Evidence map›Paper›PMID 30794318›Full record

ArticleJournal of the National Cancer Institute2019

Methylation-Based Biological Age and Breast Cancer Risk.

Jacob K Kresovich, Zongli Xu, Katie M O'Brien, Clarice R Weinberg, Dale P Sandler, Jack A Taylor

Open access · greenAbstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing papers in PubMed, 5 pooled it
8.9field-weighted citation impact, top 1% 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

127 citing papers in PubMed, 5 syntheses or guidelines pooled it, 197 citations in OpenAlex.

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  16. Association of Epigenetic Aging Biomarkers With Risk of MASLD-Related HCC.Liver international : official journal of the International Association for the Study of the Liver · 2026
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67 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Jacob K Kresovich
Zongli Xu
Katie M O'Brien
Clarice R Weinberg
Dale P Sandler
Jack A Taylor
National Institute of Environmental Health Sciences · US

Funding

Molecular Genetics Support to Identify Gene/Environment Interactions in DiseaseZICES102546 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI GERRISH, KEVIN · 2009 to 2025
$30.5M
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
The Two Sister StudyZIAES102245 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2009 to 2025
$8.6M
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 ES049033
6 · The paper itself

Abstract

backgroundAge is one of the strongest predictors of cancer, chronic disease, and mortality, but biological responses to aging differ among people. Epigenetic DNA modifications have been used to estimate "biological age," which may be a useful predictor of disease risk. We tested this hypothesis for breast cancer.

methodsUsing a case-cohort approach, we measured baseline blood DNA methylation of 2764 women enrolled in the Sister Study, 1566 of whom subsequently developed breast cancer after an average of 6 years. Using three previously established methylation-based "clocks" (Hannum, Horvath, and Levine), we defined biological age acceleration for each woman by comparing her estimated biological age with her chronological age. Hazard ratios and 95% confidence intervals for breast cancer risk were estimated using Cox regression models. All statistical tests were two-sided.

resultsEach of the three clocks showed that biological age acceleration was statistically significantly associated with increased risk of developing breast cancer (5-year age acceleration, Hannum's clock: hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.00 to 1.21, P = .04; Horvath's clock: HR = 1.08, 95% CI = 1.00 to 1.17, P = .04; Levine's clock: HR = 1.15, 95% CI = 1.07 to 1.23, P < .001). For Levine's clock, each 5-year acceleration in biological age corresponded with a 15% increase in breast cancer risk. Although biological age may accelerate with menopausal transition, age acceleration in premenopausal women independently predicted breast cancer. Case-only analysis suggested that, among women who develop breast cancer, increased age acceleration is associated with invasive cancer (odds ratio for invasive = 1.09, 95% CI = 0.98 to 1.22, P = .10).

conclusionsDNA methylation-based measures of biological age may be important predictors of breast cancer risk.

Indexed as

Disease SusceptibilityDNA MethylationAdultAgedAgingBreast NeoplasmsDinucleoside PhosphatesEpigenesis, GeneticFemaleGene Expression RegulationGenetic Predisposition to DiseaseHumansMiddle AgedOdds RatioPrognosisProportional Hazards Modelscytidylyl-(3'-5')-cytidineDinucleoside Phosphates

Identifiers

PMID30794318
PMCPMC6792078
OpenAlexW2917830189

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.