Key Points

Scientists at Osaka University have developed a revolutionary AI model that can estimate a person's biological age using just five drops of blood. By analyzing 22 key steroids and their interactions, the research team created a deep neural network that provides insights into how stress and hormone levels affect aging. The study, published in Science Advances, suggests that chronic stress can significantly accelerate biological aging, offering potential for more personalized health monitoring. This breakthrough could lead to early disease detection and customized wellness strategies tailored to individual biochemical profiles.

Key Points: AI Reveals True Biological Age from Blood Steroids

  • AI model analyzes steroid interactions to predict biological age
  • Cortisol levels directly linked to accelerated aging
  • Deep neural network provides precise health assessment
  • Potential for personalized health interventions
2 min read

AI could predict true biological age from 5 drops of blood

Japanese scientists develop groundbreaking AI model to measure biological aging using just 5 blood drops and 22 key steroids.

"Our bodies rely on hormones to maintain homeostasis, so we thought, why not use these as key indicators of aging? - Dr. Qiuyi Wang"

New Delhi, March 16

Scientists at Osaka University in Japan have devised a new AI model to estimate a person's biological age — a measure of how well their body has aged, rather than just counting the years since birth.

Using just five drops of blood, this new method analyses 22 key steroids and their interactions to provide a more precise health assessment.

The team's breakthrough study, published in Science Advances, offers a potential step forward in personalised health management, allowing for earlier detection of age-related health risks and tailored interventions.

"Our bodies rely on hormones to maintain homeostasis, so we thought, why not use these as key indicators of aging?" said Dr Qiuyi Wang, co-first author of the study.

To test this idea, the research team focused on steroid hormones, which play a crucial role in metabolism, immune function, and stress response.

The team developed a deep neural network (DNN) model that incorporates steroid metabolism pathways, making it the first AI model to explicitly account for the interactions between different steroid molecules.

One of the study's most striking findings involves cortisol, a steroid hormone commonly associated with stress. The researchers found that when cortisol levels doubled, biological age increased by approximately 1.5 times.

This suggests that chronic stress could accelerate aging at a biochemical level, reinforcing the importance of stress management in maintaining long-term health.

"Stress is often discussed in general terms, but our findings provide concrete evidence that it has a measurable impact on biological aging," said Professor Toshifumi Takao, a corresponding author and an expert in analytical chemistry and mass spectrometry.

The researchers believe this AI-powered biological age model could pave the way for more personalised health monitoring.

Future applications may include early disease detection, customised wellness programmes, and even lifestyle recommendations tailored to slow down aging.

- IANS

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