Summary of Study ST001681
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 PR001080. The data can be accessed directly via it's Project DOI: 10.21228/M83H5W 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.
| Study ID | ST001681 |
| Study Title | Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset |
| Study Summary | Estimating the time of delivery is of high clinical importance as pre- and post-term deviations are associated with complications for the mother and her offspring. However, current estimation approaches are inaccurate. As pregnancy progresses towards labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in the delivery of the fetus. The comprehensive characterization of metabolic, proteomic and immune cell events that precede the spontaneous onset of labor is a key step to understanding these physiological transitions and identifying predictive biomarkers of parturition. Here, over 7,000 circulating plasma analytes and peripheral immune cell responses collected during the last 100 days of pregnancy were integrated into a multi-omic model that accurately predicted the time to spontaneous onset of labor (R = 0.85, p-value = 1.2e-40, training set; R = 0.81, p-value = 3.9e-7, independent test set). Coordinated fluctuations marked a molecular shift from pregnancy progression to pre-labor onset biology 2–4 weeks before delivery. Our study lays the groundwork for developing blood-based methods for predicting the onset of labor, anchored in mechanisms shared in preterm, term, and postterm pregnancies. |
| Institute | Stanford University |
| Last Name | Contrepois |
| First Name | Kevin |
| Address | 1291 Welch rd, Biomedical innovations building-Room 4400, STANFORD, California, 94305, USA |
| kcontrep@stanford.edu | |
| Phone | 6506664538 |
| Submit Date | 2021-02-02 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-07-22 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN002742 | AN002743 | AN002744 | AN002745 |
|---|---|---|---|---|
| Analysis type | MS | MS | MS | MS |
| Chromatography type | HILIC | HILIC | Reversed phase | Reversed phase |
| Chromatography system | Thermo Vanquish | Thermo Vanquish | Thermo Dionex Ultimate 3000 RS | Thermo Dionex Ultimate 3000 RS |
| Column | SeQuant ZIC-HILIC (100 x 2.1mm,3.5um) | SeQuant 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 Counts | MS Counts | MS Counts | MS Counts |
MS:
| MS ID: | MS002539 |
| Analysis ID: | AN002742 |
| Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently processed using Progenesis QI software (v2.3, Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and that did not 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 were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Data were acquired in five and three batches for HILIC and RPLC modes, respectively. Missing values were imputed by drawing from a random distribution of low values in the corresponding sample. Data from each mode were merged and resulted in a dataset containing 3,529 metabolic features that was used for downstream analysis. Metabolic features of interest were tentatively identified by matching fragmentation spectra and retention time to analytical-grade standards when possible or matching experimental MS/MS to fragmentation spectra in publicly available databases. |
| Ion Mode: | POSITIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 35 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002540 |
| Analysis ID: | AN002743 |
| Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently processed using Progenesis QI software (v2.3, Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and that did not 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 were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Data were acquired in five and three batches for HILIC and RPLC modes, respectively. Missing values were imputed by drawing from a random distribution of low values in the corresponding sample. Data from each mode were merged and resulted in a dataset containing 3,529 metabolic features that was used for downstream analysis. Metabolic features of interest were tentatively identified by matching fragmentation spectra and retention time to analytical-grade standards when possible or matching experimental MS/MS to fragmentation spectra in publicly available databases. |
| Ion Mode: | NEGATIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 35 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002541 |
| Analysis ID: | AN002744 |
| Instrument Name: | Thermo Q Exactive Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently processed using Progenesis QI software (v2.3, Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and that did not 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 were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Data were acquired in five and three batches for HILIC and RPLC modes, respectively. Missing values were imputed by drawing from a random distribution of low values in the corresponding sample. Data from each mode were merged and resulted in a dataset containing 3,529 metabolic features that was used for downstream analysis. Metabolic features of interest were tentatively identified by matching fragmentation spectra and retention time to analytical-grade standards when possible or matching experimental MS/MS to fragmentation spectra in publicly available databases. |
| Ion Mode: | POSITIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 50 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002542 |
| Analysis ID: | AN002745 |
| Instrument Name: | Thermo Q Exactive Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently processed using Progenesis QI software (v2.3, Nonlinear Dynamics, Durham, NC). Metabolic features from blanks and that did not 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 were corrected using the LOESS (locally estimated scatterplot smoothing Local Regression) normalization method on QC injected repetitively along the batches (span = 0.75). Data were acquired in five and three batches for HILIC and RPLC modes, respectively. Missing values were imputed by drawing from a random distribution of low values in the corresponding sample. Data from each mode were merged and resulted in a dataset containing 3,529 metabolic features that was used for downstream analysis. Metabolic features of interest were tentatively identified by matching fragmentation spectra and retention time to analytical-grade standards when possible or matching experimental MS/MS to fragmentation spectra in publicly available databases. |
| Ion Mode: | NEGATIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 50 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
