Cao Hang, Wei Penghu, Huang Yuda, Wang Ningrui, Guo Lin-Ai, Fan Xiaotong, Wang Zhenming, Ren Liankun, Piao Yueshan, Lu Jie, Shan Yongzhi, He Xiaosong, Zhao Guoguang
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, 45 Changchun St, Beijing, 100053, China.
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, 45 Changchun St, Beijing, 100053, China; Clinical Research Center for Epilepsy, Xuanwu Hospital, Capital Medical University, 45 Changchun St, Beijing, 100053, China; Beijing Municipal Geriatric Medical Research Center, 45 Changchun St, Beijing, 100053, China.
EBioMedicine. 2023 Oct 28;97:104847. doi: 10.1016/j.ebiom.2023.104847.
Drug-resistant epilepsy (DRE) is associated with distributed laminar disruptions due to cytoarchitectonic pathologies, which may be characterized by multimodal MRI approaches such as morphometric similarity networks (MSNs). However, the genetic and histological underpinning of MSN alterations in DRE remains poorly understood, hampering its clinical application.
We enrolled 60 patients with DRE and 23 controls, acquiring T1 and diffusion spectrum imaging data with a 3.0T GE SIGNA Premier scanner. Morphometric similarity networks (MSNs) were constructed and analyzed to identify microstructure similarity differences between patients and controls. Subsequently, patient-specific MSN alteration patterns were associated with gene expression using the GAMBA tool, and layer-specific neuronal signature mapping were also applied. During these analyses, sex and age were adjusted as covariates and multiple comparisons corrections were applied when appropriate.
We observed widespread MSN changes in patients with DRE and identified five distinct MSN alteration patterns. Major patterns presented pattern-specific associations with expressions of epilepsy-related genes, particularly involving the mTOR pathway. Histological analysis confirmed the presence of cortical microstructure changes in areas with MSN alterations and revealed cellular abnormalities matching the aforementioned genetic risks.
Our findings highlight the potential of quantifying laminar-related microstructure integrity using MSN to uncover the cytoarchitectonic changes in the pathophysiology of DRE. This approach may facilitate the identification of genetic and histological underpinnings of MSN alterations in DRE, ultimately aiding in the development of targeted therapeutic strategies.
The National Natural Science Foundation of China, the Ministry of Science and Technology of the People's Republic of China, and the Beijing Municipal Health Commission.
耐药性癫痫(DRE)与细胞结构病理学导致的分布性层状破坏有关,这可能通过形态相似性网络(MSN)等多模态磁共振成像方法来表征。然而,DRE中MSN改变的遗传和组织学基础仍知之甚少,这阻碍了其临床应用。
我们招募了60例DRE患者和23名对照,使用3.0T GE SIGNA Premier扫描仪获取T1和扩散光谱成像数据。构建并分析形态相似性网络(MSN),以识别患者和对照之间的微观结构相似性差异。随后,使用GAMBA工具将患者特异性MSN改变模式与基因表达相关联,并应用层特异性神经元特征映射。在这些分析过程中,将性别和年龄作为协变量进行调整,并在适当的时候应用多重比较校正。
我们观察到DRE患者中存在广泛的MSN变化,并确定了五种不同的MSN改变模式。主要模式呈现出与癫痫相关基因表达的模式特异性关联,特别是涉及mTOR通路。组织学分析证实了MSN改变区域存在皮质微观结构变化,并揭示了与上述遗传风险相匹配的细胞异常。
我们的研究结果强调了使用MSN量化层相关微观结构完整性以揭示DRE病理生理学中细胞结构变化的潜力。这种方法可能有助于识别DRE中MSN改变的遗传和组织学基础,最终有助于制定针对性的治疗策略。
中国国家自然科学基金、中华人民共和国科学技术部以及北京市卫生健康委员会。