Soo Hyun Cho1,2, Jeong-Hyeon Shin3, Hyemin Jang1,2, Seongbeom Park1,2, Hee Jin Kim1,2, Si Eun Kim1,2, Seung Joo Kim1,2, Yeshin Kim1,2, Jin San Lee4, Duk L Na1,2,5,6, Samuel N Lockhart7, Gil D Rabinovici8, Joon-Kyung Seong9, Sang Won Seo10,11,12,13. 1. Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. 2. Neuroscience Center, Samsung Medical Center, Seoul, South Korea. 3. School of Biomedical Engineering, Korea University, Seoul, Republic of Korea. 4. Department of Neurology, Kyung Hee University Hospital, Seoul, South Korea. 5. Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, South Korea. 6. Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea. 7. Internal Medicine - Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA. 8. Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA. 9. School of Biomedical Engineering, Korea University, Seoul, Republic of Korea. jkseong@korea.ac.kr. 10. Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. sangwonseo@empal.com. 11. Neuroscience Center, Samsung Medical Center, Seoul, South Korea. sangwonseo@empal.com. 12. Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea. sangwonseo@empal.com. 13. Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea. sangwonseo@empal.com.
Abstract
PURPOSE: We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement. METHODS: Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2. RESULTS: Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (β [SE] = -0.02 [0.004], p < 0.001), ADAS-cog 13 (0.05 [0.01], p < 0.001), FDG PET SUVR (-0.0008 [0.0003], p = 0.004), and hippocampal volumes (-4.46 [0.65], p < 0.001) compared to stage 1. CONCLUSIONS: We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.
PURPOSE: We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement. METHODS: Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2. RESULTS: Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (β [SE] = -0.02 [0.004], p < 0.001), ADAS-cog 13 (0.05 [0.01], p < 0.001), FDG PET SUVR (-0.0008 [0.0003], p = 0.004), and hippocampal volumes (-4.46 [0.65], p < 0.001) compared to stage 1. CONCLUSIONS: We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.
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