| 1. |
- Altomare, Daniele, et al.
(author)
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Applying the ATN scheme in a memory clinic population : The ABIDE project
- 2019
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In: Neurology. - 1526-632X. ; 93:17, s. 1635-1646
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Journal article (peer-reviewed)abstract
- OBJECTIVE: To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features. METHODS: We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([18F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time. RESULTS: The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia. CONCLUSIONS: The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.
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| 2. |
- de Wilde, Arno, et al.
(author)
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Assessment of the appropriate use criteria for amyloid PET in an unselected memory clinic cohort : The ABIDE project
- 2019
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In: Alzheimer's and Dementia. - : Wiley. - 1552-5260.
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Journal article (peer-reviewed)abstract
- Introduction: The objective of this study was to assess the usefulness of the appropriate use criteria (AUC) for amyloid imaging in an unselected cohort. Methods: We calculated sensitivity and specificity of appropriate use (increased confidence and management change), as defined by Amyloid Imaging Taskforce in the AUC, and other clinical utility outcomes. Furthermore, we compared differences in post–positron emission tomography diagnosis and management change between “AUC-consistent” and “AUC-inconsistent” patients. Results: Almost half (250/507) of patients were AUC-consistent. In both AUC-consistent and AUC-inconsistent patients, post–positron emission tomography diagnosis (28%–21%) and management (32%–17%) change was substantial. The Amyloid Imaging Taskforce's definition of appropriate use occurred in 55/507 (13%) patients, detected by the AUC with a sensitivity of 93%, and a specificity of 56%. Diagnostic changes occurred independently of AUC status (sensitivity: 57%, specificity: 53%). Discussion: The current AUC are not sufficiently able to discriminate between patients who will benefit from amyloid positron emission tomography and those who will not.
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| 3. |
- Pelkmans, Wiesje, et al.
(author)
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Astrocyte biomarkers GFAP and YKL-40 mediate early Alzheimer's disease progression.
- 2023
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In: Alzheimer's & dementia : the journal of the Alzheimer's Association. - 1552-5279. ; 20:1, s. 483-93
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Journal article (peer-reviewed)abstract
- We studied how biomarkers of reactive astrogliosis mediate the pathogenic cascade in the earliest Alzheimer's disease (AD) stages.We performed path analysis on data from 384 cognitively unimpaired individuals from the ALzheimer and FAmilies (ALFA)+ study using structural equation modeling to quantify the relationships between biomarkers of reactive astrogliosis and the AD pathological cascade.Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/40 was associated with Aβ aggregation on positron emission tomography (PET) and with CSF p-tau181 , which was in turn directly associated with CSF neurofilament light (NfL). Plasma glial fibrillary acidic protein (GFAP) mediated the relationship between CSF Aβ42/40 and Aβ-PET, and CSF YKL-40 partly explained the association between Aβ-PET, p-tau181 , and NfL.Our results suggest that reactive astrogliosis, as indicated by different fluid biomarkers, influences the pathogenic cascade during the preclinical stage of AD. While plasma GFAP mediates the early association between soluble and insoluble Aβ, CSF YKL-40 mediates the latter association between Aβ and downstream Aβ-induced tau pathology and tau-induced neuronal injury.Lower CSF Aβ42/40 was directly linked to higher plasma GFAP concentrations. Plasma GFAP partially explained the relationship between soluble Aβ and insoluble Aβ. CSF YKL-40 mediated Aβ-induced tau phosphorylation and tau-induced neuronal injury.
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| 4. |
- Pelkmans, Wiesje, et al.
(author)
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Tau-related grey matter network breakdown across the Alzheimer’s disease continuum
- 2021
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In: Alzheimer's Research and Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 13:1
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Journal article (peer-reviewed)abstract
- Background: Changes in grey matter covariance networks have been reported in preclinical and clinical stages of Alzheimer’s disease (AD) and have been associated with amyloid-β (Aβ) deposition and cognitive decline. However, the role of tau pathology on grey matter networks remains unclear. Based on previously reported associations between tau pathology, synaptic density and brain structural measures, tau-related connectivity changes across different stages of AD might be expected. We aimed to assess the relationship between tau aggregation and grey matter network alterations across the AD continuum. Methods: We included 533 individuals (178 Aβ-negative cognitively unimpaired (CU) subjects, 105 Aβ-positive CU subjects, 122 Aβ-positive patients with mild cognitive impairment, and 128 patients with AD dementia) from the BioFINDER-2 study. Single-subject grey matter networks were extracted from T1-weighted images and graph theory properties including degree, clustering coefficient, path length, and small world topology were calculated. Associations between tau positron emission tomography (PET) values and global and regional network measures were examined using linear regression models adjusted for age, sex, and total intracranial volume. Finally, we tested whether the association of tau pathology with cognitive performance was mediated by grey matter network disruptions. Results: Across the whole sample, we found that higher tau load in the temporal meta-ROI was associated with significant changes in degree, clustering, path length, and small world values (all p < 0.001), indicative of a less optimal network organisation. Already in CU Aβ-positive individuals associations between tau burden and lower clustering and path length were observed, whereas in advanced disease stages elevated tau pathology was progressively associated with more brain network abnormalities. Moreover, the association between higher tau load and lower cognitive performance was only partly mediated (9.3 to 9.5%) through small world topology. Conclusions: Our data suggest a close relationship between grey matter network disruptions and tau pathology in individuals with abnormal amyloid. This might reflect a reduced communication between neighbouring brain areas and an altered ability to integrate information from distributed brain regions with tau pathology, indicative of a more random network topology across different AD stages.
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