Evidence map›Paper›PMID 41834712›Full record

ArticleAnalytical chemistry2026

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

Pablo Vangeenderhuysen, Matthijs Vynck, Liesa Engelen, Adrian Covaci, Tim Nawrot, Trancizeo Lipenga, Roger Pero-Gascon, Sarah De Saeger, Marthe De Boevre, Valerie McCormack and 2 more

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Article in Analytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Pablo VangeenderhuysenLaboratory of Integrative Metabolomics (LIMET), Ghent University, 9820 Merelbeke, Belgium.ORCID 0000-0002-5492-6904
Matthijs VynckLaboratory of Integrative Metabolomics (LIMET), Ghent University, 9820 Merelbeke, Belgium.ORCID 0000-0001-9875-385X
Liesa EngelenCentre for Environmental Sciences, Hasselt University, 3590 Diepenbeek, Belgium.
Adrian CovaciToxicological Centre, University of Antwerp, 2610 Wilrijk, Belgium.ORCID 0000-0003-0527-1136
Tim NawrotCentre for Environmental Sciences, Hasselt University, 3590 Diepenbeek, Belgium.
Trancizeo LipengaDepartment of Bioanalysis, Centre of Excellence in Mycotoxicology and Public Health, Ghent University, 9000 Ghent, Belgium.
Roger Pero-GasconDepartment of Bioanalysis, Centre of Excellence in Mycotoxicology and Public Health, Ghent University, 9000 Ghent, Belgium.
Sarah De SaegerDepartment of Bioanalysis, Centre of Excellence in Mycotoxicology and Public Health, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0002-2160-7253
Marthe De BoevreDepartment of Bioanalysis, Centre of Excellence in Mycotoxicology and Public Health, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0002-6151-5126
Valerie McCormackEnvironment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer (WHO-IARC), 69007 Lyon, France.
Lynn VanhaeckeLaboratory of Integrative Metabolomics (LIMET), Ghent University, 9820 Merelbeke, Belgium.ORCID 0000-0003-0400-2188
Lieselot Y HemeryckLaboratory of Integrative Metabolomics (LIMET), Ghent University, 9820 Merelbeke, Belgium.ORCID 0000-0002-2451-3375

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA adductomics is the study of the whole of DNA adducts in a biological sample and is a valuable asset to exposomics research. To date, a clear view on how to analyze larger sample series is lacking in DNA adductomics, and the preprocessing of untargeted DNA adductomics data is seldom applied. This work aimed to optimize a DNA adductomics data preprocessing workflow (in true untargeted mode). Building upon the xcms R package, we optimized parameters for peak detection, retention time alignment, and peak grouping to reliably detect and integrate putative DNA adduct LC-MS peaks. Next, to ensure reliable downstream data analysis, six sample- and feature-based normalization methods were tested and quantitatively evaluated in two data sets (placental tissue,

Indexed as

DNA AdductsFemaleHumansLiquid Chromatography-Mass SpectrometryPlacentaPregnancyDNA Adducts

Identifiers

PMID41834712
PMCPMC13147328

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.