White matter microstructural differences in children and genetic risk for multiple sclerosis: A population-based study

C Louk de Mol, Rinze F Neuteboom, Philip R Jansen, Tonya White

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

BACKGROUND: MS patients show abnormalities in white matter (WM) on brain imaging, with heterogeneity in the location of WM lesions. The "pothole" method can be applied to diffusion-weighted images to identify spatially distinct clusters of divergent brain WM microstructure.

OBJECTIVE: To investigate the association between genetic risk for MS and spatially independent clusters of decreased or increased fractional anisotropy (FA) in the brain. In addition, we studied sex- and age-related differences.

METHODS: 3 Tesla diffusion tensor imaging (DTI) data were collected in 8- to 12-year-old children from a population-based study. Global and tract-based potholes (lower FA clusters) and molehills (higher FA clusters) were quantified in 3047 participants with usable DTI data. A polygenic risk score (PRS) for MS was calculated in genotyped individuals ( n = 1087) and linear regression analyses assessed the relationship between the PRS and the number of potholes and molehills, correcting for multiple testing using the False Discovery Rate.

RESULTS: The number of molehills increased with age, potholes decreased with age, and fewer potholes were observed in girls during typical development. The MS-PRS was positively associated with the number of molehills (β = 0.9, SE = 0.29, p = 0.002). Molehills were found more often in the corpus callosum (β = 0.3, SE = 0.09, p = 0.0003).

CONCLUSION: Genetic risk for MS is associated with spatially distinct clusters of increased FA during childhood brain development.

Original languageEnglish
Pages (from-to)730-741
Number of pages12
JournalMultiple sclerosis (Houndmills, Basingstoke, England)
Volume28
Issue number5
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Anisotropy
  • Brain/diagnostic imaging
  • Child
  • Diffusion Tensor Imaging/methods
  • Female
  • Humans
  • Multiple Sclerosis/diagnostic imaging
  • Risk Factors
  • White Matter/diagnostic imaging

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