BEIJING, May 9 (Xinhua) -- A team of Chinese researchers has built a computational framework to study aging at the individual level in order to predict biological age and track the different aging rates of individual organs, according to a research article published in the journal Cell on Friday.

Human aging is characterized by complex structural and functional decline, but quantifying its heterogeneity and assessing biological age continue to pose challenges.

The study, conducted by researchers from multiple institutions, including the Chinese Academy of Sciences Institute of Zoology, the China National Center for Bioinformation, as well as four clinical research centers and seven other institutions, marks a major breakthrough by moving from simply describing aging to systematically quantifying it, potentially paving the way for future interventions.

The researchers recruited 2,019 Chinese individuals aged 18-91 years to create a standardized multicenter cohort called mCAS (multicentric Chinese Aging Standardized).

They developed a multimodal, multilayered and interpretable aging clock system by collecting over 240 clinical parameters, together with multiple layers of molecular data, creating a quantifiable, simulatable and intervenable digital aging framework of the human body.

This framework can accurately predict biological age, map the asynchronous aging patterns of human organs, and identify aging-related molecules such as coagulation factors, expanding the dimensions of aging assessment.

The collected dataset serves as the foundation for a three-tiered system of "clocks" to measure aging. More specifically, the first tier is the core capacity clock, which integrates 240 physiological indicators to reflect overall functional decline. The second and most powerful tier is the multimodal clock. It integrates multiple layers of molecular data through a deep learning process. This multimodal clock predicts chronological age with a mean absolute error of only 3.87 years.

The third tier comprises organ-specific clocks for the brain, liver, lungs, muscles, blood vessels and skin, each based on clinical markers, plasma proteins and imaging features.

One of the most remarkable findings of the study is that organs age asynchronously. For example, the liver reaches a critical aging inflection point earlier than the brain. The analysis also uncovered two major nonlinear waves of aging-related change: one occurring between ages 40 and 50, and another between 60 and 70.

Seeking the causes of these aging-related changes, the researchers analyzed plasma proteomics, examined stained liver tissue from human donors, and conducted experiments using human cell cultures and animal models. They identified age-driven accumulation of liver-derived coagulation factors as a direct driver of vascular and systemic aging.

The study also identified lifestyle factors influencing biological aging. Greater fruit intake, consistent sleep routines, and moderate walking were linked to slower aging. In contrast, smoking, insufficient sleep and high meal frequency were associated with accelerated aging.