Mois : décembre 2024

Once confined to the realms of science fiction or relatively crude internet death calculators, AI-driven predictions about longevity are inching closer to reality. Questions about the accuracy and value of these forecasts remain.

In recent years, researchers and companies around the globe have been pursuing answers to the ultimate question: How long have we got left? These models leverage cutting-edge tools, such as artificial intelligence and machine learning, drawing on a variety of parameters to deliver statistically grounded insights.

Conceptually, they function like established diagnostic tools such as QRisk for heart disease or CHA₂DS₂-VASc Score for stroke risk. Yet, the debate remains: are these predictions meaningful advancements or little more than modern-day fortune-telling?

The tech behind lifespan prediction

With the advent of artificial intelligence, increasing numbers of tools are emerging on the market. At the same time, biotech companies, such as Altos Labs and BioAge Labs, among others, are engaging such technologies to develop state-of-the-art therapeutics.

AI isn’t a one-stop fix for all challenges. The reality is that it’s a technological tool, albeit with immense potential, that utilizes sophisticated algorithms to get results, much like any other modern technology.

The same approach applies to lifespan prediction technologies built on AI. They engage a suite of technologies, such as:

Neural networks. These mimic the brain’s architecture, similarly to neurons making connections, and help uncover complex patterns in health and lifestyle data.
Machine learning algorithms. These analyze high-dimensional datasets, including genomic sequences, wearable device outputs and lifestyle choices, to establish relationships that could impact aging.
Random forests and decision trees. These can help to identify the critical biomarkers or lifestyle factors that influence the human lifespan.

The power of big data

Perhaps one of the major advantages of AI over traditional solutions hinges on its capabilities in analyzing extensive data sets. These can include:

Lifestyle metrics. By tabulating diet, exercise, sleep patterns, and other defined factors, it becomes possible to establish their roles in both healthspan and lifespan.
Medical history. This data can offer insights into chronic illnesses, prior interventions, and potential risk factors for the future.
Genomic data. Identifying hereditary risk factors and aging-related genes can establish possible risk levels.
Real-time biometrics. Data gathered from wearable technology, such as heart rate and oxygen levels, can provide insights to overall health longitudinally.

By combining these together, a bigger picture can be established that analyzes the probability of a patient developing a disease or condition or experiencing a negative health outcome within a specific period.

The relationship of risk and lifespan

Predicting the risks of specific diseases is not the same as predicting lifespan, and there may be ethical, moral, and legal concerns. To predict lifespan itself, companies working in this sector often choose to focus on specific metrics: biomarkers of aging.

Epigenetic clocks. These are used to evaluate DNA methylation patterns in order to estimate biological age. Tools such as GrimAge and DeepAge are already using this technology.
Blood and wearable biomarkers. These can be used to detect changes in inflammation or metabolism. Tthey offer real-time insights into health trajectories and risk factors.
Lifestyle biomarkers. These integrate diet, stress, and physical activity in order to allow an AI to suggest actionable interventions that could potentially improve lifespan.

Companies exploring lifespan prediction

Despite the challenges, scientific and human curiosity drive companies to seek answers to those all-important questions. Currently, multiple companies are focused on lifespan and on measuring specific risk factors.

Life2vec: This company offers a transformer-based AI model that analyzes life trajectories, predicting events such as death and health outcomes. It draws upon comprehensive datasets from six million individuals to make its predictions. These include socioeconomic, health, and behavioral data for granular predictions. According to the company’s stats, its accuracy rate is between 70% to 90%; however, it remains unclear how this is calculated.

AI-ECG Risk Estimation (Aire): Aire draws upon electrocardiograms (ECGs) to predict mortality risk. It does so by identifying subtle changes in the heart’s function and potential abnormalities. Estimates from the NHS show its accuracy at 78%.

Impacts to accuracy

As this is a new technology, questions arise relating to its accuracy. For example, Life2vec is a transformer-based system that integrates vast datasets to predict mortality risk with a level of granularity. However, challenges remain:

Fundamental limitations. Pinpointing death remains an almost unattainable goal. It’s almost impossible to approximate perfect accuracy even with a personalized risk assessment.
Data bias. AI models are often trained on data sets that lack diversity, which limits their accuracy and can make them biased in certain populations. It’s likely that such models require the same sorts of adjustments as BMI calculators.
Complexity of aging. This is a developing field, and models will struggle to account for all factors and assign the correct weights to them. In addition, evolving factors, such as emerging illnesses, pandemics, and accidents, will always play a role in lifespan.

Ethics

Like the practicalities of proving accuracy and efficacy, utilizing predictive AI technology for human health has a vast range of legal and ethical implications.

Data privacy. Health data is confidential and subject to a variety of laws, depending on jurisdiction. Misuse or incorrect use could lead to situations that result in updates to healthcare laws and data protection legislation.
Ownership and consent. Failure to get informed consent could lead to issues with the ownership of data behind AI predictions. This issue has already arisen with companies such as 23andMe, which have faced criticism for sharing genetic data with third parties.
Bias and inequality. AI is designed by human programmers that might miss biased data in datasets, which could lead to inaccuracies among some populations and possible legal implications.
Psychological impact. Just as knowing a risk factor could have health implications, so too could knowing one’s predicted lifespan. This may cause additional unwanted health outcomes, such as anxiety, depression, and orthorexia.

World Health Organization (WHO) has been vocal about such issues and calls for transparent algorithms and ethical frameworks to govern the use of AI tools in health.

The future of lifespan prediction

Advancements are on the horizon. Moving forward, the next generation of tools for enhanced biomarker analysis could seek to integrate more complex and accurate data from epigenetic clocks, wearable devices, and molecular studies. This would allow them to deliver highly personalized lifespan predictions, even if accuracy remains a point of contention.

In addition to this, wearable technology, such as watches or rings, could enable real-time updates, dynamically adjusting predictions based on daily health behaviors. This could foster a nudge-style approach to health management.

Healthspan prediction has the potential to seamlessly integrate into everyday routines, especially for consumer technology and interactions with medical practitioners. This could enable doctors to tailor healthcare treatments to include preventive care and interventions based on an individual’s projected lifespan and biomarkers.

Of course, there are much broader implications to implementing these technologies in day-to-day life, and they extend beyond healthcare to such things as societal issues, personal finance, and the relationship of work to life, which are also affected by enhanced lifespans.

Do we need to know the future?

AI’s potential to analyze data and predict outcomes is something never seen before. As the world, including healthcare, learns how to adapt to this, this knowledge should always be taken with a pinch of salt. Validating predictive tools to the level where they can be reliably used necessitates rigorous testing for accuracy and consideration of how they should be used.

In a randomized, controlled trial published in Nutrients, researchers tested supplementation with resveratrol, vitamin C, and a combination of both. They learned that all of the treatments had a similar positive impact on oxidative stress in postmenopausal women [1].

Menopausal transition

Around the world, a significant proportion of women have reached the post-menopausal stage. In Mexico, where the study was conducted, 15% of women have reaced this threshold. As life expectancy increases, this fraction will also increase in the coming years.

Menopause is followed by decreased antioxidant capacity, resulting in an imbalance between oxidant molecule generation and antioxidant capacity. Such imbalance creates oxidative stress (OS). During oxidative stress, oxidizing agents can attack and break down molecules that are essential to cells and tissues, such as lipids and proteins.

This group of researchers previously reported “that postmenopausal women present higher concentrations of OS markers than women of reproductive age” [2]. Therefore, using antioxidants seems like a reasonable strategy to reduce the detrimental effect of oxidative damage on lipids and proteins.

Those researchers chose resveratrol and vitamin C because previous research had described them as having “cardioprotective, anti-sclerotic, anti-inflammatory, and antioxidant properties“ [3].

Resveratrol is a natural phytoestrogen and a polyphenolic flavonoid that is well tolerated and not toxic. Resveratrol was previously described to have a role in increasing both the expression and activity of antioxidant enzymes while reducing oxidative load [4, 5].

Clinical trial of postmenopausal females

The researchers conducted a pilot randomized, double-blind clinical trial. They recruited women between 50 and 60 years old who were in the early postmenopause stage and had insulin resistance.

Among the exclusion criteria were the use of hormone replacement therapy or drugs such as anticoagulants, metformin, bezafibrate, statins, or any antioxidant in the three months before the beginning of the study. Active smokers and women with some health conditions were also excluded.

The study participants were divided into one of three groups: 13 participants in the resveratrol group plus a vitamin C placebo (group A), 15 participants in the resveratrol and vitamin C (group B), and 14 participants in the vitamin C plus a resveratrol placebo (group C). Depending on the group assignment, the participants received 500 mg resveratrol capsules, vitamin C/ascorbic acid tablets, or placebo tablets for three months.

Reduced oxidative stress

First, the researchers analyzed baseline clinical and biochemical blood test results. In the intra-group analysis, baseline measurements were compared to after-treatment measurements, and no significant differences were found in measurements such as weight, BMI, glucose, insulin, lipid profile, and uric acid.

When groups were compared with each other after a three-month intervention, the researchers observed significantly lower total cholesterol levels and significantly higher triglyceride levels in the vitamin C group compared to the resveratrol group. The researchers also observed significantly lower triglyceride concentrations in the combined group compared to the vitamin C-only group.

Comparing the baseline and after-treatment levels of lipohydroperoxides (LPH), a measure of oxidative deterioration of lipids, showed a significant decrease of 33% in the combined group. The resveratrol group and the vitamin C group had 25% and 15% decreases in LPH levels, respectively. However, those differences were not statistically significant. The researchers hypothesize that it was due to the sample size being too small, and future research with a bigger sample size might lead to significant results in those groups as well.

The researchers also analyzed the levels of MDA, the end product of lipoperoxidation. All three groups showed statistically significant differences between initial measurement before the treatment and following the 3-month treatmnet. MDA levels were reduced by 26% in the resveratrol group, 32% in the combined group, and 38% in the vitamin C group.

Previous experiments conducted on rats that received resveratrol achieved similar results [6]. Similarly, a study of people under 18 taking vitamin C also showed MDA reduction [7].

After measuring lipid damage, the researchers analyzed protein oxidative damage. A statistically significant reduction was also observed in all groups. The differences between before and after treatment measurements show 39% reduction in the combined group and 29% in both the resveratrol and vitamin C groups.

There were also differences in antioxidant capacity. However, this time, there was an increase of 30% for the combined group and 28% for the vitamin C group following the treatment compared to baseline.

No improvements in insulin resistance

Despite previous research linking oxidative state and insulin resistance, none of this study’s groups demonstrated statistically significant differences in insulin resistance.

The researchers discuss previous studies on humans that, except for one, all reported that resveratrol does not affect insulin resistance. Those studies looked at different populations of participants with different health conditions and variable durations and doses of treatment.

Similarity of all groups

The authors caution when interpreting the results, as the research has some limitations. For example, the generalizability of the results from a homogenous group of participants, including only females from the Valley of Mexico metropolitan area, was limited.

Additionally, the researchers did not include a control, untreated group. However, as the authors explain, their question addressed how the combined treatments compare with a single treatment and whether there is possible synergy between them. Their experimental setup allowed for those comparisons and comparisons of the changes that the women experienced compared to baseline.

The researchers conclude that despite the differences in the effects of different measurements of oxidative stress, “none of the three interventions were superior to the others.”

Literature

[1] Montoya-Estrada, A., García-Cortés, A. Y., Romo-Yañez, J., Ortiz-Luna, G. F., Arellano-Eguiluz, A., Belmont-Gómez, A., Lopéz-Ugalde, V., León-Reyes, G., Flores-Pliego, A., Espejel-Nuñez, A., Solis-Paredes, J. M., & Reyes-Muñoz, E. (2024). The Administration of Resveratrol and Vitamin C Reduces Oxidative Stress in Postmenopausal Women-A Pilot Randomized Clinical Trial. Nutrients, 16(21), 3775.

[2] Montoya-Estrada, A., Velázquez-Yescas, K. G., Veruete-Bedolla, D. B., Ruiz-Herrera, J. D., Villarreal-Barranca, A., Romo-Yañez, J., Ortiz-Luna, G. F., Arellano-Eguiluz, A., Solis-Paredes, M., Flores-Pliego, A., Espejel-Nuñez, A., Estrada-Gutierrez, G., & Reyes-Muñoz, E. (2020). Parameters of Oxidative Stress in Reproductive and Postmenopausal Mexican Women. International journal of environmental research and public health, 17(5), 1492.

[3] Breuss, J. M., Atanasov, A. G., & Uhrin, P. (2019). Resveratrol and Its Effects on the Vascular System. International journal of molecular sciences, 20(7), 1523.

[4] Xia, N., Daiber, A., Förstermann, U., & Li, H. (2017). Antioxidant effects of resveratrol in the cardiovascular system. British journal of pharmacology, 174(12), 1633–1646.

[5] Livraghi, V., Mazza, L., Chiappori, F., Cardano, M., Cazzalini, O., Puglisi, R., Capoferri, R., Pozzi, A., Stivala, L. A., Zannini, L., & Savio, M. (2024). A proteasome-dependent inhibition of SIRT-1 by the resveratrol analogue 4,4′-dihydroxy-trans-stilbene. Journal of traditional and complementary medicine, 14(5), 534–543.

[6] Kong, D., Yan, Y., He, X. Y., Yang, H., Liang, B., Wang, J., He, Y., Ding, Y., & Yu, H. (2019). Effects of Resveratrol on the Mechanisms of Antioxidants and Estrogen in Alzheimer’s Disease. BioMed research international, 2019, 8983752.

[7] Ismy, J., Soebadi, A., Mangunatmadja, I., Monica, M., Sari, T. T., & Yuliarti, K. (2024). Role of antioxidants in reducing oxidative stress and seizure frequency in drug-resistant epileptic patients. Narra J, 4(2), e790.

Turn Biotechnologies, a cell rejuvenation and restoration company developing novel mRNA medicines for untreatable, age-related conditions, announced its latest study to assess the efficacy of using epigenetic reprogramming to rejuvenate bone marrow stem cells.

The study, which is being funded by Methuselah Foundation, is the first to evaluate use of Turn Bio’s unique RNA-based ERA™ therapy to rejuvenate bone marrow function to improve the quality of donor cells used in stem cell transplantation. Healthy marrow releases blood cells into the bloodstream. As adults age, their bone marrow produces fewer disease-fighting B and T cells and other products that help reduce inflammation throughout the body. Aged stem cells also collect changes in their DNA known as clonal hematopoiesis that can serve as a prelude to leukemia development.

“Multiple studies of clinical bone marrow transplant outcomes have identified that patients who receive donor stem cells from young donors have superior outcomes, owing to more durable correction of underlying blood and immune defects, with lower risks of graft dysfunction and donor clonal hematopoiesis,” said Timothy Olson, MD, PhD, principal investigator of this study, and Medical Director of the Blood and Marrow Transplant and Co-Chief of the Cellular Therapy & Transplant Section at Children’s Hospital of Philadelphia (CHOP). “We hope the study shows that epigenetic reprogramming can help to make bone marrow transplants both more effective and more accessible to patients.”

Rejuvenating older bone marrow cells could improve the body’s ability to fight disease, speed wound healing, improve the blood cells’ capacity to carry oxygen, and enhance the success of donor-to-patient transplantations. This could allow the use of older donors for transplants.

Transplants replace a patient’s diseased blood-forming cells with healthy cells. The procedures are used to treat certain types of cancer, blood disorders, and autoimmune diseases. Nearly half of the world’s annual 50,000 bone marrow transplants are performed in the United States.

Methuselah Foundation is interested in increasing survival rates for marrow transplant and gene therapy patients where current survival rates for patients with nonmalignant diseases is over 70% with a matched sibling donor and over 36% with unrelated donors.

By rejuvenating donor stem cells, researchers aim to increase the safety and efficacy of these intensive treatments. Additionally, with the growing use of gene therapy and gene editing, the ability to rejuvenate stem cells during these processes can potentially make the one-time treatments safer and more effective.

“We believe this study will confirm that epigenetic reprogramming can effectively rejuvenate bone marrow cells and restore their youthful performance —which will potentially extend the healthy human lifespan,” said David Gobel, co-founder and CEO of Methuselah Foundation, the world’s first biomedical non-profit focused on human longevity.

The year-long study will measure the effectiveness of Turn’s ERA solution by treating mouse blood progenitor cells and transplanting those cells into irradiated mice of the same genetic background.

“This study represents a significant milestone for Turn Bio as it demonstrates how we are taking our science beyond individual therapeutics to create solutions for a variety of diseases. We are optimistic it will validate the dramatic impact of epigenetic reprogramming in improving the human healthspan,” said Anja Krammer, Turn Bio CEO. “We have repeatedly demonstrated that ERA treatments can safely rejuvenate human cells. This is an opportunity to bring theory to life.”

The study will be conducted by Timothy S. Olson, MD, PhD, Associate Section Chief, Cell Therapy & Transplant Program at Children’s Hospital of Philadelphia (CHOP), with the support of Turn Bio Scientific Advisors: Joseph Hai Oved, MD, Leader of the Primary Immunodeficiency and Immune Dysregulation Program at Memorial Sloan Kettering Cancer Center  in New York, and Kevin J. Curran, MD, Director of the Immune Effector Cell Program, Memorial Sloan Kettering Cancer Center.

About Turn Biotechnologies

Turn Bio is a pre-clinical-stage company focused on repairing tissue at the cellular level and developing transformative drug delivery systems. The company’s proprietary mRNA-based ERA™ technology restores optimal gene expression by combatting the effects of aging in the epigenome. This restores cells’ ability to prevent or treat disease and heal or regenerate tissue. It will help to fight incurable chronic diseases. Its eTurna™ Delivery Platform uses unique formulations to precisely deliver cargo to specific organs, tissues, and cell types.

The company is completing pre-clinical research on tailored therapies targeting indications in dermatology and immunology, and developing therapies for ophthalmology, osteo-arthritis, and the muscular system. For more information, see www.turn.bio.