Ramírez-Toraño F, Abbas Kausar, Bruña Ricardo, Marcos de Pedro Silvia, Gómez-Ruiz Natividad, Barabash Ana, Pereda Ernesto, Marcos Alberto, López-Higes Ramón, Maestu Fernando, Goñi Joaquín
Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain.
Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, IN 46202, USA.
Cereb Cortex Commun. 2021 Aug 27;2(4):tgab051. doi: 10.1093/texcom/tgab051. eCollection 2021.
The concept of the brain has shifted to a complex system where different subnetworks support the human cognitive functions. Neurodegenerative diseases would affect the interactions among these subnetworks and, the evolution of impairment and the subnetworks involved would be unique for each neurodegenerative disease. In this study, we seek for structural connectivity traits associated with the family history of Alzheimer's disease, that is, early signs of subnetworks impairment due to Alzheimer's disease. The sample in this study consisted of 123 first-degree Alzheimer's disease relatives and 61 nonrelatives. For each subject, structural connectomes were obtained using classical diffusion tensor imaging measures and different resolutions of cortical parcellation. For the whole sample, independent structural-connectome-traits were obtained under the framework of . Finally, we tested the association of the structural-connectome-traits with different factors of relevance for Alzheimer's disease by means of a multiple linear regression. The analysis revealed a structural-connectome-trait obtained from fractional anisotropy associated with the family history of Alzheimer's disease. The structural-connectome-trait presents a reduced fractional anisotropy pattern in first-degree relatives in the tracts connecting posterior areas and temporal areas. The family history of Alzheimer's disease structural-connectome-trait presents a posterior-posterior and posterior-temporal pattern, supplying new evidences to the cascading network failure model.
大脑的概念已转变为一个复杂的系统,其中不同的子网络支持人类认知功能。神经退行性疾病会影响这些子网络之间的相互作用,并且,损伤的演变以及所涉及的子网络对于每种神经退行性疾病而言都是独特的。在本研究中,我们寻找与阿尔茨海默病家族史相关的结构连接特征,即阿尔茨海默病导致的子网络损伤的早期迹象。本研究中的样本包括123名阿尔茨海默病一级亲属和61名非亲属。对于每个受试者,使用经典扩散张量成像测量和不同分辨率的皮质分区来获取结构连接组。对于整个样本,在……框架下获得独立的结构连接组特征。最后,我们通过多元线性回归测试了结构连接组特征与阿尔茨海默病不同相关因素之间的关联。分析揭示了一种从分数各向异性获得的与阿尔茨海默病家族史相关的结构连接组特征。该结构连接组特征在连接后部区域和颞部区域的纤维束中,一级亲属呈现出分数各向异性降低的模式。阿尔茨海默病家族史的结构连接组特征呈现出后部-后部和后部-颞部模式,为级联网络故障模型提供了新证据。