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.

中文翻译：

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基于簇的白质特征与社区居住成年人的痴呆、中风和死亡风险。


背景和目的脑 MRI 上的白质 (WM) 损伤标志物是大脑健康的重要指标。 WM 萎缩、WM 高信号 (WMH) 和微观结构完整性的不同模式可以反映不同的病理和疾病风险，但缺乏调查 WM 特征的大规模影像学研究。本研究旨在利用社区成年人的脑部 MRI 来识别不同的 WM 特征，确定潜在的危险因素概况，并评估与每个特征相关的痴呆、中风和死亡风险。方法 2005 年至 2016 年间，我们使用鹿特丹研究中年龄超过 45 岁的社区居民的结构和扩散 MRI 自动管道测量了 WMH 体积、WM 体积、分数各向异性 (FA) 和平均扩散率 (MD)。对痴呆、中风和死亡率进行了持续监测。我们应用层次聚类来识别单独的 WM 损伤簇，并应用 Cox 比例风险模型来确定他们患痴呆、中风和死亡的风险。结果 我们纳入了 5,279 名参与者（平均年龄 65.0 岁，56.0% 为女性），并确定了 4 个不同的数据驱动的 WM 特征：（1）高于平均水平的微观结构完整性和很少的 WM 萎缩和 WMH； (2) 微观结构完整性高于平均水平，WMH 很少，但 WM 明显萎缩； (3)微观结构完整性较差，WMH较多，但WM萎缩很少； (4) 微观结构完整性差，WMH 和 WM 严重萎缩。第 3 组和第 4 组中心血管危险因素、腔隙和脑微出血的患病率高于第 1 组和第 2 组。在中位 10.7 年的随访期间，291 名参与者出现痴呆，220 人中风，910 人死亡。 与聚类 1 相比，所有聚类的痴呆风险均增加，尤其是聚类 3（风险比 [HR] 3.06，95% CI 2.12-4.42），其次是聚类 4（HR 2.31，95% CI 1.58-3.37）和聚类 2 （HR 1.67，95% CI 1.17-2.38）。与聚类 1 相比，仅聚类 3（HR 1.55，95% CI 1.02-2.37）和聚类 4（HR 1.94，95% CI 1.30-2.89）的卒中风险较高，而所有聚类（聚类 2）的死亡风险均增加：与聚类 1 相比，HR 1.27，95% CI 1.06-1.53​​，聚类 3：HR 1.65，95% CI 1.35-2.03，聚类 4：HR 1.76，95% CI 1.44-2.15）。模型包含聚类而不是个体成像标记物对痴呆和死亡率显示出优异的拟合优度，但对中风则不然。讨论 聚类可以得出与痴呆、中风和死亡风险有差异相关的 WM 特征。未来的研究应该纳入成像标记的空间信息。