Research Confirms the Superior Precision of Technology Powering Index

In recent years, epigenetic predictors of age—also known as epigenetic clocks—have been shown to be highly predictive of chronological and biological age. Just like many other types of product, these clocks have varying degrees of accuracy. So how do you know which is the most precise predictor of your biological age?

In 2018, Yale School of Medicine professor and Elysium bioinformatics advisor Morgan Levine, Ph.D., published the “Levine DNAmPhenoAge” clock, which is predictive of a variety of aging outcomes such as physical functioning and healthspan. 

In collaboration with Dr. Levine, the Elysium bioinformatics team developed Index with the goal to build a superior predictor of biological age with accuracy at the individual level. 

When developing Index, Dr. Levine and the Elysium team started by testing the reliability of existing epigenetic clocks using available technology. The ensuing discovery was startling—a single sample processed repeatedly resulted in epigenetic age estimates that varied dramatically, up to 25 years apart. 

The team focused their efforts to computationally minimize this variation, known as technical noise, and develop a more accurate and reliable clock.

Morgan Levine PhD at Yale

A paper recently released in Cold Spring Laboratory’s archive BioRxIV details this methodological approach (on which Elysium’s epigenetic clock Index is based) and finds that it improves the general reliability of epigenetic clocks. This enables their utility as markers to track how a person’s aging changes over both the short and long term. 

This advancement has launched a new generation of epigenetic age biomarkers that are far less noisy and exhibit superior precision and accuracy compared to their former versions, warranting their incorporation as a way for both individuals and researchers to track rate of aging—with practical applications for personalizing health care routines in everyday life or for use in clinical trials. 

According to Dr. Levine, the algorithm has dramatically simplified the assessment of “phenotypic age,” or what we now call biological age.

“A lot of work went into developing the algorithm that is used to calculate biological age,” says Dr. Levine. “However, now that we know which CpGs to include and how to mathematically combine the information across them, calculating an individual’s result is relatively easy. After we measure methylation levels for an individual, we simply plug them into the algorithm and very quickly, get back a biological age and cumulative rate of aging.

“Through epidemiological research, we’ve identified lifestyle and environmental factors that on average characterize people with lower biological ages. We’ve laid out some of these more ‘controllable’ factors in the Index report so people can use that information to see if they can impact their age in the future.”

APEX has been shown, through extensive validation of Index, to output results that dramatically increase precision relative to other published DNA methylation measurements. This is what sets Index apart and makes it a superior predictor of biological age: one of the most important measures of overall health.

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