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总脑小血管病负荷不同患者脑结构网络拓扑属性改变及其与认知障碍的相关性研究
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Abstract:
目的：研究总脑小血管病(cerebral small vessel disease, CSVD)负荷不同患者脑结构连接的拓扑属性及其与认知功能的关系。方法：纳入2018年12月至2021年12月期间招募的54名总CSVD负荷严重患者(CSVD-s组)、117名总CSVD负荷轻微患者(CSVD-m组)和73名健康对照者(HC组)。我们使用概率性纤维追踪及图论方法构建白质结构网络，并描述网络的拓扑属性(如小世界属性和网络效率等)。利用单因素协方差分析(analysis of covariance, ANCOVA)对图论指标进行组间比较，进而分析组间显著改变的节点效率与认知参数之间的Pearson相关性。结果：CSVD组和HC组在白质结构网络中均表现出小世界属性。与CSVD-m组和HC组相比，CSVD-s组的局部效率、归一化集聚系数及小世界指数显著(p < 0.05)增加，枢纽分布部分重组。此外，CSVD-s组在左侧眶部额回、海马、丘脑及基底神经节节点效率显著(ANCOVA, p < 0.05)增加。虽然在CSVD-m组中没有发现明显的全局和区域拓扑属性发生变化，但是该组右侧眶内额上回、眶部额中回、杏仁核、苍白球及前扣带回的节点效率与认知参数显著(p < 0.05，FDR校正)相关。值得注意的是，CSVD-s组中却没有发现节点效率与认知功能之间存在显著相关关系。结论：总CSVD负荷不同患者结构网络的改变为辨别CSVD疾病严重程度提供了新的理论依据。认知功能与拓扑属性的相关性表明它们有可能被用作评估CSVD风险的生物标志物。
Objective: To investigate the topological properties of brain structural connectivity and its rela-tionship to cognitive function in cerebral small vessel disease (CSVD) patients with different total CSVD burden. Methods: Fifty-four patients with severe total CSVD burden (CSVD-s group), 117 pa-tients with mild total CSVD burden (CSVD-m group), and 73 healthy controls (HC group) were re-cruited between December 2018 and December 2021. We used probabilistic tractography and graph theory methods to construct white matter structural networks and describe the topological properties of the network (e.g., small-world properties and network efficiency). One-way analysis of covariance (ANCOVA) was used to compare graph theoretic indicators among groups, and thus to assess Pearson’s correlations between significantly changed nodal indicators and cognitive param-eters. Results: Both the CSVD and HC groups exhibited efficient small-world properties in white matter structural networks. Compared with the CSVD-m group and the control group, the CSVD-s group showed significantly (p < 0.05) increased local efficiency, normalized clustering coefficient and small world index, with partially reorganized hub distributions. In addition, the CSVD-s group showed significantly (ANCOVA, p < 0.05) increased nodal efficiency in the left orbital frontal gyrus, hippocampus, thalamus, basal ganglia. Although no significant global and regional topological al-terations were found in the CSVD-m group, the nodal efficiency in the medial orbital superior frontal gyrus, orbital middle frontal gyrus, amygdala, pallidum and anterior cingulate gyrus was signifi-cantly (p < 0.05, FDR corrected) correlated with cognitive parameters. Notably, no significant Pear-son’s correlation between nodal metrics and cognitive function was found in the CSVD-s group. Con-clusion: The alterations of structural networks in
| [1] | Cuadrado-Godia, E., Dwivedi, P., Sharma, S., et al. (2018) Cerebral Small Vessel Disease: A Review Focusing on Pathophysiology, Biomarkers, and Machine Learning Strategies. Journal of Stroke, 20, 302-320.
https://doi.org/10.5853/jos.2017.02922 |
| [2] | Wardlaw, J.M., Smith, E.E., Biessels, G.J., et al. (2013) Neuroimag-ing Standards for Research into Small Vessel Disease and Its Contribution to Ageing and Neurodegeneration. The Lancet Neurology, 12, 822-838.
https://doi.org/10.1016/S1474-4422(13)70124-8 |
| [3] | Klarenbeek, P., van Oostenbrugge, R.J., Rouhl, R.P., Knottnerus, I.L. and Staals, J. (2013) Ambulatory Blood Pressure in Patients with Lacunar Stroke: Association with Total MRI Burden of Cerebral Small Vessel Disease. Stroke, 44, 2995- 2999. https://doi.org/10.1161/STROKEAHA.113.002545 |
| [4] | Brickman, A.M. (2013) Contemplating Alzheimer’s Dis-ease and the Contribution of White Matter Hyperintensities. Current Neurology and Neuroscience Reports, 13, 415. https://doi.org/10.1007/s11910-013-0415-7 |
| [5] | Pinter, D., Enzinger, C. and Fazekas, F. (2015) Cerebral Small Vessel Disease, Cognitive Reserve and Cognitive Dysfunction. Journal of Neurology, 262, 2411-2419. https://doi.org/10.1007/s00415-015-7776-6 |
| [6] | He, Y. and Evans, A. (2010) Graph Theoretical Modeling of Brain Connectivity. Current Opinion in Neurology, 23, 341-350. https://doi.org/10.1097/WCO.0b013e32833aa567 |
| [7] | Fazekas, F., Chawluk, J.B., Alavi, A., Hurtig, H.I. and Zimmerman, R.A. (1987) MR Signal Abnormalities at 1.5 T in Alzheimer’s Dementia and Normal Aging. AJR American Journal of Roentgenology, 149, 351-356.
https://doi.org/10.2214/ajr.149.2.351 |
| [8] | Wen, H., Liu, Y., Rekik, I., et al. (2017) Disrupted Topological Organi-zation of Structural Networks Revealed by Probabilistic Diffusion Tractography in Tourette Syndrome Children. Human Brain Mapping, 38, 3988-4008.
https://doi.org/10.1002/hbm.23643 |
| [9] | Cao, Q., Shu, N., An, L., et al. (2013) Probabilistic Diffusion Tractog-raphy and Graph Theory Analysis Reveal Abnormal White Matter Structural Connectivity Networks in Drug-Naive Boys with Attention Deficit/Hyperactivity Disorder. Journal of Neuroscience, 33, 10676-10687. https://doi.org/10.1523/JNEUROSCI.4793-12.2013 |
| [10] | He, Y., Wang, J., Wang, L., et al. (2009) Uncovering In-trinsic Modular Organization of Spontaneous Brain Activity in Humans. PLOS ONE, 4, e5226. https://doi.org/10.1371/journal.pone.0005226 |
| [11] | Sporns, O. (2011) The Human Connectome: A Complex Net-work. Annals of the New York Academy of Sciences, 1224, 109-125. https://doi.org/10.1111/j.1749-6632.2010.05888.x |
| [12] | Sporns, O., Tononi, G. and K？tter, R. (2005) The Human Connectome: A Structural Description of the Human Brain. PLOS Computational Biology, 1, e42. https://doi.org/10.1371/journal.pcbi.0010042 |
| [13] | He, Y., Dagher, A., Chen, Z., et al. (2009) Impaired Small-World Efficiency in Structural Cortical Networks in Multiple Sclerosis Associated with White Matter Lesion Load. Brain, 132, 3366-3379.
https://doi.org/10.1093/brain/awp089 |
| [14] | Sporns, O. and Honey, C.J. (2006) Small Worlds inside Big Brains. Proceedings of the National Academy of Sciences of the United States of America, 103, 19219-19220. https://doi.org/10.1073/pnas.0609523103 |
| [15] | Xin, H., Wen, H., Feng, M., et al. (2022) Disrupted Topological Organization of Resting-State Functional Brain Networks in Cerebral Small Vessel Disease. Human Brain Mapping, 43, 2607-2620. https://doi.org/10.1002/hbm.25808 |
| [16] | Wang, Z., Dai, Z., Gong, G., Zhou, C. and He, Y. (2015) Un-derstanding Structural-Functional Relationships in the Human Brain: A Large-Scale Network Perspective. Neuroscientist, 21, 290-305.
https://doi.org/10.1177/1073858414537560 |
| [17] | van den Heuvel, M.P. and Sporns, O. (2013) Network Hubs in the Human Brain. Trends in Cognitive Sciences, 17, 683-696. https://doi.org/10.1016/j.tics.2013.09.012 |
| [18] | Triarhou, L.C. (2021) Cytoarchitectonics of the Rolandic Operculum: Morphofunctional Ponderings. Brain Structure and Function, 226, 941-950. https://doi.org/10.1007/s00429-021-02258-z |
| [19] | Wada, S., Honma, M., Masaoka, Y., et al. (2021) Volume of the Right Supramarginal Gyrus Is Associated with a Maintenance of Emotion Recognition Ability. PLOS ONE, 16, e0254623.
https://doi.org/10.1371/journal.pone.0254623 |
| [20] | Zhao, P., Yan, R., Wang, X., et al. (2019) Reduced Resting State Neural Activity in the Right Orbital Part of Middle Frontal Gyrus in Anxious Depression. Front Psychiatry, 10, 994. https://doi.org/10.3389/fpsyt.2019.00994 |
| [21] | Zhao, C., Zhu, J., Liu, X., et al. (2018) Structural and Func-tional Brain Abnormalities in Schizophrenia: A Cross-Sec- tional Study at Different Stages of the Disease. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 83, 27-32. https://doi.org/10.1016/j.pnpbp.2017.12.017 |
| [22] | Milad, M.R. and Rauch, S.L. (2012) Obsessive-Compulsive Disorder: Beyond Segregated Cortico-Striatal Pathways. Trends in Cognitive Sciences, 16, 43-51. https://doi.org/10.1016/j.tics.2011.11.003 |
| [23] | Liu, R., Wu, W., Ye, Q., et al. (2019) Distinctive and Pervasive Al-terations of Functional Brain Networks in Cerebral Small Vessel Disease with and without Cognitive Impairment. De-mentia and Geriatric Cognitive Disorders, 47, 55-67.
https://doi.org/10.1159/000496455 |
| [24] | Papma, J.M., de Groot, M., de Koning, I., et al. (2014) Cerebral Small Vessel Disease Affects White Matter Microstructure in Mild Cognitive Impairment. Human Brain Mapping, 35, 2836-2851. https://doi.org/10.1002/hbm.22370 |
| [25] | Chen, X., Wang, J., Shan, Y., et al. (2019) Cerebral Small Vessel Disease: Neuroimaging Markers and Clinical Implication. Journal of Neurology, 266, 2347-2362. https://doi.org/10.1007/s00415-018-9077-3 |
| [26] | Chen, H., Wan, H., Zhang, M., et al. (2021) Cerebral Small Ves-sel Disease May Worsen Motor Function, Cognition, and Mood in Parkinson’s Disease. Parkinsonism & Related Dis-orders, 83, 86-92.
https://doi.org/10.1016/j.parkreldis.2020.12.025 |
