School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore.
School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore.
Neuroimage Clin. 2018;20:1222-1232. doi: 10.1016/j.nicl.2018.10.026. Epub 2018 Oct 29.
The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Although white matter (WM) impairment also contributes to AD pathology, its heterogeneity remains unclear. The Latent Dirichlet Allocation (LDA) method is a suitable framework to study heterogeneity and allows to identify latent impairment factors of AD instead of simply mapping an overall disease effect. By exploring whole brain WM skeleton images by using LDA, three latent factors were revealed in AD: a temporal-frontal impairment factor (temporal and frontal lobes, especially hippocampus and para-hippocampus), a parietal factor (parietal lobe, especially precuneus), and a long fibre bundle factor (corpus callosum and superior longitudinal fasciculus). As revealed by longitudinal analysis, the latent factors have distinct impact on cognitive decline: for executive function (EF), the temporal-frontal factor was more strongly associated with baseline EF compared with the parietal factor, while the long-fibre bundle factor was most associated with decline rate of EF; for memory, the three factors showed almost equal effect on the baseline memory and decline rate. For each participant, LDA estimates his/her composition profile of latent impairment factors, which indicates disease subtype. We also found that the APOE genotype affects the AD subtype. Specifically, APOE ε4 was more associated with the long fibre bundle factor and APOE ε2 was more associated with temporal-frontal factor. By investigating heterogeneity and subtypes of AD through white matter impairment factors, our study could facilitate precision medicine.
阿尔茨海默病（AD）的临床表现并非单一，因为疾病的临床和解剖特征存在异质性。MRI 研究表明，不均匀的灰质萎缩模式与特定的认知衰退特征有关。尽管白质（WM）损伤也与 AD 病理学有关，但它的异质性尚不清楚。潜在狄利克雷分配（LDA）方法是研究异质性的合适框架，可以识别 AD 的潜在损伤因素，而不是简单地映射整体疾病效应。通过使用 LDA 探索全脑 WM 骨架图像，在 AD 中发现了三个潜在因素：颞额叶损伤因素（颞叶和额叶，特别是海马体和海马旁回）、顶叶因素（顶叶，特别是楔前叶）和长纤维束因素（胼胝体和上纵束）。通过纵向分析发现，潜在因素对认知衰退有明显的影响：对于执行功能（EF），颞额叶因素与基线 EF 的相关性强于顶叶因素，而长纤维束因素与 EF 的下降速度相关性最强；对于记忆，三个因素对基线记忆和下降速度的影响几乎相同。对于每个参与者，LDA 估计其潜在损伤因素的组成分布，这表明疾病亚型。我们还发现 APOE 基因型影响 AD 亚型。具体来说，APOE ε4 与长纤维束因素更相关，APOE ε2 与颞额叶因素更相关。通过研究 WM 损伤因素的 AD 异质性和亚型，我们的研究可以促进精准医学。
