Summary of Study ST001930
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 PR001219. The data can be accessed directly via it's Project DOI: 10.21228/M84Q3H 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 | ST001930 |
Study Title | Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry |
Study Type | Untargeted Metabolomics |
Study Summary | Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010 and analyzed using untargeted high-resolution metabolomics to characterize association with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and gene expression changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution. |
Institute | Icahn School of Medicine at Mount Sinai |
Department | Environmental Medicine and Public Health |
Laboratory | High Resolution Exposomics |
Last Name | Walker |
First Name | Douglas |
Address | Atran Building RM AB3-39, 1428 Madison Ave, New York, NY, 10029, USA |
douglas.walker@mssm.edu | |
Phone | 1-212-241-4392 |
Submit Date | 2021-09-30 |
Num Groups | 1 |
Total Subjects | 95 |
Num Males | 94 |
Num Females | 1 |
Publications | DI Walker, JE Hart, CJ Patel, R Rudel, J Chu, E Garshick, KD Pennel, F Laden, DP Jones. Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry. Environment International. In review |
Raw Data Available | Yes |
Raw Data File Type(s) | mzXML, raw(Thermo) |
Analysis Type Detail | LC-MS |
Release Date | 2021-10-29 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001219 |
Project DOI: | doi: 10.21228/M84Q3H |
Project Title: | Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry |
Project Summary: | Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010 and analyzed using untargeted high-resolution metabolomics to characterize association with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and gene expression changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution. |
Institute: | Icahn School of Medicine at Mount Sinai |
Department: | Environmental Medicine and Public Health |
Laboratory: | High Resolution Exposomics |
Last Name: | Walker |
First Name: | Douglas |
Address: | Atran Building RM AB3-39, 1428 Madison Ave, New York, NY, 10029, USA |
Email: | douglas.walker@mssm.edu |
Phone: | 1-212-241-4392 |
Funding Source: | This work was supported by funds received from the National Institute of Health, award numbers ES019776, ES025632, ES030859, ES013726, CA090792, ES016284, P30 ES000002 and OD018006. |
Publications: | DI Walker, JE Hart, CJ Patel, R Rudel, J Chu, E Garshick, KD Pennel, F Laden, DP Jones. Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry. Environment International. In review |
Subject:
Subject ID: | SU002008 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Gender: | Male and female |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Class |
---|---|---|
SA178554 | q15b | QC |
SA178555 | q16a | QC |
SA178556 | q11a | QC |
SA178557 | q5a | QC |
SA178558 | q6a | QC |
SA178559 | q14b | QC |
SA178560 | q15a | QC |
SA178561 | q4b | QC |
SA178562 | q16b | QC |
SA178563 | q18a | QC |
SA178564 | q3a | QC |
SA178565 | q17b | QC |
SA178566 | q3b | QC |
SA178567 | q17a | QC |
SA178568 | q4a | QC |
SA178569 | q6b | QC |
SA178570 | q7a | QC |
SA178571 | q11b | QC |
SA178572 | q12a | QC |
SA178573 | q9b | QC |
SA178574 | q10a | QC |
SA178575 | q10b | QC |
SA178576 | nist1a | QC |
SA178577 | q9a | QC |
SA178578 | q8b | QC |
SA178579 | q13b | QC |
SA178580 | q14a | QC |
SA178581 | q7b | QC |
SA178582 | q8a | QC |
SA178583 | q12b | QC |
SA178584 | q13a | QC |
SA178585 | q2b | QC |
SA178586 | q5b | QC |
SA178587 | q19a | QC |
SA178588 | q1b | QC |
SA178589 | q18b | QC |
SA178590 | q19b | QC |
SA178591 | nist1b | QC |
SA178592 | q2a | QC |
SA178593 | q1a | QC |
SA178594 | S-001175855 | Study |
SA178595 | S-001175864 | Study |
SA178596 | S-001175846 | Study |
SA178597 | S-001175954 | Study |
SA178598 | S-001175828 | Study |
SA178599 | S-001175837 | Study |
SA178600 | S-001175873 | Study |
SA178601 | S-001175827 | Study |
SA178602 | S-001175872 | Study |
SA178603 | S-001175881 | Study |
SA178604 | S-001175952b | Study |
SA178605 | S-001175998b | Study |
SA178606 | S-001175863 | Study |
SA178607 | S-001175854 | Study |
SA178608 | S-001175939 | Study |
SA178609 | S-001175963 | Study |
SA178610 | S-001175836 | Study |
SA178611 | S-001175845 | Study |
SA178612 | S-001175882 | Study |
SA178613 | S-001175883 | Study |
SA178614 | S-001175857 | Study |
SA178615 | S-001175866 | Study |
SA178616 | S-001175875 | Study |
SA178617 | S-001175884 | Study |
SA178618 | S-001175848 | Study |
SA178619 | S-001175839 | Study |
SA178620 | S-001175821 | Study |
SA178621 | S-001175999 | Study |
SA178622 | S-001175990 | Study |
SA178623 | S-001175830 | Study |
SA178624 | S-001175941 | Study |
SA178625 | S-001175820 | Study |
SA178626 | S-001175865 | Study |
SA178627 | S-001175874 | Study |
SA178628 | S-001175890 | Study |
SA178629 | S-001175940 | Study |
SA178630 | S-001175972 | Study |
SA178631 | S-001175981 | Study |
SA178632 | S-001175829 | Study |
SA178633 | S-001175838 | Study |
SA178634 | S-001175847 | Study |
SA178635 | S-001175856 | Study |
SA178636 | S-001175819 | Study |
SA178637 | S-001175989b | Study |
SA178638 | S-001175760 | Study |
SA178639 | S-001175769 | Study |
SA178640 | S-001175816 | Study |
SA178641 | S-001175705 | Study |
SA178642 | S-001175751 | Study |
SA178643 | S-001175742 | Study |
SA178644 | S-001175715 | Study |
SA178645 | S-001175953b | Study |
SA178646 | S-001175724 | Study |
SA178647 | S-001175733 | Study |
SA178648 | S-001175714 | Study |
SA178649 | S-001175723 | Study |
SA178650 | S-001175815 | Study |
SA178651 | S-001175704 | Study |
SA178652 | S-001175713 | Study |
SA178653 | S-001175722 | Study |
Collection:
Collection ID: | CO002001 |
Collection Summary: | A total of four blood samples was collected from each participant over the course of the workweek. The first blood sample was collected from each participant prior to the day’s work shift on their first day back after at least two days off, followed by a second blood sample at the end of the first work shift. Pre- and post-shift samples were collected again on the last day of the same workweek. Following each blood draw, blood tubes were stored at 4°C until processing. EDTA plasma samples for metabolomic analysis were centrifuged, aliquoted, and stored in the vapor phase of liquid nitrogen freezers at < -130°C. |
Sample Type: | Blood (plasma) |
Treatment:
Treatment ID: | TR002020 |
Treatment Summary: | This study included workers employed in the US trucking industry as drivers, dockworkers and office workers. Within this study population, exposure to common traffic-related pollutants was evaluated. No intervention was used. |
Sample Preparation:
Sampleprep ID: | SP002014 |
Sampleprep Summary: | Untargeted HRM profiling was completed using verified protocols. (Accardi et al. 2016a; Go et al. 2015) Plasma aliquots were removed from storage and thawed on ice. A 65 μL aliquot of plasma was then added to 130 μL of acetonitrile containing a mixture of stable isotopic standards that included [13C6]-D- glucose, [15N]-indole, [2-15N]-L-lysine dihydrochloride, [13C5]-L-glutamic acid, [13C7]-benzoic acid, [3,4-13C2]- cholesterol, [15N]-L-tyrosine, [trimethyl-13C3]-caffeine, [15N2]-uracil, [3,3-13C2]-cystine, [1,2-13C2]-palmitic acid, [15N,13C5]-L-methionine, [15N]-choline chloride, and 2’- deoxyguanosine-15N2,13C10-5’-monophosphate, vortexed, and allowed to equilibrate for 30 minutes. (Soltow et al. 2013) |
Processing Storage Conditions: | On ice |
Extraction Method: | 2:1 addition of acetonitrile |
Sample Spiking: | [13C6]-D-glucose, [15N,13C5]-L-methionine, [13C5]-L-glutamic acid, [15N]-L-tyrosine, [3,3-13C2]-cystine, [trimethyl-13C3]-caffeine, [U-13C5, U-15N2]-L-glutamine, [15N]-indole |
Combined analysis:
Analysis ID | AN003138 |
---|---|
Analysis type | MS |
Chromatography type | Reversed phase |
Chromatography system | Thermo Dionex Ultimate 3000 |
Column | Targa 100 mm x 2.1mm x 2.6 μm, Higgins Analytical Inc |
MS Type | ESI |
MS instrument type | Orbitrap |
MS instrument name | Thermo Q Exactive Orbitrap |
Ion Mode | POSITIVE |
Units | Peak area |
Chromatography:
Chromatography ID: | CH002320 |
Chromatography Summary: | Triplicate 10 μL aliquots were analyzed by reverse-phase C18 liquid chromatography (Targa 100 mm x 2.1mm x 2.6 μm, Higgins Analytical Inc) with detection by a Thermo Scientific Q-Exactive high-resolution mass spectrometer. Analyte separation was accomplished using water, acetonitrile and 2% [v/v] formic acid in water (solution A) mobile phases operating under the following gradient: initial 2 min period of 80% A, 5% water, 15% acetonitrile, followed by linear increase to 0% A, 5% water, 95% acetonitrile at 6 min and then held for an additional 4 min. Mobile phase flow rate was held at 0.35 mL/min for 6 min, and then increased to 0.5 mL/min. |
Instrument Name: | Thermo Dionex Ultimate 3000 |
Column Name: | Targa 100 mm x 2.1mm x 2.6 μm, Higgins Analytical Inc |
Column Temperature: | 60 |
Flow Gradient: | initial 2 min period of 80% A, 5% water, 15% acetonitrile, followed by linear increase to 0% A, 5% water, 95% acetonitrile at 6 min and then held for an additional 4 min |
Flow Rate: | Held at 0.35 mL/min for 6 min, and then increased to 0.5 mL/min |
Solvent A: | water/acetonitrile; 2% formic acid |
Chromatography Type: | Reversed phase |
MS:
MS ID: | MS002918 |
Analysis ID: | AN003138 |
Instrument Name: | Thermo Q Exactive Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | The high-resolution mass spectrometer was equipped with an electrospray ionization source operated in positive ion mode with spray voltage of 4.5 kV, probe, capillary temperature 275°C, sheath gas flow 45 (arbitrary units), auxiliary gas flow 5 (arbitrary units) and S-lens RF level of 69. Resolution was set at 70,000 (FWHM) and mass-to-charge (m/z) scan range 85-1275. Spectra were collected in full scan only without MSMS. Samples were analyzed in batches of 20, in addition to a quality control (QC) pooled reference sample included at the beginning and end of each batch of samples to evaluate batch effects and reproducibility of the detected metabolite features. Upon injection of all study and quality control samples, mass spectral features with replicate coefficient of variation (CV) ≤ 100% were extracted and aligned using apLCMS (Yu et al. 2013) with modifications by xMSanalyzer (Uppal et al. 2013) and batch effect correction by ComBat (Johnson et al. 2007). |
Ion Mode: | POSITIVE |
Capillary Voltage: | 275 |
Ionization: | Positive |