Joseph-Mathurin, Nelly

AbstractINTRODUCTIONAmyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin‐1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre‐/postcodon 200) influences these pathologic features and dementia at different stages.METHODSIndividuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross‐sectionally evaluated regional Pittsburgh compound B‐positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging‐based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition.RESULTSPostcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures.DISCUSSIONWe demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials.Highlights Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre‐200 group had stronger associations between Aβ burden and disease stage. PSEN1 post‐200 group had stronger associations between SVD markers and disease stage. PSEN1 post‐200 group had worse dementia score than pre‐200 in late disease stage. Diffusion tensor imaging‐based SVD markers mediated mutation position effects on dementia in the late stage.

ObjectiveTo determine the characteristics of participants with amyloid‐related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD).Methods142 DIAD mutation carriers received either gantenerumab SC (n = 52), solanezumab IV (n = 50), or placebo (n = 40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, β‐amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross‐sectional and longitudinal analyses evaluated potential ARIA‐related risk factors.ResultsEleven participants developed ARIA‐E, including 3 with mild symptoms. No ARIA‐E was reported under solanezumab while gantenerumab was associated with ARIA‐E compared to placebo (odds ratio [OR] = 9.1, confidence interval [CI][1.2, 412.3]; p = 0.021). Under gantenerumab, APOE‐ɛ4 carriers were more likely to develop ARIA‐E (OR = 5.0, CI[1.0, 30.4]; p = 0.055), as were individuals with microhemorrhage at baseline (OR = 13.7, CI[1.2, 163.2]; p = 0.039). No ARIA‐E was observed at the initial 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. At first ARIA‐E occurrence, all ARIA‐E participants were amyloid‐PET+, 60% were CDR >0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA‐H. Most ARIA‐E radiologically resolved after dose adjustment and developing ARIA‐E did not significantly increase odds of trial discontinuation. ARIA‐E was more frequently observed in the occipital lobe (90%). ARIA‐E severity was associated with age at time of ARIA‐E.InterpretationIn DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg increased ARIA‐E risk, with additional risk for individuals APOE‐ɛ4(+) or with microhemorrhage. ARIA‐E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation. ANN NEUROL 2022;92:729–744

Autosomal‐dominant, Dutch‐type cerebral amyloid angiopathy (D‐CAA) offers a unique opportunity to develop biomarkers for pre‐symptomatic cerebral amyloid angiopathy (CAA). We hypothesized that neuroimaging measures of white matter injury would be present and progressive in D‐CAA prior to hemorrhagic lesions or symptomatic hemorrhage. In a longitudinal cohort of D‐CAA carriers and non‐carriers, we observed divergence of white matter injury measures between D‐CAA carriers and non‐carriers prior to the appearance of cerebral microbleeds and >14 years before the average age of first symptomatic hemorrhage. These results indicate that white matter disruption measures may be valuable cross‐sectional and longitudinal biomarkers of D‐CAA progression. ANN NEUROL 2022;92:358–363

Abstract Introduction Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD‐MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD‐MC and could help predict risk for dementia during trial enrollment. Methods We created a dementia risk score by entering standardized gray‐matter volumes from 231 DIAD‐MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD‐MC followed longitudinally. Results Our risk score separated asymptomatic versus demented DIAD‐MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD‐MC participants for prevention trials.

AbstractIntroductionMachine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.MethodsLongitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non‐carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status.ResultsThe Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non‐carriers.DiscussionResults suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.

Abstract Introduction Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B–based and florbetapir‐based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter‐individual variability of the two tracers were compared using multivariate linear models both cross‐sectionally and longitudinally. Results Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

AbstractIntroduction18F‐fluorodeoxyglucose (FDG) positron emission tomography (PET) is commonly used to estimate neuronal injury in Alzheimer's disease (AD). Here, we evaluate the utility of dynamic PET measures of perfusion using 11C‐Pittsburgh compound B (PiB) to estimate neuronal injury in comparison to FDG PET.MethodsFDG, early frames of PiB images, and relative PiB delivery rate constants (PiB‐R1) were obtained from 110 participants from the Dominantly Inherited Alzheimer Network. Voxelwise, regional cross‐sectional, and longitudinal analyses were done to evaluate the correlation between images and estimate the relationship of the imaging biomarkers with estimated time to disease progression based on family history.ResultsMetabolism and perfusion images were spatially correlated. Regional PiB‐R1 values and FDG, but not early frames of PiB images, significantly decreased in the mutation carriers with estimated year to onset and with increasing dementia severity.DiscussionHypometabolism estimated by PiB‐R1 may provide a measure of brain perfusion without increasing radiation exposure.