A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease.
A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease.
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一种全脑计算建模方法来解释阿尔茨海默氏病进展过程中静息状态功能连通性的变化。
DOI：
10.1016/j.nicl.2017.08.006
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Deco G
中科院分区：
文献类型：
--
作者：
Demirtaş M;Falcon C;Tucholka A;Gispert JD;Molinuevo JL;Deco G
阿尔茨海默病(AD)是最常见的痴呆症，后果严重。对结构和功能神经成像的研究表明，阿尔茨海默病患者的大脑连接性发生了变化。在这项研究中，我们研究了临床前阿尔茨海默病(PAD)、AD引起的轻度认知障碍(MCI)和阿尔茨海默病(AD)引起的轻度痴呆(AD)受试者的全脑静息状态功能连通性(FC)，APOE4携带的影响，以及与核心AD脑脊液生物标志物变化的关系。在疾病的发展过程中，全脑的同步性单调地降低。此外，在AD患者中，我们发现功能连接性(FC)强度普遍显著下降，特别是在具有高全球连接性的大脑区域。我们采用了全脑计算建模的方法来研究这些变化背后的机制。为了描述大脑区域之间的因果相互作用，我们估计了模型中的有效连接性(EC)。我们发现AD患者EC的显著差异主要位于左侧颞叶。然后，我们系统地操纵模型的潜在动力学，以健康对照受试者为基础，研究FC的模拟变化。此外，我们还发现了脑脊液中淀粉样β蛋白(Aβ1和−42)、总tau(t-tau)和磷酸化tau(p-tau)生物标志物的不同模式。脑脊液Aβ-1和−-42与健康对照组和临床组之间的对比有关。然而，tau-csf生物标志物与全脑同步区和感觉统合区的变异性有关。这些关联在临床组中很强，不同于在脑脊液Aβ1和−42中发现的关联。载脂蛋白E4运载量与连通性指标无显著相关性。对临床前阿尔茨海默病(PAD)、AD所致轻度认知损害(MCI)和阿尔茨海默病(AD)所致轻度痴呆患者的全脑静息状态功能连接性(FC)进行了研究。随着AD的进展，全脑同步化的均值和标准差逐渐减小。阿尔茨海默病患者的局部功能障碍表现为广泛的下降，而全脑计算模拟方法揭示了左侧颞叶是这些改变的核心。在健康对照受试者中系统地操纵模型的动态机制产生与临床组(PAD、MCI、AD)中经验观察到的FC相匹配的模拟FC模式。淀粉样β-脑脊液生物标记物主要反映临床组相对于健康对照组的连接性改变。总tau和磷酸化tau-csf生物标志物显示出明显的地区性关联，这种关联也存在于临床分组中。
Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 − 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 − 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 − 42. APOE4 carriership showed no significant correlations with the connectivity measures. Whole-brain resting state functional connectivity (FC) is investigated in subjects with preclinical Alzheimer’s disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer’s disease (AD). Mean and standard deviation of the whole-brain synchronization reduce during the progression of AD. Regional FC shows widespread decreases in AD group, whereas whole-brain computational modeling approach reveals the left temporal lobe as the core of these alterations. Systematically manipulating the dynamical regime of the model in healthy control subjects generates simulated FC patterns that match to the empirically observed FC in clinical groups (PAD, MCI, AD). Amyloid-beta CSF biomarker primarily reflects the connectivity alterations in clinical groups with respect to the healthy control group. Total tau and phosphorylated tau CSF biomarkers show distinct regional associations that are present also across clinical groups.
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DOI：
10.1016/s0140-6736(20)32205-4
发表时间：
2021-04-24
期刊：
Lancet (London, England)
影响因子：
--
作者：
Scheltens P;De Strooper B;Kivipelto M;Holstege H;Chételat G;Teunissen CE;Cummings J;van der Flier WM
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van der Flier WM
DOI：
10.1073/pnas.0308627101
发表时间：
2004-03-30
影响因子：
11.1
作者：
Greicius, MD;Srivastava, G;Menon, V
通讯作者：
Menon, V
影响因子：
4.6
作者：
Deco, Gustavo;Kringelbach, Morten L.;Ritter, Petra
通讯作者：
Ritter, Petra
影响因子：
3.4
作者：
Glerean, Enrico;Salmi, Juha;Sams, Mikko
通讯作者：
Sams, Mikko
DOI：
10.1016/j.jalz.2011.03.004
发表时间：
2011-05
期刊：
Alzheimer's & dementia : the journal of the Alzheimer's Association
影响因子：
--
作者：
Jack CR Jr;Albert MS;Knopman DS;McKhann GM;Sperling RA;Carrillo MC;Thies B;Phelps CH
通讯作者：
Phelps CH