Abstract
BACKGROUND AND OBJECTIVES: Markers of white matter (WM) injury on brain MRI are important indicators of brain health. Different patterns of WM atrophy, WM hyperintensities (WMHs), and microstructural integrity could reflect distinct pathologies and disease risks, but large-scale imaging studies investigating WM signatures are lacking. This study aims to identify distinct WM signatures using brain MRI in community-dwelling adults, determine underlying risk factor profiles, and assess risks of dementia, stroke, and mortality associated with each signature. METHODS: Between 2005 and 2016, we measured WMH volume, WM volume, fractional anisotropy (FA), and mean diffusivity (MD) using automated pipelines on structural and diffusion MRI in community-dwelling adults aged older than 45 years of the Rotterdam study. Continuous surveillance was conducted for dementia, stroke, and mortality. We applied hierarchical clustering to identify separate WM injury clusters and Cox proportional hazard models to determine their risk of dementia, stroke, and mortality. RESULTS: We included 5,279 participants (mean age 65.0 years, 56.0% women) and identified 4 distinct data-driven WM signatures: (1) above-average microstructural integrity and little WM atrophy and WMH; (2) above-average microstructural integrity and little WMH, but substantial WM atrophy; (3) poor microstructural integrity and substantial WMH, but little WM atrophy; and (4) poor microstructural integrity with substantial WMH and WM atrophy. Prevalence of cardiovascular risk factors, lacunes, and cerebral microbleeds was higher in clusters 3 and 4 than in clusters 1 and 2. During a median 10.7 years of follow-up, 291 participants developed dementia, 220 had a stroke, and 910 died. Compared with cluster 1, dementia risk was increased for all clusters, notably cluster 3 (hazard ratio [HR] 3.06, 95% CI 2.12-4.42), followed by cluster 4 (HR 2.31, 95% CI 1.58-3.37) and cluster 2 (HR 1.67, 95% CI 1.17-2.38). Compared with cluster 1, risk of stroke was higher only for clusters 3 (HR 1.55, 95% CI 1.02-2.37) and 4 (HR 1.94, 95% CI 1.30-2.89), whereas mortality risk was increased in all clusters (cluster 2: HR 1.27, 95% CI 1.06-1.53, cluster 3: HR 1.65, 95% CI 1.35-2.03, cluster 4: HR 1.76, 95% CI 1.44-2.15), compared with cluster 1. Models including clusters instead of an individual imaging marker showed a superior goodness of fit for dementia and mortality, but not for stroke. DISCUSSION: Clustering can derive WM signatures that are differentially associated with dementia, stroke, and mortality risk. Future research should incorporate spatial information of imaging markers.