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1.
  • De Meyer, Steffi, et al. (author)
  • Plasma pTau181 and pTau217 predict asymptomatic amyloid accumulation equally well as amyloid PET
  • 2024
  • In: BRAIN COMMUNICATIONS. - 2632-1297. ; 6:4
  • Journal article (peer-reviewed)abstract
    • The dynamic phase of preclinical Alzheimer's disease, as characterized by accumulating cortical amyloid-beta, is a window of opportunity for amyloid-beta-lowering therapies to have greater efficacy. Biomarkers that accurately predict amyloid-beta accumulation may be of critical importance for participant inclusion in secondary prevention trials and thus enhance development of early Alzheimer's disease therapies. We compared the abilities of baseline plasma pTau181, pTau217 and amyloid-beta PET load to predict future amyloid-beta accumulation in asymptomatic elderly. In this longitudinal cohort study, baseline plasma pTau181 and pTau217 were quantified using single molecule array assays in cognitively unimpaired elderly selected from the community-recruited F-PACK cohort based on the availability of baseline plasma samples and longitudinal amyloid-beta PET data (median time interval = 5 years, range 2-10 years). The predictive abilities of pTau181, pTau217 and PET-based amyloid-beta measures for PET-based amyloid-beta accumulation were investigated using receiver operating characteristic analyses, correlations and stepwise regression analyses. We included 75 F-PACK subjects (mean age = 70 years, 48% female), of which 16 were classified as amyloid-beta accumulators [median (interquartile range) Centiloid rate of change = 3.42 (1.60) Centiloids/year). Plasma pTau181 [area under the curve (95% confidence interval) = 0.72 (0.59-0.86)] distinguished amyloid-beta accumulators from non-accumulators with similar accuracy as pTau217 [area under the curve (95% confidence interval) = 0.75 (0.62-0.88) and amyloid-beta PET [area under the curve (95% confidence interval) = 0.72 (0.56-0.87)]. Plasma pTau181 and pTau217 strongly correlated with each other (r = 0.93, P-false discovery rate < 0.001) and, together with amyloid-beta PET, similarly correlated with amyloid-beta rate of change (r(pTau181) = 0.33, r(pTau217) = 0.36, r(amyloid-beta PET) = 0.35, all P-false discovery rate <= 0.01). Addition of plasma pTau181, plasma pTau217 or amyloid-beta PET to a linear demographic model including age, sex and APOE-epsilon 4 carriership similarly improved the prediction of amyloid-beta accumulation (Delta Akaike information criterion <= 4.1). In a multimodal biomarker model including all three biomarkers, each biomarker lost their individual predictive ability. These findings indicate that plasma pTau181, plasma pTau217 and amyloid-beta PET convey overlapping information and therefore predict the dynamic phase of asymptomatic amyloid-beta accumulation with comparable performances. In clinical trial recruitment, confirmatory PET scans following blood-based prescreening might thus not provide additional value for detecting participants in these early disease stages who are destined to accumulate cortical amyloid-beta. Given the moderate performances, future studies should investigate whether integrating plasma pTau species with other factors can improve performance and thus enhance clinical and research utility.
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2.
  • Quenon, Lisa, et al. (author)
  • Amyloid-PET imaging predicts functional decline in clinically normal individuals
  • 2024
  • In: Alzheimer's Research and Therapy. - 1758-9193. ; 16:1
  • Journal article (peer-reviewed)abstract
    • Background: There is good evidence that elevated amyloid-β (Aβ) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aβ burden and decline in daily living activities in this population. Moreover, Aβ-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. Methods: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aβ groups (CL < 12 = Aβ-, 12 ≤ CL ≤ 50 = Aβ-intermediate/Aβ±, CL > 50 = Aβ+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. Results: Participants included 765 Aβ- (61%, Mdnage = 66.0, IQRage = 61.0–71.0; 59% women), 301 Aβ± (24%; Mdnage = 69.0, IQRage = 64.0–75.0; 53% women) and 194 Aβ+ individuals (15%, Mdnage = 73.0, IQRage = 68.0–78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p =.003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p =.002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aβ+ CN individuals (HRAβ+ vs Aβ- = 2.55, 95% CI [1.16,5.60], p =.020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAβ+ vs Aβ- = 0.137/year, 95% CI [0.069,0.206], p <.001) and 28 CL using the A-IADL-Q (bAβ+ vs Aβ- = -0.693/year, 95% CI [-1.179,-0.208], p =.005). Conclusions: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. Trial registration: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.
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