Epigenetic clock analysis of diet, exercise, education, and lifestyle factors

By Austin Quach, M. Levine, Toshiko Tanaka, A. Lu, Brian H. Chen, Luigi Ferrucci, B. Ritz, Stefania Bandinelli, M. Neuhouser, J. Beasley and 11 more. Aging, 2017

671 citations recorded by the source corpus.

Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti. Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3×10-5), BMI (p=0.01), and blood carotenoid levels (p=1×10-5)—an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin—the first-line medication for the treatment of type 2 diabetes—does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA. Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

Subfields: Endocrine and Autonomic Systems, Pediatrics, Perinatology and Child Health, Physiology

View Paper: https://www.semanticscholar.org/paper/45202663d2f6259bca3951bc61793c2ebe4487d3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Endocrine and Autonomic Systems

M. Levine

In Pediatrics, Perinatology and Child Health

In Physiology

Citations in the corpus

Measuring biological aging in humans: A quest (2019, background): “Their discovery has been confirmed by many studies across tissues, individuals, and populations, in addition to examining gestational age, and in longitudinal analyses (Horvath, 2013; Knight et al., 2016; Maierhofer et al., 2017; Quach et al., 2017; Sehl, Henry, Storniolo, Ganz, & Horvath, 2017).”
Biological Age Predictors (2017, background): “Both the Horvath and the Hannum clock have also demonstrated associationswith an increase in BMI andwith indicators of the metabolic syndrome (Quach et al., 2017).”
An epigenetic biomarker of aging for lifespan and healthspan (2018, background): “The first generation of DNAm age estimators only exhibit weak associations with clinical measures of physiological dysregulation [24, 45].”
Immunosenescence and Inflamm-Aging As Two Sides of the Same Coin: Friends or Foes? (2018, background): “Specific epigenetic diets may have their role in this modulation (124, 125).”