Summary of Study ST001801
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 PR001136. The data can be accessed directly via it's Project DOI: 10.21228/M8VQ4D 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 | ST001801 |
| Study Title | CHDWB human plasma exposomics analysis - 1 |
| Study Type | Untargeted MS anlaysis |
| Study Summary | We analyzed 80 archival samples from individuals (57 females, 23 males; aged 41 to 68 y) without known disease or occupational or environmental exposures of concern as a pilot to test the utility of XLE in large-scale human biomonitoring studies. Using a requirement for at least 3 co-eluting accurate mass m/z features ( 5 ppm) within 30 s of database retention time, we identified 49 chemicals belonging to various environmental chemical classes. An unsupervised 2-way hierarchical cluster analysis (HCA) of log transformed intensity showed clustering according to chemical class. In particular, persistent chemicals were highly correlated with each other (all raw P < 0.001), including p,p’-DDE, PCBs 153, 180, 138, 118 and 74, PBDE-47, hexachlorobenzene (HCB) and trans-nonachlor. Results showed a general increase of chemical levels with increasing age quartiles (Q3 and Q4 : 53 to 68 versus Q1 and Q2: 41 to 52) using unsupervised clustering, a trend particularly evident for the cluster of p,p’-DDE, PCBs 153, 180, 138, 118 and 74, PBDE-47, HCB and trans-nonachlor. Examination of data according to body mass index (BMI) showed that individuals with BMI ≥ 40 had lower levels of environmental chemicals, which may be attributed to high lipophilicity and propensity to distribute in adipose tissue versus plasma. Quantification with reference standardization showed that use of two SRM samples with differing environmental chemical concentrations can overcome variable batch effects in quantification for large-scale studies. Examples of the most frequently detected chemicals shows that overall distributions were positively skewed by a small subset of individuals with high concentrations. |
| Institute | Emory University |
| Department | Medicine/Pulmonary |
| Laboratory | Dean Jones |
| Last Name | Hu |
| First Name | Xin |
| Address | Emory University Whitehead building (Rm 225), 615 Michael Street |
| xin.hu2@emory.edu | |
| Phone | 4047275091 |
| Submit Date | 2021-05-06 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | GC-MS |
| Release Date | 2021-05-28 |
| Release Version | 1 |
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Combined analysis:
| Analysis ID | AN002923 |
|---|---|
| Analysis type | MS |
| Chromatography type | GC |
| Chromatography system | Thermo Trace 1310 |
| Column | Agilent DB5-MS (15m x 0.25mm,0.25um) |
| MS Type | EI |
| MS instrument type | Orbitrap |
| MS instrument name | Thermo Q Exactive Orbitrap |
| Ion Mode | POSITIVE |
| Units |
