Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Ontario, Canada.
Hum Brain Mapp. 2022 Aug 15;43(12):3680-3693. doi: 10.1002/hbm.25876. Epub 2022 Apr 15.
White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. Two hundred and fifty-four participants from the Coronary Artery Risk Development in Young Adults study were selected and stratified by WMH burden into Lo-WMH (mean age = 50 ± 3.5 years) and Hi-WMH (mean age = 51 ± 3.7 years) groups of equal size. We constructed group-level covariance networks based on cerebral blood flow (CBF) and gray matter volume (GMV) maps across 74 gray matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo- and Hi-WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no between-group differences in either CBF or GMV covariance networks. In contrast, we found between-group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence that WMH-related network alterations are present at midlife.
脑白质高信号(WMHs)是脑小血管病的标志,但在中年时其对大脑的影响尚未得到很好的描述。在这里,我们研究了 WMH 体积是否与中年成年人的大脑网络改变有关。从冠状动脉风险发展在年轻人研究中选择了 254 名参与者,并根据 WMH 负担分为低 WMH(平均年龄= 50 ± 3.5 岁)和高 WMH(平均年龄= 51 ± 3.7 岁)两组,每组大小相等。我们基于 74 个灰质区域的脑血流(CBF)和灰质体积(GMV)图谱构建了组水平协方差网络。通过共识聚类,我们发现 CBF 和 GMV 协方差网络都分为模块,这些模块在两组之间基本一致。接下来,我们比较了 Lo-和 Hi-WMH 组之间 CBF 和 GMV 协方差网络的拓扑结构,包括全局(聚类系数、特征路径长度、全局效率)和局部(度、介数中心性、局部效率)水平。在全局水平上,无论是 CBF 还是 GMV 协方差网络,两组之间都没有差异。相比之下,我们发现 CBF 和 GMV 协方差网络中的几个脑区的局部度、介数中心性和局部效率存在组间差异。总之,CBF 和 GMV 协方差分析提供了证据表明,WMH 相关的网络改变存在于中年时期。