A new study in Science Advances has found a way to predict biological aging (BA) using artificial intelligence (AI). Researchers used a deep neural network (DNN) to analyze steroid hormone levels and understand how they relate to aging.
What is Aging?
Aging is a natural process where cells and tissues wear down over time, increasing the risk of diseases like Alzheimer’s, Parkinson’s, and osteoporosis. While chronological aging (CA) is simply the number of years a person has lived, BA shows how a person’s body is aging on a biological level.
Measuring Biological Aging
BA is difficult to measure because it depends on both genetics and lifestyle factors. Traditional methods, like checking lung capacity or grip strength, are not always reliable. Scientists now use blood tests and molecular analysis to get a more accurate picture of aging.
AI and Steroid Pathways
This study used AI to predict BA based on steroid levels in the body. Steroids were measured using advanced lab techniques, and AI was trained to find patterns in the data. The model considered factors like sex, blood type, and smoking habits to improve accuracy.
Key Findings
- Cortisol, a stress hormone, was a major marker of aging. Higher cortisol levels were linked to faster aging.
- Different steroids influenced aging in men and women. For example, testosterone affected male aging, while other hormones played a bigger role in female aging.
- Smoking sped up aging in men, but not significantly in women, possibly due to differences in smoking habits.
Conclusion
The AI model successfully predicted BA and showed how steroid levels impact aging. In the future, researchers plan to improve the model by including more data and considering factors like cholesterol levels. This could lead to better tools for understanding and slowing down aging.
Source: news-medical
