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The Most Promising Biomarkers of Aging

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Recently, researcher Dr. Alexey Moskalev has published a mini review that takes a look at aging biomarkers and how some of them compare with each other [1].

A major challenge in developing therapies that target the aging processes in order to prevent or reverse age-related diseases is having accurate ways to determine if a therapeutic intervention has worked or not. In order to determine this, researchers rely on aging biomarkers, which can take the form of a naturally occurring molecule, changes to gene expression, or a characteristic that is indicative of biological change.

Epigenetic clocks 

The aging process causes epigenetic alterations to occur, which includes alterations to DNA methylation, histone modification, transcriptional alterations (variance in gene expression), and the remodeling of chromatin (a DNA support structure that assists or impedes gene transcription). These epigenetic alterations are a hallmark of aging, and experiments that reverse these alterations are already showing promise in animal studies and may one day help us to prevent or reverse age-related diseases.

The epigenetic clocks are biomarkers that measure the state of DNA methylation and can be used to track changes to them over time. The author suggests that these clocks are one of the most promising aging biomarkers during the course of the review. Epigenetic clocks are comprised of a set of CpG sites, regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide and whose DNA methylation levels can be used to predict subject age.

Several of these epigenetic clocks have been around for a few years now, including the recent GrimAge clock that measures the methylation state of 353 DNA locations and uses an estimator to measure 71 locations of DNA in leukocytes, the white blood cells that form part of the immune system [2].

The estimator then predicts lifespan after adjusting for chronological age and other known risk factors. During the process, it examines the DNA sites linked to a wide variety of age-related diseases and conditions to give an estimate of time-to-death due to all-cause mortality. In essence, GrimAge could almost be considered as a kind of death clock, counting down how much life you have left.

There are a number of other epigenetic clocks, each measuring different sites, and while there is some debate over what the clocks are actually measuring, in general, these clocks are considered to be the gold standard of aging biomarkers. That said, there is certainly room for improvement and deeper understanding of how and what exactly they are measuring.

Frailty index



The author also suggests that the frailty index is another good aging biomarker and reliable for predicting the biological age of a person. The frailty index is used to determine the health status of an older person; it can serve as a proxy measure of how that person is aging and that person’s prognosis of a poor outcome.

A person’s frailty index is determined by the proportion of deficits present in an individual out of the total number of age-related health variables considered. These deficits include diseases, signs, symptoms, laboratory abnormalities, cognitive impairments, and impairment to daily living activities.

The frailty index is worked out by taking the number of health deficits present and dividing it by the number of health deficits measured. For example, if someone scores 20 out of 40 deficits, that person has an FI score of 20/40, or 0.5; a person scoring only 10 deficits has a 10/40 score, or 0.25.

The frailty index can be easily created using this procedure, and it can be used across different databases due to how it is created, allowing it to cope with different numbers and items used between databases [3]. The frailty index is a popular and useful biomarker that has a great level of flexibility and gives a great indication of a person’s functional age.

To see if treatments to ward off aging work, first we need a way to measure biological age reliably (Moskalev, 2019). Biological age is a complex parameter involving the calendar age of a person, their health as relating to their age, and medical signs of when they might die of old age.

Conclusion

As research methods advance and the use of techniques such as deep learning increase in the lab, we will no doubt see ever-more sophisticated aging biomarkers arriving, and that could not be soon enough. With a number of potential therapies poised to attempt translation from animal studies to humans in the next decade or so, the need for accurate and meaningful aging biomarkers has never been greater.

Literature 

[1] Moskalev, A. (2020). Mortality: The challenges of estimating biological age. eLife, 9, e54969.



[2] Lu, A. T., Quach, A., Wilson, J. G., Reiner, A. P., Aviv, A., Raj, K., … & Whitsel, E. A. (2019). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging.

[3] Searle, S. D., Mitnitski, A., Gahbauer, E. A., Gill, T. M., & Rockwood, K. (2008). A standard procedure for creating a frailty index. BMC geriatrics, 8(1), 24.



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About the author

Steve Hill

Steve serves on the LEAF Board of Directors and is the Editor in Chief, coordinating the daily news articles and social media content of the organization. He is an active journalist in the aging research and biotechnology field and has to date written over 500 articles on the topic as well as attending various medical industry conferences. In 2019 he was listed in the top 100 journalists covering biomedicine and longevity research in the industry report – Top-100 Journalists covering advanced biomedicine and longevity created by the Aging Analytics Agency. His work has been featured in H+ magazine, Psychology Today, Singularity Weblog, Standpoint Magazine, and, Keep me Prime, and New Economy Magazine. Steve has a background in project management and administration which has helped him to build a united team for effective fundraising and content creation, while his additional knowledge of biology and statistical data analysis allows him to carefully assess and coordinate the scientific groups involved in the project. In 2015 he led the Major Mouse Testing Program (MMTP) for the International Longevity Alliance and in 2016 helped the team of the SENS Research Foundation to reach their goal for the OncoSENS campaign for cancer research.
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