Life's Essential 8: key to reducing heart disease and mortality through epigenetics

In a recent study published in the Journal of the American Heart Association, researchers investigated whether Deoxyribonucleic Acid (DNA) methylation-based epigenetic age biomarkers mediate the associations between Life's Essential 8 (LE8) score and risks of cardiovascular disease (CVD), CVD-specific mortality, and all-cause mortality.

Study: Epigenetic Age Mediates the Association of LifeStudy: Epigenetic Age Mediates the Association of Life's Essential 8 With Cardiovascular Disease and Mortality. Image Credit: fizkes/


CVD is the leading cause of death in the United States (U.S). The American Heart Association (AHA) proposed a new cardiovascular health (CVH) metric, LE8, which includes diet, physical activity, nicotine exposure, sleep health, body mass index (BMI), blood lipid levels, blood glucose levels, and blood pressure.

Optimal levels of these factors reduce the risk of CVD and other diseases. However, ideal CVH levels are low among Americans. DNA methylation, influenced by genetics and lifestyle, is linked to CVD and mortality.

Further research is needed to understand better the molecular mechanisms by which DNA methylation influences CVH and to develop targeted prevention and intervention strategies.

About the study 

Data from participants in the Framingham Heart Study (FHS) Offspring and Third Generation cohorts were analyzed. Of the 6,432 participants at baseline, 5,682 had complete LE8 data, 4,130 had epigenetic age score data, and 3,693 had both.

The study received approval from the Institutional Review Boards of Boston University Medical Center and Tufts University, with written informed consent from participants.

LE8 scores were calculated using dietary intakes, physical activity indices, sleep hours, BMI, blood pressure, non‐high‐density lipoprotein cholesterol, and fasting glucose following AHA guidelines. Smoking scores followed AHA guidelines, with adjustments for those who recently quit.

DNA methylation profiles were measured using the Infinium HumanMethylation450 BeadChip, assessing approximately 450,000 Cytosine-phosphate-Guanine sites (CpGs).

Four DNA methylation-based epigenetic age scores, DunedinPACE, Phenotypic Age (PhenoAge), DNA methylation-based Telomere Length

(DNAmTL), and GrimAge were calculated. Polygenetic scores (PGS)s for PhenoAge and GrimAge were derived using Bayesian regression and genotype information.

Primary clinical outcomes included incident CVD, CVD-specific mortality, and all-cause mortality, tracked over a mean follow-up of 14 years for Offspring and 11 years for Third Generation participants.

Linear mixed models examined associations between LE8 and DNA methylation scores, while mixed proportional hazard models assessed risks of clinical outcomes. Mediation and interaction analyses explored the roles of DNA methylation and genetic background in the relationships between LE8 and clinical outcomes.

Study results 

The mean LE8 score among FHS participants was 68.7, with a range of 20.6 to 100 and a median of 68.8. Women and younger participants generally had higher LE8 scores.

The BMI component showed the highest correlation with the LE8 score (Pearson r=0.59), followed by blood pressure (r=0.55), blood glucose (r=0.52), diet (r=0.50), blood lipids (r=0.46), physical activity (r=0.40), smoking (r=0.38), and sleep (r=0.26).

The four epigenetic age scores were moderately correlated, with pairwise Pearson r values ranging from 0.28 to 0.68.

After adjusting for various factors, a higher LE8 score was associated with lower residuals for DunedinPACE, GrimAge, and PhenoAge, and higher residuals for DNAmTL. A 1 SD increase in the LE8 score (13 points) corresponded to 0.39 SD lower DunedinPACE, 0.42 SD lower GrimAge, 0.15 SD lower PhenoAge, and 0.10 SD higher DNAmTL.

Higher LE8 scores were linked to a lower risk of incident CVD, CVD-specific mortality, and all-cause mortality. Each 1 SD increase in LE8 score resulted in a 35% lower risk of incident CVD, a 36% lower risk of CVD-related mortality, and a 29% lower risk of all-cause mortality.

There was a dose-response relationship between LE8 scores and these outcomes. Health factors in the LE8 had stronger associations with incident CVD and CVD mortality, while health behaviors were more strongly associated with all-cause mortality.

Higher DunedinPACE, GrimAge, and PhenoAge scores and lower DNAmTL scores were linked to increased risks of incident CVD, all-cause mortality, and CVD-related mortality.

Mediation analyses showed that nearly all epigenetic age scores significantly mediated the associations between LE8 scores and clinical outcomes, with DunedinPACE and GrimAge scores showing the highest mediation proportions.

Stratified analyses by PGS showed significant interactions between LE8 scores and GrimAge and PhenoAge PGS, with stronger associations in participants with higher PGS values. Mediation analyses in stratified groups indicated significant effects for higher PGS groups, particularly for GrimAge, but not for lower PGS groups.


To summarize, this analysis in middle- to older-aged adults revealed a strong inverse relationship between CVH, as measured by the LE8 score, and the incidence of CVD, CVD-specific mortality, and all-cause mortality.

The study suggests that favorable CVH may lower CVD and mortality risks through epigenetic effects. The benefit of optimal CVH on reducing epigenetic burden is more evident in those genetically predisposed to an older epigenetic age.

Improving CVH appears to be a promising strategy to delay CVD onset and promote healthy aging. The findings emphasize the importance of promoting CVH in the general population, especially for those genetically predisposed to higher epigenetic age.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    


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