Physical clock using routine biomarkers and physical performance: development, validation and health associations
Researchers developed a physical clock combining routine clinical biomarkers with physical performance; accelerated aging on this clock was associated with disease, functional decline and mortality in validation cohorts. [1]
Automatic summary · not editorially reviewed
The key findings
A physical clock combining routine clinical biomarkers with multidimensional physical performance was developed using ElasticNet regression in the PENG ZU cohort and reduced to an 11-marker model. [1]
Accelerated aging measured as ΔPhysicalAge was associated with chronic disease incidence, functional decline, reduced intrinsic capacity and mortality, and predicted outcomes in UK Biobank and NHANES validation. [1]
Healthy reference intervals were derived from people with normal or decelerated aging, and postmenopausal HRT use was associated with lower ΔPhysicalAge as preliminary evidence. [1]
The source at a glance
- Study type / format
- Model development and validation study (abstract)
- Population / context
- Participants in the PENG ZU cohort, with independent validation in UK Biobank and NHANES.
- Summary based on
- Study abstract
- Original publication
- June 18, 2026
Physical clock built in the PENG ZU cohort
The authors note that aging is the main risk factor for most chronic diseases, but that multi-omics clocks are costly and complex to use clinically. They therefore built a physical clock from routine clinical biomarkers plus multidimensional physical performance, using ElasticNet regression in the large-scale PENG ZU cohort. This was reduced to a simplified 11-marker model, mainly covering kidney function, glucose metabolism and physical performance.
Supporting source [1]
Accelerated aging linked to disease and mortality
Accelerated aging, measured as ΔPhysicalAge from the physical clock, was strongly associated with chronic disease incidence, functional decline, reduced intrinsic capacity and mortality. In independent validation in the UK Biobank and NHANES, it predicted disease onset as well as disease-specific and all-cause mortality. ΔPhysicalAge outperformed ΔPhenoAge for major age-related diseases and allowed risk stratification even among people conventionally classified as low risk. These are associations, not proof of causation.
Supporting source [1]
Reference intervals, HRT and lifestyle associations
To support clinical use, the authors established age- and sex-specific healthy reference intervals from people with normal or decelerated aging; staying within these ranges was associated with substantially reduced mortality risk. They also observed an association between postmenopausal hormone replacement therapy use and lower ΔPhysicalAge, described as preliminary evidence. Modifiable lifestyle and psychosocial factors, including healthy diet, physical activity, health consciousness and social engagement, were associated with slower aging.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. The abstract reports associations, not causal effects, and the HRT finding is described by the authors as preliminary. The physical clock is a research model, not a validated clinical product.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Wang XM, Pang J, Yu X, Zhang X, Wang SB, Pan Q, Chen A, Xu L, Li N, Li X, Wang Y, Gu Y, Chen S, Ma W, Zhang LQ, Zhang C, Liu W, Li CB, Shen T, Dai DP, Wang F, Li Y, Li Y, Dong J, Chen W, Yao Y, Liu B, Cai JP, Zhang T, Cui J. · europepmc.org · June 18, 2026