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0The paper details a large-scale study of over 13,000 older adults that utilizes metabolomics and machine learning to redefine metabolic health beyond traditional Body Mass Index (BMI) categories. By analyzing 39 core metabolites, researchers developed a BMI-metabolic health score (BMHS) that accurately identifies metabolic dysfunction and independently predicts cardiovascular and all-cause mortality. The study highlights how specific metabolic pathways, such as taurine and choline metabolism, vary across different weights and how a high-risk BMHS significantly influences long-term prognosis. Integrating these biological signatures with lifestyle factors like sleep, diet, and physical activity allows for a more precise, multidimensional approach to risk stratification. Ultimately, this framework challenges BMI-centric paradigms by offering a scalable, personalized strategy for managing the health of aging populations.
References:
Chen Y, Huang H, Xu W, et al. Metabolomic and lifestyle profiles refine BMI-metabolic phenotypes in older adults[J]. Cell Reports Medicine, 2026.
