阿尔茨海默病功能网络损伤亚型数据集

阿尔茨海默病是一种高异质性的疾病。个体之间的异质性对疾病的诊疗和机制研究造成了重要不利影响。本研究以阿尔茨海默病功能连接标记物为特征，利用非平滑非负矩阵分解算法探究了阿尔茨海默病的功能连接损伤亚型。阿尔茨海默病患者被可重复地分为4个损伤亚型，其中包括表现为弥散和轻度功能连接损伤的亚型1；表现为默认模式网络损伤并伴随前额叶连接增强的亚型2；表现为前扣带皮层连接损伤并伴随前额叶连接增强的亚型3；表现为基底神经节相关的功能连接损伤并伴随前额叶连接增强的亚型4。本数据集包括各个亚型的重要相关的功能连接数据。

Alzheimer's disease (AD) is a highly heterogeneous disorder. Inter-individual heterogeneity exerts substantial adverse effects on the diagnosis, treatment, and mechanistic studies of this disease. In this study, taking functional connectivity markers of AD as features, we explored the functional connectivity impairment subtypes of AD using the non-smooth non-negative matrix factorization algorithm. AD patients were reproducibly classified into four impairment subtypes, including Subtype 1, which exhibits diffuse and mild functional connectivity impairments; Subtype 2, which shows default mode network (DMN) impairment accompanied by enhanced prefrontal cortex connectivity; Subtype 3, which exhibits anterior cingulate cortex connectivity impairment accompanied by enhanced prefrontal cortex connectivity; and Subtype 4, which shows basal ganglia-related functional connectivity impairment accompanied by enhanced prefrontal cortex connectivity. This dataset contains critical functional connectivity data associated with each of the subtypes.