Summary of Study ST001889

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 PR001190. The data can be accessed directly via it's Project DOI: 10.21228/M8WD84 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 IDST001889
Study TitleMultiomics Longitudinal Modeling of Preeclamptic Pregnancies (part I)
Study SummaryPreeclampsia is a complex disease of pregnancy whose physiopathology remains unclear and that poses a threat to both mothers and infants. Specific complex changes in women's physiology precede a diagnosis of preeclampsia. Understanding multiple aspects of such a complex changes at different levels of biology can be enabled by simultaneous application of multiple assays. We developed prediction models for preeclampsia risk by analyzing six omics datasets from a longitudinal cohort of pregnant women. A machine learning-based multiomics model had high accuracy (area under the receiver operating characteristics curve (AUC) of 0.94, 95% confidence intervals (CI): [0.90, 0.99]). A prediction model using only ten urine metabolites provided an accuracy of the whole metabolomic dataset and was validated using an independent cohort of 16 women (AUC=0.87, 95% CI: [0.76, 0.99]). Integration with clinical variables further improved prediction accuracy of the urine metabolome model (AUC=0.90, 95% CI: [0.80, 0.99], urine metabolome, validated). We identified several biological pathways to be associated with preeclampsia. The findings derived from models were integrated with immune system cytometry data, confirming known physiological alterations associated with preeclampsia and suggesting novel associations between the immune and proteomic dynamics. While further validation in larger populations is necessary, these encouraging results will serve as a basis for a simple, early diagnostic test for preeclampsia.
Institute
Stanford University
Last NameContrepois
First NameKevin
Address300 Pasteur Dr
Emailkcontrep@stanford.edu
Phone6506664538
Submit Date2021-07-26
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2022-07-26
Release Version1
Kevin Contrepois Kevin Contrepois
https://dx.doi.org/10.21228/M8WD84
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001190
Project DOI:doi: 10.21228/M8WD84
Project Title:Preeclampsia and plasma metabolomics
Project Summary:Longitudinal untargeted plasma metabolomics of pregnant women with preeclampsia
Institute:Stanford University
Last Name:Contrepois
First Name:Kevin
Address:300 Pasteur Dr
Email:kcontrep@stanford.edu
Phone:6506664538

Subject:

Subject ID:SU001967
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Species Group:Mammals

Factors:

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

mb_sample_id local_sample_id Gestational Age At Sampling Gestational Age At Delivery Preeclampsia
SA175485108360810910 35 1
SA175486190170810510 37 1
SA175487105280810510 38 -
SA175488105510810510 39 -
SA175489105470810510 39 -
SA175490105020810510 41 -
SA175491108160811411 30 1
SA175492107270811411 37 1
SA175493105610811511 37 1
SA175494108090811411 37 1
SA175495105350811511 38 -
SA175496105240811511 38 -
SA175497106340811411 38 1
SA175498107210811411 39 -
SA175499108330811911 39 1
SA175500107320811411 40 -
SA175501105150811511 40 -
SA175502106010811311 40 1
SA175503107130811311 41 -
SA175504106390811411 41 1
SA175505107220812412 30 1
SA175506108400812912 37 1
SA175507108240812912 37 1
SA175508107330812412 41 -
SA175509108220813913 33 1
SA175510108030813413 36 1
SA175511107360813413 39 1
SA175512107120813413 40 -
SA175513107230813513 40 1
SA175514108360815915 35 1
SA175515105300815515 36 1
SA175516100560815515 36 1
SA175517105580815515 38 1
SA175518105470815515 39 -
SA175519105510815515 39 -
SA175520108040815415 39 -
SA175521105410815515 39 -
SA175522108330815915 39 1
SA175523101120815515 39 1
SA175524105150815515 40 -
SA175525105230815515 41 -
SA175526105460815515 41 -
SA175527107330815515 41 -
SA175528108160816416 30 1
SA175529101040816516 32 1
SA175530108220816916 33 1
SA175531108030816416 36 1
SA175532190170816516 37 1
SA175533107270816416 37 1
SA175534108240816916 37 1
SA175535105350816516 38 -
SA175536106340816416 38 1
SA175537105380816516 39 -
SA175538107120816516 40 -
SA175539106010816316 40 1
SA175540106390816416 41 1
SA175541107220817417 30 1
SA175542105050817517 37 -
SA175543105530817517 37 1
SA175544105330817517 37 1
SA175545196000817517 39 1
SA175546107360817417 39 1
SA175547107230817517 40 1
SA175548107130817417 41 -
SA175549108090818418 37 1
SA175550105240818418 38 -
SA175551107210818218 39 -
SA175552105480818518 40 -
SA175553107320818418 40 -
SA175554105030818518 41 -
SA175555101040823523 32 1
SA175556108160824824 30 1
SA175557105530824524 37 1
SA175558108090824424 37 1
SA175559106340824424 38 1
SA175560105470824524 39 -
SA175561108330824924 39 1
SA175562107320824224 40 -
SA175563107220825425 30 1
SA175564105610825525 37 1
SA175565190170825525 37 1
SA175566105580825525 38 1
SA175567107360825425 39 1
SA175568196000825325 39 1
SA175569105150825425 40 -
SA175570107120825225 40 -
SA175571105480825525 40 -
SA175572107230825525 40 1
SA175573105020825525 41 -
SA175574100560826526 36 1
SA175575108030826426 36 1
SA175576105050826426 37 -
SA175577105330826526 37 1
SA175578105240826526 38 -
SA175579105510826526 39 -
SA175580101120826526 39 1
SA175581107130826226 41 -
SA175582107330826226 41 -
SA175583107270827427 37 1
SA175584105350827527 38 -
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Collection:

Collection ID:CO001960
Collection Summary:Intravenous blood was collected from pregnant women
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR001979
Treatment Summary:N/A

Sample Preparation:

Sampleprep ID:SP001973
Sampleprep Summary:Plasma samples were thawed on ice, prepared and analyzed randomly as previously described (Contrepois et al., 2015, Contrepois et al., 2018). Briefly, metabolites were extracted using 1:1:1 acetone:acetonitrile:methanol, evaporated to dryness under nitrogen and reconstituted in 1:1 methanol:water before analysis. Fifteen labeled metabolite internal standards (IS) were added to each sample to control for extraction efficiency and LC-MS performance. Complex lipids were prepared using a biphasic separation with cold methyl tert-butyl ether (MTBE), methanol and water and reconstituted in 9:1 methanol:toluene. Each sample was spiked-in with deuterated lipid IS (Sciex, cat#: 5040156) used for quantification. For quality controls, 3 reference plasma samples (40 µl plasma) and 1 preparation blank were processed in parallel.

Combined analysis:

Analysis ID AN003062 AN003063 AN003064 AN003065
Analysis type MS MS MS MS
Chromatography type HILIC HILIC Reversed phase Reversed phase
Chromatography system Thermo Dionex Ultimate 3000 RS Thermo Dionex Ultimate 3000 RS Thermo Dionex Ultimate 3000 RS Thermo Dionex Ultimate 3000 RS
Column EMD Millipore ZIC-HILIC (100 x 2.1mm,3.5um) EMD Millipore ZIC-HILIC (100 x 2.1mm,3.5um) Agilent Zorbax SBaq (50 x 2.1mm,1.7um) Agilent Zorbax SBaq (50 x 2.1mm,1.7um)
MS Type ESI ESI ESI ESI
MS instrument type Orbitrap Orbitrap Orbitrap Orbitrap
MS instrument name Thermo Q Exactive HF hybrid Orbitrap Thermo Q Exactive HF hybrid Orbitrap Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode POSITIVE NEGATIVE POSITIVE NEGATIVE
Units MS count MS count MS count MS count

Chromatography:

Chromatography ID:CH002268
Chromatography Summary:HILIC experiments were performed using a ZIC-HILIC column 2.1 x 100 mm, 3.5 μm, 200Å (Merck Millipore, Darmstadt, Germany) and mobile phase solvents consisting of 10 mM ammonium acetate in 50/50 acetonitrile/water (A) and 10 mM ammonium acetate in 95/5 acetonitrile/water (B).
Instrument Name:Thermo Dionex Ultimate 3000 RS
Column Name:EMD Millipore ZIC-HILIC (100 x 2.1mm,3.5um)
Solvent A:50% acetonitrile/50% water; 10 mM ammonium acetate
Solvent B:95% acetonitrile/5% water; 10 mM ammonium acetate
Chromatography Type:HILIC
  
Chromatography ID:CH002269
Chromatography Summary:RPLC experiments were performed using a Zorbax SBaq column 2.1 x 50 mm, 1.7 μm, 100Å (Agilent Technologies, Palo Alto, CA) and mobile phase solvents consisting of 0.06% acetic acid in water (A) and 0.06% acetic acid in methanol (B).
Instrument Name:Thermo Dionex Ultimate 3000 RS
Column Name:Agilent Zorbax SBaq (50 x 2.1mm,1.7um)
Solvent A:100% water; 0.06% acetic acid
Solvent B:100% methanol; 0.06% acetic acid
Chromatography Type:Reversed phase

MS:

MS ID:MS002849
Analysis ID:AN003062
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data were acquired on a Thermo Q Exactive HF mass spectrometer for HILIC and a Thermo Q Exactive mass spectrometer for RPLC operated in full MS scan mode. MS/MS data were acquired on quality control samples (QC) consisting of an equimolar mixture of all samples in the study. Data from each mode were independently processed using Progenesis QI software (v2.3) (Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and those that didn’t show sufficient linearity upon dilution in QC samples (r<0.6) were discarded. Only metabolic features present in >2/3 of the samples were kept for further analysis. Inter- and intra-batch variations was were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Missing values were imputed by drawing from a random distribution of low values in the corresponding sample.
Ion Mode:POSITIVE
  
MS ID:MS002850
Analysis ID:AN003063
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data were acquired on a Thermo Q Exactive HF mass spectrometer for HILIC and a Thermo Q Exactive mass spectrometer for RPLC operated in full MS scan mode. MS/MS data were acquired on quality control samples (QC) consisting of an equimolar mixture of all samples in the study. Data from each mode were independently processed using Progenesis QI software (v2.3) (Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and those that didn’t show sufficient linearity upon dilution in QC samples (r<0.6) were discarded. Only metabolic features present in >2/3 of the samples were kept for further analysis. Inter- and intra-batch variations was were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Missing values were imputed by drawing from a random distribution of low values in the corresponding sample.
Ion Mode:NEGATIVE
  
MS ID:MS002851
Analysis ID:AN003064
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data were acquired on a Thermo Q Exactive HF mass spectrometer for HILIC and a Thermo Q Exactive mass spectrometer for RPLC operated in full MS scan mode. MS/MS data were acquired on quality control samples (QC) consisting of an equimolar mixture of all samples in the study. Data from each mode were independently processed using Progenesis QI software (v2.3) (Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and those that didn’t show sufficient linearity upon dilution in QC samples (r<0.6) were discarded. Only metabolic features present in >2/3 of the samples were kept for further analysis. Inter- and intra-batch variations was were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Missing values were imputed by drawing from a random distribution of low values in the corresponding sample.
Ion Mode:POSITIVE
  
MS ID:MS002852
Analysis ID:AN003065
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Data were acquired on a Thermo Q Exactive HF mass spectrometer for HILIC and a Thermo Q Exactive mass spectrometer for RPLC operated in full MS scan mode. MS/MS data were acquired on quality control samples (QC) consisting of an equimolar mixture of all samples in the study. Data from each mode were independently processed using Progenesis QI software (v2.3) (Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and those that didn’t show sufficient linearity upon dilution in QC samples (r<0.6) were discarded. Only metabolic features present in >2/3 of the samples were kept for further analysis. Inter- and intra-batch variations was were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Missing values were imputed by drawing from a random distribution of low values in the corresponding sample.
Ion Mode:NEGATIVE
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