Summary of Study ST001407
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 PR000963. The data can be accessed directly via it's Project DOI: 10.21228/M86X2T 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 | ST001407 |
| Study Title | Environmental chemical burden in metabolic tissues and systemic biological pathways in adolescent bariatric surgery patients: A pilot untargeted metabolomic approach |
| Study Type | Subcutaneous adipose tissue (AT); Visceral AT; Liver Tissue; Plasma |
| Study Summary | Background: Advances in untargeted metabolomic technologies have great potential for insight into adverse metabolic effects underlying exposure to environmental chemicals. However, important challenges need to be addressed, including how biological response corresponds to the environmental chemical burden in different target tissues. Aim: We performed a pilot study using state-of-the-art ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of lipophilic persistent organic pollutants (POPs) in metabolic tissues and associated alterations in the plasma metabolome. Methods: We studied 11 adolescents with severe obesity at the time of bariatric surgery. We measured 18 POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11 organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver samples using gas chromatography with UHRMS. Biological pathways were evaluated by measuring the plasma metabolome using high-resolution metabolomics. Network and pathway enrichment analysis assessed correlations between the tissue-specific burden of three frequently detected POPs (i.e. p,p’-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and PBDE-47) and plasma metabolic pathways. Results: Concentrations of 4 OCs and 3 PBDEs were quantifiable in at least one metabolic tissue for >80% of participants. All POPs had the highest median concentrations in adipose tissue, especially sAT, except for PBDE-154, which had comparable average concentrations across all tissues. Pathway analysis showed high correlations between tissue-specific POPs and metabolic alterations in pathways of amino acid metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism. Conclusions: Most of the measured POPs appear to accumulate preferentially in adipose tissue compared to liver. Findings of plasma metabolic pathways potentially associated with tissue-specific POPs concentrations merit further investigation in larger populations. |
| Institute | Icahn School of Medicine at Mount Sinai |
| Department | Environmental Medicine and Public Health |
| Laboratory | High Resolution Exposomics Research Group |
| Last Name | Walker |
| First Name | Doug |
| Address | One Gustave L. Levy Place, Box 1057, New York, NY 10029 |
| douglas.walker@mssm.edu | |
| Phone | 212-241-9891 |
| Submit Date | 2020-06-22 |
| Num Groups | 1 |
| Total Subjects | 11 |
| Num Males | 1 |
| Num Females | 10 |
| Study Comments | Upload #1: Visceral and subcutaneous abdominal adipose tissue, liver tissue. Plasma metabolomics are in upload #2 |
| Publications | Valvi D, Walker DI, Inge T, Bartell SM, Jenkins T, Helmrath M, Ziegler TR, La Merrill MA, Eckel SP, Conti D, Liang Y, Jones DP, McConnell R, Chatzi L. (2020). Environmental chemical burden in metabolic tissues and systemic biological pathways in adolescent bariatric surgery patients: A pilot untargeted metabolomic approach. Environment International. In Press. |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-06-19 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN002350 | AN002351 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | HILIC | Reversed phase |
| Chromatography system | Thermo Dionex Ultimate 3000 | Thermo Dionex Ultimate 3000 |
| Column | Waters XBridge BEH Amide XP HILIC (50 x 2.1mm,2.5um) | Higgins endcapped C18 stainless steel (50 x 2.1mm,3um) |
| MS Type | ESI | ESI |
| MS instrument type | Orbitrap | Orbitrap |
| MS instrument name | Thermo Q Exactive HF hybrid Orbitrap | Thermo Q Exactive HF hybrid Orbitrap |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | Peak intensity | Peak intensity |
MS:
| MS ID: | MS002192 |
| Analysis ID: | AN002350 |
| Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | The high-resolution mass spectrometer was operated at 120,000 resolution and mass-to-charge ratio (m/z) range 85-1275. Probe temperature, capillary temperature, sweep gas and S-Lens RF levels were maintained at 200°C, 300°C, 1 arbitrary units (AU), and 45, respectively. Additional source settings were optimized for sensitivity using a standard mixture, tune settings for sheath gas, auxiliary gas, sweep gas and spray voltage setting were 45 AU, 25 AU and 3.5 kV, respectively. Maximum C-trap injection times were set at 100 milliseconds and automatic gain control target 1 × 106. During untargeted data acquisition, no exclusion or inclusion masses were selected, and data was acquired in MS1 mode only. Raw data files were then extracted using apLCMS (Yu et al. 2009) at five different peak detection settings that have been separately optimized for detection of a wide range of peak intensities and abundances. Peaks detected during each injection were aligned using a mass tolerance of 5 ppm (parts-per-million) and retention grouping was accomplished using non-parametric density estimation grouping, with a maximum retention time deviation of 30 seconds. The resulting feature tables were merged using xMSanalyzer, which identifies overlapping or unique features detected across the different peak detection parameters, and retains the peak with the lowest replicate CV and non-detects for inclusion in the final feature table (Uppal et al. 2013). All R-scripts for data extraction with apLCMS and data merging with xMSanalyzer are provided in the supplementary material. Uniquely detected ions consisted of m/z, retention time and ion abundance, referred to as m/z features. Prior to data analysis, triplicate m/z features averaged and filtered to remove those with triplicate coefficient of variation (CV) ≥ 100% and non-detected values greater than 10%. |
| Ion Mode: | POSITIVE |
| Capillary Temperature: | 300C |
| Ion Source Temperature: | 200C |
| Ion Spray Voltage: | 3.5kV |
| Ionization: | Postive |
| Mass Accuracy: | 5ppm |
| Source Temperature: | 200C |
| MS ID: | MS002193 |
| Analysis ID: | AN002351 |
| Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | The high-resolution mass spectrometer was operated at 120,000 resolution and mass-to-charge ratio (m/z) range 85-1275. Probe temperature, capillary temperature, sweep gas and S-Lens RF levels were maintained at 200°C, 300°C, 1 arbitrary units (AU), and 45, respectively. Additional source settings were optimized for sensitivity using a standard mixture, tune settings for sheath gas, auxiliary gas, sweep gas and spray voltage setting were 45 AU, 25 AU and 3.5 kV, respectively. Maximum C-trap injection times were set at 100 milliseconds and automatic gain control target 1 × 106. During untargeted data acquisition, no exclusion or inclusion masses were selected, and data was acquired in MS1 mode only. Raw data files were then extracted using apLCMS (Yu et al. 2009) at five different peak detection settings that have been separately optimized for detection of a wide range of peak intensities and abundances. Peaks detected during each injection were aligned using a mass tolerance of 5 ppm (parts-per-million) and retention grouping was accomplished using non-parametric density estimation grouping, with a maximum retention time deviation of 30 seconds. The resulting feature tables were merged using xMSanalyzer, which identifies overlapping or unique features detected across the different peak detection parameters, and retains the peak with the lowest replicate CV and non-detects for inclusion in the final feature table (Uppal et al. 2013). All R-scripts for data extraction with apLCMS and data merging with xMSanalyzer are provided in the supplementary material. Uniquely detected ions consisted of m/z, retention time and ion abundance, referred to as m/z features. Prior to data analysis, triplicate m/z features averaged and filtered to remove those with triplicate coefficient of variation (CV) ≥ 100% and non-detected values greater than 10%. |
| Ion Mode: | NEGATIVE |
| Capillary Temperature: | 300C |
| Ion Source Temperature: | 200C |
| Ion Spray Voltage: | 3.5kV |
| Ionization: | NEgative |
| Mass Accuracy: | 5ppm |
| Source Temperature: | 200C |
