Wang Yisong, Yang Longtao, Liu Jun
Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410011, China.
Clinical Research Center for Medical Imaging in Hunan Province, Changsha 410011, China.
Biomedicines. 2023 May 29;11(6):1575. doi: 10.3390/biomedicines11061575.
Disruption of brain resting-state networks (RSNs) is known to be related to stroke exposure, but determining causality can be difficult in epidemiological studies. We used data on genetic variants associated with the levels of functional (FC) and structural connectivity (SC) within 7 RSNs identified from a genome-wide association study (GWAS) meta-analysis among 24,336 European ancestries. The data for stroke and its subtypes were obtained from the MEGASTROKE consortium, including up to 520,000 participants. We conducted a two-sample bidirectional Mendelian randomization (MR) study to investigate the causality relationship between FC and SC within 7 RSNs and stroke and its subtypes. The results showed that lower global mean FC and limbic network FC were associated with a higher risk of any ischemic stroke and small vessel stroke separately. Moreover, ventral attention network FC and default mode network SC have a positive causal relationship with the risk of small vessel stroke and large artery stroke, respectively. In the inverse MR analysis, any stroke and large artery stroke were causally related to dorsal attention network FC and somatomotor FC, respectively. The present study provides genetic support that levels of FC or SC within different RSNs have contrasting causal effects on stroke and its subtypes. Moreover, there is a combination of injury and compensatory physiological processes in brain RSNs following a stroke. Further studies are necessary to validate our results and explain the physiological mechanisms.
已知大脑静息态网络（RSNs）的破坏与中风暴露有关，但在流行病学研究中确定因果关系可能很困难。我们使用了与从一项针对24336名欧洲血统个体的全基因组关联研究（GWAS）荟萃分析中确定的7个RSNs内的功能连接（FC）和结构连接（SC）水平相关的基因变异数据。中风及其亚型的数据来自MEGASTROKE联盟，包括多达520000名参与者。我们进行了一项两样本双向孟德尔随机化（MR）研究，以调查7个RSNs内的FC和SC与中风及其亚型之间的因果关系。结果表明，较低的全脑平均FC和边缘网络FC分别与任何缺血性中风和小血管中风的较高风险相关。此外，腹侧注意网络FC和默认模式网络SC分别与小血管中风和大动脉中风的风险呈正因果关系。在反向MR分析中，任何中风和大动脉中风分别与背侧注意网络FC和躯体运动FC存在因果关系。本研究提供了基因支持，表明不同RSNs内的FC或SC水平对中风及其亚型具有相反的因果效应。此外，中风后大脑RSNs中存在损伤和代偿性生理过程的组合。需要进一步的研究来验证我们的结果并解释其生理机制。
