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- Collij, Lyduine E., et al.
(författare)
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Quantification of [18F]florbetaben amyloid-PET imaging in a mixed memory clinic population : The ABIDE project
- 2023
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Ingår i: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 19:6, s. 2397-2407
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: We investigated amyloid-burden quantification in a mixed memory clinic population. Methods: [18F]Florbetaben amyloid-PET (positron emission tomography) scans of 348 patients were visually read and quantified using the Centiloid (CL) method. General linear models were used to assess CL differences across syndromic and etiological diagnosis. Linear mixed models were fitted to assess the predictive value of visual read (VR) and CL on longitudinal Mini-Mental Status Examination (MMSE). Results: CL was associated with syndromic (F = 4.42, p = 0.014) and etiological diagnosis (F = -12.66, p < 0.001), with Alzheimer's disease (AD) patients showing the highest amyloid burden (62.9 ± 27.5), followed by dementia with Lewy bodies (DLB) (25.3 ± 35.5) and cardiovascular disease (CVD) (16.7 ± 24.5), and finally frontotemporal lobe degeneration (FTLD) (5.0 ± 17.22, t = –12.66, p < 0.001). CL remained predictive of etiological diagnosis (t = –2.41, p = 0.017) within the VR+ population (N = 157). VR was not a significant predictor of MMSE (t = –1.53, p = 0.13) for the SCD population (N = 90), whereas CL was (t = -3.30, p = 0.001). Discussion: The extent of amyloid pathology through quantification holds clinical value, potentially in the context of differential diagnosis as well as prognosis.
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| 2. |
- Salvadó, Gemma, et al.
(författare)
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Optimal combinations of CSF biomarkers for predicting cognitive decline and clinical conversion in cognitively unimpaired participants and mild cognitive impairment patients: A multi-cohort study
- 2023
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 19:7, s. 2943-2955
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases.Methods: We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of A beta 42, A beta 40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, alpha-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit).Results: Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/A beta 42 alone (R-2 >= 0.31) or together with NfL (R-2 = 0.25), while p-tau/A beta 42 (R-2 >= 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/A beta 42 (AUC >= 0.87) and p-tau/A beta 42 together with NfL (AUC >= 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively.Discussion: P-tau/A beta 42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline.
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| 3. |
- Salvadó, Gemma, et al.
(författare)
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The protective gene dose effect of the APOE ε2 allele on gray matter volume in cognitively unimpaired individuals
- 2022
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Ingår i: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:7, s. 1383-1395
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Harboring two copies of the apolipoprotein E (APOE) ε2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described. Methods: Multicenter brain magnetic resonance images (MRIs) from cognitively unimpaired ε2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of ε2 genotypic groups were compared to each other and to the reference group (APOE ε3/ε3). Results: Carrying at least one ε2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE ε2 homozygotes, but not APOE ε2 heterozygotes, showed larger GM volumes in areas related to successful aging. Discussion: In addition to the known resistance against amyloid-β deposition, the larger GM volumes in key brain regions may confer APOE ε2 homozygotes additional protection against AD-related cognitive decline.
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| 4. |
- Wink, Alle Meije, et al.
(författare)
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Quantifying AD-related brain amyloid with linearised progression models : model-based vs. data-based.
- 2022
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Ingår i: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:S1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Brain amyloid-β (Aβ) is the pathological hallmark of Alzheimer's disease (AD). In logistic disease models, Aβ accumulation is a sigmoid function of time-since-disease-onset (TSDO) (figure 1). Previous positron emission tomography (PET)-based models vary accumulation onset(t50) and duration(r) globally; capacity(K) and baseline(NS) regionally (Whittington2018). We confirm existing approaches and propose a more powerful ICA-based approach to quantify disease severity and estimate TSDO. Method: We used 1071 18F-florbetapir standard uptake value ratio (SUVR) images from the ADNI-2 study (adni.loni.usc.edu/data-samples/data-types/pet). Images were mapped into MNI space. Averages were extracted using the Harvard-Oxford brain-atlas. Whole-brain tracer-specific sigmoid parameters (Jack2013) obtained from the literature were used to estimate TSDO. Of 16 models of regional Aβ accumulation (each of the 4 regional sigmoid parameters varied either regionally or globally), the optimal Bayesian information criterion was found with global t50 and r, and regional NS and K (figure 1) with global values r=6.16y and t50=4.10y. Linearised maps of NS and K were obtained by regressing the SUVR maps onto the global sigmoid. We also estimated these maps as independent components, using a 2-component ICA on the SUVR maps. Both outcomes were used to quantify Aβ accumulation from SUVR images as weighting factors of the accumulation map. We compared the weights from the logistic model and the ICA model in ADNI, using effect size measured with Hedges' g between cognitively normal (CN), subjective memory complaints (SMC), mild cognitive impairment (EMCI/MCI/LMCI) and AD groups. We compared 3 longitudinal visits (N=112) in the OASIS-3 study (see www.oasis-brains.org) with both methods, global SUVR and Centiloid (Klunk2015) using 11C-PiB PET SUVR images. Result: Maps of accumulation capacity from both models had spatial correlation of 0.86 (figure 2); baseline maps had spatial correlation of 0.95. Hedges' g between ADNI groups was 2.25 for K, and 2.42 for ICA (1.46 for global SUVR). In OASIS-3, Hedges' g between visits was 1.24 for K, 1.46 for ICA (global SUVR 0.15, Centiloid 0.4). Conclusion: We demonstrate that linear accumulation models can be used to quantify brain Aβ with PET; maps obtained by ICA yield larger effect sizes than the logistic method for differentiating groups and measuring changes between visits.
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