Evidence map›Paper›PMID 30879037›Full record

ArticleInternational journal of epidemiology2019

Shift work, DNA methylation and epigenetic age.

Alexandra J White, Jacob K Kresovich, Zongli Xu, Dale P Sandler, Jack A Taylor

Abstract read
In one paragraph

Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 2 pooled it
–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

42 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

5 authors.

Alexandra J WhiteEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.
Jacob K KresovichEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.
Zongli XuEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.
Dale P SandlerEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.
Jack A TaylorEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.

Funding

Environmental and Genetic Risk Factors For Breast Cancer: The Sister StudyZIAES044005 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 2009 to 2025
$22.7M
Environmental Exposure and DNA DamageZIAES049032 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI TAYLOR, JACK A · 2009 to 2022
$13.4M
Environment and Cancer EpidemiologyZIAES103332 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WHITE, ALEXANDRA · 2019 to 2025
$8.9M
Genetic Susceptibility And The Environment In Cancer RiskZIAES049033 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI TAYLOR, JACK A · 2009 to 2022
$7.7M
GENETIC SUSCEPTIBILITY AND THE ENVIRONMENT IN CANCER RISKZ01ES049033 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI TAYLOR, JACK A · 1997 to 2008
$1.4M
Genetic and Environmental Risk Factors for Breast Cancer: The Sister StudyZ01ES044005 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 1999 to 2008
$1.3M
EXPOSURE SPECIFIC MUTATION IN CRITICAL TARGET GENESZ01ES049032 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI TAYLOR, JACK A · 1997 to 2008
$1.0M
Intramural NIH HHS Z01 ES044005Intramural NIH HHS Z01 ES049032Intramural NIH HHS Z01 ES049033NIEHS NIH HHS Z01 ES044005NIEHS NIH HHS Z01 ES049032NIEHS NIH HHS Z01 ES049033
6 · The paper itself

Abstract

backgroundShift work has been associated with increased risk of age-related morbidity and mortality. Biological age, estimated using DNA methylation (DNAm), may quantify the biological consequences of shift work on the risk of age-related disease. We examined whether prior employment in shift-working occupations was associated with epigenetic age acceleration.

methodsIn a sample of non-Hispanic White women aged 35-74 (n = 2574), we measured DNAm using the Illumina Infinium Human450 BeadChip and calculated DNAm age using three established epigenetic clocks. Age-acceleration metrics were derived by regressing DNAm age on chronological age and predicting the residuals. Using linear regression, we estimated associations between shift work history and age acceleration. We also conducted an epigenome-wide association study using robust linear-regression models corrected with false discovery rate (FDR) q-values.

resultsApproximately 7% of women reported any shift work. Higher age acceleration was observed for a 1-year increase in overall [β = 0.11, 95% confidence interval (CI): 0.02-0.21] and night-specific shift work (β = 0.12, 95% CI: 0.03-0.21). The association was strongest for ≥10 years of night shift work (β = 3.16, 95% CI: 1.17-5.15). From the epigenome-wide association study, years of overall and night shift work were associated with DNAm at 66 and 85 CpG sites (FDR < 0.05), respectively. Years of night shift work was associated with lower methylation of a CpG in the gene body of ZFHX3 (cg04994202, q = 0.04), a gene related to circadian rhythm.

conclusionsShift work was associated with differential CpG site methylation and with differential DNAm patterns, measured by epigenetic age acceleration, consistent with long-term negative health effects.

Indexed as

DNA MethylationAdultAgedAgingCpG IslandsEpigenesis, GeneticFemaleGenome-Wide Association StudyHumansLinear ModelsMiddle AgedProspective StudiesShift Work Scheduleageingcircadian rhythmDNA methylationepigenomicsShift-work schedule

Identifiers

PMID30879037
PMCPMC6857743

What OpenQuestion holds

Textmetadata
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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.