What This Means
This research suggests that biological age — how old a person's body and brain appear to be based on measurable indicators — can be estimated much more accurately when multiple types of health data are combined. The researchers collected information from 908 older adults (all over age 60 and without dementia), measuring how they walk, how their eyes move, how different brain regions communicate at rest (using functional brain imaging), and levels of two proteins in the blood associated with brain health. When all of these data types were combined into one model, it could predict biological age with a mean error of less than 2 years, compared to about 3 years when using eye movement data alone — which was the best single measure.
Among the individual measures, eye movement patterns were surprisingly the most informative single predictor of biological age, outperforming gait, brain connectivity, and blood biomarkers on their own. In total, 14 walking features, 2 eye movement features, 19 brain connectivity patterns, and blood levels of a protein called GFAP were all meaningfully linked to how old a person appeared biologically. Notably, another blood protein called NfL was not significantly associated with age in this non-dementia group.
This research suggests that combining different types of easily measurable physical and neurological data — rather than relying on any single test — could lead to better tools for assessing how a person is aging. Such tools could potentially help identify individuals at higher risk for age-related diseases before symptoms appear, enabling more timely and targeted preventive strategies for healthy aging.