Characterizing the Brains of People Who Retain Cognitive Function into Late Life

What distinguishes the brains and biochemistry of people who retain good cognitive function into late life? That question provokes studies such as the one noted here, in which researchers assess structural and biochemical differences between older people with good cognitive function versus those on the more usual declining trajectory. It remains a matter for hypothesis and discussion as to how exactly cognitive function is maintained in only some individuals, in apparent opposition to the mechanisms of aging and their effects on the integrity of the brain. Gathering data remains an important activity at this stage of research.

Some individuals, often designated as superagers, can reach late life with the memory function of individuals 30 years younger. Previous neuroimaging studies have shown that superagers have larger hippocampal volumes, thicker anterior cingulate cortices, and slower cortical atrophy than do typical older adults. Previous studies also explored the association between superager status and some lifestyle factors, such as satisfaction with social relationships. However, most studies had small sample sizes and were cross-sectional in nature, hindering distinction between long-standing structural differences and differential atrophy rates in superageing brains compared with normal ageing brains.

One approach to obtaining larger samples of deeply phenotyped (a cohort of participants with a rich set of different variables, including data for clinical history, lifestyle, neuroimaging data, etc) superagers with longitudinal data is to investigate large longitudinal ageing cohorts. We applied this approach to the Vallecas Project longitudinal study aiming, first, to characterise superagers' cerebral grey matter volume, cross-sectionally and longitudinally, relative to that of age-matched typical older adults; and second, to apply machine learning to identify which demographic, lifestyle, and clinical variables are the greatest differentiating factors between superagers and typical older adults.

We included 64 superagers (mean age 81.9 years) and 55 typical older adults (82.4 years). The median number of follow-up visits was 5.0 for superagers and typical older adults. Superagers exhibited higher grey matter volume cross-sectionally in the medial temporal lobe, cholinergic forebrain, and motor thalamus. Longitudinally, superagers also showed slower total grey matter atrophy, particularly within the medial temporal lobe, than did typical older adults. A machine learning classification including 89 demographic, lifestyle, and clinical predictors showed that faster movement speed (despite no group differences in exercise frequency) and better mental health were the most differentiating factors for superagers. Similar concentrations of dementia blood biomarkers in superager and typical older adult groups suggest that group differences reflect inherent superager resistance to typical age-related memory loss.

Link: https://doi.org/10.1016/S2666-7568(23)00079-X