Frontoparietal atrophy trajectories in cognitively unimpaired elderly individuals using longitudinal Bayesian clustering

Comput Biol Med. 2024 Nov:182:109190. doi: 10.1016/j.compbiomed.2024.109190. Epub 2024 Oct 2.

Abstract

Introduction: Frontal and/or parietal atrophy has been reported during aging. To disentangle the heterogeneity previously observed, this study aimed to uncover different clusters of grey matter profiles and trajectories within cognitively unimpaired individuals.

Methods: Structural magnetic resonance imaging (MRI) data of 307 Aβ-negative cognitively unimpaired individuals were modelled between ages 60-85 from three cohorts worldwide. We applied unsupervised clustering using a novel longitudinal Bayesian approach and characterized the clusters' cerebrovascular and cognitive profiles.

Results: Four clusters were identified with different grey matter profiles and atrophy trajectories. Differences were mainly observed in frontal and parietal brain regions. These distinct frontoparietal grey matter profiles and longitudinal trajectories were differently associated with cerebrovascular burden and cognitive decline.

Discussion: Our findings suggest a conciliation of the frontal and parietal theories of aging, uncovering coexisting frontoparietal GM patterns. This could have important future implications for better stratification and identification of at-risk individuals.

Keywords: Aging; Atrophy; Clustering; Heterogeneity; Longitudinal; MRI.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Aging / pathology
  • Aging / physiology
  • Atrophy* / pathology
  • Bayes Theorem*
  • Cluster Analysis
  • Cognition / physiology
  • Cognitive Dysfunction / diagnostic imaging
  • Cognitive Dysfunction / pathology
  • Female
  • Frontal Lobe* / diagnostic imaging
  • Frontal Lobe* / pathology
  • Gray Matter / diagnostic imaging
  • Gray Matter / pathology
  • Humans
  • Longitudinal Studies
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Parietal Lobe* / diagnostic imaging