Published March 5, 2026 | Version v1
Preprint Open

Air pollution exposure in Generation Scotland: molecular fingerprints and health outcomes

Authors/Creators

  • 1. ROR icon Institute of Science and Technology Austria
  • 2. EDMO icon University of Edinburgh
  • 3. Imperial College London
  • 4. ROR icon The Francis Crick Institute
  • 5. UK Centre for Ecology and Hydrology
  • 6. Eliptica
  • 7. ROR icon University of Liverpool
  • 8. Eliptica Limited
  • 9. ROR icon University of Zurich
  • 10. ROR icon King's College London
  • 11. ROR icon Chalmers University of Technology
  • 12. Charite Universitaetsmedizin Berlin
  • 13. EDMO icon University of Edinburgh, School of GeoSciences
  • 14. Institute of Science and Techology Austria

Description

Air pollution exposure in Generation Scotland: molecular fingerprints and health outcomes

Ambient air pollution has been associated with increased incidence of chronic disease and is estimated to contribute towards 4.2 million early deaths annually. Whilst the health impacts are well described, less is understood about the underlying biological mechanisms, particularly when considering the co-occurrence of multiple pollutants. Using an atmospheric chemistry transportation model (EMEP4UK), we generate pre-baseline sampling pollution exposure estimates for eight pollutants in Generation Scotland (N = 22,071, recruited between 2006 - 2011). Cox-proportional hazard models reveal associations between pollution exposure and all-cause dementia (PM2.5) and myocardial infarction (NO3_Coarse) over 18 years of follow-up. We perform Bayesian multivariate epigenome-wide (N = 18,512, Illumina EPIC v.1) and proteomic (N = 15,314, 133 mass-spectrometry proteins) association studies, revealing 11 pollutant-methylation associations and 140 pollutant-protein associations. We identify positive associations between exposure (PM2.5 and NO3_Fine) and epigenetic age-acceleration (PhenoAge epigenetic clock). Furthermore, we explore the development of pollutant EpiScores, assessing these in holdout and independent test sets. Our results enhance knowledge of molecular correlates of air pollution exposure, whilst providing further evidence of contributions of air pollutants to chronic disease.

This dataset contains EWAS and PWAS summary statistics from multivariate and univariate analyses of different pollution exposure durations.

Preprint url: https://www.medrxiv.org/content/10.64898/2026.03.04.26347573v1

Files

gmrm_fullresults_EWAS_1yr.csv

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Additional details

Software

Repository URL
https://github.com/marioni-group/GS_Molecular_markers_air_pollution