Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease
| Autor: | Dincer, Aylin, Gordon, Brian A, Allegri, Ricardo, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Brooks, William S, Cash, David M, Chhatwal, Jasmeer P, Farlow, Martin R, la Fougère, Christian, Fox, Nick C, Hari-Raj, Amrita, Fulham, Michael J, Jack, Clifford R, Joseph-Mathurin, Nelly, Karch, Celeste M, Lee, Athene, Levin, Johannes, Masters, Colin L, McDade, Eric M, Oh, Hwamee, Perrin, Richard J, Keefe, Sarah J, Raji, Cyrus, Salloway, Stephen P, Schofield, Peter R, Su, Yi, Villemagne, Victor L, Wang, Qing, Weiner, Michael W, Xiong, Chengjie, Yakushev, Igor, Morris, John C, Flores, Shaney, Bateman, Randall J, L S Benzinger, Tammie, DIAN, Dominantly Inherited Alzheimer Network, McKay, Nicole S, Paulick, Angela M, Shady Lewis, Kristine E, Feldman, Rebecca L, Hornbeck, Russ C |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Aging
mcSUVR mean cortical standardized uptake value ratio LOAD late-onset Alzheimer disease ROI region of interest Hippocampus AUROC area under the receiver operating characteristic genetics [Alzheimer Disease] Neurodegenerative Alzheimer's Disease lcsh:RC346-429 pathology [Alzheimer Disease] 0302 clinical medicine ADAD autosomal dominant Alzheimer disease 2.1 Biological and endogenous factors CNADRC/DIAN cognitively normal controls Aetiology PCDIAN preclinical autosomal dominant Alzheimer disease pathology [Atrophy] PiB Pittsburg compound-B 05 social sciences Neurodegeneration Regular Article PSEN1 Presenilin 1 Magnetic Resonance Imaging Preclinical Neurology Knight ADRC Knight Alzheimer Disease Research Center Cohort Neurological Biomarker (medicine) lcsh:R858-859.7 Alzheimer's disease Alzheimer disease Cortical signature Amyloid PSEN2 Presenilin 2 Cognitive Neuroscience metabolism [Amyloid beta-Peptides] Dominantly Inherited Alzheimer Network DIAN lcsh:Computer applications to medicine. Medical informatics 050105 experimental psychology PET positron emission tomography Temporal lobe Cortical thickness 03 medical and health sciences Atrophy Clinical Research APP amyloid precursor protein medicine Acquired Cognitive Impairment PCADRC preclinical Alzheimer disease Humans 0501 psychology and cognitive sciences Radiology Nuclear Medicine and imaging DIAN Dominantly Inherited Alzheimer Network ddc:610 lcsh:Neurology. Diseases of the nervous system Amyloid beta-Peptides AD Alzheimer disease business.industry Neurosciences Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) medicine.disease CDR clinical dementia rating Brain Disorders HCV total hippocampal volume ROC receiver operating characteristic Cortical map pathology [Hippocampus] Autosomal dominant Alzheimer disease AV-45 florbetapir Positron-Emission Tomography Dementia APOE apolipoprotein E SUVR standardized uptake value ratio Neurology (clinical) business Neuroscience MRI magnetic resonance imaging diagnostic imaging [Alzheimer Disease] 030217 neurology & neurosurgery |
| Zdroj: | NeuroImage: Clinical 28, 102491-(2020). doi:10.1016/j.nicl.2020.102491 NeuroImage: Clinical, Vol 28, Iss, Pp 102491-(2020) NeuroImage : Clinical |
| Popis: | Highlights • Cortical signatures selective to AD could provide an early MRI biomarker. • Autosomal dominant Alzheimer disease (ADAD) may model an ideal AD signature. • ADAD and late-onset maps overlap in parietal cortex but contain unique features. • Signatures predicted increasing amyloid within their own, but not across cohorts. • These results indicate atrophy in AD can take multiple spatial patterns. Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD. |
| Databáze: | OpenAIRE |
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