Zhang Shiyu, Chen Yue, Zhou Hua, Zhao Zhong
The First People's Hospital of Kunshan, Suzhou, China.
Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Liaoning, China.
Front Neurol. 2025 Apr 8;16:1541709. doi: 10.3389/fneur.2025.1541709. eCollection 2025.
Cerebral small vessel disease (CSVD) is a heterogeneous cerebrovascular syndrome with a variety of pathological mechanisms and clinical manifestations. A majority of research have shown that CSVD is associated with reduced expression of structural covariance networks (SCNs), but most of these SCN studies based on the group-level, which limits their ability to reflect individual variations in heterogeneous diseases. The purpose of this study is to analyze the structural covariance aberrations in patients with cerebral small vessels by utilizing individualized differential structural covariance network (IDSCN) analysis to explore the differences in SCNs and depressive states at the individual-level.
A total of 22 CSVD patients with depression (CSVD+D) and 34 healthy controls (HCs) were included in this study. IDSCNs were constructed for each subject based on regional gray matter volumes derived from their T1-weighted MRI images. The unpaired-sample t-test was used to compare the IDSCNs between the two groups to obtain the differential structural covariance edge and its distribution. Finally, correlation analyses were performed between the differential edge, the total CSVD imaging burden and Hamilton Rating Scale for Depression (HAMD) score.
(1) Compared with HCs, the CSVD+D patients exhibited heterogeneous distributions of differential structural covariance edge, with the differential edge located between the caudate nucleus and the cerebellum. (2) There was a significant positive correlation between the total CSVD imaging burden and HAMD scores in CSVD patients with depression ( = 0.692, < 0.001).
This study analyzed the IDSCNs between CSVD+D patients and HCs, which may indicate that the individual structural covariance aberrations between the caudate nucleus and cerebellum may contribute to depression in CSVD patients. Additionally, the higher total CSVD imaging burden of CSVD patients may indicate more severe depression. This finding suggests that early magnetic resonance imaging (MRI) assessment in CSVD patients may facilitate the early identification of depressive states and their severity in the near future.
脑小血管病（CSVD）是一种具有多种病理机制和临床表现的异质性脑血管综合征。大多数研究表明，CSVD与结构协方差网络（SCNs）表达降低有关，但这些SCN研究大多基于组水平，这限制了它们反映异质性疾病个体差异的能力。本研究的目的是通过利用个体化差异结构协方差网络（IDSCN）分析来分析脑小血管病患者的结构协方差异常，以探索个体水平上SCNs与抑郁状态的差异。
本研究共纳入22例伴有抑郁的CSVD患者（CSVD+D）和34例健康对照者（HCs）。基于从其T1加权MRI图像得出的区域灰质体积为每个受试者构建IDSCNs。采用非配对样本t检验比较两组之间的IDSCNs，以获得差异结构协方差边及其分布。最后，对差异边、CSVD总成像负荷与汉密尔顿抑郁量表（HAMD）评分进行相关性分析。
（1）与HCs相比，CSVD+D患者表现出差异结构协方差边的异质性分布，差异边位于尾状核和小脑之间。（2）伴有抑郁的CSVD患者中，CSVD总成像负荷与HAMD评分之间存在显著正相关（r=0.692, P<0.001）。
本研究分析了CSVD+D患者与HCs之间的IDSCNs，这可能表明尾状核和小脑之间的个体结构协方差异常可能导致CSVD患者出现抑郁。此外，CSVD患者较高的CSVD总成像负荷可能表明抑郁更严重。这一发现表明，CSVD患者早期的磁共振成像（MRI）评估可能在不久的将来有助于早期识别抑郁状态及其严重程度。
