Evidence map›Paper›PMID 35732753›Full record

ArticleScientific reports2022

Association between DNA methylation variability and self-reported exposure to heavy metals.

Anna Freydenzon, Marta F Nabais, Tian Lin, Kelly L Williams, Leanne Wallace, Anjali K Henders, Ian P Blair, Naomi R Wray, Roger Pamphlett, Allan F McRae

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

10 authors.

Anna FreydenzonInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Marta F NabaisInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Tian LinInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Kelly L WilliamsCentre for Motor Neuron Disease Research, Macquarie University, Exeter, NSW, 2109, Australia.
Leanne WallaceInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Anjali K HendersInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Ian P BlairCentre for Motor Neuron Disease Research, Macquarie University, Exeter, NSW, 2109, Australia.
Naomi R WrayInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Roger PamphlettBrain and Mind Centre, The University of Sydney, Sydney, NSW, 2050, Australia.
Allan F McRaeInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. a.mcrae@uq.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals encounter varying environmental exposures throughout their lifetimes. Some exposures such as smoking are readily observed and have high personal recall; others are more indirect or sporadic and might only be inferred from long occupational histories or lifestyles. We evaluated the utility of using lifetime-long self-reported exposures for identifying differential methylation in an amyotrophic lateral sclerosis cases-control cohort of 855 individuals. Individuals submitted paper-based surveys on exposure and occupational histories as well as whole blood samples. Genome-wide DNA methylation levels were quantified using the Illumina Infinium Human Methylation450 array. We analyzed 15 environmental exposures using the OSCA software linear and MOA models, where we regressed exposures individually by methylation adjusted for batch effects and disease status as well as predicted scores for age, sex, cell count, and smoking status. We also regressed on the first principal components on clustered environmental exposures to detect DNA methylation changes associated with a more generalised definition of environmental exposure. Five DNA methylation probes across three environmental exposures (cadmium, mercury and metalwork) were significantly associated using the MOA models and seven through the linear models, with one additionally across a principal component representing chemical exposures. Methylome-wide significance for four of these markers was driven by extreme hyper/hypo-methylation in small numbers of individuals. The results indicate the potential for using self-reported exposure histories in detecting DNA methylation changes in response to the environment, but also highlight the confounded nature of environmental exposure in cohort studies.

Indexed as

DNA MethylationMetals, HeavyEnvironmental ExposureHumansSelf ReportSmokingMetals, Heavy

Identifiers

PMID35732753
PMCPMC9217962

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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.