Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) 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 Aß burden and decline in daily living activities in this population. Moreover, Aß-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 Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). 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 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ 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 Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -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.

The spatial extent of tauopathy on [18F]MK-6240 tau PET shows stronger association with cognitive performances than the standard uptake value ratio in Alzheimer's disease.

PURPOSE: [18F]MK-6240, a second-generation tau PET tracer, is increasingly used for the detection and the quantification of in vivo cerebral tauopathy in Alzheimer's disease (AD). Given that neurological symptoms are better explained by the topography rather than by the nature of brain lesions, our study aimed to evaluate whether cognitive impairment would be more closely associated with the spatial extent than with the intensity of tau-PET signal, as measured by the standard uptake value ratio (SUVr). METHODS: [18F]MK6240 tau-PET data from 82 participants in the AD spectrum were quantified in three different brain regions (Braak ≤ 2, Braak ≤ 4, and Braak ≤ 6) using SUVr and the extent of tauopathy (EOT, percentage of voxels with SUVr ≥ 1.3). PET data were first compared between diagnostic categories, and ROC curves were computed to evaluate sensitivity and specificity. PET data were then correlated to cognitive performances and cerebrospinal fluid (CSF) tau values. RESULTS: The EOT in the Braak ≤ 2 region provided the highest diagnostic accuracies, distinguishing between amyloid-negative and positive clinically unimpaired individuals (threshold = 9%, sensitivity = 79%, specificity = 82%) as well as between prodromal AD and preclinical AD (threshold = 38%, sensitivity = 81%, specificity = 93%). The EOT better correlated with cognition than SUVr (∆R2 + 0.08-0.09) with the best correlation observed for EOT in the Braak ≤ 4 region (R2 = 0.64). Cognitive performances were more closely associated with PET metrics than with CSF values. CONCLUSIONS: Quantifying [18F]MK-6240 tau PET in terms of EOT rather than SUVr significantly increases the correlation with cognitive performances. Quantification in the mesiotemporal lobe is the most useful to diagnose preclinical AD or prodromal AD.

Suspecting Non-Alzheimer's Pathologies and Mixed Pathologies: A Comparative Study Between Brain Metabolism and Tau Images.

BACKGROUND: Alzheimer's disease (AD) pathology can be disclosed in vivo using amyloid and tau imaging, unlike non-AD neuropathologies for which no specific markers exist. OBJECTIVE: We aimed to compare brain hypometabolism and tauopathy to unveil non-AD pathologies. METHODS: Sixty-one patients presenting cognitive complaints (age 48-90), including 32 with positive AD biomarkers (52%), performed [18F]-Fluorodeoxyglucose (FDG)-PET (brain metabolism) and [18F]-MK-6240-PET (tau). We normalized these images using data from clinically normal individuals (n = 30), resulting in comparable FDG and tau z-scores. We computed between-patients correlations to evaluate regional associations. For each patient, a predominant biomarker (i.e., Hypometabolism > Tauopathy or Hypometabolism≤Tauopathy) was determined in the temporal and frontoparietal lobes. We computed within-patient correlations between tau and metabolism and investigated their associations with demographics, cognition, cardiovascular risk factors (CVRF), CSF biomarkers, and white matter hypointensities (WMH). RESULTS: We observed negative associations between tau and FDG in 37 of the 68 cortical regions-of-interest (average Pearson's r = -0.25), mainly in the temporal lobe. Thirteen patients (21%) had Hypometabolism > Tauopathy whereas twenty-five patients (41%) had Hypometabolism≤Tauopathy. Tau-predominant patients were more frequently females and had greater amyloid burden. Twenty-three patients (38%) had Hypometabolism≤Tauopathy in the temporal lobe, but Hypometabolism > Tauopathy in the frontoparietal lobe. This group was older and had higher CVRF than Tau-predominant patients. Patients with more negative associations between tau and metabolism were younger, had worse cognition, and greater amyloid and WMH burdens. CONCLUSIONS: Tau-FDG comparison can help suspect non-AD pathologies in patients presenting cognitive complaints. Stronger Tau-FDG correlations are associated with younger age, worse cognition, and greater amyloid and WMH burdens.