Did you know there is a concept called biological age? Unlike your chronological age, the number of years you've been alive, biological age reflects your physical and biological state. This means two people of the…
AI Model Predicts Your Biological Age!
Scientists are constantly searching for ways to understand and potentially slow the aging process. Recently, researchers made a significant breakthrough using artificial intelligence (AI) to predict your biological age, a measure of how old your body is, rather than your chronological age. Some people may have a biological age younger than their chronological age, while others might be older. This exciting development could revolutionize how we approach age-related diseases and health management.
Predicting Your Biological Age with AI
This new research leverages the power of deep neural networks (DNNs), a type of AI model, to analyze steroid hormone levels in blood samples. Steroid hormones play a crucial role in many bodily functions, and changes in their levels can be linked to the aging process. The study showed that doubling cortisol levels could increase biological age by about 1.5 times! This underscores the importance of stress management for healthy aging. This new model isn’t just about numbers; it provides concrete evidence of the impact of stress on aging at a biochemical level.
The Power of Steroid Hormones
The study highlights the importance of steroid hormones in aging. In a recent study, researchers measured the levels of 22 different steroids in blood samples from individuals aged 20 to 73. By analyzing this data using DNNs, they identified patterns that show how steroid levels relate to biological aging.
The AI Model: A Deep Dive
The researchers used a sophisticated DNN model trained on data from 148 serum samples. This model was specifically designed to account for the increasing complexity of aging over time and sex-specific differences. Interestingly, the model highlighted the crucial role of cortisol, a stress hormone, in the aging process, demonstrating the intricate interplay between stress, hormones, and aging.
Aging isn’t just a one-size-fits-all process; it is complex and varies widely among individuals—this variation is known as heterogeneity. The new DNN models take this variation into account! They allow scientists to see differences between how human beings experience aging based on their steroid levels.
Beyond Prediction: Understanding the Mechanism
This study is groundbreaking not just because it accurately predicts your biological age, but also because it provides insights into the biological mechanisms of aging. By analyzing which steroid hormones were most important for the prediction, the researchers gained a better understanding of how hormonal pathways contribute to aging. This knowledge can pave the way for developing new strategies to intervene in the aging process.
Implications for the Future
As researchers continue their work, the new models developed through this study will offer fresh insights into aging. It helps scientists identify when someone might be at risk for diseases linked to getting older. It also opens doors for potential personalized treatments!
Reference
- Wang, Q., Wang, Z., Mizuguchi, K., & Takao, T. (2025). Biological age prediction using a DNN model based on pathways of steroidogenesis. Science Advances, 11(11). https://doi.org/10.1126/sciadv.adt2624
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Neha Adikane holds a Master’s degree in Environmental Science from Pune University, bringing a unique blend of scientific expertise and creative writing skills to her craft. She specializes in creating engaging, insightful, and impactful content across various niches. With a passion for translating complex ideas into simple, relatable narratives, she excels at crafting blogs, articles, website content, and social media posts that captivate readers and drive engagement. Neha’s background in environmental science adds depth to her writing, allowing her to effectively cover topics related to sustainability, eco-awareness, and scientific innovations.