From the Department of Radiology & Nuclear Medicine, Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX Maastricht, the Netherlands (L.W.M.V., J.F.A.J., S.K., M.P.J.v.B., J.J.A.d.J., W.H.B.); MHeNs School for Mental Health and Neuroscience (L.W.M.V., J.F.A.J., S.K., M.P.J.v.B., J.J.A.d.J., M.T.S., W.H.B.), Department of Internal Medicine (T.T.v.S., C.D.A.S., N.C.S., P.C.D., A.A.K., M.T.S.), School for Cardiovascular Disease (CARIM) (L.W.M.V., T.T.v.S., C.D.A.S., N.C.S., P.C.D., A.A.K., M.T.S., W.H.B.), Care and Public Health Institute (CAPHRI) (N.C.S.), School of Nutrition and Translational Research in Metabolism (NUTRIM) (A.W., M.T.S.), and Department of Complex Genetics & Epidemiology (A.W.), Maastricht University, Maastricht, the Netherlands; and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.).
Radiology. 2021 Feb;298(2):384-392. doi: 10.1148/radiol.2021202634. Epub 2020 Dec 22.
Background Lesions of cerebral small vessel disease, such as white matter hyperintensities (WMHs) in individuals with cardiometabolic risk factors, interfere with the trajectories of the white matter and eventually contribute to cognitive decline. However, there is no consensus yet about the precise underlying topological mechanism. Purpose To examine whether WMH and cognitive function are associated and whether any such association is mediated or explained by structural connectivity measures in an adult population. In addition, to investigate underlying local abnormalities in white matter by assessing the tract-specific WMH volumes and their tract-specific association with cognitive function. Materials and Methods In the prospective type 2 diabetes-enriched population-based Maastricht Study, structural and diffusion-tensor MRI was performed (December 2013 to February 2017). Total and tract-specific WMH volumes; network measures; cognition scores; and demographic, cardiovascular, and lifestyle characteristics were determined. Multivariable linear regression and mediation analyses were used to investigate the association of WMH volume, tract-specific WMH volumes, and network measures with cognitive function. Associations were adjusted for age, sex, education, diabetes status, and cardiovascular risk factors. Results A total of 5083 participants (mean age, 59 years ± 9 [standard deviation]; 2592 men; 1027 with diabetes) were evaluated. Larger WMH volumes were associated with stronger local (standardized β coefficient, 0.065; < .001), but not global, network efficiency and lower information processing speed (standardized β coefficient, -0.073; < .001). Moreover, lower local efficiency (standardized β coefficient, -0.084; < .001) was associated with lower information processing speed. In particular, the relationship between WMHs and information processing speed was mediated (percentage mediated, 7.2% [95% CI: 3.5, 10.9]; < .05) by the local network efficiency. Finally, WMH load was larger in the white matter tracts important for information processing speed. Conclusion White matter hyperintensity volume, local network efficiency, and information processing speed scores are interrelated, and local network properties explain lower cognitive performance due to white matter network alterations. © RSNA, 2020
有心脏代谢危险因素的个体的脑小血管病病变，如脑白质高信号（WMH），会干扰脑白质的轨迹，最终导致认知能力下降。然而，对于确切的潜在拓扑机制，目前尚未达成共识。目的：在成年人中，检查 WMH 与认知功能是否相关，以及任何这种关联是否通过结构连通性测量来介导或解释。此外，通过评估特定白质束的 WMH 体积及其与认知功能的特定白质束关联，来研究白质内的潜在局部异常。材料与方法：在 2 型糖尿病丰富的前瞻性人群为基础的 Maastricht 研究中，进行了结构和弥散张量 MRI 检查（2013 年 12 月至 2017 年 2 月）。测定总 WMH 体积和特定白质束的 WMH 体积；网络指标；认知评分；以及人口统计学、心血管和生活方式特征。使用多变量线性回归和中介分析来研究 WMH 体积、特定白质束的 WMH 体积和网络指标与认知功能的关系。协变量包括年龄、性别、教育、糖尿病状态和心血管危险因素。结果：共评估了 5083 名参与者（平均年龄，59 岁±9[标准差]；2592 名男性；1027 名患有糖尿病）。更大的 WMH 体积与更强的局部（标准化β系数，0.065；<0.001）而不是全局网络效率和更低的信息处理速度相关（标准化β系数，-0.073；<0.001）。此外，较低的局部效率（标准化β系数，-0.084；<0.001）与较低的信息处理速度相关。特别是，WMH 与信息处理速度之间的关系通过局部网络效率来介导（介导百分比，7.2%[95%CI：3.5，10.9]；<0.05）。最后，在与信息处理速度相关的白质束中，WMH 负荷更大。结论：WMH 体积、局部网络效率和信息处理速度评分相互关联，由于白质网络改变，局部网络特性解释了较低的认知表现。
