Summary of Study ST001827

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 PR001154. The data can be accessed directly via it's Project DOI: 10.21228/M8J97M This work is supported by NIH grant, U2C- DK119886.

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Study IDST001827
Study TitleThe pregnancy metabolome from a multi-ethnic pregnancy cohort
Study SummaryThe PRogramming of Intergenerational Stress Mechanisms (PRISM) study is an urban, ethnically diverse pregnancy cohort that was designed to study a range of chemical and non-chemical stressors in relation to maternal health, pregnancy outcomes, and child development. Pregnant women were enrolled from Boston and New York City hospitals and affiliated prenatal clinics beginning in 2011. Eligibility criteria included English or Spanish-speaking, over 18 years of age at enrollment, and singleton pregnancy. Exclusion criteria included HIV+ status or self-reported drinking ≥7 alcoholic drinks per week before pregnancy or any alcohol after pregnancy recognition
Institute
Icahn School of Medicine at Mount Sinai
Last NameWright
First NameRosalind J
Address5 E.98st FL 10th floor
Emailrosalind.wright@mssm.edu
Phone(212) 241-5287
Submit Date2021-06-10
Analysis Type DetailLC-MS
Release Date2021-06-28
Release Version1
Rosalind J Wright Rosalind J Wright
https://dx.doi.org/10.21228/M8J97M
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001154
Project DOI:doi: 10.21228/M8J97M
Project Title:The pregnancy metabolome from a multi-ethnic pregnancy cohort
Project Type:cohort study
Project Summary:The PRogramming of Intergenerational Stress Mechanisms (PRISM) study is an urban, ethnically diverse pregnancy cohort that was designed to study a range of chemical and non-chemical stressors in relation to maternal health, pregnancy outcomes, and child development. Pregnant women were enrolled from Boston and New York City hospitals and affiliated prenatal clinics beginning in 2011. Eligibility criteria included English or Spanish-speaking, over 18 years of age at enrollment, and singleton pregnancy. Exclusion criteria included HIV+ status or self-reported drinking ≥7 alcoholic drinks per week before pregnancy or any alcohol after pregnancy recognition.
Institute:Icahn School of Medicine at Mount Sinai
Last Name:Wright
First Name:Rosalind J
Address:5 E 98st FL 10th floor
Email:rosalind.wright@mssm.edu
Phone:(212) 241-5287
Funding Source:R01 HL095606, R01 HL114396, UG3 OD023337, P30 ES023515, UL1 TR001433
Contributors:Robert O Wright, Elena Colicino, Megan M Niedzwiecki

Subject:

Subject ID:SU001904
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606

Factors:

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

mb_sample_id local_sample_id gestage_serum
SA169371id_35811
SA169372id_29214
SA169373id_37814
SA169374id_36716
SA169375id_34318
SA169376id_21718
SA169377id_31719
SA169378id_12719
SA169379id_37420
SA169380id_37921
SA169381id_36621
SA169382id_32922
SA169383id_23722
SA169384id_35622
SA169385id_31223
SA169386id_16423
SA169387id_32423
SA169388id_1523
SA169389id_20424
SA169390id_19824
SA169391id_35524
SA169392id_26124
SA169393id_11224
SA169394id_28524
SA169395id_13624
SA169396id_10724
SA169397id_36024
SA169398id_19624
SA169399id_14024
SA169400id_19724
SA169401id_6924
SA169402id_40524
SA169403id_22524
SA169404id_21024
SA169405id_24324
SA169406id_24724
SA169407id_30525
SA169408id_27025
SA169409id_15725
SA169410id_33125
SA169411id_27125
SA169412id_18125
SA169413id_27325
SA169414id_6625
SA169415id_18525
SA169416id_38925
SA169417id_9125
SA169418id_9025
SA169419id_17225
SA169420id_17125
SA169421id_9425
SA169422id_17325
SA169423id_17525
SA169424id_17025
SA169425id_8325
SA169426id_17825
SA169427id_16525
SA169428id_32525
SA169429id_15625
SA169430id_5325
SA169431id_29325
SA169432id_12925
SA169433id_12425
SA169434id_20025
SA169435id_28025
SA169436id_5625
SA169437id_21625
SA169438id_14525
SA169439id_28325
SA169440id_2825
SA169441id_15025
SA169442id_22925
SA169443id_29425
SA169444id_35125
SA169445id_16626
SA169446id_23526
SA169447id_226
SA169448id_13726
SA169449id_14226
SA169450id_28626
SA169451id_28926
SA169452id_9726
SA169453id_39726
SA169454id_22626
SA169455id_30326
SA169456id_27926
SA169457id_27426
SA169458id_12326
SA169459id_28126
SA169460id_30726
SA169461id_15326
SA169462id_16326
SA169463id_30826
SA169464id_8526
SA169465id_34126
SA169466id_6026
SA169467id_19026
SA169468id_25926
SA169469id_26026
SA169470id_18826
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Collection:

Collection ID:CO001897
Collection Summary:At the time of metabolomics profiling (March 2018), 843 women had delivered a live born infant. The analytic sample includes a random subset of 410 mother-child pairs with maternal metabolomics measured during pregnancy (week of serum collection: 25th, 50th, 75th percentiles: 26, 29, 33 weeks).
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR001917
Treatment Summary:Maternal blood was collected by venipuncture (mean ± standard deviation (SD): 29.6 ± 4.90 weeks) and serum aliquots were stored at −80℃ until assayed. Untargeted metabolomics analysis was conducted on 100µl of serum at Metabolon, Inc (Durham, NC, USA) with ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS). The method utilized an ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. One aliquot was analyzed using acidic positive ion conditions, chromatographically optimized for more hydrophilic compounds; the extract compound was gradient eluted from a C18 column using water and methanol, containing 0.05% perfluoropentanoic acid (PFPA) and 0.1% formic acid (FA). Another aliquot was analyzed with the prior approach but it was chromatographically optimized for more hydrophobic compounds and operated at an overall higher organic content. A third aliquot was analyzed using basic negative ion optimized conditions using a separate dedicated C18 column. The basic extracts were gradient eluted from the column using methanol and water, however with 6.5mM Ammonium Bicarbonate at pH 8. The fourth aliquot was analyzed via negative ionization following elution from a HILIC column using a gradient consisting of water and acetonitrile with 10mM Ammonium Formate, pH 10.8. The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range between methods covered 70-1000 m/z. Raw data was extracted, peak-identified and QC processed using Metabolon’s hardware and software. Peaks were quantified using area-under-the-curve. Batch adjustment to correct variation resulting from instrument inter-day tuning differences was performed for each compound in run-day blocks by dividing by the median of the values for the experimental samples for each instrument run day, then multiplying these values by the original median. In one serum sample with a lower volume (65µl instead of 80µl), metabolite intensities were scaled accounting for the volume of serum available, under the assumption that metabolite signal intensities scale linearly with the sample volume. We normalized all metabolomic data using first the natural base for log-scaling, thus removing skewness of the data. We then used a Pareto scaling approach, which incorporates a scaling factor equal to the square root of the standard deviation of individual metabolites so that larger fold changes were scaled more than smaller fold changes (Grace and Hudson, 2016). A total of 1,110 biochemicals were detected across all four assays. Potential sample outliers were examined using principal component analysis (PCA), though none were identified. Final data were presented as normalized levels to facilitate both linear and non-linear analyses and to harmonize all variables on a common scale.

Sample Preparation:

Sampleprep ID:SP001910
Sampleprep Summary:Following receipt, samples were inventoried and immediately stored at -80℃. Each sample received was accessioned into the Metabolon LIMS system and was assigned by the LIMS a unique identifier that was associated with the original source identifier only. This identifier was used to track all sample handling, tasks, results, etc. The samples (and all derived aliquots) were tracked by the LIMS system. All portions of any sample were automatically assigned their own unique identifiers by the LIMS when a new task was created; the relationship of these samples was also tracked. All samples were maintained at -80℃ until processed.

Combined analysis:

Analysis ID AN002963
Analysis type MS
Chromatography type HILIC
Chromatography system Thermo Scientific Q-Exactive
Column SeQuant ZIC-HILIC (150 x 4.6mm, 3.5um)
MS Type ESI
MS instrument type Orbitrap
MS instrument name Thermo Q Exactive Orbitrap
Ion Mode UNSPECIFIED
Units pmoles/l

Chromatography:

Chromatography ID:CH002196
Instrument Name:Thermo Scientific Q-Exactive
Column Name:SeQuant ZIC-HILIC (150 x 4.6mm, 3.5um)
Chromatography Type:HILIC

MS:

MS ID:MS002753
Analysis ID:AN002963
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Untargeted metabolomics analysis was conducted on 100µl of serum at Metabolon, Inc (Durham, NC, USA) with ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS). The method utilized an ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. One aliquot was analyzed using acidic positive ion conditions, chromatographically optimized for more hydrophilic compounds; the extract compound was gradient eluted from a C18 column using water and methanol, containing 0.05% perfluoropentanoic acid (PFPA) and 0.1% formic acid (FA). Another aliquot was analyzed with the prior approach but it was chromatographically optimized for more hydrophobic compounds and operated at an overall higher organic content. A third aliquot was analyzed using basic negative ion optimized conditions using a separate dedicated C18 column. The basic extracts were gradient eluted from the column using methanol and water, however with 6.5mM Ammonium Bicarbonate at pH 8. The fourth aliquot was analyzed via negative ionization following elution from a HILIC column using a gradient consisting of water and acetonitrile with 10mM Ammonium Formate, pH 10.8. The MS analysis alternated between MS and data-dependent MSn scans using dynamic exclusion. The scan range between methods covered 70-1000 m/z. Raw data was extracted, peak-identified and QC processed using Metabolon’s hardware and software. Peaks were quantified using area-under-the-curve. Batch adjustment to correct variation resulting from instrument inter-day tuning differences was performed for each compound in run-day blocks by dividing by the median of the values for the experimental samples for each instrument run day, then multiplying these values by the original median. In one serum sample with a lower volume (65µl instead of 80µl), metabolite intensities were scaled accounting for the volume of serum available, under the assumption that metabolite signal intensities scale linearly with the sample volume.
Ion Mode:UNSPECIFIED
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