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- Cedres, N, et al.
(författare)
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Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease
- 2021
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Ingår i: Neuro-degenerative diseases. - : S. Karger AG. - 1660-2862 .- 1660-2854. ; 20:4, s. 153-164
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Tidskriftsartikel (refereegranskat)abstract
- <b><i>Introduction:</i></b> We investigated the association between atrophy subtypes of Alzheimer’s disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer’s Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]). <b><i>Methods:</i></b> A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and <i>APOE</i> genotype. <b><i>Results:</i></b> Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N− profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T−N− or A+T−N+ profiles clustered together and were mainly from KIDS. <i>APOE</i> ε4 carriers more frequently showed the A+T−N− and A+T+N− profiles. <b><i>Conclusions:</i></b> Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.
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- Ferreira, D, et al.
(författare)
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Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications
- 2017
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7, s. 46263-
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Tidskriftsartikel (refereegranskat)abstract
- Atrophy patterns on MRI can reliably predict three neuropathological subtypes of Alzheimer’s disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to enable their investigation in the clinical routine is still lacking. We aimed to (1) validate the combined use of visual rating scales for identification of AD subtypes; (2) characterise these subtypes at baseline and over two years; and (3) investigate how atrophy patterns and non-memory cognitive domains contribute to memory impairment. AD patients were classified as either typical AD (n = 100), limbic-predominant (n = 33), or hippocampal-sparing (n = 35) by using the Scheltens’ scale for medial temporal lobe atrophy (MTA), the Koedam’s scale for posterior atrophy (PA), and the Pasquier’s global cortical atrophy scale for frontal atrophy (GCA-F). A fourth group with no atrophy was also identified (n = 30). 230 healthy controls were also included. There was great overlap among subtypes in demographic, clinical, and cognitive variables. Memory performance was more dependent on non-memory cognitive functions in hippocampal-sparing and the no atrophy group. Hippocampal-sparing and the no atrophy group showed less aggressive disease progression. Visual rating scales can be used to identify distinct AD subtypes. Recognizing AD heterogeneity is important and visual rating scales may facilitate investigation of AD heterogeneity in clinical routine.
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- Ferreira, D, et al.
(författare)
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Electroencephalography Is a Good Complement to Currently Established Dementia Biomarkers
- 2016
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Ingår i: Dementia and geriatric cognitive disorders. - : S. Karger AG. - 1421-9824 .- 1420-8008. ; 42:1-2, s. 80-92
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Tidskriftsartikel (refereegranskat)abstract
- <b><i>Background/Aims:</i></b> Dementia biomarkers that are accessible and easily applicable in nonspecialized clinical settings are urgently needed. Quantitative electroencephalography (qEEG) is a good candidate, and the statistical pattern recognition (SPR) method has recently provided promising results. We tested the diagnostic value of qEEG-SPR in comparison to cognition, structural imaging, and cerebrospinal fluid (CSF) biomarkers. <b><i>Methods:</i></b> A total of 511 individuals were recruited from the multicenter NORD EEG study [141 healthy controls, 64 subjective cognitive decline, 124 mild cognitive impairment, 135 Alzheimer's disease (AD), 15 dementia with Lewy bodies/Parkinson's disease with dementia (DLB/PDD), 32 other dementias]. The EEG data were recorded in a standardized way. Structural imaging data were visually rated using scales of atrophy in the medial temporal, frontal, and posterior cortex. <b><i>Results:</i></b> qEEG-SPR outperformed structural imaging, cognition, and CSF biomarkers in DLB/PDD diagnosis, outperformed structural imaging in AD diagnosis, and improved the differential diagnosis of AD. In addition, qEEG-SPR allowed differentiation of two clinically different AD subtypes. <b><i>Conclusion:</i></b> Adding qEEG to the diagnostic workup substantially increases the detection of AD pathology even in pre-dementia stages and improves differential diagnosis. EEG could serve as a good complement to currently established dementia biomarkers since it is cheap, noninvasive, and extensively applied outside academic centers.
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