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Study Uncovers How Much of Biological Aging is Driven by Random Noise Versus Dynamic Biologic Change

TruDiagnostic is a leading health data company with a focus on multi omics and insights gained from the fluid epigenome. Established in early 2020, after development and build out of its 10,000 sq ft state of the art laboratory with Illumina equipment and consultation it launched its first provider and patient test “TruAge”. Today, TruDiagnostic has built a premiere epigenetic database of DNA Methylation markers and covariates which is one of the largest in the world. (PRNewsfoto/TruDiagnostic)

News provided by

TruDiagnostic

May 23, 2024, 11:00 ET

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LEXINGTON, Ky., May 23, 2024 /PRNewswire/ -- A new groundbreaking study, recently published in *Nature Aging*, by researchers from the University of Chinese Academy of Sciences, TruDiagnostic, and Harvard, has unveiled significant insights into the mechanisms of epigenetic clocks, which are widely used to predict biological age. The study's findings suggest that a large portion of the predictive accuracy of chronological clocks can be attributed to stochastic, or random, DNA methylation (DNAm) changes rather than deterministic biological aging processes.

Epigenetic clocks, such as those developed by Horvath and Zhang, have gained prominence for their ability to estimate an individual's biological age with remarkable accuracy, based solely on patterns of DNA methylation. However, the precise mechanisms by which these changes in DNAm occur has remained largely unexplored until now.

The research team, led by Dr. Andrew Teschendorff, utilized sophisticated simulation models and extensive DNAm data from over 25 independent cohorts totaling 22,770 samples. Their analysis revealed that between 66% to 90% of the accuracy of various epigenetic clocks could be explained by stochastic processes. This finding was particularly pronounced in Zhang's clock, which showed that up to 90% of its predictive capability could be attributed to these random changes.

Dr. Andrew E. Teschendorff, a senior author of the study, noted, "Our results further indicate that biological age-acceleration is unlikely to be the result of an increased rate of stochastic change, but instead being driven by non-stochastic processes. However, one exception to this seems to be mitotic age-acceleration in precancerous lesions."

Furthermore, the study distinguished between different types of epigenetic clocks, finding that those more predictive of chronological age, like Zhang's clock, were largely influenced by stochastic DNAm changes. In contrast, clocks like PhenoAge, which are more reflective of biological age, showed a lower degree of stochastic influence. This suggests that first generation clocks, trained to predict chronological age, have less utility in predicting outcomes of aging than clocks trained on other phenotypes of aging or biomarkers.

These insights are vital for the future development and refinement of epigenetic clocks, potentially guiding medical professionals towards more accurate assessments of biological aging and associated health risks.

"One trend we have seen in recent years is that clocks trained to predict chronological age have lower predictive power than newer clocks trained on biological information. Additionally, chronological clocks can sometimes increase with known lifespan extension interventions. This is counter intuitive. This study might explain why. Clocks trained to predict chronological age are driven by random variation over time while clocks which are predictive of lifespan seem to be much more dynamic and responsive to the ways we live our life" added Dr. Varun Dwaraka, a co-author of the study. 

The full study is available in the latest issue of *Nature Aging* and provides a comprehensive view of the stochastic components influencing epigenetic aging. This research not only advances our understanding of genetic aging mechanisms but also enhances the potential for personalized medical strategies based on more accurate DNA methylation profiling.

For further information, access the full paper here.

About TruDiagnostic

Home to the largest, private DNA methylation database in the world, TruDiagnostic is a leading health data company and CLIA-certified laboratory that specializes in epigenetic testing and research. In partnership with notable biotech developers, researchers, and academic institutions, we are transforming the healthcare potential of epigenetic data into actionable applications. We aim to improve people's lives by arming patients and physicians with novel biological insights; enabling them to make the right lifestyle and medical decisions through information found in the fluid epigenome. With the ability to analyze more than 1,000,000 locations on one's DNA, our TruAge biological aging tests provide the most in-depth results, and multi-omic correlations to accelerated aging.

Additional Contacts

Hannah Went, Director of Operations


General Inquiries  


(937) 570-0471  


(833) 963-1700


[email protected]


[email protected]


www.trudiagnostic.com


www.trudiagnostic.com


**Contact:**
Dr. Andrew E. Teschendorff
Email: [email protected]
University of Chinese Academy of Sciences, Shanghai, China

Emilie Arroyo, Media Relations
(786) 247-4579
[email protected]  
www.trudiagnostic.com

SOURCE TruDiagnostic

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