Evidence map›Paper›PMID 35799271›Full record

ArticleClinical epigenetics2022

Relative contributions of six lifestyle- and health-related exposures to epigenetic aging: the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Kyeezu Kim, Yinan Zheng, Brian T Joyce, Hongmei Jiang, Philip Greenland, David R Jacobs, Kai Zhang, Lei Liu, Norrina B Allen, John T Wilkins and 3 more

Abstract read
In one paragraph

Article in Clinical epigenetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Quantification of Epigenetic Aging in Public Health.Annual review of public health · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. The Role of Aryl Hydrocarbon Receptor in Bone Biology.International journal of tryptophan research : IJTR · 2024
    Review
  20. Article
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

13 authors.

Kyeezu KimDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Yinan ZhengDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Brian T JoyceDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Hongmei JiangDepartment of Statistics, Northwestern University, Evanston, IL, USA.
Philip GreenlandDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
David R JacobsDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA.
Kai ZhangDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA.
Lei LiuDivision of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA.
Norrina B AllenDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
John T WilkinsDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Sarah N ForresterDepartment of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA.
Donald M Lloyd-JonesDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Lifang HouDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA. l-hou@northwestern.edu.

Funding

Pregnancy-Related Risk Factors and Glucose Intolerance in Women during MidlifeR01DK106201 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI GUNDERSON, ERICA PAULINE · 2015 to 2018
$2.7M
Epigenetic Determinants of Lipoproteins Across the Early Adult Life CourseR01HL146844 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI WILKINS, JOHN THOMAS · 2020 to 2023
$2.2M
Innovative Analytical Methods for DNA Methylation AgeR21AG068955 · NIA · WASHINGTON UNIVERSITY · PI LIU, LEI, ZHENG, YINAN · 2021 to 2022
$448k
NHLBI NIH HHS HHSN268201800003INHLBI NIH HHS HHSN268201800004INHLBI NIH HHS HHSN268201800005INHLBI NIH HHS HHSN268201800006INHLBI NIH HHS HHSN268201800007INHLBI NIH HHS R01 HL146844NIA NIH HHS R21 AG068955NIDDK NIH HHS R01 DK106201
6 · The paper itself

Abstract

backgroundDNA methylation-based GrimAge acceleration (GrimAA) is associated with a wide range of age-related health outcomes including cardiovascular disease. Since DNA methylation is modifiable by external and behavioral exposures, it is important to identify which of these exposures may have the strongest contributions to differences in GrimAA, to help guide potential intervention strategies. Here, we assessed the relative contributions of lifestyle- and health-related components, as well as their collective association, to GrimAA.

resultsWe included 744 participants (391 men and 353 women) from the Coronary Artery Risk Development in Young Adults (CARDIA) study with blood DNA methylation information at CARDIA Exam Year (Y) 20 (2005-2006, mean age 45.9 years). Six cumulative exposures by Y20 were included in the analysis: total packs of cigarettes, total alcohol consumption, education years, healthy diet score, sleep hours, and physical activity. We used quantile-based g-computation (QGC) and Bayesian kernel machine regression (BKMR) methods to assess the relative contribution of each exposure to a single overall association with GrimAA. We also assessed the collective association of the six components combined with GrimAA. Smoking showed the greatest positive contribution to GrimAA, accounting for 83.5% of overall positive associations of the six exposures with GrimAA (QGC weight = 0.835). The posterior inclusion probability (PIP) of smoking also achieved the highest score of 1.0 from BKMR analysis. Healthy diet and education years showed inverse contributions to GrimAA. We observed a U-shaped pattern in the contribution of alcohol consumption to GrimAA. While smoking was the greatest contributor across sex and race subgroups, the relative contributions of other components varied by subgroups.

conclusionsSmoking, alcohol consumption, and education showed the highest contributions to GrimAA in our study. Higher amounts of smoking and alcohol consumption were likely to contribute to greater GrimAA, whereas achieved education was likely to contribute to lower GrimAA. Identifying pertinent lifestyle- and health-related exposures in a context of collective components can provide direction for intervention strategies and suggests which components should be the primary focus for promoting younger GrimAA.

Indexed as

Coronary VesselsDNA MethylationAgingBayes TheoremEpigenesis, GeneticFemaleHumansLife StyleMaleMiddle AgedRisk FactorsYoung AdultAccelerated epigenetic ageDNA methylationEpigenetic agingLifestyle- and health-related components

Identifiers

PMID35799271
PMCPMC9264709

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Registered trials

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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.