新的AI模型来估计一个人的生物年龄

这种新方法仅使用五滴血液，分析22种关键类固醇及其相互作用，以提供更精确的健康评估。

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.

日本大阪大学的科学家设计了一种新的AI模型来估计一个人的生物年龄，这是对自己的身体老化的衡量标准，而不仅仅是算出出生以来的几年。

This new method, which uses just five drops of blood to analyse 22 key steroids and their interactions, provides 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.

这种新方法仅使用5滴血液来分析22种关键类固醇及其相互作用，可提供更精确的健康评估。该团队的突破性研究在《科学进步》上发表，在个性化的健康管理方面迈出了潜在的一步，可以早期发现与年龄相关的健康风险和量身定制的干预措施。

“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.

“我们的身体依靠激素来维持体内平衡，所以我们认为，为什么不将其用作衰老的关键指标？”该研究的联合第一作者Qiuyi Wang博士说。

To test this idea, the research team focused on steroid hormones, which play a crucial role in metabolism, immune function, and stress response. They collected blood samples from 130 individuals ranging in chronological age from 20 to 79 years old.

为了检验这一想法，研究小组专注于类固醇激素，这些激素在代谢，免疫功能和压力反应中起着至关重要的作用。他们收集了从20至79岁的年代年龄段的130名个人中收集的血液样本。

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. This approach enabled the DNN to learn complex relationships between steroids and biological age.

该团队开发了一个深神网络（DNN）模型，该模型结合了类固醇代谢途径，使其成为第一个明确说明不同类固醇分子之间相互作用的AI模型。这种方法使DNN能够学习类固醇与生物年龄之间的复杂关系。

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.

该研究最引人注目的发现之一是皮质醇，皮质醇是一种通常与压力相关的类固醇激素。研究人员发现，当皮质醇水平翻了一番时，生物年龄增加了约1.5倍。

This observation, supported by further analysis of steroid ratios and interaction terms, suggests that chronic stress could accelerate aging at a biochemical level, reinforcing the importance of stress management in maintaining long-term health.

这一观察结果得到了对类固醇比和相互作用术语的进一步分析的支持，这表明慢性压力可以在生化水平上加速衰老，从而增强了压力管理在维持长期健康方面的重要性。

“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.

“压力通常是一般性的，但是我们的发现提供了具体的证据，表明它对生物衰老产生了可衡量的影响，”分析化学和质谱法专家Toshifumi Takao教授说。

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

研究人员乐观地认为，这种AI驱动的生物年龄模型可以为更个性化的健康监测铺平道路。

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

未来的应用可能包括较早的疾病检测，定制的健康计划，甚至是针对减慢衰老的量身定制的生活方式建议。