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Related Experiment Video

Updated: May 6, 2026

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Challenges and Good Practices in Preprocessing and Normalization of Untargeted DNA Adductomics Data in Exposomics

Pablo Vangeenderhuysen1, Matthijs Vynck1, Liesa Engelen2

  • 1Laboratory of Integrative Metabolomics (LIMET), Ghent University, 9820 Merelbeke, Belgium.

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Summary

This study optimizes untargeted DNA adductomics data preprocessing for exposomics research. We developed a reproducible workflow using the xcms R package for reliable analysis of large sample sets.

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Area of Science:

  • Environmental Health Sciences
  • Analytical Chemistry
  • Biomolecular Analysis

Background:

  • DNA adductomics is crucial for exposomics, but lacks standardized preprocessing for large sample series.
  • Untargeted DNA adductomics data preprocessing is essential for accurate analysis but is seldom applied.
  • Optimizing data preprocessing is vital for advancing exposomics research through DNA adductomics.

Purpose of the Study:

  • To optimize a DNA adductomics data preprocessing workflow in true untargeted mode.
  • To establish a reproducible procedure for analyzing large sample series in DNA adductomics.
  • To evaluate normalization methods for reliable downstream data analysis in DNA adductomics.

Main Methods:

  • Utilized the xcms R package to optimize parameters for peak detection, retention time alignment, and peak grouping.
  • Applied LC-MS data from placental tissue (n=375) and blood samples (n=51) for workflow optimization.
  • Tested and quantitatively evaluated six sample- and feature-based normalization methods.

Main Results:

  • A successful and reproducible procedure for optimizing xcms parameters for DNA adductomics was developed.
  • Evaluation of normalization methods highlighted the importance and limitations of objective (RSD*, D-ratio) and subjective (PCA score plot) metrics.
  • The optimized workflow enables reliable detection and integration of putative DNA adduct LC-MS peaks.

Conclusions:

  • The proposed workflow supports reproducible and transparent untargeted DNA adductomics data preprocessing.
  • This advancement is critical for implementing DNA adductomics in large-scale exposomics studies.
  • Standardized preprocessing enhances the reliability and comparability of DNA adductomics data.