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Measuring Age: Steve Horvath, PhD, and Epigenetic Clocks

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When a person is asked how old they are, the number of years since their birth is a typical response. However, if age is measured in terms of biology, individuals of the same chronological age may be older or younger due to differing susceptibilities or risk levels for age-related diseases.

Underlying biological aging processes down to the epigenomic function of cells and tissues help to explain discrepancies in the manifestation of aging.1,2 DNA methylation (DNAm) is an epigenetic mechanism that regulates gene expression and has been associated with biological aging in humans. This association forms the basis for epigenetic clocks that measure age across tissue types and predict health outcomes.1-4 How can DNAm biomarkers of aging inform personalized health care? Can lifestyle interventions impact epigenetic aging to extend the lifespan as well as the healthspan? Steve Horvath, PhD, ScD, who developed the first generation of a DNAm-based biomarker of aging known as Horvath’s Clock, will explore this topic at IFM’s 2021 AIC in his presentation, Epigenetic Clocks for Clinical and Preclinical Applications.

Dr. Steve Horvath, Epigenetic Clocks, and Predicting Health Outcomes

Dr. Horvath develops and applies methodological approaches at the intersection of systems biology, genetics, chronic disease, epidemiology, bioinformatics, biostatistics, and machine learning. He is known for developing a biomarker of aging known as the epigenetic clock that is based on DNAm, which is known to be highly accurate and relevant for multiple tissue types. In addition, Dr. Horvath developed the widely used data mining method called weighted correlation network analysis, which can be used when studying biological networks.

Dr. Steven Horvath, PhD, ScD
Steve Horvath, PhD, ScD, developed the first-generation epigenetic biomarker of aging known as Horvath’s Clock and will be exploring the clinical applications of epigenetic clocks at IFM’s AIC 2021.

Dr. Horvath’s continuing age-related research investigates the relationship between methylation and the processes of epigenetic aging.5 This includes an epigenetic clock measure that goes beyond prediction of chronological age to the prediction of health outcomes for an individual3,6 and even to measuring the pace of biological aging.4 Epigenetic clock models that have been developed include Horvath, Hannum, PhenoAge, GrimAge, telomere length, and DunedinPoAm, which acts as a speedometer measurement of aging.4 A 2020 study tested the association between some epigenetic measures of aging and the prevalence and incidence of diseases and mortality. Among the results, researchers found that:4

  • DNAm PhenoAge predicted incidence of type 2 diabetes.
  • DNAm GrimAge is associated with all-cause mortality and predicted incidence of chronic obstructive pulmonary disease (COPD), type 2 diabetes, and ischemic heart disease after 13 years of follow-up.
  • DNAm telomere length is associated with the incidence of ischemic heart disease.
  • DunedinPoAm predicted the incidence of COPD and lung cancer.

DNAm biomarkers of aging have also demonstrated the ability to predict cardiovascular disease and coronary heart disease,2 and as the predictive utility of epigenetic clocks expands, predictions of age-related health outcomes for specific populations may be possible. As an example, the DNAm GrimAge epigenetic clock has been noted for its predictive ability for time-to-death, time-to-coronary heart disease, and time-to-cancer.3 A 2020 study was the first to assess DNAm GrimAge in patients with post-traumatic stress disorder (PTSD).7 Using two independent cohorts of trauma-exposed combat veterans with and without PTSD, researchers investigated the acceleration of GrimAge relative to chronological age, termed AgeAccelGrim.7 In both cohorts, the AgeAccelGrim was significantly higher in the PTSD group compared to the control group, suggesting accelerated biological aging in those patients with PTSD.7 

Epigenetic aging is an integral part of both the overall aging process and of the life-course stages that occur during the development and the homeostasis of organisms.5 Of course, environmental factors may impact the speed of biological aging and ultimately the lifespan and healthspan as well. Epigenetic clocks may provide insight into promising clinical interventions that positively impact an individual’s health at the molecular level.

Pilot Clinical Trial: Lifestyle Factors & Epigenetic Aging

Specific to lifestyle intervention impacts on epigenetic age, a new randomized controlled pilot trial led by researcher and IFM educator Kara Fitzgerald, ND, IFMCP, reported groundbreaking results.8 The trial included 43 healthy adult males (~84% self-identified as white, Caucasian, or European American) between the ages of 50 and 72. Approximately half of the participants followed an eight-week treatment program that included diet, sleep, exercise, and relaxation guidance plus supplemental probiotics and phytonutrients. The remaining participants served as the control group and received no intervention. Details of the treatment were as follows:8

  • The dietary intervention was plant-centered, with high intake of nutrients that support methylation pathways (e.g., folate, vitamin C, vitamin A, curcumin, quercetin, etc.), included limited animal proteins and carbohydrates as well as intermittent fasting periods, and supplemented diet with daily fruit and vegetable powder as well as probiotics.
  • Lifestyle guidance included a minimum of 30 minutes of exercise per day at least five days per week at 60-80% intensity, 20-minute breathing exercises that elicit the relaxation response twice per day, and the recommendation of at least seven hours of sleep each night.

Researchers conducted DNAm analysis on saliva samples from participants, and epigenetic age was calculated using the online Horvath DNAmAge clock. Results found that the diet and lifestyle treatment was associated with a 3.23 year decrease in DNAmAge compared with controls. This first-of-its-kind controlled study suggests that specific diet and lifestyle interventions may reverse epigenetic aging in healthy adult males.8

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References

  1. Horvath S. DNA methylation age of human tissues and cell types [published correction appears in Genome Biol. 2015;16(1):96]. Genome Biol. 2013;14(10):R115. doi:10.1186/gb-2013-14-10-r115
  2. Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573-591. doi:10.18632/aging.101414
  3. Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019;11(2):303-327. doi:10.18632/aging.101684
  4. Hillary RF, Stevenson AJ, McCartney DL, et al. Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden. Clin Epigenetics. 2020;12(1):115. doi:10.1186/s13148-020-00905-6
  5. Raj K, Horvath S. Current perspectives on the cellular and molecular features of epigenetic ageing. Exp Biol Med (Maywood). 2020;245(17):1532-1542. doi:10.1177/1535370220918329
  6. McCrory C, Fiorito G, Hernandez B, et al. GrimAge outperforms other epigenetic clocks in the prediction of age-related clinical phenotypes and all-cause mortality. J Gerontol A Biol Sci Med Sci. 2020:76(5):741-749. doi:10.1093/gerona/glaa286
  7. Yang R, Wu GWY, Verhoeven JE, et al. A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD. Mol Psychiatry. Published online May 7, 2020. doi:10.1038/s41380-020-0755-z
  8. Fitzgerald KN, Hodges R, Hanes D, et al. Potential reversal of epigenetic age using a diet and lifestyle intervention: a pilot randomized clinical trial. Aging (Albany NY). 2021;13(7):9419-9432. doi:10.18632/aging.202913

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