Background

Alzheimer’s disease (AD) is a neurodegenerative disorder with significant heterogeneity. Different AD phenotypes may be associated with specific brain network changes. Uncovering disease heterogeneity by using functional networks could provide insights into precise diagnoses.

Methods

We investigated the subtypes of AD using nonnegative matrix factorization clustering on the previously identified 216 resting-state functional connectivities that differed between AD and normal control subjects. We conducted the analysis using a discovery dataset (n = 809) and a validated dataset (n = 291). Next, we grouped individuals with mild cognitive impairment according to the model obtained in the AD groups. Finally, the clinical measures and brain structural characteristics were compared among the subtypes to assess their relationship with differences in the functional network.

Results

Individuals with AD were clustered into 4 subtypes reproducibly, which included those with 1) diffuse and mild functional connectivity disruption (subtype 1), 2) predominantly decreased connectivity in the default mode network accompanied by an increase in the prefrontal circuit (subtype 2), 3) predominantly decreased connectivity in the anterior cingulate cortex accompanied by an increase in prefrontal cortex connectivity (subtype 3), and 4) predominantly decreased connectivity in the basal ganglia accompanied by an increase in prefrontal cortex connectivity (subtype 4). In addition to these differences in functional connectivity, differences between the AD subtypes were found in cognition, structural measures, and cognitive decline patterns.

Conclusions

These comprehensive results offer new insights that may advance precision medicine for AD and facilitate strategies for future clinical trials.

中文翻译：

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基于静息状态连通性生物标志物的四种不同的阿尔茨海默病亚型

背景

阿尔茨海默病 (AD) 是一种具有显着异质性的神经退行性疾病。不同的 AD 表型可能与特定的大脑网络变化有关。通过使用功能网络发现疾病异质性可以提供对精确诊断的洞察力。

方法

我们使用非负矩阵分解聚类对先前确定的 216 个静息态功能连接性进行了研究，这些连接性在 AD 和正常对照受试者之间存在差异。我们使用发现数据集 ( n  = 809) 和经过验证的数据集 ( n  = 291)进行了分析。接下来，我们根据在 AD 组中获得的模型对具有轻度认知障碍的个体进行分组。最后，比较不同亚型的临床指标和脑结构特征，以评估它们与功能网络差异的关系。

结果

患有 AD 的个体可重复地分为 4 种亚型，其中包括 1) 弥漫性和轻度功能连接中断（亚型 1），2）默认模式网络中连接性显着降低，同时前额叶回路增加（亚型 2）， 3) 前扣带回皮层的连通性显着降低，同时前额皮质连通性增加（3 型），以及 4)基底神经节的连通性显着降低，并伴有前额叶皮质连通性的增加（4 型）。除了功能连接的这些差异外，AD 亚型之间的差异还存在于认知、结构测量和认知衰退模式中。

结论

这些全面的结果提供了新的见解，可能会推进 AD 的精准医学并促进未来临床试验的策略。