Evidence map›Paper›PMID 23855992›Full record

ArticleParticle and fibre toxicology2013

Evolutionary age of repetitive element subfamilies and sensitivity of DNA methylation to airborne pollutants.

Hyang-Min Byun, Valeria Motta, Tommaso Panni, Pier Alberto Bertazzi, Pietro Apostoli, Lifang Hou, Andrea A Baccarelli

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Particle and fibre toxicology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% of its field
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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.

  1. Welding Fume Exposure and Epigenetic Alterations: A Systematic Review.International journal of environmental research and public health · 2019
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  10. Particulate matter-induced hypomethylation of Alu and LINE1 in normal human bronchial epithelial cells and epidermal keratinocytes.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2022
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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

7 authors at 5 institutions in 2 countries.

Hyang-Min ByunLaboratory of Environmental Epigenetics, Exposure Epidemiology and Risk Program, Harvard School of Public Health, Boston, MA, USA. hmbyun@hsph.harvard.edu
Valeria Motta
Tommaso Panni
Pier Alberto Bertazzi
Pietro Apostoli
Lifang Hou
Andrea A Baccarelli
Harvard University · USBrescia University · USFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITNorthwestern University · USUniversity of Milano-Bicocca · IT

Funding

Molecular and Epigenetic Mitochondriomics of Air Particles, Lead and CognitionR01ES021733 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BACCARELLI, ANDREA · 2012 to 2015
$2.4M
Histone modifications and respiratory effects of traffic particle exposureR21ES020984 · NIEHS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI BACCARELLI, ANDREA, HOU, LIFANG · 2012 to 2013
$455k
Air Pollution, Epigenetics and Cardiovascular Health: A Human Intervention TrialR21ES021895 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BACCARELLI, ANDREA · 2012 to 2013
$376k
NIEHS NIH HHS ES020010NIEHS NIH HHS ES020984NIEHS NIH HHS ES021733NIEHS NIH HHS ES021895NIEHS NIH HHS R01 ES021733
6 · The paper itself

Abstract

backgroundRepetitive elements take up >40% of the human genome and can change distribution through transposition, thus generating subfamilies. Repetitive element DNA methylation has associated with several diseases and environmental exposures, including exposure to airborne pollutants. No systematic analysis has yet been conducted to examine the effects of exposures across different repetitive element subfamilies. The purpose of the study is to evaluate sensitivity of DNA methylation in differentially‒evolved LINE, Alu, and HERV subfamilies to different types of airborne pollutants.

methodsWe sampled a total of 120 male participants from three studies (20 high-, 20 low-exposure in each study) of steel workers exposed to metal-rich particulate matter (measured as PM10) (Study 1); gas-station attendants exposed to air benzene (Study 2); and truck drivers exposed to traffic-derived elemental carbon (Study 3). We measured methylation by bisulfite-PCR-pyrosequencing in 10 differentially‒evolved repetitive element subfamilies.

resultsHigh-exposure groups exhibited subfamily-specific methylation differences compared to low-exposure groups: L1PA2 showed lower DNA methylation in steel workers (P=0.04) and gas station attendants (P=0.03); L1Ta showed lower DNA methylation in steel workers (P=0.02); AluYb8 showed higher DNA methylation in truck drivers (P=0.05). Within each study, dose-response analyses showed subfamily-specific correlations of methylation with exposure levels. Interaction models showed that the effects of the exposures on DNA methylation were dependent on the subfamily evolutionary age, with stronger effects on older LINEs from PM10 (p‒interaction=0.003) and benzene (p‒interaction=0.04), and on younger Alus from PM10 (p-interaction=0.02).

conclusionsThe evolutionary age of repetitive element subfamilies determines differential susceptibility of DNA methylation to airborne pollutants.

Indexed as

Air PollutionRepetitive Sequences, Nucleic AcidAdultAir Pollutants, OccupationalBenzeneCpG IslandsDNA MethylationEvolution, MolecularHumansInhalation ExposureMaleMiddle AgedOccupational ExposureParticulate MatterPolymerase Chain ReactionSequence Analysis, DNAAir Pollutants, OccupationalBenzeneParticulate MatterSteelVehicle Emissions

Identifiers

PMID23855992
PMCPMC3717285
OpenAlexW2140136687

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.