Summary of Study ST001430

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000918. The data can be accessed directly via it's Project DOI: 10.21228/M81H58 This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001430
Study TitleMetabolic dynamics and prediction og gestational ange and time to delivery in pregant women
Study SummaryMetabolism during pregnancy is a constantly changing yet precisely programmed process, the failure of which may have devastating consequences for the fetus. To capture in high resolution the sequence of metabolic events underlying the normal human pregnancy, we carried out an untargeted metabolome investigation on 784 weekly blood samples collected from 30 Danish pregnant women. The study revealed extensive metabolome alterations over the course of normal pregnancy: of 9,651 detected metabolic features, 4,995 were significantly changed (FDR < 0.05). Many metabolic changes were timed precisely according to pregnancy progression so that the overall metabolic profile demonstrated a highly choreographed pattern. Using machine-learning methods, we were able to build a linear models with five metabolites (four steroids and one phospholipid) that predicts gestational age with high accuracy (Pearson correlation coefficient, R = 0.95).
Institute
Stanford University
LaboratorySnyder lab
Last NameLiang
First NameLiang
AddressAlway M339, 300 Pasteur Drive, Palo Alto, California, 94305, USA
Emailliangtro@stanford.edu
Phone+1 8167852490
Submit Date2019-08-30
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailLC-MS
Release Date2020-07-24
Release Version1
Liang Liang Liang Liang
https://dx.doi.org/10.21228/M81H58
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR000918
Project DOI:doi: 10.21228/M81H58
Project Title:Metabolic dynamics and prediction of gestational age and time to delivery in pregnant women
Project Summary:Metabolism during pregnancy is a constantly changing yet precisely programmed process, the failure of which may have devastating consequences for the fetus. To capture in high resolution the sequence of metabolic events underlying the normal human pregnancy, we carried out an untargeted metabolome investigation on 784 weekly blood samples (3 outlier samples are removed) collected from 30 Danish pregnant women. The study revealed extensive metabolome alterations over the course of normal pregnancy: of 9,651 detected metabolic features, 4,995 were significantly changed (FDR < 0.05). Many metabolic changes were timed precisely according to pregnancy progression so that the overall metabolic profile demonstrated a highly choreographed pattern. Using machine-learning methods, we were able to build a linear models with five metabolites (four steroids and one phospholipid) that predicts gestational age with high accuracy (Pearson correlation coefficient, R = 0.95).
Institute:Stanford University
Last Name:Liang
First Name:Liang
Address:Alway M339, 300 Pasteur Drive, Palo Alto, California, 94305, USA
Email:liangtro@stanford.edu
Phone:8167852490
Publications:https://doi.org/10.1016/j.cell.2020.05.002

Subject:

Subject ID:SU001504
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Female
Species Group:Mammals

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Gestational age Range
SA120934635>20
SA120935235>20
SA120936147>20
SA120937166>20
SA120938551>20
SA120939173>20
SA120940255>20
SA12094116>20
SA120942644>20
SA120943215>20
SA120944313>20
SA120945209>20
SA12094642>20
SA120947460>20
SA1209481>20
SA120949394>20
SA120950699>20
SA120951225>20
SA12095223>20
SA12095389>20
SA120954420>20
SA120955256>20
SA12095695>20
SA120957485>20
SA120958740>20
SA120959662>20
SA120960643>20
SA120961743>20
SA12096238>20
SA120963248>20
SA120964788>20
SA120965590>20
SA120966609>20
SA120967619>20
SA12096878>20
SA120969167>20
SA120970728>20
SA120971597>20
SA120972473>20
SA120973130>20
SA120974732>20
SA120975278>20
SA120976368>20
SA12097788>20
SA120978132>20
SA12097920>20
SA12098019>20
SA120981655>20
SA12098236>20
SA120983238>20
SA120984123>20
SA12098534>20
SA120986247>20
SA120987717>20
SA120988752>20
SA120989742>20
SA120990486>20
SA120991312>20
SA120992385>20
SA120993335>20
SA120994283>20
SA120995631>20
SA120996570>20
SA12099749>20
SA120998588>20
SA120999554>20
SA121000322>20
SA121001310>20
SA121002469>20
SA121003304>20
SA121004766>20
SA121005663>20
SA121006555>20
SA121007471>20
SA121008457>20
SA121009287>20
SA121010746>20
SA121011521>20
SA121012776>20
SA121013390>20
SA121014279>20
SA121015793>20
SA121016496>20
SA121017458>20
SA121018376>20
SA121019715>20
SA121020432>20
SA121021526>20
SA121022673>20
SA121023375>20
SA121024580>20
SA121025523>20
SA121026726>20
SA121027545>20
SA121028488>20
SA121029510>24
SA121030628>24
SA121031585>24
SA121032149>24
SA121033155>24
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Collection:

Collection ID:CO001499
Collection Summary:To capture the highly dynamic pregnancy process, we established a multi-year single-center Danish normal pregnancy cohort with a unique design of high-density blood sampling. Consented female participants submitted weekly blood draws beginning in week 5 of pregnancy until the postpartum period. A total of 30 women with weekly blood samples were assigned to a discovery (N=21) and a validation (Validation-1, N=9) cohort , whose samples were analyzed in two separated years.
Sample Type:Blood (plasma)
Storage Conditions:-80℃

Treatment:

Treatment ID:TR001519
Treatment Summary:No treatment.

Sample Preparation:

Sampleprep ID:SP001512
Sampleprep Summary:784 normal pregnancy samples (3 outlier samples were removed) were completely randomized within each cohort (Discovery and Validation - 1) and analyzed in 12 batches across two years. 200 μL plasma was extracted by mixing 800 μL 1:1:1 acetone: acetonitrile: methanol with the internal standard mixture. The extraction mixture was vortexed and mixed for 15 min at 4 C and incubated at -20 C for 2 hours to allow protein precipitation. The supernatant was collected after centrifugation and evaporated to dryness under nitrogen (Biotage Turbovap). The dry extracts were reconstituted with 200 μL 1:1 methanol: water before analysis.

Chromatography:

Chromatography ID:CH001758
Chromatography Summary:Chromatographic conditions RPLC separation was performed using Zorbax SB columns (2.1 X 50mm, 1.8 Micron, 600 Bar; 827700-914) purchased from Agilent Technologies (Santa Clara, CA, USA). Mobile phases for RPLC consisted of 0.06% acetic acid in water (phase A) and 0.06% acetic acid in MeOH (phase B). Metabolites were eluted from the column at a flow rate of 0.6 mL/min, leading to a backpressure of 220– 280 bar at 99% phase A. A linear 1%–80% phase B gradient was applied over 9–10 min. The oven temperature was set to 60C, and the sample injection volume was 5 mL.
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:Agilent Zorbax Eclipse Plus C18 (100 x 2.1mm, 1.8 um)
Chromatography Type:Reversed phase

Analysis:

Analysis ID:AN002391
Analysis Type:MS
Chromatography ID:CH001758
Num Factors:6
Has Mz:1
Has Rt:1
Rt Units:Minutes
Results File:ST001430_AN002391_Results.txt
Units:peak area
  
Analysis ID:AN002392
Analysis Type:MS
Chromatography ID:CH001758
Num Factors:6
Has Mz:1
Has Rt:1
Rt Units:Minutes
Results File:ST001430_AN002392_Results.txt
Units:peak area
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