China develops two metabolomic aging indicators using data from 18,476 people — News-Medical
Researchers in Shanghai, China, analyzed blood plasma samples from 18,476 people aged from one to 96 and developed two metabolomic aging indicators. They are intended to assess how an individual’s biochemical state differs from their chronological age and how it is associated with risks of chronic diseases and death, News-Medical reports.
The work was published in the journal Science Translational Medicine. The scientists used mass spectrometry to study metabolites in the plasma of participants in the Shanghai Pudong Cohort. Initial examinations took place in 2019, chronic disease status was reassessed in 2023, and mortality data were tracked through January 2025.
Two indicators for different groups
A metabolomic age model was created for 5,252 healthy participants with a mean age of 55. It made it possible to determine metabolomic age acceleration — the difference between the age estimated from metabolites and a person’s actual age. The model was tested on another 5,456 healthy participants.
For 7,768 people with existing diseases, the researchers developed a separate age-deviation indicator associated with mortality risk. It reflected how the mortality risk estimated from metabolites differed from that expected for the corresponding age. Among people with pre-existing diseases, the primary metabolomic age model corresponded less accurately to chronological age, so the authors used a separate metric.
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Links to health status
Higher values of metabolomic age acceleration were associated with a greater likelihood of developing diabetes, hypertension, and fatty liver disease, as well as a higher risk of death from all causes. The association between higher values of this indicator and mortality risk remained after accounting for established health indicators. A panel of 56 metabolites retained most of the age-prediction information provided by the 232 studied metabolic indicators.
Higher values of the metric were also associated with smoking, exposure to tobacco smoke, shift work, hair dye use, and a family history of early cardiovascular disease. Consumption of organ meats, sugar, processed meat, seafood, and fried foods was associated with higher values, while physical activity and consumption of mixed grains were associated with lower values.
The authors emphasize that these are observational data that do not prove a direct effect of individual foods or lifestyle changes on biological aging. Clinical application of the approach is limited by the predominantly Chinese sample, the small number of repeated samples, and the need for independent validation of mortality predictions in other populations.
