Everything Epigenetics - How Fit Are You According to Your DNA? With Kristen McGreevy

How Fit Are You According to Your DNA? With Kristen McGreevy

07/05/23 • 49 min

As we age, physical fitness tends to decline. This decline can be attributed to various factors such as changes in body composition, reduced muscle mass and strength, decreased flexibility, and diminished cardiovascular endurance. Additionally, the body's ability to recover from physical exertion also tends to slow down with age.
It has been well validated that the rate at which this decline occurs varies among individuals. However, those who maintain their physical fitness as they age experience a lower risk of various diseases and tend to enjoy longer lives.
At the molecular level, changes in fitness and related indicators of functional capacity coincide with molecular markers of decline, which are believed to reflect underlying biological aging processes. Therefore, measurements of fitness offer a novel perspective on biological aging.
Nevertheless, the measurement of fitness parameters presents challenges due to the need for in-person data collection by skilled experts utilizing specialized equipment. Moreover, remote data collection or studies involving stored biospecimens do not facilitate direct assessments of fitness.
To overcome this limitation and facilitate the evaluation of fitness in such scenarios, Kristen Mcgreevy has developed blood-based DNAm biomarkers that encompass various aspects of fitness, including mobility (gait speed), strength (grip strength), lung function (forced expiratory volume in one second), and cardiovascular fitness (VO2 max). These biomarkers form the basis of a groundbreaking indicator known as DNAmFitAge, which quantifies biological age based on fitness levels. This research also highlights the influence lifestyle has on the aging methylome.
In this week’s Everything Epigenetics podcast, Kristen and I chat about the importance of physical fitness as we age, how she developed blood DNAm biomarkers for four fitness parameters, and how she created DNAmFitAge. We also focus on FitAgeAcceleration in age-related conditions and DNAmFitAge relationship to physical activity and body builders.
Kristen is in the final year of her PhD, studying biostatistics at UCLA.
In this episode of Everything Epigenetics, you’ll learn about:

Kristen McGreevy’s interest in biostatistics and epigenetics
Why Kristen made the decision to get her PhD
The definition of strength training
Why physical fitness is important for aging
Which aspect of physical activity is the most important for longevity and health
What prompted Kristen to create DNAm estimators of fitness parameters
Gait speed (walking speed)
Handgrip strength
Forced expiratory volume in 1 second (FEV1; an index of lung function)
Maximal oxygen uptake (VO2max; a measure of cardiorespiratory fitness
Why Kristen chose gait speed, grip strength, FEV1, and VO2max for h

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Thank you for joining us at the Everything Epigenetics Podcast and remember you have control over your Epigenetics, so tune in next time to learn more about how to harness this knowledge for your benefit.

Kristen McGreevy’s interest in biostatistics and epigenetics
Why Kristen made the decision to get her PhD
The definition of strength training
Why physical fitness is important for aging
Which aspect of physical activity is the most important for longevity and health
What prompted Kristen to create DNAm estimators of fitness parameters
Gait speed (walking speed)
Handgrip strength
Forced expiratory volume in 1 second (FEV1; an index of lung function)
Maximal oxygen uptake (VO2max; a measure of cardiorespiratory fitness
Why Kristen chose gait speed, grip strength, FEV1, and VO2max for h

Support the show

Where to Find Us:
Instagram

Visit our website for more information and resources: everythingepigenetics.com

Previous Episode

Predicting Mental Illnesses Using Epigenetics with Dr. Zachary Kaminsky

According to the National Institute of Mental Health, approximately 20% of adults (around 51.5 million people) experience a mental illness each year. I believe that is 51.5 million people too many!
There is a HUGE need for the ability to predict mental illness, as the current diagnostic process has many limitations and challenges.
By analyzing epigenetic markers associated with mental disorders, we can actually predict the likelihood of developing these conditions and tailor personalized treatment plans for improved outcomes.
Predicting mental illness using epigenetics is paramount for early intervention, personalized medicine, and improved outcomes. With DNA methylation marks in peripheral tissues serving as predictive biomarkers, healthcare professionals can identify those at high risk and initiate targeted support.
Early detection enables timely interventions, potentially mitigating the severity and progression of these disorders. By leveraging cutting-edge technologies like artificial intelligence and natural language processing, we can even analyze social media data to predict suicidal thoughts and behaviors, revolutionizing suicide prevention strategies.
In this week’s Everything Epigenetics podcast, Zach and I chat about his work which primarily concentrates on identifying the epigenetic factors that contribute to psychiatric diseases, specifically focusing on mood disorders.
We discuss the microarray technology he utilizes to conduct genome-wide exploratory analyses, aiming to discover disease associations in both human subjects and animal models. We focus on Zach’s investigations which encompass a range of conditions, including major depression, postpartum depression, and suicide.
Another significant area of Zach’s research that we explore is centered around the development of predictive biomarkers for disease risk, using DNA methylation patterns in peripheral tissues.
Furthermore, we talk about his research program that involves the development and application of artificial intelligence-driven natural language processing techniques, and how he applies these techniques to social media data to predict the likelihood of future suicidal thoughts and behaviors.
Additionally, Zach is focused on creating and evaluating innovative digitally delivered suicide interventions that make use of these technologies.

In this episode of Everything Epigenetics, you’ll learn about:

Zach’s story starting with, “I met a girl...”
Zach’s focus on suicide, PTSD, and post-partum depression epigenetics
Dionysus digital health
Why epigenetics is giving researchers hope as a diagnostic tool
Epigenetics being the common denominator of nature and nurture
Stress vulnerability and epigenetic variation
The importance of replication and validation studies
Mol

Support the show

Where to Find Us:
Instagram

Visit our website for more information and resources: everythingepigenetics.com

Next Episode

A Deeper Dive into DunedinPACE with Dr. Daniel Belsky

According to Dr. Daniel Belsky at Columbia University, there are three limitations of epigenetic biological age clocks:

1. Mortality selection

Essentially, biological age measures may underestimate true aging because older participants represent slower agers.
2. Cohort Effects

Biological age measures may overestimate true aging because older participants carry an excess burden of early-life exposure to environmental toxicants, pathogens, poor nutrition, smoking, etc.
3. Uncertain Timing
Biological age measures summarize total aging over the lifespan and cannot distinguish differences established early in development from ongoing processes of aging. As a result, biological clocks may have lower sensitivity to effects of intervention.

So, you’re probably wondering, how do we account for these limitations?
Dr. Belsky and his team have created a tool that enhances the precision of measuring the rate of biological aging. Their work involved observing the health outcomes of 954 participants across four different age groups spanning from the mid-20s to the mid-40s. The researchers examined biomarkers believed to indicate how well various organs are functioning, as well as others linked to general health. Using this data, they devised an epigenetic "speedometer" to forecast how these values would change over time.
This tool is called the DunedinPACE.
As you may already know, the DunedinPACE measures how fast you are aging biologically for every one chronological year. If you need an introduction to DunedinPACE, check out my episode with Dr. Terrie Moffitt HERE.
In this week’s Everything Epigenetics podcast, Dan Belsky and I take a deeper dive into why Biological Age is limited and how DunedinPACE overcomes these limitations. Dr. Belsky speaks with me about a geroscience model of aging-related burden of disease, DunedinPACE test-retest reliability, and why the DunedinPACE indicates a faster pace of aging in individuals with an older chronological age.
We also discuss the effect of long-term caloric restriction on DNA methylation measures of biological aging in healthy adults from the CALERIE trial.
The DunedinPACE is a new tool for geoscience to investigate etiology in epidemiological studies and to evaluate the treatment effects of randomized controlled trials.
Dr. Belsky continues to validate the DunedinPACE in other populations around the world.
In this episode of Everything Epigenetics, you’ll learn about: