Individual variation in brain microstructural-cognition relationships in aging
Citation
Raihaan Patela, Clare E. Mackay, Michelle G. Jansen , Gabriel A. Devenyi, M. Clare O’Donoghue , Mika Kivimäki , Archana Singh-Manouxg,h, Enikő Zsoldos, Klaus P. Ebmeier , M. Mallar Chakravarty, Sana Suri. Individual variation in brain microstructural-cognition relationships in aging. bioRxiv preprint February 2021
Abstract
While all individuals are susceptible to age-related cognitive decline, significant inter- and
intra-individual variability exists. However, the sources of this variation remain poorly understood. Here,
we examined the association between 30-year trajectories of cognitive decline and multimodal indices of
brain microstructure and morphology in older age. We used the Whitehall II Study, an extensively
characterised cohort using 3T brain magnetic resonance images acquired at older age (mean age = 69.52
± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 4.9 years) ±
and late-life (mean age = 67.7 4.9). Using non-negative matrix factorization, we identified 10 brain ±
microstructural components that integrate measures of cortical thickness, surface area, fractional
anisotropy, and mean and radial diffusivities. We observed two modes of variance that describe the
association between cognition and brain microstructure. The first describes variations in 5 microstructural
components associated with low mid-life performance across multiple cognitive domains, decline in
reasoning abilities, but a relative maintenance of lexical and semantic fluency from mid-to-late life. The
second describes variations in 5 microstructural components that are associated with low mid-life
performance in lexical fluency, semantic fluency and short-term memory performance, but a retention of
abilities in multiple domains from mid-to-late life. The extent to which a subject loads onto a latent
variables predicts their future cognitive performance 3.2 years later (mean age = 70.87 4.9). This ±
data-driven approach highlights a complex pattern of brain-behavior relationships, wherein the same
individuals express both decline and maintenance in function across cognitive domains and in brain
structural features.
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