AI Model Accurately Estimates Biological Age Using 5 Drops of Blood, Reveals Impact of Stress on Aging

Mar 23, 2025

AI in Healthcare, Hormone Analysis, Healthcare Technology, Aging Research
AI in Healthcare, Hormone Analysis, Healthcare Technology, Aging Research

Source: SciTechDaily

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Researchers at Osaka University have developed an innovative AI-driven model that can estimate a person’s biological age using just five drops of blood. The new model analyzes hormone metabolism pathways, particularly steroid interactions, providing a more accurate picture of aging and health than conventional methods. This breakthrough opens doors for personalized interventions to manage age-related health risks.

Key HighlightsAI-Based Biological Age Estimation

  • Uses only five drops of blood to analyze 22 key steroid hormones and their interactions.

  • Focuses on steroid metabolism pathways to assess the body's internal balance.

  • Provides a more precise health assessment than DNA methylation or protein-based biomarkers.

Stress and Accelerated Aging

  • Findings show that doubling cortisol (stress hormone) levels increases biological age by approximately 1.5 times.

  • Reinforces concrete evidence of how chronic stress biochemically accelerates aging.

AI Model Advantages

  • Incorporates steroid ratios rather than absolute levels to reduce variability between individuals.

  • Developed using deep neural network (DNN) architecture trained on hundreds of blood samples.

  • Demonstrated that biological age differences widen as people grow older.

Statements from Researchers

  • Dr. Qiuyi Wang, co-first author, stated: “Our bodies rely on hormones to maintain homeostasis, so we thought, why not use these as key indicators of aging?”

  • Dr. Zi Wang, co-first and corresponding author, added: “Our approach reduces the noise caused by individual steroid level differences and allows the model to focus on meaningful patterns.”

  • Professor Toshifumi Takao emphasized: “Stress is often discussed in general terms, but our findings provide concrete evidence that it has a measurable impact on biological aging.”

The research team aims to expand their dataset and integrate additional biological markers to refine the model further. This AI-powered innovation could revolutionize preventive healthcare by enabling early disease detection, tailored wellness programs, and lifestyle recommendations to slow down aging.

AI in Healthcare
Hormone Analysis
Healthcare Technology
Aging Research
AI in Healthcare
Hormone Analysis
Healthcare Technology
Aging Research

AI Model Accurately Estimates Biological Age Using 5 Drops of Blood, Reveals Impact of Stress on Aging

Mar 23, 2025

AI in Healthcare, Hormone Analysis, Healthcare Technology, Aging Research
AI in Healthcare, Hormone Analysis, Healthcare Technology, Aging Research

Source: SciTechDaily

Researchers at Osaka University have developed an innovative AI-driven model that can estimate a person’s biological age using just five drops of blood. The new model analyzes hormone metabolism pathways, particularly steroid interactions, providing a more accurate picture of aging and health than conventional methods. This breakthrough opens doors for personalized interventions to manage age-related health risks.

Key HighlightsAI-Based Biological Age Estimation

  • Uses only five drops of blood to analyze 22 key steroid hormones and their interactions.

  • Focuses on steroid metabolism pathways to assess the body's internal balance.

  • Provides a more precise health assessment than DNA methylation or protein-based biomarkers.

Stress and Accelerated Aging

  • Findings show that doubling cortisol (stress hormone) levels increases biological age by approximately 1.5 times.

  • Reinforces concrete evidence of how chronic stress biochemically accelerates aging.

AI Model Advantages

  • Incorporates steroid ratios rather than absolute levels to reduce variability between individuals.

  • Developed using deep neural network (DNN) architecture trained on hundreds of blood samples.

  • Demonstrated that biological age differences widen as people grow older.

Statements from Researchers

  • Dr. Qiuyi Wang, co-first author, stated: “Our bodies rely on hormones to maintain homeostasis, so we thought, why not use these as key indicators of aging?”

  • Dr. Zi Wang, co-first and corresponding author, added: “Our approach reduces the noise caused by individual steroid level differences and allows the model to focus on meaningful patterns.”

  • Professor Toshifumi Takao emphasized: “Stress is often discussed in general terms, but our findings provide concrete evidence that it has a measurable impact on biological aging.”

The research team aims to expand their dataset and integrate additional biological markers to refine the model further. This AI-powered innovation could revolutionize preventive healthcare by enabling early disease detection, tailored wellness programs, and lifestyle recommendations to slow down aging.

Share:

AI in Healthcare
Hormone Analysis
Healthcare Technology
Aging Research
AI in Healthcare
Hormone Analysis
Healthcare Technology
Aging Research