bioRxivNeurosciencePreprint
Individual variation in brain structural-cognition relationships in aging
Raihaan PateliD, Clare E. MackayiD, Michelle G. JanseniD, Gabriel A. DevenyiiD, M Clare O'DonoghueiD, Mika Kivimaki BiD, Archana Singh‐ManouxiD, Enikő ZsoldosiD, Klaus P. EbmeieriD, M. Mallar ChakravartyiD, Sana SuriiD
Abstract
The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 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 components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 {+/-}4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions that are both positively and negatively associated with cortical structure.
- organism: human
- assay: bulk RNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: trajectory inference
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 3
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