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Reconfigured metabolism brain network in asymptomatic microtubule-associated protein tau mutation carriers: a graph theoretical analysis

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机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Changchun St 45, Beijing, Peoples R China [2]Shenyang Fifth People Hosp, Dept Neurol, Shenyang, Peoples R China [3]Chinese Acad Sci, Beijing Engn Res Ctr Radiog Tech & Equipment, Inst High Energy Phys, Beijing, Peoples R China [4]Univ Chinese Acad Sci, Sch Nucl Sci & Technol, Beijing, Peoples R China [5]Shanxi Med Univ, Dept Neurol, Hosp 2, Taiyuan, Peoples R China [6]Arizona State Univ, Arizona Alzheimers Consortium, Univ Arizona, Sch Math & Stat,Banner Alzheimers Inst, Tempe, AZ USA [7]McGill Ctr Studies Aging, Alzheimers Dis Res Unit, Montreal, PQ H4H 1R3, Canada [8]Natl Clin Res Ctr Geriatr Dis, Beijing, Peoples R China
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关键词: Frontotemporal dementia MAPT gene FDG-PET Brain network Graph theory

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Background Studies exploring topological properties of the metabolic network during the presymptomatic stage of genetic frontotemporal dementia (FTD) are scarce. However, such knowledge is important for understanding brain function and disease pathogenesis. Therefore, we aimed to explore FTD-specific patterns of metabolism topology reconfiguration in microtubule-associated protein tau (MAPT) mutation carriers before the onset of symptoms. Methods Six asymptomatic carriers of the MAPT P301L mutation were compared with 12 non-carriers who all belonged to the same family of FTD. For comparison, we included 32 behavioral variant FTD (bvFTD) patients and 33 unrelated healthy controls. Each participant underwent neuropsychological assessments, genetic testing, and a hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) scan. Voxel-wise gray matter volumes and standardized uptake value ratios were calculated and compared for structural MRI and fluorodeoxyglucose (FDG)-PET, separately. The sparse inverse covariance estimation method (SICE) was applied to topological properties and metabolic connectomes of brain functional networks derived from F-18-FDG PET/MRI data. Independent component analysis was used to explore the metabolic connectivity of the salience (SN) and default mode networks (DMN). Results The asymptomatic MAPT carriers performed normal global parameters of the metabolism network, whereas bvFTD patients did not. However, we revealed lost hubs in the ventromedial prefrontal, orbitofrontal, and anterior cingulate cortices and reconfigured hubs in the anterior insula, precuneus, and posterior cingulate cortex in asymptomatic carriers compared with non-carriers, which overlapped with the comparisons between bvFTD patients and controls. Similarly, significant differences in local parameters of these nodes were present between asymptomatic carriers and non-carriers. The reduction in the connectivity of lost hub regions and the enhancement of connectivity between reconfigured hubs and components of the frontal cortex were marked during the asymptomatic stage. Metabolic connectivity within the SN and DMN was enhanced in asymptomatic carriers compared with non-mutation carriers but reduced in bvFTD patients relative to controls. Conclusions Our findings showed that metabolism topology reconfiguration, characterized by the earliest involvement of medial prefrontal areas and active compensation in task-related regions, was present in the presymptomatic phase of genetic FTD with MAPT mutation, which may be used as an imaging biomarker of increased risk of FTD.

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出版当年[2021]版:
大类 | 2 区 医学
小类 | 2 区 临床神经病学 2 区 神经科学
最新[2023]版:
大类 | 1 区 医学
小类 | 1 区 临床神经病学 1 区 神经科学
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出版当年[2020]版:
Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES
最新[2023]版:
Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

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第一作者机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Changchun St 45, Beijing, Peoples R China [2]Shenyang Fifth People Hosp, Dept Neurol, Shenyang, Peoples R China
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通讯机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Changchun St 45, Beijing, Peoples R China [8]Natl Clin Res Ctr Geriatr Dis, Beijing, Peoples R China
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