Cluster-Based White Matter Signatures and the Risk of Dementia, Stroke, and Mortality in Community-Dwelling Adults

Mathijs T Rosbergen1, Frank J Wolters1, Elisabeth J Vinke1

  • 1From the Department of Epidemiology (M.T.R., F.J.W., E.J.V., F.U.S.M.-R., G.V.R., M.A.I., M.W.V.), Department of Radiology and Nuclear Medicine (M.T.R., F.J.W., E.J.V., G.V.R., M.W.V.), Department of Internal Medicine (F.U.S.M.-R.), and Department of Medical Informatics (G.V.R.), Erasmus MC University Medical Center, Rotterdam, the Netherlands.

Neurology
|September 10, 2024
PubMed
Abstract

Insights

Brain MRI reveals four distinct white matter (WM) injury signatures. These signatures, characterized by atrophy and microstructural integrity, predict varying risks of dementia, stroke, and mortality in older adults.

Area of Science:

  • Neuroimaging
  • Gerontology
  • Public Health

Background:

  • White matter (WM) injury markers on brain MRI are crucial for assessing brain health.
  • Distinct patterns of WM atrophy, WM hyperintensities (WMHs), and microstructural integrity may indicate different pathologies and disease risks.
  • Large-scale studies identifying WM signatures and their associated risks are limited.

Purpose of the Study:

  • To identify distinct WM signatures in community-dwelling adults using brain MRI.
  • To determine the underlying risk factor profiles for each identified WM signature.
  • To assess the risks of dementia, stroke, and mortality associated with each WM signature.

Main Methods:

  • Utilized structural and diffusion MRI data from 5,279 participants (aged >45) in the Rotterdam study.
  • Measured WMH volume, WM volume, fractional anisotropy (FA), and mean diffusivity (MD) using automated pipelines.
  • Applied hierarchical clustering to identify WM injury clusters and Cox proportional hazard models to assess risks.

Main Results:

  • Identified 4 distinct WM signatures based on microstructural integrity, WM atrophy, and WMH.
  • Clusters with poorer microstructural integrity and substantial WMH/atrophy showed higher prevalence of cardiovascular risk factors.
  • Increased risks for dementia, stroke, and mortality were associated with specific WM signatures compared to the healthiest signature.

Conclusions:

  • Data-driven WM signatures derived through clustering are differentially associated with dementia, stroke, and mortality risks.
  • These signatures offer a more comprehensive understanding of WM injury beyond individual markers.
  • Future research should integrate spatial information of imaging markers for enhanced predictive power.