Abstract
Epidemiological links between cognition and body physiology in aging are well established, but their strength and drivers remain unclear. Which physiological systems – from body composition to cardiovascular, pulmonary, renal, hepatic, immune, metabolic, and musculoskeletal – best predict cognition, and to what extent are cognition–body associations linked to brain variation across aging? We examined 19 physiological phenotypes alongside three neuroimaging modalities in over 30,000 UK Biobank participants. Machine learning models integrating body measures predicted cognition at r = 0.4, demonstrating a cognition–body covariation at 16%. Body composition and bone health emerged as the strongest predictors. Notably, 85.1% of cognition–body covariance overlapped with neuroimaging, especially white matter features. Moreover, 71.7% of cognition–age covariance was jointly shared with neuroimaging and physiology, and 96.8% was shared with either brain or body markers, or their overlap. Together, these findings clarify how body physiology and brain structure and function covary with cognitive aging.