- Title
- The interplay of age, gender and amyloid on brain and cognition in mid-life and older adults
- Creator
- Borne, Léonie; Thienel, Renate; Fazlollahi, Amir; Maruff, Paul; Rowe, Christopher C.; Masters, Colin L.; Fripp, Jurgen; Robinson, Gail A.; Breakspear, Michael; Lupton, Michelle K.; Guo, Christine; Mosley, Philip; Behler, Anna; Giorgio, Joseph; Adam, Robert; Ceslis, Amelia; Bourgeat, Pierrick
- Relation
- Scientific Reports Vol. 14, no. 27207 (2024)
- Publisher Link
- http://dx.doi.org/10.1038/s41598-024-78308-3
- Publisher
- Nature Publishing Group
- Resource Type
- journal article
- Date
- 2024
- Description
- Deficits in memory are seen as a canonical sign of aging and a prodrome to dementia in older adults. However, our understanding of age-related cognition and brain morphology occurring throughout a broader spectrum of adulthood remains limited. We quantified the relationship between cognitive function and brain morphology (sulcal width, SW) using three cross-sectional observational datasets (PISA, AIBL, ADNI) from mid-life to older adulthood, assessing the influence of age, sex, amyloid (Aβ) and genetic risk for dementia. The data comprised cognitive, genetic and neuroimaging measures of a total of 1570 non-clinical mid-life and older adults (mean age 72, range 49–90 years, 1330 males) and 1365 age- and sex-matched adults with mild cognitive impairment (MCI) or Alzheimer’s disease (AD). Among non-clinical adults, we found robust modes of co-variation between regional SW and multidomain cognitive function that differed between the mid-life and older age range. These cortical and cognitive profiles derived from healthy cohorts predicted out-of-sample AD and MCI. Furthermore, Aβ-deposition and educational attainment levels were associated with cognition but not SW. These findings underscoring the complex interplay between factors influencing cognition and brain structure from mid-life onwards, providing valuable insights for future research into neurodegeneration and the development of future screening algorithms.
- Subject
- Alzheimer's disease; cognitive ageing; computational neuroscience; neuroscience
- Identifier
- http://hdl.handle.net/1959.13/1518021
- Identifier
- uon:57216
- Identifier
- ISSN:2045-2322
- Rights
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Language
- eng
- Full Text
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