Authors
Ophir Keret
Adam M. Staffaroni
John M. Ringman
Yann Cobigo
Sheng-Yang M. Goh
Amy Wolf
Isabel Elaine Allen
Stephen Salloway
Jasmeer Chhatwal
Adam M. Brickman
Dolly Reyes-Dumeyer
Randal J. Bateman
Tammie L.S. Benzinger
John C. Morris
Beau M. Ances
Nelly Joeseph-Mathurin
Richard J. Perrin
Brian A. Gordon
Johannes Levin
Jonathan Voglein
Mathias Jucker
Christian la Fougere
Ralph N. Martins, Edith Cowan UniversityFollow
Hamid R. Sohrabi, Edith Cowan UniversityFollow
Kevin Taddei, Edith Cowan UniversityFollow
Victor L. Villemagne
Peter R. Schofield
William S. Brooks
Michael Fulham
Colin L. Masters
Bernardino Ghetti
Andrew J. Saykin
Clifford R. Jack
Neill R. Graff-Radford
Michael Weiner
David M. Cash
Ricardo F. Allegri
Patricio Chrem
Su Yi
Bruce L. Miller
Gil D. Rabinovici
Howard J. Rosen
Dominantly Inherited Alzheimer Network
Document Type
Journal Article
Publication Title
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
Publisher
Wiley
School
Centre of Excellence for Alzheimer's Disease Research and Care / School of Medical and Health Sciences
RAS ID
39721
Funders
Funding information available in the Acknowledgements section of the PDF
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.
DOI
10.1002/dad2.12197
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Comments
Keret, O., Staffaroni, A. M., Ringman, J. M., Cobigo, Y., Goh, S. Y. M., Wolf, A., ... & Dominantly Inherited Alzheimer Network. (2021). Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 13(1), e12197. https://doi.org/10.1002/dad2.12197