Department of Computer Sciences and Engineering, University of Texas, Arlington, TX, U.S.A.; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Institute for Aging Research, Harvard Medical School, Boston, MA, U.S.A.; Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Neuroimage Clin. 2019;21:101586. doi: 10.1016/j.nicl.2018.10.024. Epub 2018 Oct 23.
In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia.
除了β淀粉样斑块和神经原纤维缠结的发展外,阿尔茨海默病(AD)还涉及连接结构的丧失,包括髓鞘轴突和突触连接的退化。然而,AD 无症状、临床前阶段的白质束变化程度,尤其是纵向变化程度,仍未得到充分描述。在这项研究中,我们使用了一种新的图小波算法,来确定微观结构脑变化与 CSF 生物标志物观察到的 AD 神经病理学发展的协调程度。从两个观察性和纵向随访队列中选择了 118 名至少有两次弥散张量成像(DTI)扫描和一次腰椎穿刺的 CSF 的参与者。CSF 被用于检测 AD 特有的病理(Aβ42 和磷酸化 tau)、神经退行性变(总 tau)、轴突变性(神经丝轻链蛋白;NFL)和突触变性(神经颗粒蛋白)。在 DTI 扫描上进行了轨迹学,以获得具有 160 个节点的结构连接网络,其中节点对应于特定的脑感兴趣区(ROI),其连接由 DTI 指标(即分数各向异性(FA)和平均弥散度(MD))定义。在分析中,我们采用了一种称为小波连接签名(WaCS)的多分辨率图小波技术,该技术从每个大脑连接的 DTI 指标中得出更高阶的表示。我们的统计分析显示了 CSF 测量值和 MRI 时间间隔之间的相互作用,例如,升高的 CSF 生物标志物和更长的时间与白质微观结构的纵向变化更大相关(FA 降低和 MD 增加)。具体来说,我们检测到总共 17 条纤维束,其 WaCS 表示与白质微观结构的纵向下降与 CSF p-tau 和神经颗粒蛋白之间存在关联。虽然神经原纤维缠结和突触变性的发展是皮质现象,但结果表明,它们也与基础白质束的退化有关,这一过程最终可能在认知能力下降和痴呆的发展中发挥作用。