, Nan Meng, Ping Liu, Jin Fu, Xiaomin Chen, Weiqiao Rao, Hui Jiang, Xun Xu, Zongwei CAI^*, Jun Wang

^*Corresponding author for this work

Department of Chemistry

Research output: Contribution to journal › Journal article › peer-review

19 Citations (Scopus)

Abstract

Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

Original language	English
Article number	16
Journal	GigaScience
Volume	4
Issue number	1
DOIs	https://doi.org/10.1186/s13742-015-0054-9
Publication status	Published - 9 Apr 2015

Scopus Subject Areas

Computer Science Applications
Health Informatics

User-Defined Keywords

Lipidomics
Maternal plasma
Metabolic phenotype
Metabolomics
Pregnancy

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10.1186/s13742-015-0054-9

Cite this

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title = "Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women",

abstract = "Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.",

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AU - Luan, Hemi

AU - Meng, Nan

AU - Liu, Ping

AU - Fu, Jin

AU - Chen, Xiaomin

AU - Rao, Weiqiao

AU - Jiang, Hui

AU - Xu, Xun

AU - CAI, Zongwei

AU - Wang, Jun

PY - 2015/4/9

Y1 - 2015/4/9

N2 - Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

AB - Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

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KW - Maternal plasma

KW - Metabolic phenotype

KW - Metabolomics

KW - Pregnancy

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Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women

Abstract

Scopus Subject Areas

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