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Trajectories of Physiological Brain Aging and Related Factors in People Aged from 20 to over-80

  • Jin San Lee
  • , Seonwoo Kim
  • , Heejin Yoo
  • , Seongbeom Park
  • , Young Kyoung Jang
  • , Hee Jin Kim
  • , Ko Woon Kim
  • , Yeshin Kim
  • , Hyemin Jang
  • , Key Chung Park
  • , Kristine Yaffe
  • , Jin Ju Yang
  • , Jong Min Lee
  • , Duk L. Na
  • , Sang Won Seo*
  • *Corresponding author for this work
  • Kyung Hee University
  • Samsung Medical Center, Sungkyunkwan university
  • Sungkyunkwan University
  • Kangwon National University
  • University of California at San Francisco
  • Hanyang University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Background/Objective: In this study, we investigated a long-term trajectory of brain aging (from the 20 s to over-80) in cognitively normal (CN) individuals. We further determined whether differences in sex, education years, and apolipoprotein E 4 status affect age-related cortical thinning. Methods: A total of 2,944 CN individuals who underwent high-resolution (3.0-Tesla) magnetic resonance imaging were included in this study. Cortical thickness was measured using a surface-based method. Multiple linear regression analyses were performed to evaluate age-related cortical thinning and related factors. Results: Compared to those in their 20 s/30 s, participants in their 40 s showed thinning primarily in the medial and lateral frontal and inferior parietal regions, and cortical thinning occurred across most of the cortices with increasing age. Notably, the precuneus, inferior temporal and lateral occipital regions were relatively spared until later in life. Male and lower education years were associated with greater cortical thinning with distinct regional specificity. Conclusion: Our findings provide an important clue to understanding the mechanism of age-related cognitive decline and new strategies for preventing the acceleration of pathological brain aging.

Original languageEnglish
Pages (from-to)1237-1246
Number of pages10
JournalJournal of Alzheimer's Disease
Volume65
Issue number4
DOIs
StatePublished - 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Alzheimer's disease
  • cognitive disorders
  • dementia
  • magnetic resonance imaging

Quacquarelli Symonds(QS) Subject Topics

  • Psychology
  • Medicine

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