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

Abstract

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 ClinicalTrials.gov (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.

Conflict of interest statement

Declarations of Interest

BAG and BMA report participating in a clinical trial of AV-1451 sponsored by Avid Radiopharmaceuticals. EM reports grants from Dominantly Inherited Alzheimer Network Trials Unit Pharma Consortium, outside the submitted work. CX reports grants from the NIA outside the submitted work. JH reports personal fees from Biogen and Lundbeck, outside the submitted work. CRJ reports consulting services for Lilly Co. and grants from NIH, outside the submitted work. DSM reports grants from the NIH outside and support from Radiologics, Inc., both outside the conduct of the study. AMF reports personal fees from DiamiR, personal fees from LabCorp, personal fees from IBL International, personal fees from Genentech, grants from Roche Diagnostics, grants from Fujirebio, grants from Biogen, outside the submitted work. DMC reports grants from Alzheimer’s Society, during the conduct of the study. JL reports grants from German Ministry of Reseach and Education, during the conduct of the study. AJS reports non-financial support from Avid Radiopharmaceuticals and grants from Eli Lilly, outside the submitted work. SBB reports grants from NIH, during the conduct of the study; other from Lundbeck, other from Grifols Biologicals, outside the submitted work. MNR reports support from Servier and Merck outside the submitted work. NCF reports personal fees from Janssen, Roche/Genentech, Janssen Alzheimer’s Immunotherapy, Eli Lilly, Novartis Pharma AG, Sanofi GSK, and Biogen, outside the submitted work. NRG reports Eli Lilly Multi center Treatment Study Grant, Biogen Multi center Treatment Study Grant, and Cytox consultation. PRS reports grants from NIH/NIA, the Anonymous Foundation, the Mason Foundation, from Roth Charitable Foundation during the conduct of the study; personal fees from ICME Speakers & Entertainers, outside the submitted work; and serving as the Interim Director of the Australian National Health and Medical Research Council (NHMRC). DMH co-founded and is on the scientific advisory board of C2N Diagnostics. DMH is an inventor on a submitted patent “Antibodies to Tau” that is licensed by Washington University to C2N Diagnostics. This patent was subsequently licensed to AbbVie. DMH is an inventor on patents licensed by Washington University to Eli Lilly and Company based on intellectual property related to the anti-Abeta antibody solanezumab. DMH consults for Genentech, AbbVie, Eli Lilly, GlaxoSmithKline, Proclara Biosciences, and Denali. MMW reports grants from NIH/NIA/NIMH, grants from DOD, grants from CA Dept. of Public Health, grants and other from Alzheimer’s Drug Discovery Foundation (ADDF), grants from Larry L. Hillblom Foundation, grants from PCORI, grants from Global Alzheimer’s Platform Foundation, grants from Monell Chemical Senses Center, grants and other from Alzheimer’s Association, other from Pfizer, other from Alzheon, Inc., other from Eli Lilly, other from Dolby Ventures, other from ADNI, other from MRI Magazine, other from Alzheimer’s & Dementia Magazine, other from Synarc, other from Janssen, other from Accera Pharma, other from Avid Radiopharma, other from Araclon, other from Merck, other from Scienomics Group, other from AVOS Consulting, other from INC Research, other from Biogen Idec, other from BioClinica, other from Howard University, other from Guidepoint, other from GLG Research, other from Genentech, other from Alzeca, outside the submitted work. PMT reports grants from NIA, NIBIB, and NINDS outside of the submitted work. JCM reports grants from NIH grant P50AG005681, grants from NIH grant P01AG003991, grants from NIH grant P01AG026276, grants from NIH grant UF01AG032438, during the conduct of the study; other from Lilly USA, outside the submitted work. RJB reports grants from NIH/NIA U19AG32438 and an Anonymous Foundation, during the conduct of the study, grants from Eli Lilly, Roche, Pharma Consortium (Abbvie, AstraZeneca, Biogen, Eisai, Eli Lilly and Co., Hoffman La-Roche Inc., Janssen, Pfizer, Sanofi-Aventi), and Tau SILK/PET Consortium (Biogen/Abbvie/Lilly), non-financial support from Avid Radiopharmaceuticals, personal fees and other from Washington University, personal fees and non-financial support from Roche, IMI, FORUM, and Pfizer, and personal fees from Merck, Johnson and Johnson, outside the submitted work. TLSB reports grants, non-financial support and other from Avid Radiopharmaceuticals/Eli Lilly, other from Roche, outside the submitted work. TMB, YS, AH, AD, SF, JC, GW, NJC, RCH, KLP, AMB, JPC, SC, StF, CF, CLM, SS, and MER report no conflicts.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Figures

Figure 1

Modeling longitudinal change in the precuneus for PiB (top), FDG (middle), and cortical thickness (bottom). The left-hand panels (A, D, & G) depict the model estimates of longitudinal biomarkers. The middle panels (B, E, & H) depict the estimated rate of change across the course of the disease for mutation carriers and non-carriers. Individual random effect slope estimates are plotted as colored dots. The right hand panels (C, F, and I) depict the difference in rate of biomarker change between mutation carriers and non-carriers across the course of the disease. For both the middle and right-hand panels the shaded areas represent 99% credible intervals around the model estimates. The credible intervals are drawn from the actual distributions of model fits derived by the Hamilton Markov Chain Monte Carlos analyses. Any point in this difference curves where the shaded area is not touching the zero axis is a point in the disease progression (as measured by EYO) where the biomarker accumulation rate is different between groups. The first EYO point that was significantly different between groups was considered the initial diverge between groups. Figures depicting the model results for every ROI are available in supplemental materials. To avoid inadvertently revealing mutation status figures are displayed with baseline EYO −29 to +10.

Figure 2

Emergence of neuroimaging biomarkers. The color scale represents the first point in the disease relative to estimated age at onset (EYO) where rates of biomarker change in that cortical region are significantly different between mutation carriers and non-carriers (akin to the first point where credible interval are different from zero in Figure 1 right panels). There is a temporal evolution where increased Aβ deposition precedes hypometabolism that in turn is followed by cortical thinning. Information for all modalities and regions is presented in numeric form in Supplemental Tables 1 and 2.

Figure 3

Trajectories of biomarker accumulation in mutation carriers for three cortical (top) and three subcortical regions (bottom) for PiB (left), FDG (middle), and structural MRI (right) that highlight different patterns of change seen in different brain regions.

Figure 4

Depictions of model estimates of rate of change in PiB (top), FDG (middle), and cortical thickness (bottom) in mutation carriers at an EYO of −25, −15, −5, and +5.