Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study

Brian A. Gordon, Tyler M. Blazey, Yi Su, Amrita Hari-Raj, Aylin Dincer, Shaney Flores, Jon Christensen, Eric McDade, Guoqiao Wang, Chengjie Xiong, Nigel J. Cairns, Jason Hassenstab, Daniel S. Marcus, Anne M. Fagan, Clifford R. Jack, Russ C. Hornbeck, Katrina L. Paumier, Beau M. Ances, Sarah B. Berman, Adam M. BrickmanDavid M. Cash, Jasmeer P. Chhatwal, Stephen Correia, Stefan Förster, Nick C. Fox, Neill R. Graff-Radford, Christian la Fougère, Johannes Levin, Colin L. Masters, Martin N. Rossor, Stephen Salloway, Andrew J. Saykin, Peter R. Schofield, Paul M. Thompson, Michael M. Weiner, David M. Holtzman, Marcus E. Raichle, John C. Morris, Randall J. Bateman, Tammie L.S. Benzinger

Research output: Contribution to journalArticlepeer-review

125 Scopus citations


Background: Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal. Methods: Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at (number NCT00869817) Findings: 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning). Interpretation: Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials. Funding: US National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK.

Original languageEnglish (US)
Pages (from-to)241-250
Number of pages10
JournalThe Lancet Neurology
Issue number3
StatePublished - Mar 2018

ASJC Scopus subject areas

  • Clinical Neurology


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