Published July 28, 2023 | Version v1
Dataset Open

Processed metabolomic data from the EXPOsOMICS Personal Exposure Monitoring study

Authors/Creators

  • 1. Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
  • 2. Swiss Tropical and Public Health Institute, Allschwil, Switzerland;University of Basel, Basel, Switzerland
  • 3. Italian Institute for Genomic Medicine (IIGM), c/o IRCCS, Turin, Italy
  • 4. Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
  • 5. National Heart and Lung Institute, Imperial College London, London, UK; NIHR Imperial Biomedical Research Centre, London, UK
  • 6. Medical Research Council-Public Health England Center for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, United Kingdom
  • 7. Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the NetherlandsDivision of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands;Medical Research Council-Public Health England Center for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
  • 8. Medical Research Council-Public Health England Center for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; Italian Institute for Genomic Medicine (IIGM), c/o IRCCS, Turin, Italy
  • 9. Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands;Medical Research Council-Public Health England Center for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom

Description

Metabolomic data from the 'Variability of the Human Serum Metabolome over 3 Months in the EXPOsOMICS Personal Exposure Monitoring Study' paper DOI: 10.1021/acs.est.3c03233 . 

The data was originally collected and generated by the multicenter EXPOsOMICS Personal Exposure Monitoring study. Details on data collection and processing are described in the aforementioned paper. The statistical analysis from that paper is available at https://github.com/moosterwegel/variability-metabolites-paper and may contain useful information/code to work with this data.

`processed_covariate_data.csv`:
```
Rows: 298
Columns: 7
$ subjectid: hashed identifier subject
$ sample_code: indicates if it's the first (A) or second (B) blood sample
$ centre: indicates in which centre the data was collected
$ age_cat: indicates age category at the time of a PEM session
$ sq_sex:  indicates the sex of the participant (male, female) as filled in during the screening questionaire
$ traf: indicates the exposure to traffic (PM2.5 and UFP) as measured during the PEM sessions. 
$ bmi_cat: indicates BMI category at the time of a PEM session
```

`processed_lcms_data data.csv` contains the processed LCMS data:
```
Rows: 298
Columns: 4297
$ subjectid: hashed identifier subject
$ sample_code: indicates if it's the first (A) or second (B) blood sample
$ centre: indicates in which centre the data was collected
$ compounds: measured features (compounds) are prefixed by the letter X. The name contains information on the measured monoisotopicmass_retentiontime.
Non-detects (below limit of detection (LOD) are coded as 1 for the compounds.
....
```
In the datasets each row indicates a measurement on a day (`sample_code`) and person (`subjectid`). The datasets can be joined on these variables.

The other data files (`annotations.xslx`, `ancestors_annotations.xlsx`, `annotations_plus_kegg_pathways.csv`) contain the annotations, ancestors of the annotations (to assign a class to a compound based on ChEBI ontology, see our paper for details), annotations plus KEGG pathways respectively. 

Notes

The study center in Basel was additionally funded by Grants from the Swiss National Science Foundation 33CS30-148470 and 33CS30-177506. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/World Health Organization.

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Additional details

Related works

Is published in
Journal article: 10.1021/acs.est.3c03233 (DOI)

Funding

Dutch Research Council
Exposome-NL 34729
European Commission
EXPANSE - EXposome Powered tools for healthy living in urbAN SEttings 874627
European Commission
EXPOSOMICS - Enhanced exposure assessment and omic profiling for high priority environmental exposures in Europe. 308610