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

被引:403
作者
Gordon, Brian A. [1 ,2 ,6 ]
Blazey, Tyler M. [1 ,3 ]
Su, Yi [1 ]
Hari-Raj, Amrita [1 ]
Dincer, Aylin [1 ]
Flores, Shaney [1 ]
Christensen, Jon [1 ]
McDade, Eric [4 ]
Wang, Guoqiao [4 ]
Xiong, Chengjie [2 ,5 ]
Cairns, Nigel J. [2 ,4 ]
Hassenstab, Jason [2 ,4 ,6 ]
Marcus, Daniel S. [1 ]
Fagan, Anne M. [2 ,4 ,7 ]
Jack, Clifford R., Jr. [8 ]
Hornbeck, Russ C. [1 ]
Paumier, Katrina L. [4 ]
Ances, Beau M. [4 ,7 ]
Berman, Sarah B. [9 ]
Brickman, Adam M. [10 ,11 ]
Cash, David M. [12 ,13 ]
Chhatwal, Jasmeer P. [14 ]
Correia, Stephen [15 ]
Forster, Stefan [17 ,18 ,19 ]
Fox, Nick C. [12 ]
Graff-Radford, Neill R. [20 ]
la Fougere, Christian [19 ,21 ]
Levin, Johannes [18 ,22 ]
Masters, Colin L. [23 ]
Rossor, Martin N. [12 ]
Salloway, Stephen [16 ]
Saykin, Andrew J. [24 ]
Schofield, Peter R. [25 ,26 ]
Thompson, Paul M. [27 ]
Weiner, Michael M. [28 ]
Holtzman, David M. [2 ,4 ,7 ]
Raichle, Marcus E. [1 ,4 ,7 ]
Morris, John C. [2 ,4 ]
Bateman, Randall J. [2 ,4 ,7 ]
Benzinger, Tammie L. S. [1 ,2 ]
机构
[1] Washington Univ, Mallinckrodt Inst Radiol, St Louis, MO 63110 USA
[2] Washington Univ, Knight Alzheimers Dis Res, St Louis, MO USA
[3] Washington Univ, Div Biol & Biomed Sci, St Louis, MO USA
[4] Washington Univ, Dept Neurol, St Louis, MO USA
[5] Washington Univ, Dept Biostat, St Louis, MO USA
[6] Washington Univ, Dept Psychol & Brain Sci, St Louis, MO USA
[7] Hope Ctr Neurol Disorders, St Louis, MO USA
[8] Mayo Clin & Mayo Fdn, Dept Radiol, Rochester, MN USA
[9] Univ Pittsburgh, Dept Neurol, Pittsburgh, PA 15260 USA
[10] Columbia Univ, Taub Inst Res Alzheimers Dis & Aging Brain, Coll Phys & Surg, New York, NY USA
[11] Columbia Univ, Dept Neurol, New York, NY USA
[12] UCL, Dementia Res Ctr, Dept Neurodegenerat Dis, Inst Neurol, London, England
[13] UCL, Ctr Med Image Comp, Translat Imaging Grp, London, England
[14] Harvard Med Sch, Massachusetts Gen Hosp, Dept Neurol, Boston, MA USA
[15] Brown Univ, Sch Med, Dept Psychiat, Providence, RI 02912 USA
[16] Brown Univ, Sch Med, Dept Neurol, Providence, RI 02912 USA
[17] Tech Univ Munich, Dept Nucl Med, Munich, Germany
[18] German Ctr Neurodegenerat Dis DZNE Munich, Munich, Germany
[19] German Ctr Neurodegenerat Dis DZNE Tubingen, Tubingen, Germany
[20] Mayo Clin, Dept Neurol, Jacksonville, FL 32224 USA
[21] Univ Tubingen Hosp, Div Nucl Med & Clin Mol Imaging, Tubingen, Germany
[22] Ludwig Maximilians Univ Munchen, Dept Neurol, Munich, Germany
[23] Univ Melbourne, Florey Inst, Parkville, Vic, Australia
[24] Indiana Univ, Sch Med, Indianapolis, IN USA
[25] Neurosci Res Australia, Sydney, NSW, Australia
[26] Univ New South Wales, Sch Med Sci, Sydney, NSW, Australia
[27] Univ Southern Calif, Imaging Genet Ctr, Marina Del Rey, CA USA
[28] Univ Calif San Francisco, Dept Radiol & Biomed Imaging, San Francisco, CA 94143 USA
基金
美国国家卫生研究院; 英国医学研究理事会;
关键词
AMYLOID DEPOSITION; REGIONAL VARIABILITY; HYPOMETABOLISM; TRAJECTORIES; THICKNESS; ATROPHY; MODEL; ONSET; LOAD;
D O I
10.1016/S1474-4422(18)30028-0
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background Models of Alzheimer's disease propose a sequence of amyloid beta (A beta) 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 C-11-Pittsburgh Compound B (C-11-PiB) PET, F-18-Fluorodeoxyglucose (F-18-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 ClinicalTrials.gov (number NCT00869817). Findings C-11-PiB PET was available for 346 individuals (162 with longitudinal imaging), F-18-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 A beta 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 A beta 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 A beta 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 A beta, 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.
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页码:241 / 250
页数:10
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