Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease
| Autor: | Stephen Salloway, Michael J. Fulham, John M. Ringman, Ophir Keret, David M. Cash, Sheng-Yang M. Goh, Colin L. Masters, Beau M. Ances, Amy Wolf, Ricardo F. Allegri, Christian la Fougère, Dolly Reyes-Dumeyer, Adam M. Staffaroni, Su Yi, Johannes Levin, Kevin Taddei, Nelly Joseph-Mathurin, Gil D. Rabinovici, Peter R. Schofield, Richard J. Perrin, Ralph N. Martins, Andrew J. Saykin, Neill R. Graff-Radford, Jonathan Vöglein, Michael W. Weiner, Mathias Jucker, Randal J Bateman, Hamid R. Sohrabi, Isabel E. Allen, Brian A. Gordon, Tammie L.S. Benzinger, Jasmeer P. Chhatwal, William S. Brooks, Patricio Chrem, Victor L. Villemagne, Bruce L. Miller, Bernardino Ghetti, John C. Morris, Yann Cobigo, Clifford R. Jack, Howard J. Rosen, Adam M. Brickman |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Aging Disease mutation preclinical Alzheimer's disease Neuroimaging Neurodegenerative Alzheimer's Disease autosomal dominant Alzheimer's disease Atrophy medicine Acquired Cognitive Impairment Genetics Dementia ddc:610 Psychiatry RC346-429 Framingham Risk Score Proportional hazards model Prevention Hazard ratio RC952-954.6 Neurosciences Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) medicine.disease Brain Disorders Psychiatry and Mental health Good Health and Well Being Geriatrics Neurological Dominantly Inherited Alzheimer Network Neurology (clinical) Neurology. Diseases of the nervous system Patient Safety Prevention trials Alzheimer's disease Psychology brain atrophy Research Article |
| Zdroj: | Alzheimer's & dementia / Diagnosis, assessment & disease monitoring 13(1), e12197 (2021). doi:10.1002/dad2.12197 Alzheimer's & dementia (Amsterdam, Netherlands), vol 13, iss 1 Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, Vol 13, Iss 1, Pp n/a-n/a (2021) |
| Popis: | Author(s): 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 LS; Morris, John C; Ances, Beau M; Joseph-Mathurin, Nelly; Perrin, Richard J; Gordon, Brian A; Levin, Johannes; Voglein, Jonathan; Jucker, Mathias; la Fougere, 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; Dominantly Inherited Alzheimer Network | Abstract: IntroductionAsymptomatic 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.MethodsWe 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.ResultsOur risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard errorn=n0.02) and predicted conversion to dementia at next visit (hazard ration=n1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curven=n90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset.DiscussionIndividualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials. |
| Databáze: | OpenAIRE |
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