Mountain View
biomedical and healthCAre Data Discovery Index Ecosystem
help Advanced Search
Title: Nontargeted metabolomics and lipidomics HPLC-MS data from maternal plasma of 180 healthy pregnant women.      
dateReleased:
02-18-2015
privacy:
not applicable
aggregation:
instance of dataset
dateCreated:
02-18-2015
refinement:
curated
ID:
doi:10.5524/100108
creators:
Luan, H
Meng, N
Liu, P
Feng, Q
Lin, S
Fu, J
Chen, X
Rao, W
Chen, F
Jiang, H
Xu, X
Cai, Z
Wang, J
availability:
available
types:
sequence
description:
Metabolic variations occur during normal pregnancy to provide the growing fetus with a supply of nutrients required for its development and to ensure the health of the woman during gestation. Mass spectrometry-based metabolomics was employed to study the metabolic phenotype variations in the maternal plasma that are induced by pregnancy in each of its three trimesters. Here we provide the LC-MS data from 180 healthy pregnant women, each individual was followed up to term to make sure that women had normal term pregnancy and healthy babies. All volunteers gave written consent and filled out individual questionnaire at the time of sample collection. The samples were divided into six sub-groups according to the gestational week of their pregnancy at the time of sampling, T1 (n= 30, 9-12 weeks), T2 (n=30, 13-16 weeks), T3 (n=30, 17-20 weeks), T4 (n=30, 21-24 weeks), T5 (n=30, 25-28 weeks), and T6 (n=30, 29-40 weeks). Body mass index (BMI), age, and gestational week were recorded for each individual. The repository contains data in 3 modalities: positive and negative ion 'global' non-targeted LC-MS and shotgun lipidomics (including carnitine profiling) LC-MS.
accessURL: https://doi.org/10.5524/100108
storedIn:
GigaScience Database
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
GigaDB
homePage: http://gigadb.org/
ID:
SCR:006565
name:
Giga Science Database

Feedback?

If you are having problems using our tools, or if you would just like to send us some feedback, please post your questions on GitHub.