Inter- and intra-individual variation in brain structural-cognition relationships in aging

NeuroImage

Clare E. Mackay¹  Archana Singh-Manoux²  Gabriel A. Devenyi³  Klaus P. Ebmeier³  Raihaan Patel⁴  Mika Kivimäki⁴  M. Mallar Chakravarty⁵  Sana Suri⁵  Enikő Zsoldos⁶  Michelle G. Jansen⁶  M. Clare O'Donoghue⁷ 

[1] Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada;Department of Psychiatry, McGill University, Montréal, Québec, H3A 1A1, Canada;Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom;Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada;Department of Epidemiology and Public Health, University College London, WC1E 6BT, London, United Kingdom;Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom;Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands;

关键词: Multimodal;    Structure;    Cognition;    MRI;    Aging;   

DOI  :  

来源: DOAJ

【 摘 要 】

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 are both positively and negatively associated with markers of cortical structure.

【 授权许可】

Unknown