Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume

Stuart J. Ritchie*, David Alexander Dickie, Simon R. Cox, Maria Del C. Valdés Hernández, Ruth Sibbett, Alison Pattie, Devasuda Anblagan, Paul Redmond, Natalie A. Royle, Janie Corley, Susana Muñoz Maniega, Adele M. Taylor, Sherif Karama, Tom Booth, Alan J. Gow, John M. Starr, Mark E. Bastin, Joanna M. Wardlaw, Ian J. Deary

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
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Abstract

Fully characterizing age differences in the brain is a key task for combating aging-related cognitive decline. Using propensity score matching on 2 independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age of 92 years (n = 42) to very similar participants at mean age of 73 years (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in gray and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and general cognitive ability (tissue volumes and cortical thickness were not significant mediators in this analysis). These findings provide an unusual and valuable perspective on neurostructural aging, in which brains from the 8th and 10th decades of life differ widely despite the same cognitive, socioeconomic, and brain-volumetric starting points.

Original languageEnglish
Pages (from-to)146-158
Number of pages13
JournalNeurobiology of Aging
Volume62
Early online date16 Oct 2017
DOIs
Publication statusPublished - Feb 2018

Keywords

  • Aging
  • Brain volume
  • Lesion mapping
  • Structural MRI
  • White matter hyperintensities

ASJC Scopus subject areas

  • General Neuroscience
  • Ageing
  • Clinical Neurology
  • Developmental Biology
  • Geriatrics and Gerontology

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