Browsing by Author "Allen, Isabel Elaine"

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    Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis
    (Elsevier, 2024) Chapleau, Marianne; La Joie, Renaud; Yong, Keir; Agosta, Federica; Allen, Isabel Elaine; Apostolova, Liana; Best, John; Boon, Baayla D. C.; Crutch, Sebastian; Filippi, Massimo; Fumagalli, Giorgio Giulio; Galimberti, Daniela; Graff-Radford, Jonathan; Grinberg, Lea T.; Irwin, David J.; Josephs, Keith A.; Mendez, Mario F.; Mendez, Patricio Chrem; Migliaccio, Raffaella; Miller, Zachary A.; Montembeault, Maxime; Murray, Melissa E.; Nemes, Sára; Pelak, Victoria; Perani, Daniela; Phillips, Jeffrey; Pijnenburg, Yolande; Rogalski, Emily; Schott, Jonathan M.; Seeley, William; Sullivan, A. Campbell; Spina, Salvatore; Tanner, Jeremy; Walker, Jamie; Whitwell, Jennifer L.; Wolk, David A.; Ossenkoppele, Rik; Rabinovici, Gil D.; PCA International Work Group; Neurology, School of Medicine
    Background: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. Methods: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. Findings: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). Interpretation: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity.
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    Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease
    (Wiley, 2021-07-05) Keret, Ophir; Staffaroni, Adam M.; Ringman, John M.; Cobigo, Yann; Goh, Sheng-Yang M.; Wolf, Amy; Allen, Isabel Elaine; Salloway, Stephen; Chhatwal, Jasmeer; Brickman, Adam M.; Reyes-Dumeyer, Dolly; Bateman, Randal J.; Benzinger, Tammie L.S.; Morris, John C.; Ances, Beau M.; Joseph-Mathurin, Nelly; Perrin, Richard J.; Gordon, Brian A.; Levin, Johannes; Vöglein, Jonathan; Jucker, Mathias; la Fougère, Christian; Martins, Ralph N.; Sohrabi, Hamid R.; Taddei, Kevin; Villemagne, Victor L.; Schofield, Peter R.; Brooks, William S.; Fulham, Michael; Masters, Colin L.; Ghetti, Bernardino; Saykin, Andrew J.; Jack, Clifford R.; Graff-Radford, Neill R.; Weiner, Michael; Cash, David M.; Allegri, Ricardo F.; Chrem, Patricio; Yi, Su; Miller, Bruce L.; Rabinovici, Gil D.; Rosen, Howard J.; Pathology and Laboratory Medicine, School of Medicine
    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.