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Aging research, especially thanks to new technologies, is making great strides.
While aging research advances, the world seems split into opposing views. Some longevity researchers and optimists believe that we're about to fight aging and reach biological immortality. Other scientists, and those with a more pessimistic outlook, believe that certain limits simply cannot be crossed, no matter how far we advance. We at Tomorrow are definitely part of the first group. We don't know whether we'll be able to defeat aging in this lifetime. However, we believe that the development of medical technology has no (or very few) limits. If you too are a life-extension enthusiast, check out our compilation of 3 recent articles on aging research.
Aging consists of several complex, interconnected processes that occur simultaneously and influence each other. Researchers have recently managed to define and (in part) understand these processes, called the 9 hallmarks of aging:
That said, one solution is not enough to defeat aging. We’ll probably need several years and talented minds to find solutions that can effectively tackle all 9 interconnected denominators of aging. Luckily, we already have many dedicated researchers working on the problem. Let’s have a look at some of their most recent works.
In order to understand the aging process, researchers have developed dozens of aging clocks in the last decades. The purpose of these clocks is to accurately determine a person's biological age. Biological age represents the speed at which a given body is aging and depends on genetics, accumulated lifestyle factors, demographic, diet, and much more. While chronological age (how many days you spent alive) is an easily calculable number, biological age is much more difficult to define. Aging involves several different processes that affect the body in various ways. Considering that each aging clock focuses on one or two of these effects, also known as biomarkers, it’s not surprising that we ended up with so many of them!
The next step is to compare these clocks and the methods used, as the scientists behind the study “Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities” did. As the introduction points out: Putting together a conclusive theory of aging has been difficult due to the inability to properly quantify and define aging. Consequently, the efficacy of various geroprotective interventions remains subject to controversy. Without general agreement as to what constitutes aging and biological age (BA), and how to measure their progression, conclusions on the benefits of particular therapies are likely to be biased. [1]
This comprehensive study focuses on a few specific biomarkers: telomere length, genomic instability, epigenetic marks, biochemical compounds and gene expression levels. The reason for this choice is that, while some marks of the passage of age are tissue- and species-specific, the selected ones exist across different tissues and structures. Analyses and findings of the latter could be more generally applicable. Nevertheless, the conclusions we can come to at the moment are still limited. Have a look at this comprehensive article to find out more.
That artificial intelligence is, among other things, revolutionizing the healthcare system is no secret. From drug research to early detection and diagnosis of diseases, few fields haven’t been positively affected by these new technologies. Developments in the coming decades might be able to significantly extend the human lifespan.
That being said, if you want to dive deep into the correlation between AI and aging research, we have the article for you. “Artificial intelligence for aging and longevity research: Recent advances and perspectives” emphasizes the tremendous opportunities that AI algorithms offer within the field of aging research. As the study points out, in the last few years we have managed to generate and accumulate a huge amount of aging-related data. To analyze and understand this data, we need the help of artificial intelligence. More specifically, machine learning and deep learning techniques are the keys to getting the results we are looking for. The attractive feature of AI is its ability to identify relevant patterns within complex, nonlinear data, without the need for any a priori mechanistic understanding of the biological processes. AI unveils the mechanistic relationships taking place within the body. [2]
Some of the applications of AI for aging research analyzed in this study are:
Telomeres are short sections of disposable DNA positioned at the end of our chromosomes. Every time a cell duplicates, a part of these telomeres gets lost. As telomeres are expendable, there’s no harm in losing a section of them. Yet, once they are depleted, chromosomes lose their ability to divide themselves, causing the cells to become senescent and increasing the incidence of diseases. The actual understanding of telomeres and their correlation to aging are a rather recent discovery. In 2009 Elizabeth Blackburn, together with Carol W. Greider and Jack W. Szostak, received a Nobel Prize for her discovery of “how chromosomes are protected by telomeres and the enzyme telomerase“. Her work is one of the most significant studies on telomeres and cellular division.
That said, the study of telomeres is decisive for making headway in defeating aging. Scientists have decided to approach it from different angles. The study “Stress and telomere shortening: insights from cellular mechanisms” investigates their correlation with stress. Chronic psychological stress leads to the development of several age-related disorders: cardiovascular disease, type 2 diabetes, metabolic syndrome, autoimmune disease, and depression. Telomeres, according to the study, have emerged not only as biomarkers, but as mediators through which chronic psychosocial stress leads to diseases. [3]
The study covers several aspects. It presents and analyzes telomere length as a biomarker of aging, their connection with diseases and stress, and their relation with chronic age-related inflammation (inflammaging) to name a few. The conclusion opens up the field for a lot of further research: With the recent advancement in the last two decades on the consistent and cross species role of telomere maintenance in aging and aging-related diseases, it is clear that the initial simplistic view of telomere length as a mitotic clock has evolved into a far more complex picture of interconnected molecular and cellular pathways and networks as hallmarks of aging. Nevertheless, it is clear that telomere maintenance is a key player in these networks. [3]
There is an endless number of insightful studies related to aging. Therefore, it's almost impossible to make a comprehensive summary of the current state of aging research. Here we have decided to present three papers that caught our attention. Many more are to come.
At Tomorrow we look forward to advances in medical technology. We cannot say whether scientists will be able to defeat old age anytime soon, but this is an essential step for successful revival after cryopreservation. Our members will possibly be revived in a future where they will have their diseases cured and their healthy bodies restored. When this will happen we cannot yet say. Certainly, we are on the right track.
If you have any questions about cryopreservation, schedule a call with a member of our team. We are always happy to help.
[1] Galkin, F., Mamoshina, P., Aliper, A., de Magalhães, J. P., Gladyshev, V. N., & Zhavoronkov, A. (2020). Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities. Ageing research reviews, 60, 101050. https://doi.org/10.1016/j.arr.2020.101050
[2] Zhavoronkov, A., Mamoshina, P., Vanhaelen, Q., Scheibye-Knudsen, M., Moskalev, A., & Aliper, A. (2019). Artificial intelligence for aging and longevity research: Recent advances and perspectives. Ageing research reviews, 49, 49–66. https://doi.org/10.1016/j.arr.2018.11.003
[3] Lin, J., & Epel, E. (2022). Stress and telomere shortening: Insights from cellular mechanisms. Ageing research reviews, 73, 101507. https://doi.org/10.1016/j.arr.2021.101507
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