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Data‐driven approach reveals heterogeneity and region‐specific association of white matter hyperintensities with the APOE genotype

We used a transparent machine learning algorithm to identify subtypes of white matter damage in aging and to characterize their clinical representations. White matter hyperintensities (WMH), a common finding on brain magnetic resonance imaging (MRI), are known to be associated with cognitive impairment and dementia. Previous studies have shown spatial heterogeneity of WMH appearance, but the contribution of Alzheimer disease (AD) dementia and related genetic risk factors to this heterogeneity remains unclear. We sought to investigate the heterogeneity of WMH, in the general population, leveraging state of the art pattern analysis methods and exploring whether the APOE genotype is contributing to this heterogeneity.