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Kim HH, Kwon MJ, Jo S, Park JE, Kim JW, Kim JH, Kim SE, Kim KW, Han JW. Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals. Sci Rep 2024; 14:10083. [PMID: 38698190 PMCID: PMC11066072 DOI: 10.1038/s41598-024-60843-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/28/2024] [Indexed: 05/05/2024] Open
Abstract
Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.
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Affiliation(s)
- Hak Hyeon Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, South Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea
| | - Min Jeong Kwon
- Department of Brain and Cognitive Science, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Sungman Jo
- Department of Health Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - Ji Eun Park
- Department of Brain and Cognitive Science, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Ji Won Kim
- Department of Brain and Cognitive Science, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Jae Hyoung Kim
- Department of Radiology, Seoul National University Bundang Hospital, College of Medicine, Seoul National University, Seongnam-si, Gyeonggi-do, South Korea
| | - Sang Eun Kim
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, College of Medicine, Seoul National University, Seongnam-si, Gyeonggi-do, Korea
- Center for Nanomolecular Imaging and Innovative Drug Development, Advanced Institutes of Convergence Technology, Suwon, Republic of Korea
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, South Korea
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea
- Department of Brain and Cognitive Science, College of Natural Sciences, Seoul National University, Seoul, South Korea
- Department of Health Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, South Korea.
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea.
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Phan TX, Baratono S, Drew W, Tetreault AM, Fox MD, Darby RR. Increased Cortical Thickness in Alzheimer's Disease. Ann Neurol 2024; 95:929-940. [PMID: 38400760 PMCID: PMC11060923 DOI: 10.1002/ana.26894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 01/31/2024] [Accepted: 02/03/2024] [Indexed: 02/26/2024]
Abstract
OBJECTIVE Patients with Alzheimer's disease (AD) have diffuse brain atrophy, but some regions, such as the anterior cingulate cortex (ACC), are spared and may even show increase in size compared to controls. The extent, clinical significance, and mechanisms associated with increased cortical thickness in AD remain unknown. Recent work suggested neural facilitation of regions anticorrelated to atrophied regions in frontotemporal dementia. Here, we aim to determine whether increased thickness occurs in sporadic AD, whether it relates to clinical symptoms, and whether it occur in brain regions functionally connected to-but anticorrelated with-locations of atrophy. METHODS Cross-sectional clinical, neuropsychological, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative were analyzed to investigate cortical thickness in AD subjects versus controls. Atrophy network mapping was used to identify brain regions functionally connected to locations of increased thickness and atrophy. RESULTS AD patients showed increased thickness in the ACC in a region-of-interest analysis and the visual cortex in an exploratory analysis. Increased thickness in the left ACC was associated with preserved cognitive function, while increased thickness in the left visual cortex was associated with hallucinations. Finally, we found that locations of increased thickness were functionally connected to, but anticorrelated with, locations of brain atrophy (r = -0.81, p < 0.05). INTERPRETATION Our results suggest that increased cortical thickness in Alzheimer's disease is relevant to AD symptoms and preferentially occur in brain regions functionally connected to, but anticorrelated with, areas of brain atrophy. Implications for models of compensatory neuroplasticity in response to neurodegeneration are discussed. ANN NEUROL 2024;95:929-940.
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Affiliation(s)
- Tony X. Phan
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Sheena Baratono
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - William Drew
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Aaron M. Tetreault
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Michael D. Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - R. Ryan Darby
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
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3
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Cai Y, Shi D, Lan G, Chen L, Jiang Y, Zhou L, Guo T. Association of β-Amyloid, Microglial Activation, Cortical Thickness, and Metabolism in Older Adults Without Dementia. Neurology 2024; 102:e209205. [PMID: 38489560 DOI: 10.1212/wnl.0000000000209205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/13/2023] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Plasma β-amyloid42 (Aβ42)/Aβ40 levels have shown promise in identifying Aβ-PET positive individuals. This study explored the concordance and discordance of plasma Aβ42/Aβ40 positivity (Plasma±) with CSF Aβ42/Aβ40 positivity (CSF±) and Aβ-PET positivity (PET±) in older adults without dementia. Associations of Aβ deposition, cortical thickness, glucose metabolism, and microglial activation were also investigated. METHODS We selected participants without dementia who had concurrent plasma Aβ42/Aβ40 and Aβ-PET scans from the Alzheimer's Disease Neuroimaging Initiative cohort. Participants were categorized into Plasma±/PET± based on thresholds of composite 18F-florbetapir (FBP) standardized uptake value ratio (SUVR) ≥1.11 and plasma Aβ42/Aβ40 ≤0.1218. Aβ-PET-negative individuals were further divided into Plasma±/CSF± (CSF Aβ42/Aβ40 ≤0.138), and the concordance and discordance of Aβ42/Aβ40 in the plasma and CSF were investigated. Baseline and slopes of regional FBP SUVR were compared among Plasma±/PET± groups, and associations of regional FBP SUVR, FDG SUVR, cortical thickness, and CSF soluble Triggering Receptor Expressed on Myeloid Cell 2 (sTREM2) levels were analyzed. RESULTS One hundred eighty participants (mean age 72.7 years, 51.4% female, 96 cognitively unimpaired, and 84 with mild cognitive impairment) were included. We found that the proportion of Plasma+/PET- individuals was 6.14 times higher (odds ratio (OR) = 6.143, 95% confidence interval (CI) 2.740-16.185, p < 0.001) than that of Plasma-/PET+ individuals, and Plasma+/CSF- individuals showed 8.5 times larger percentage (OR = 8.5, 95% CI: 3.031-32.974, p < 0.001) than Plasma-/CSF+ individuals in Aβ-PET-negative individuals. Besides, Plasma+/PET- individuals exhibited faster (p < 0.05) Aβ accumulation predominantly in bilateral banks of superior temporal sulcus (BANKSSTS) and supramarginal, and superior parietal cortices compared with Plasma-/PET- individuals, despite no difference in baseline FBP SUVRs. In Plasma+/PET+ individuals, higher CSF sTREM2 levels correlated with slower BANKSSTS Aβ accumulation (standardized β (βstd) = -0.418, 95% CI -0.681 to -0.154, p = 0.002). Conversely, thicker cortical thickness and higher glucose metabolism in supramarginal and superior parietal cortices were associated with faster (p < 0.05) CSF sTREM2 increase in Plasma+/PET- individuals rather than in Plasma+/PET+ individuals. DISCUSSION These findings suggest that plasma Aβ42/Aβ40 abnormalities may predate CSF Aβ42/Aβ40 and Aβ-PET abnormalities. Higher sTREM2-related microglial activation is linked to thicker cortical thickness and higher metabolism in early amyloidosis stages but tends to mitigate Aβ accumulation primarily at relatively advanced stages.
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Affiliation(s)
- Yue Cai
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Dai Shi
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Guoyu Lan
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Linting Chen
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Yanni Jiang
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Liemin Zhou
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
| | - Tengfei Guo
- From the Institute of Biomedical Engineering (Y.C., G.L., L.C., T.G.), Shenzhen Bay Laboratory; Neurology Medicine Center (D.S., L.Z.), The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China; Department of Psychology (Y.J.), University of Texas at Austin; and Institute of Biomedical Engineering (T.G.), Peking University Shenzhen Graduate School, China
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Keuss SE, Coath W, Cash DM, Barnes J, Nicholas JM, Lane CA, Parker TD, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris M, Lu K, James SN, Street R, Malone IB, Sudre CH, Thomas DL, Dickson JC, Barkhof F, Murray-Smith H, Wong A, Richards M, Fox NC, Schott JM. Rates of cortical thinning in Alzheimer's disease signature regions associate with vascular burden but not with β-amyloid status in cognitively normal adults at age 70. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332067. [PMID: 38199813 DOI: 10.1136/jnnp-2023-332067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Consistent patterns of reduced cortical thickness have been identified in early Alzheimer's disease (AD). However, the pathological factors that influence rates of cortical thinning within these AD signature regions remain unclear. METHODS Participants were from the Insight 46 substudy of the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort), a prospective longitudinal cohort study. Linear regression was used to examine associations of baseline cerebral β-amyloid (Aβ) deposition, measured using florbetapir positron emission tomography, and baseline white matter hyperintensity volume (WMHV) on MRI, a marker of cerebral small vessel disease, with subsequent longitudinal changes in AD signature cortical thickness quantified from baseline and repeat MRI (mean [SD] interval 2.4 [0.2] years). RESULTS In a population-based sample of 337 cognitively normal older white adults (mean [SD] age at baseline 70.5 [0.6] years; 48.1% female), higher global WMHV at baseline related to faster subsequent rates of cortical thinning in both AD signature regions (~0.15%/year faster per 10 mL additional WMHV), whereas baseline Aβ status did not. Among Aβ positive participants (n=56), there was some evidence that greater global Aβ standardised uptake value ratio at baseline related to faster cortical thinning in the AD signature Mayo region, but this did not reach statistical significance (p=0.08). CONCLUSIONS Cortical thinning within AD signature regions may develop via cerebrovascular pathways. Perhaps reflecting the age of the cohort and relatively low prevalence of Aβ-positivity, robust Aβ-related differences were not detected. Longitudinal follow-up incorporating additional biomarkers will allow assessment of how these relationships evolve closer to expected dementia onset.
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Affiliation(s)
- Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Dementia Research Institute, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Aaron Z Wagen
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Mathew Storey
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthew Harris
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Rebecca Street
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Centre for Medical Imaging Computing, University College London, London, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain Repair and Neurorehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Centre for Medical Imaging Computing, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Dementia Research Institute, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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Yan H, Feng L, Li M. The Role of Traditional Chinese Medicine Natural Products in β-Amyloid Deposition and Tau Protein Hyperphosphorylation in Alzheimer's Disease. Drug Des Devel Ther 2023; 17:3295-3323. [PMID: 38024535 PMCID: PMC10655607 DOI: 10.2147/dddt.s380612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/02/2023] [Indexed: 12/01/2023] Open
Abstract
Alzheimer's disease is a prevalent form of dementia among elderly individuals and is characterized by irreversible neurodegeneration. Despite extensive research, the exact causes of this complex disease remain unclear. Currently available drugs for Alzheimer's disease treatment are limited in their effectiveness, often targeting a single aspect of the disease and causing significant adverse effects. Moreover, these medications are expensive, placing a heavy burden on patients' families and society as a whole. Natural compounds and extracts offer several advantages, including the ability to target multiple pathways and exhibit high efficiency with minimal toxicity. These attributes make them promising candidates for the prevention and treatment of Alzheimer's disease. In this paper, we provide a summary of the common natural products used in Chinese medicine for different pathogeneses of AD. Our aim is to offer new insights and ideas for the further development of natural products in Chinese medicine and the treatment of AD.
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Affiliation(s)
- Huiying Yan
- Department of Neurology, the Third Affiliated Clinical Hospital of the Changchun University of Chinese Medicine, Changchun, Jilin Province, People’s Republic of China
| | - Lina Feng
- Shandong Key Laboratory of TCM Multi-Targets Intervention and Disease Control, the Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong Province, People’s Republic of China
| | - Mingquan Li
- Department of Neurology, the Third Affiliated Clinical Hospital of the Changchun University of Chinese Medicine, Changchun, Jilin Province, People’s Republic of China
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Rozalem Aranha M, Iulita MF, Montal V, Pegueroles J, Bejanin A, Vaqué-Alcázar L, Grothe MJ, Carmona-Iragui M, Videla L, Benejam B, Arranz J, Padilla C, Valldeneu S, Barroeta I, Altuna M, Fernández S, Ribas L, Valle-Tamayo N, Alcolea D, González-Ortiz S, Bargalló N, Zetterberg H, Blennow K, Blesa R, Wisniewski T, Busciglio J, Cuello AC, Lleó A, Fortea J. Basal forebrain atrophy along the Alzheimer's disease continuum in adults with Down syndrome. Alzheimers Dement 2023; 19:4817-4827. [PMID: 37021589 DOI: 10.1002/alz.12999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/30/2022] [Accepted: 01/04/2023] [Indexed: 04/07/2023]
Abstract
BACKGROUND Basal forebrain (BF) degeneration occurs in Down syndrome (DS)-associated Alzheimer's disease (AD). However, the dynamics of BF atrophy with age and disease progression, its impact on cognition, and its relationship with AD biomarkers have not been studied in DS. METHODS We included 234 adults with DS (150 asymptomatic, 38 prodromal AD, and 46 AD dementia) and 147 euploid controls. BF volumes were extracted from T-weighted magnetic resonance images using a stereotactic atlas in SPM12. We assessed BF volume changes with age and along the clinical AD continuum and their relationship to cognitive performance, cerebrospinal fluid (CSF) and plasma amyloid/tau/neurodegeneration biomarkers, and hippocampal volume. RESULTS In DS, BF volumes decreased with age and along the clinical AD continuum and significantly correlated with amyloid, tau, and neurofilament light chain changes in CSF and plasma, hippocampal volume, and cognitive performance. DISCUSSION BF atrophy is a potentially valuable neuroimaging biomarker of AD-related cholinergic neurodegeneration in DS.
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Affiliation(s)
- Mateus Rozalem Aranha
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Maria Florencia Iulita
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Lídia Vaqué-Alcázar
- Institute of Neurosciences, Universitat de Barcelona, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Michel J Grothe
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Maria Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Laura Videla
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Bessy Benejam
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Javier Arranz
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Concepción Padilla
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Sílvia Valldeneu
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Isabel Barroeta
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Miren Altuna
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Susana Fernández
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Laia Ribas
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Natalia Valle-Tamayo
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Sofía González-Ortiz
- Hospital del Mar - Parc de Salut Mar, Barcelona, Spain
- Neuroradiology Section, Radiology Department, Diagnostic Image Center, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain
| | - Núria Bargalló
- Neuroradiology Section, Radiology Department, Diagnostic Image Center, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain
- Magnetic Resonance Image Core Facility (IDIBAPS), Barcelona, Spain
| | - Henrik Zetterberg
- Queen Square Institute of Neurology, University College London, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- UK Dementia Research Institute, University College London, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Hong Kong Center for Neurodegenerative Diseases, China, Hong Kong
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Thomas Wisniewski
- Departments of Neurology, Pathology and Psychiatry and Center for Cognitive Neurology, New York University Grossman School of Medicine, New York, New York, USA
| | - Jorge Busciglio
- Department of Neurobiology & Behavior, Institute for Memory Impairments and Neurological Disorders (iMIND), Center for the Neurobiology of Learning and Memory, University of California at Irvine, Irvine, California, USA
| | - A Claudio Cuello
- Department of Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec, Canada
- Department of Pharmacology, Oxford University, Oxford, UK
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Facultad de Medicina - Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
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7
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Pais MV, Kuo C, Ances BM, Wetherell JL, Lenze EJ, Diniz BS. Relationship between baseline plasma p-tau181 and longitudinal changes in cognition and structural brain measures in a cohort of cognitively unimpaired older adults. Alzheimers Dement (Amst) 2023; 15:e12487. [PMID: 37954547 PMCID: PMC10634375 DOI: 10.1002/dad2.12487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/22/2023] [Indexed: 11/14/2023]
Abstract
INTRODUCTION Preclinical Alzheimer's disease (AD) affects a significant proportion of cognitively unimpaired (CU) older adults. Currently, blood-based biomarkers detect very early changes in the AD continuum with great accuracy. METHODS We measured baseline plasma phosphorylated tau (p-tau)181 using electrochemiluminescence (ECL)-based assay (MesoScale Discovery) in 533 CU older adults. Follow-up lasted up to 18 months. Cognitive performance assessment included memory and cognitive control. Structural brain measures included cortical thickness, which includes the AD magnetic resonance imaging (AD MRI) signature, and hippocampal volume. RESULTS In this cohort of CU older adults, baseline plasma p-tau181 levels were not associated with short-term changes in cognition and structural brain measures. Also, baseline plasma p-tau levels did not influence the effects of behavioral interventions (exercise or mindfulness) on cognitive and structural brain changes. DISCUSSION The short follow-up and healthy status of this CU cohort might have limited the sensitivity of plasma p-tau181 in detecting changes associated with AD pathology.
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Affiliation(s)
- Marcos V. Pais
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
- Laboratory of Neuroscience (LIM‐27)Departamento e Instituto de PsiquiatriaFaculdade de Medicina, Universidade de Sao Paulo (FMUSP)Sao PauloBrazil
| | - Chia‐Ling Kuo
- Department of Public Health SciencesUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - Beau M. Ances
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
| | | | - Eric J. Lenze
- Healthy Mind Lab, Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Breno S. Diniz
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
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Abstract
Developing effective treatments for patients with Huntington's disease (HD)-a neurodegenerative disorder characterized by severe cognitive, motor and psychiatric impairments-is proving extremely challenging. While the monogenic nature of this condition enables to identify individuals at risk, robust biomarkers would still be extremely valuable to help diagnose disease onset and progression, and especially to confirm treatment efficacy. If measurements of cerebrospinal fluid neurofilament levels, for example, have demonstrated use in recent clinical trials, other proteins may prove equal, if not greater, relevance as biomarkers. In fact, proteins such as tau could specifically be used to detect/predict cognitive affectations. We have herein reviewed the literature pertaining to the association between tau levels and cognitive states, zooming in on Alzheimer's disease, Parkinson's disease and traumatic brain injury in which imaging, cerebrospinal fluid, and blood samples have been interrogated or used to unveil a strong association between tau and cognition. Collectively, these areas of research have accrued compelling evidence to suggest tau-related measurements as both diagnostic and prognostic tools for clinical practice. The abundance of information retrieved in this niche of study has laid the groundwork for further understanding whether tau-related biomarkers may be applied to HD and guide future investigations to better understand and treat this disease.
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Affiliation(s)
- Eva Lepinay
- Centre de Recherche du CHU de Québec, Axe Neurosciences, Québec, QC, Canada
- Département de Psychiatrie & Neurosciences, Université Laval, Québec, QC, Canada
| | - Francesca Cicchetti
- Centre de Recherche du CHU de Québec, Axe Neurosciences, Québec, QC, Canada.
- Département de Psychiatrie & Neurosciences, Université Laval, Québec, QC, Canada.
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9
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Williams ME, Elman JA, Bell TR, Dale AM, Eyler LT, Fennema-Notestine C, Franz CE, Gillespie NA, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Higher cortical thickness/volume in Alzheimer's-related regions: protective factor or risk factor? Neurobiol Aging 2023; 129:185-194. [PMID: 37343448 PMCID: PMC10676195 DOI: 10.1016/j.neurobiolaging.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/18/2023] [Accepted: 05/03/2023] [Indexed: 06/23/2023]
Abstract
Some evidence suggests a biphasic pattern of changes in cortical thickness wherein higher, rather than lower, thickness is associated with very early Alzheimer's disease (AD) pathology. We examined whether integrating information from AD brain signatures based on mean diffusivity (MD) can aid in the interpretation of cortical thickness/volume as a risk factor for future AD-related changes. Participants were 572 men in the Vietnam Era Twin Study of Aging who were cognitively unimpaired at baseline (mean age = 56 years; range = 51-60). Individuals with both high thickness/volume signatures and high MD signatures at baseline had lower cortical thickness/volume in AD signature regions and lower episodic memory performance 12 years later compared to those with high thickness/volume and low MD signatures at baseline. Groups did not differ in level of young adult cognitive reserve. Our findings are in line with a biphasic model in which increased cortical thickness may precede future decline and establish the value of examining cortical MD alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Tyler R Bell
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
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10
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Gagliardi G, Rodriguez-Vieitez E, Montal V, Sepulcre J, Diez I, Lois C, Hanseeuw B, Schultz AP, Properzi MJ, Papp KV, Marshall GA, Fortea J, Johnson KA, Sperling RA, Vannini P. Cortical microstructural changes predict tau accumulation and episodic memory decline in older adults harboring amyloid. Commun Med (Lond) 2023; 3:106. [PMID: 37528163 PMCID: PMC10394044 DOI: 10.1038/s43856-023-00324-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/19/2023] [Indexed: 08/03/2023] Open
Abstract
INTRODUCTION Non-invasive diffusion-weighted imaging (DWI) to assess brain microstructural changes via cortical mean diffusivity (cMD) has been shown to be cross-sectionally associated with tau in cognitively normal older adults, suggesting that it might be an early marker of neuronal injury. Here, we investigated how regional cortical microstructural changes measured by cMD are related to the longitudinal accumulation of regional tau as well as to episodic memory decline in cognitively normal individuals harboring amyloid pathology. METHODS 122 cognitively normal participants from the Harvard Aging Brain Study underwent DWI, T1w-MRI, amyloid and tau PET imaging, and Logical Memory Delayed Recall (LMDR) assessments. We assessed whether the interaction of baseline amyloid status and cMD (in entorhinal and inferior-temporal cortices) was associated with longitudinal regional tau accumulation and with longitudinal LMDR using separate linear mixed-effects models. RESULTS We find a significant interaction effect of the amyloid status and baseline cMD in predicting longitudinal tau in the entorhinal cortex (p = 0.044) but not the inferior temporal lobe, such that greater baseline cMD values predicts the accumulation of entorhinal tau in amyloid-positive participants. Moreover, we find a significant interaction effect of the amyloid status and baseline cMD in the entorhinal cortex (but not inferior temporal cMD) in predicting longitudinal LMDR (p < 0.001), such that baseline entorhinal cMD predicts the episodic memory decline in amyloid-positive participants. CONCLUSIONS The combination of amyloidosis and elevated cMD in the entorhinal cortex may help identify individuals at short-term risk of tau accumulation and Alzheimer's Disease-related episodic memory decline, suggesting utility in clinical trials.
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Affiliation(s)
- Geoffroy Gagliardi
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Elena Rodriguez-Vieitez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Stockholm, 14152, Sweden
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, 08041, Spain
- Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, 28031, Spain
| | - Jorge Sepulcre
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Ibai Diez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Cristina Lois
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Bernard Hanseeuw
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Saint Luc University Hospital, Université Catholique de Louvain, Brussels, 1200, Belgium
| | - Aaron P Schultz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
| | - Michael J Properzi
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Kathryn V Papp
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Gad A Marshall
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, 08041, Spain
- Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, 28031, Spain
| | - Keith A Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Patrizia Vannini
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA.
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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11
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Verdi S, Kia SM, Yong KXX, Tosun D, Schott JM, Marquand AF, Cole JH. Revealing Individual Neuroanatomical Heterogeneity in Alzheimer Disease Using Neuroanatomical Normative Modeling. Neurology 2023; 100:e2442-e2453. [PMID: 37127353 PMCID: PMC10264044 DOI: 10.1212/wnl.0000000000207298] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 03/02/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Alzheimer disease (AD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology. To explore this, we used neuroanatomical normative modeling to index regional patterns of variability in cortical thickness. We aimed to characterize individual differences and outliers in cortical thickness in patients with AD, people with mild cognitive impairment (MCI), and controls. Furthermore, we assessed the relationships between cortical thickness heterogeneity and cognitive function, β-amyloid, phosphorylated-tau, and ApoE genotype. Finally, we examined whether cortical thickness heterogeneity was predictive of conversion from MCI to AD. METHODS Cortical thickness measurements across 148 brain regions were obtained from T1-weighted MRI scans from 62 sites of the Alzheimer's Disease Neuroimaging Initiative. AD was determined by clinical and neuropsychological examination with no comorbidities present. Participants with MCI had reported memory complaints, and controls were cognitively normal. A neuroanatomical normative model indexed cortical thickness distributions using a separate healthy reference data set (n = 33,072), which used hierarchical Bayesian regression to predict cortical thickness per region using age and sex, while adjusting for site noise. Z-scores per region were calculated, resulting in a Z-score brain map per participant. Regions with Z-scores <-1.96 were classified as outliers. RESULTS Patients with AD (n = 206) had a median of 12 outlier regions (out of a possible 148), with the highest proportion of outliers (47%) in the parahippocampal gyrus. For 62 regions, over 90% of these patients had cortical thicknesses within the normal range. Patients with AD had more outlier regions than people with MCI (n = 662) or controls (n = 159) (F(2, 1,022) = 95.39, p = 2.0 × 10-16). They were also more dissimilar to each other than people with MCI or controls (F(2, 1,024) = 209.42, p = 2.2 × 10-16). A greater number of outlier regions were associated with worse cognitive function, CSF protein concentrations, and an increased risk of converting from MCI to AD within 3 years (hazard ratio 1.028, 95% CI 1.016-1.039, p = 1.8 × 10-16). DISCUSSION Individualized normative maps of cortical thickness highlight the heterogeneous effect of AD on the brain. Regional outlier estimates have the potential to be a marker of disease and could be used to track an individual's disease progression or treatment response in clinical trials.
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Affiliation(s)
- Serena Verdi
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Seyed Mostafa Kia
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Keir X X Yong
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Duygu Tosun
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Jonathan M Schott
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Andre F Marquand
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - James H Cole
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands.
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Heinzinger N, Maass A, Berron D, Yakupov R, Peters O, Fiebach J, Villringer K, Preis L, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Bartels C, Jessen F, Maier F, Glanz W, Buerger K, Janowitz D, Perneczky R, Rauchmann BS, Teipel S, Killimann I, Göerß D, Laske C, Munk MH, Spottke A, Roy N, Heneka MT, Brosseron F, Dobisch L, Ewers M, Dechent P, Haynes JD, Scheffler K, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Düzel E, Ziegler G. Exploring the ATN classification system using brain morphology. Alzheimers Res Ther 2023; 15:50. [PMID: 36915139 PMCID: PMC10009950 DOI: 10.1186/s13195-023-01185-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 02/08/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND The NIA-AA proposed amyloid-tau-neurodegeneration (ATN) as a classification system for AD biomarkers. The amyloid cascade hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (amyloid-conversion first, tau-conversion second, N-conversion last) and alternative progressions using voxel-based morphometry (VBM) in a large cross-sectional MRI cohort. METHODS We used baseline data of the DELCODE cohort of 437 subjects (127 controls, 168 SCD, 87 MCI, 55 AD patients) which underwent lumbar puncture, MRI scanning, and neuropsychological assessment. ATN classification was performed using CSF-Aβ42/Aβ40 (A+/-), CSF phospho-tau (T+/-), and adjusted hippocampal volume or CSF total-tau (N+/-). We compared voxel-wise model evidence for monotonic decline of gray matter volume across various sequences over ATN groups using the Bayesian Information Criterion (including also ROIs of Braak stages). First, face validity of the ACH transition sequence A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was compared against biologically less plausible (permuted) sequences among AD continuum ATN groups. Second, we evaluated evidence for 6 monotonic brain volume progressions from A-T-N- towards A+T+N+ including also non-AD continuum ATN groups. RESULTS The ACH-based progression A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was consistent with cognitive decline and clinical diagnosis. Using hippocampal volume for operationalization of neurodegeneration (N), ACH was most evident in 9% of gray matter predominantly in the medial temporal lobe. Many cortical regions suggested alternative non-monotonic volume progressions over ACH progression groups, which is compatible with an early amyloid-related tissue expansion or sampling effects, e.g., due to brain reserve. Volume decline in 65% of gray matter was consistent with a progression where A status converts before T or N status (i.e., ACH/ANT) when compared to alternative sequences (TAN/TNA/NAT/NTA). Brain regions earlier affected by tau tangle deposition (Braak stage I-IV, MTL, limbic system) present stronger evidence for volume decline than late Braak stage ROIs (V/VI, cortical regions). Similar findings were observed when using CSF total-tau for N instead. CONCLUSION Using the ATN classification system, early amyloid status conversion (before tau and neurodegeneration) is associated with brain volume loss observed during AD progression. The ATN system and the ACH are compatible with monotonic progression of MTL atrophy. TRIAL REGISTRATION DRKS00007966, 04/05/2015, retrospectively registered.
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Affiliation(s)
- Nils Heinzinger
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany.
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Jochen Fiebach
- Center for Stroke Research Berlin, Charité-Universitätsmedizin, Berlin, Germany
| | - Kersten Villringer
- Center for Stroke Research Berlin, Charité-Universitätsmedizin, Berlin, Germany
| | - Lukas Preis
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany.,University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jacob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany.,Department of Medical Sciences, Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Franziska Maier
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Killimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Doreen Göerß
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michael T Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Göttingen, Göttingen, Germany
| | - John Dylan Haynes
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin, Berlin, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Institute for Medical Biometry, University Hospital Bonn, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, University Hospital Bonn, Bonn, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
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Groechel RC, Tripodis Y, Alosco ML, Mez J, Qiu WQ, Mercier G, Goldstein L, Budson AE, Kowall N, Killiany RJ. Annualized changes in rate of amyloid deposition and neurodegeneration are greater in participants who become amyloid positive than those who remain amyloid negative. Neurobiol Aging 2023; 127:33-42. [PMID: 37043881 DOI: 10.1016/j.neurobiolaging.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 03/01/2023] [Accepted: 03/06/2023] [Indexed: 03/12/2023]
Abstract
This study longitudinally examined participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) who underwent a conversion in amyloid-beta (Aβ) status in comparison to a group of ADNI participants who did not show a change in amyloid status over the same follow-up period. Participants included 136 ADNI dementia-free participants with 2 florbetapir positron emission tomography (PET) scans. Of these participants, 68 showed amyloid conversion as measured on florbetapir PET, and the other 68 did not. Amyloid converters and non-converters were chosen to have representative demographic data (age, education, sex, diagnostic status, and race). The amyloid converter group showed increased prevalence of APOE ε4 (p < 0.001), greater annualized percent volume loss in selected magnetic resonance imaging (MRI) regions (p < 0.05), lower cerebrospinal fluid Aβ1-42 (p < 0.001), and greater amyloid retention (as measured by standard uptake value ratios) on florbetapir PET scans (p < 0.001) in comparison to the non-converter group. These results provide compelling evidence that important neuropathological changes are occurring alongside amyloid conversion.
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14
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Yoon EJ, Lee JY, Kwak S, Kim YK. Mild behavioral impairment linked to progression to Alzheimer's disease and cortical thinning in amnestic mild cognitive impairment. Front Aging Neurosci 2023; 14:1051621. [PMID: 36688162 PMCID: PMC9846631 DOI: 10.3389/fnagi.2022.1051621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023] Open
Abstract
Background Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for dementia. However, the associations between MBI and a risk of progression to Alzheimer's disease (AD) and its neuroanatomical correlates in mild cognitive impairment (MCI) are still unclear. Method A total 1,184 older adults with amnestic MCI was followed for a mean of 3.1 ± 2.0 years. MBI was approximated using a transformation algorithm for the Neuropsychiatric Inventory at baseline. A two-step cluster analysis was used to identify subgroups of individuals with amnestic MCI based on profiles of 5 MBI domain symptoms (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate differences in the risk of progression to AD between subgroups. A subset of participants (n = 202) underwent 3D T1-weighted MRI scans at baseline and cortical thickness was compared between the subgroups of amnestic MCI patients. Result The cluster analysis classified the patients into 3 groups: (1) patients without any MBI domain symptoms (47.4%, asymptomatic group); (2) those with only affective dysregulation (29.4%, affective dysregulation group); (3) those with multiple MBI domain symptoms, particularly affective dysregulation, decreased motivation and impulse dyscontrol (23.2%, complex group). Compared to the asymptomatic group, the complex group was associated with a higher risk of progression to AD (hazard ratio = 2.541 [1.904-3.392], p < 0.001), but the affective dysregulation group was not (1.214 [0.883-1.670], p = 0.232). In cortical thickness analysis, the complex group revealed cortical thinning bilaterally in the inferior parietal, lateral occipital, lateral superior temporal, and frontopolar regions compared with the affective dysregulation group. Conclusion The multiple co-occuring MBI domains in individuals with amnestic MCI are associated with a higher risk of progression to AD and cortical thinning in temporal, parietal and frontal areas. These results suggest that evaluation of MBI could be useful for risk stratification for AD and appropriate intervention in MCI individuals.
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Affiliation(s)
- Eun Jin Yoon
- Memory Network Medical Research Center, Seoul National University, Seoul, South Korea,Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Jun-Young Lee
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea,Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea,Department of Medical Device Development, Seoul National University College of Medicine, Seoul, South Korea
| | - Seyul Kwak
- Department of Psychology, Pusan National University, Busan, South Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea,Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, South Korea,*Correspondence: Yu Kyeong Kim,
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15
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Wu X, Iliuk AB, Tao WA. Translational proteomics and phosphoproteomics: Tissue to extracellular vesicles. Adv Clin Chem 2023; 112:119-53. [PMID: 36642482 DOI: 10.1016/bs.acc.2022.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We are currently experiencing a rapidly developing era in terms of translational and clinical medical sciences. The relatively mature state of nucleic acid examination has significantly improved our understanding of disease mechanism and therapeutic potential of personalized treatment, but misses a large portion of phenotypic disease information. Proteins, in particular phosphorylation events that regulates many cellular functions, could provide real-time information for disease onset, progression and treatment efficacy. The technical advances in liquid chromatography and mass spectrometry have realized large-scale and unbiased proteome and phosphoproteome analyses with disease relevant samples such as tissues. However, tissue biopsy still has multiple shortcomings, such as invasiveness of sample collection, potential health risk for patients, difficulty in protein preservation and extreme heterogeneity. Recently, extracellular vesicles (EVs) have offered a great promise as a unique source of protein biomarkers for non-invasive liquid biopsy. Membranous EVs provide stable preservation of internal proteins and especially labile phosphoproteins, which is essential for effective routine biomarker detection. To aid efficient EV proteomic and phosphoproteomic analyses, recent developments showcase clinically-friendly EV techniques, facilitating diagnostic and therapeutic applications. Ultimately, we envision that with streamlined sample preparation from tissues and EVs proteomics and phosphoproteomics analysis will become routine in clinical settings.
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16
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Nakaya M, Sato N, Matsuda H, Maikusa N, Shigemoto Y, Sone D, Yamao T, Ogawa M, Kimura Y, Chiba E, Ohnishi M, Kato K, Okita K, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease. Alzheimers Dement (N Y) 2022; 8:e12356. [PMID: 36304723 PMCID: PMC9594557 DOI: 10.1002/trc2.12356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/03/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). METHODS Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. RESULTS In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions. DISCUSSION FW imaging could be a biomarker for tau in AD alongside clinical correlations.
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Affiliation(s)
- Moto Nakaya
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
| | - Noriko Sato
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Hiroshi Matsuda
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Drug Discovery and Cyclotron Research CenterSouthern TOHOKU Research Institute for NeuroscienceKoriyamaJapan
| | - Norihide Maikusa
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Yoko Shigemoto
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Daichi Sone
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan,Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tensho Yamao
- Department of Radiological SciencesSchool of Health SciencesFukushima Medical UniversityFukushimaJapan
| | - Masayo Ogawa
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Yukio Kimura
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Emiko Chiba
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Masahiro Ohnishi
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Koichi Kato
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Kyoji Okita
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tadashi Tsukamoto
- Department of NeurologyNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Yuma Yokoi
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masuhiro Sakata
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Osamu Abe
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
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17
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Salvadó G, Shekari M, Falcon C, Operto G, Milà-Alomà M, Sánchez-Benavides G, Cacciaglia R, Arenaza-Urquijo E, Niñerola-Baizán A, Perissinotti A, Minguillon C, Fauria K, Kollmorgen G, Suridjan I, Molinuevo JL, Zetterberg H, Blennow K, Suárez-Calvet M, Gispert JD. Brain alterations in the early Alzheimer's continuum with amyloid-β, tau, glial and neurodegeneration CSF markers. Brain Commun 2022; 4:fcac134. [PMID: 35702732 PMCID: PMC9185381 DOI: 10.1093/braincomms/fcac134] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 03/03/2022] [Accepted: 05/20/2022] [Indexed: 11/15/2022] Open
Abstract
Higher grey matter volumes/cortical thickness and fluorodeoxyglucose uptake have been consistently found in cognitively unimpaired individuals with abnormal Alzheimer’s disease biomarkers compared with those with normal biomarkers. It has been hypothesized that such transient increases may be associated with neuroinflammatory mechanisms triggered in response to early Alzheimer’s pathology. Here, we evaluated, in the earliest stages of the Alzheimer’s continuum, associations between grey matter volume and fluorodeoxyglucose uptake with CSF biomarkers of several pathophysiological mechanisms known to be altered in preclinical Alzheimer’s disease stages. We included 319 cognitively unimpaired participants from the ALFA+ cohort with available structural MRI, fluorodeoxyglucose PET and CSF biomarkers of amyloid-β and tau pathology (phosphorylated tau and total tau), synaptic dysfunction (neurogranin), neuronal and axonal injury (neurofilament light), glial activation (soluble triggering receptor on myeloid cells 2, YKL40, GFAP, interleukin-6 and S100b) and α-synuclein using the Roche NeuroToolKit. We first used the amyloid-β/tau framework to investigate differences in the neuroimaging biomarkers between preclinical Alzheimer’s disease stages. Then, we looked for associations between the neuroimaging markers and all the CSF markers. Given the non-negative nature of the concentrations of CSF biomarkers and their high collinearity, we clustered them using non-negative matrix factorization approach (components) and sought associations with the imaging markers. By groups, higher grey matter volumes were found in the amyloid-β-positive tau-negative participants with respect to the reference amyloid-β-negative tau-negative group. Both amyloid-β and tau-positive participants showed higher fluorodeoxyglucose uptake than tau-negative individuals. Using the obtained components, we observed that tau pathology accompanied by YKL-40 (astrocytic marker) was associated with higher grey matter volumes and fluorodeoxyglucose uptake in extensive brain areas. Higher grey matter volumes in key Alzheimer-related regions were also found in association with two other components characterized by a higher expression of amyloid-β in combination with different glial markers: one with higher GFAP and S100b levels (astrocytic markers) and the other one with interleukin-6 (pro-inflammatory). Notably, these components’ expression had different behaviours across amyloid-β/tau stages. Taken together, our results show that CSF amyloid-β and phosphorylated tau, in combination with different aspects of glial response, have distinctive associations with higher grey matter volumes and increased glucose metabolism in key Alzheimer-related regions. These mechanisms combine to produce transient higher grey matter volumes and fluorodeoxyglucose uptake at the earliest stages of the Alzheimer’s continuum, which may revert later on the course of the disease when neurodegeneration drives structural and metabolic cerebral changes.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Eider Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aida Niñerola-Baizán
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Andrés Perissinotti
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
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18
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Sadiq MU, Kwak K, Dayan E. Model-based stratification of progression along the Alzheimer disease continuum highlights the centrality of biomarker synergies. Alzheimers Res Ther 2022; 14:16. [PMID: 35073974 PMCID: PMC8787915 DOI: 10.1186/s13195-021-00941-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/23/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND The progression rates of Alzheimer's disease (AD) are variable and dynamic, yet the mechanisms that contribute to heterogeneity in progression rates remain ill-understood. Particularly, the role of synergies in pathological processes reflected by biomarkers for amyloid-beta ('A'), tau ('T'), and neurodegeneration ('N') in progression along the AD continuum is not fully understood. METHODS Here, we used a combination of model and data-driven approaches to address this question. Working with a large dataset (N = 321 across the training and testing cohorts), we first applied unsupervised clustering on longitudinal cognitive assessments to divide individuals on the AD continuum into those showing fast vs. moderate decline. Next, we developed a deep learning model that differentiated fast vs. moderate decline using baseline AT(N) biomarkers. RESULTS Training the model with AT(N) biomarker combination revealed more prognostic utility than any individual biomarkers alone. We additionally found little overlap between the model-driven progression phenotypes and established atrophy-based AD subtypes. Our model showed that the combination of all AT(N) biomarkers had the most prognostic utility in predicting progression along the AD continuum. A comprehensive AT(N) model showed better predictive performance than biomarker pairs (A(N) and T(N)) and individual biomarkers (A, T, or N). CONCLUSIONS This study combined data and model-driven methods to uncover the role of AT(N) biomarker synergies in the progression of cognitive decline along the AD continuum. The results suggest a synergistic relationship between AT(N) biomarkers in determining this progression, extending previous evidence of A-T synergistic mechanisms.
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Affiliation(s)
- Muhammad Usman Sadiq
- Biomedical Research Imaging Center (BRIC), UNC-Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kichang Kwak
- Biomedical Research Imaging Center (BRIC), UNC-Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eran Dayan
- Biomedical Research Imaging Center (BRIC), UNC-Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Radiology, UNC-Chapel Hill, Chapel Hill, NC, 27599, USA.
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19
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Padilla C, Montal V, Walpert MJ, Hong YT, Fryer TD, Coles JP, Aigbirhio FI, Hartley SL, Cohen AD, Tudorascu DL, Christian BT, Handen BL, Klunk WE, Holland AJ, Zaman SH. Cortical atrophy and amyloid and tau deposition in Down syndrome: A longitudinal study. Alzheimers Dement (Amst) 2022; 14:e12288. [PMID: 35386472 PMCID: PMC8974205 DOI: 10.1002/dad2.12288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/30/2021] [Accepted: 01/10/2022] [Indexed: 11/17/2022]
Abstract
Introduction: The Down syndrome population has a high prevalence for dementia, often showing their first clinical symptoms in their 40s. Methods: In a longitudinal cohort, we investigate whether amyloid deposition at time point 1 (TP1) could predict cortical thickness change at time point 2 (TP2). The association between tau burden and cortical thickness was also examined at time point 3 (TP3). Results: Between TP1 and TP2 there was pronounced cortical thinning in temporo-parietal cortices and cortical thickening in the frontal cortex. Baseline amyloid burden was strongly associated to cortical thinning progression, especially in the temporo-parietal regions. At TP3, tau deposition negatively correlated with cortical atrophy in regions where tau usually accumulates at later Braak stages. Discussion: A higher amount of amyloid accumulation triggers a cascade of changes of disease-causing processes that eventually lead to dementia. As expected, we found that regions where tau usually accumulates were those also displaying high levels of cortical atrophy.
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Affiliation(s)
- Concepcion Padilla
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry University of Cambridge Cambridge UK.,Memory Unit and Biomedical Research Institute Sant Pau (IIB Sant Pau), Neurology Department Santa Creu and Sant Pau Hospital Barcelona Spain.,The Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED) Madrid Spain
| | - Victor Montal
- Memory Unit and Biomedical Research Institute Sant Pau (IIB Sant Pau), Neurology Department Santa Creu and Sant Pau Hospital Barcelona Spain.,The Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED) Madrid Spain
| | - Madeleine J Walpert
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry University of Cambridge Cambridge UK
| | - Young T Hong
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, Cambridge Biomedical Campus University of Cambridge Cambridge UK
| | - Tim D Fryer
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, Cambridge Biomedical Campus University of Cambridge Cambridge UK
| | - Jonathan P Coles
- Division of Anaesthesia, Department of Medicine, Cambridge Biomedical Campus University of Cambridge Cambridge UK
| | - Franklin I Aigbirhio
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, Cambridge Biomedical Campus University of Cambridge Cambridge UK
| | - Sigan L Hartley
- Waisman Center University of Wisconsin-Madison Madison Wisconsin USA
| | - Ann D Cohen
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Dana L Tudorascu
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | | | - Benjamin L Handen
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - William E Klunk
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Anthony J Holland
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry University of Cambridge Cambridge UK.,Cambridgeshire and Peterborough NHS Foundation Trust Fulbourn Hospital Cambridge UK
| | - Shahid H Zaman
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry University of Cambridge Cambridge UK.,Cambridgeshire and Peterborough NHS Foundation Trust Fulbourn Hospital Cambridge UK
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20
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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21
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22
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Frigerio I, Boon BDC, Lin CP, Galis-de Graaf Y, Bol J, Preziosa P, Twisk J, Barkhof F, Hoozemans JJM, Bouwman FH, Rozemuller AJM, van de Berg WDJ, Jonkman LE. Amyloid-β, p-tau and reactive microglia are pathological correlates of MRI cortical atrophy in Alzheimer’s disease. Brain Commun 2021; 3:fcab281. [PMID: 34927073 PMCID: PMC8677327 DOI: 10.1093/braincomms/fcab281] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 10/14/2021] [Accepted: 10/21/2021] [Indexed: 12/15/2022] Open
Abstract
Alzheimer’s disease is characterized by cortical atrophy on MRI and abnormal depositions of amyloid-beta, phosphorylated-tau and inflammation pathologically. However, the relative contribution of these pathological hallmarks to cortical atrophy, a widely used MRI biomarker in Alzheimer’s disease, is yet to be defined. Therefore, the aim of this study was to identify the histopathological correlates of MRI cortical atrophy in Alzheimer’s disease donors, and its typical amnestic and atypical non-amnestic phenotypes. Nineteen Alzheimer’s disease (of which 10 typical and 9 atypical) and 10 non-neurological control brain donors underwent post-mortem in situ 3T 3D-T1, from which cortical thickness was calculated with Freesurfer. Upon subsequent autopsy, 12 cortical brain regions from the right hemisphere and 9 from the left hemisphere were dissected and immunostained for amyloid-beta, phosphorylated-tau and reactive microglia, and percentage area load was calculated for each marker using ImageJ. In addition, post-mortem MRI was compared to ante-mortem MRI of the same Alzheimer’s disease donors when available. MRI-pathology associations were assessed using linear mixed models. Higher amyloid-beta load weakly correlated with higher cortical thickness globally (r = 0.22, P = 0.022). Phosphorylated-tau strongly correlated with cortical atrophy in temporal and frontal regions (−0.76 < r < −1.00, all P < 0.05). Reactive microglia load strongly correlated with cortical atrophy in the parietal region (r = −0.94, P < 0.001). Moreover, post-mortem MRI scans showed high concordance with ante-mortem scans acquired <1 year before death. In conclusion, distinct histopathological markers differently correlated with cortical atrophy, highlighting their different roles in the neurodegenerative process, and therefore contributing to the understanding of the pathological underpinnings of MRI atrophic patterns in Alzheimer’s disease. In our cohort, no or only subtle differences were found in MRI-pathology associations in Alzheimer’s disease phenotypes, indicating that the histopathological correlates of cortical atrophy in typical and atypical phenotypes might be similar. Moreover, we show that post-mortem in situ MRI can be used as proxy for ante-mortem in vivo MRI.
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Affiliation(s)
- Irene Frigerio
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - Baayla D C Boon
- Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Chen-Pei Lin
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - Yvon Galis-de Graaf
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - John Bol
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 60-20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 60-20132 Milan, Italy
| | - Jos Twisk
- Department of Epidemiology and Biostatistics, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, the Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London WC1E, UK
| | - Jeroen J M Hoozemans
- Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Femke H Bouwman
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Alzheimer Centrum Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Annemieke J M Rozemuller
- Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Wilma D J van de Berg
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - Laura E Jonkman
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
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23
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Chauveau L, Kuhn E, Palix C, Felisatti F, Ourry V, de La Sayette V, Chételat G, de Flores R. Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study. Front Aging Neurosci 2021; 13:750154. [PMID: 34720998 PMCID: PMC8554299 DOI: 10.3389/fnagi.2021.750154] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 09/13/2021] [Indexed: 11/13/2022] Open
Abstract
Medial temporal lobe (MTL) atrophy is a key feature of Alzheimer's disease (AD), however, it also occurs in typical aging. To enhance the clinical utility of this biomarker, we need to better understand the differential effects of age and AD by encompassing the full AD-continuum from cognitively unimpaired (CU) to dementia, including all MTL subregions with up-to-date approaches and using longitudinal designs to assess atrophy more sensitively. Age-related trajectories were estimated using the best-fitted polynomials in 209 CU adults (aged 19–85). Changes related to AD were investigated among amyloid-negative (Aβ−) (n = 46) and amyloid-positive (Aβ+) (n = 14) CU, Aβ+ patients with mild cognitive impairment (MCI) (n = 33) and AD (n = 31). Nineteen MCI-to-AD converters were also compared with 34 non-converters. Relationships with cognitive functioning were evaluated in 63 Aβ+ MCI and AD patients. All participants were followed up to 47 months. MTL subregions, namely, the anterior and posterior hippocampus (aHPC/pHPC), entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36 [as perirhinal cortex (PRC) substructures], and parahippocampal cortex (PHC), were segmented from a T1-weighted MRI using a new longitudinal pipeline (LASHiS). Statistical analyses were performed using mixed models. Adult lifespan models highlighted both linear (PRC, BA35, BA36, PHC) and nonlinear (HPC, aHPC, pHPC, ERC) trajectories. Group comparisons showed reduced baseline volumes and steeper volume declines over time for most of the MTL subregions in Aβ+ MCI and AD patients compared to Aβ− CU, but no differences between Aβ− and Aβ+ CU or between Aβ+ MCI and AD patients (except in ERC). Over time, MCI-to-AD converters exhibited a greater volume decline than non-converters in HPC, aHPC, and pHPC. Most of the MTL subregions were related to episodic memory performances but not to executive functioning or speed processing. Overall, these results emphasize the benefits of studying MTL subregions to distinguish age-related changes from AD. Interestingly, MTL subregions are unequally vulnerable to aging, and those displaying non-linear age-trajectories, while not damaged in preclinical AD (Aβ+ CU), were particularly affected from the prodromal stage (Aβ+ MCI). This volume decline in hippocampal substructures might also provide information regarding the conversion from MCI to AD-dementia. All together, these findings provide new insights into MTL alterations, which are crucial for AD-biomarkers definition.
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Affiliation(s)
- Léa Chauveau
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Elizabeth Kuhn
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Cassandre Palix
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France
| | | | - Valentin Ourry
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France.,U1077 NIMH, Inserm, Caen-Normandie University, École Pratique des Hautes Études, Caen, France
| | - Vincent de La Sayette
- U1077 NIMH, Inserm, Caen-Normandie University, École Pratique des Hautes Études, Caen, France
| | - Gaël Chételat
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France
| | - Robin de Flores
- U1237 PhIND, Inserm, Caen-Normandie University, GIP Cyceron, Caen, France
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24
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Guo T, Landau SM, Jagust WJ. Age, vascular disease, and Alzheimer's disease pathologies in amyloid negative elderly adults. Alzheimers Res Ther 2021; 13:174. [PMID: 34654465 PMCID: PMC8520216 DOI: 10.1186/s13195-021-00913-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/03/2021] [Indexed: 02/04/2023]
Abstract
Background We recently reported that CSF phosphorylated tau (p-Tau181) relative to Aβ40 (CSF p-Tau/Aβ40 ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau181 alone. While elevations of CSF p-Tau/Aβ40 can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity. Methods We examined relationships between CSF p-Tau/Aβ40, and CSF Aβ42/Aβ40, Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had 18F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ40 associations with these measures as well. Results Elevated CSF p-Tau/Aβ40 was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ42/Aβ40, higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ40 increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ40 and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements. Conclusions These data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00913-5.
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Affiliation(s)
- Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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25
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Cho YH, Lee H, Kim NR, Choi JW, Roh HW, Ha JH, Hong CH, Seo SW, Choi SH, Kim EJ, Kim BC, Kim SY, Cheong J, Park B, Son SJ. Cortical thickness is differently associated with ALDH2 rs671 polymorphism according to level of amyloid deposition. Sci Rep 2021; 11:19529. [PMID: 34593890 DOI: 10.1038/s41598-021-98834-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 09/15/2021] [Indexed: 11/20/2022] Open
Abstract
Accumulating evidence indicates that amyloid-beta (Aβ) deposition and biogenic aldehyde accumulation contribute to the pathogenesis of neurodegenerative diseases. Human aldehyde dehydrogenase 2 (ALDH2) metabolizes biogenic aldehydes produced in the brain to prevent damage. However, r671G>A, a single nucleotide polymorphism of ALDH2, causes aldehyde accumulation and decreased ALDH2 activity. We aimed to investigate whether Aβ deposition and rs671 polymorphism have an interaction effect on cortical thickness (CTh). We grouped 179 participants in the Biobank Innovations for chronic Cerebrovascular disease With ALZheimer's disease Study as follows: amyloid (–) [A(–)] and amyloid (+) [A(+)] groups based on the Aβ deposition degree; A-carrier (AC) and GG (GG) groups based on the presence/absence of the rs671 A allele; and their combinations, i.e., A(–)AC, A(–)GG, A(+)AC, and A(+)GG groups. A multiple regression analysis identified nine regions of interest. Compared with the A(–)GG group, the A(–)AC group showed thinner CTh in all regions. There were no significant differences between the A(+)AC and A(+)GG groups. We observed an interaction effect of amyloid deposition and rs671 polymorphism on CTh. The CTh in the A(–) group appeared to be strongly influenced by rs671 polymorphism, which could have contributed to cortical thinning and biogenic aldehyde accumulation in the AC group. Additionally, CTh in the A(+) group appeared to be strongly influenced by amyloid deposition.
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26
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Yoon B, Guo T, Provost K, Korman D, Ward TJ, Landau SM, Jagust WJ. Abnormal tau in amyloid PET negative individuals. Neurobiol Aging 2021; 109:125-134. [PMID: 34715443 DOI: 10.1016/j.neurobiolaging.2021.09.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 09/03/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
We examined the characteristics of individuals with biomarker evidence of tauopathy but without β-amyloid (Aβ) (A-T+) in relation to individuals with (A+T+) and without (A-T-) evidence of Alzheimer's disease (AD). We included 561 participants with Aβ and tau PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared A-T- (n = 316), A-T+ (n = 63), and A+T+ (n = 182) individuals on demographics, amyloid, tau, hippocampal volumes, and cognition. A-T+ individuals were low on apolipoprotein E ɛ4 prevalence (17%) and had no evidence of subtly elevated brain Aβ within the negative range. The severity of tau deposition, hippocampal atrophy, and cognitive dysfunction in the A-T+ group was intermediate between A-T- and A+T+ (all p < 0.001). Tau uptake patterns in A-T+ individuals were heterogeneous, but approximately 29% showed tau deposition in the medial temporal lobe only, consistent with primary age-related tauopathy and an additional 32% showed a pattern consistent with AD. A-T+ individuals also share other features that are characteristic of AD such as cognitive impairment and neurodegeneration, but this group is heterogeneous and likely reflects more than one disorder.
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Affiliation(s)
- Bora Yoon
- Department of Neurology, Konyang University Hospital, Konyang University, College of Medicine, Daejeon, Korea.
| | - Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Karine Provost
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Tyler J Ward
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Fox‐Fuller JT, Torrico‐Teave H, d'Oleire Uquillas F, Chen K, Su Y, Chen Y, Brickhouse M, Sanchez JS, Aguero C, Jacobs HI, Hampton O, Guzmán‐Vélez E, Vila‐Castelar C, Aguirre‐Acevedo DC, Baena A, Artola A, Martinez J, Pluim CF, Alvarez S, Ochoa‐Escudero M, Reiman EM, Sperling RA, Lopera F, Johnson KA, Dickerson BC, Quiroz YT. Cortical thickness across the lifespan in a Colombian cohort with autosomal-dominant Alzheimer's disease: A cross-sectional study. Alzheimers Dement (Amst) 2021; 13:e12233. [PMID: 34541287 PMCID: PMC8438687 DOI: 10.1002/dad2.12233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/22/2021] [Accepted: 06/28/2021] [Indexed: 01/10/2023]
Abstract
INTRODUCTION Cortical thinning is a marker of neurodegeneration in Alzheimer's disease (AD). We investigated the age-related trajectory of cortical thickness across the lifespan (9-59 years) in a Colombian kindred with autosomal dominant AD (ADAD). METHODS Two hundred eleven participants (105 presenilin-1 [PSEN1] E280A mutation carriers, 16 with cognitive impairment; 106 non-carriers) underwent magnetic resonance imaging. A piecewise linear regression identified change-points in the age-related trajectory of cortical thickness in carriers and non-carriers. RESULTS Unimpaired carriers exhibited elevated cortical thickness compared to non-carriers, and thickness more negatively correlated with age and cognition in carriers relative to non-carriers. We found increased cortical thickness in child carriers, after which thickness steadied compared to non-carriers prior to a rapid reduction in the decade leading up to the expected age at cognitive impairment in carriers. DISCUSSION Findings suggest that cortical thickness may fluctuate across the ADAD lifespan, from early-life increased thickness to atrophy proximal to clinical onset.
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Affiliation(s)
- Joshua T. Fox‐Fuller
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Heirangi Torrico‐Teave
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Federico d'Oleire Uquillas
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Princeton Neuroscience InstitutePrinceton UniversityPrincetonNew JerseyUSA
| | - Kewei Chen
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Yi Su
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | | | - Michael Brickhouse
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Justin S. Sanchez
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Cinthya Aguero
- MassGeneral Institute for Neurodegenerative DiseaseCharlestownMassachusettsUSA
| | - Heidi I.L. Jacobs
- Division of Nuclear MedicineDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- School for Mental Health and NeuroscienceAlzheimer CentreLimburgMaastricht UniversityMaastrichtThe Netherlands
| | - Olivia Hampton
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Edmarie Guzmán‐Vélez
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Clara Vila‐Castelar
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | | | - Ana Baena
- Grupo de NeurociencasUniversidad de AntioquiaMedellínAntioquiaColombia
| | - Arabiye Artola
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jairo Martinez
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Celina F. Pluim
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Sergio Alvarez
- Department of RadiologyHospital Pablo Tobon UribeMedellínColombia
| | | | | | - Reisa A. Sperling
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A.Massachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
- Department of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Francisco Lopera
- Grupo de NeurociencasUniversidad de AntioquiaMedellínAntioquiaColombia
| | - Keith A. Johnson
- Division of Nuclear MedicineDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A.Massachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Bradford C. Dickerson
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A.Massachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Yakeel T. Quiroz
- Department of PsychiatryMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Grupo de NeurociencasUniversidad de AntioquiaMedellínAntioquiaColombia
- Athinoula A.Massachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
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Pegueroles J, Montal V, Bejanin A, Vilaplana E, Aranha M, Santos‐Santos MA, Alcolea D, Carrió I, Camacho V, Blesa R, Lleó A, Fortea J. AMYQ: An index to standardize quantitative amyloid load across PET tracers. Alzheimers Dement 2021; 17:1499-1508. [PMID: 33797846 PMCID: PMC8519100 DOI: 10.1002/alz.12317] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/21/2021] [Accepted: 01/31/2021] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations. METHODS We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance. RESULTS AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs. DISCUSSION AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.
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Affiliation(s)
- Jordi Pegueroles
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Victor Montal
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Mateus Aranha
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Miguel Angel Santos‐Santos
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Ignasi Carrió
- Department of Nuclear MedicineHospital de la Santa Creu i Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Valle Camacho
- Department of Nuclear MedicineHospital de la Santa Creu i Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
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Hays CC, Zlatar ZZ, Meloy MJ, Osuna J, Liu TT, Galasko DR, Wierenga CE. Anterior Cingulate Structure and Perfusion is Associated with Cerebrospinal Fluid Tau among Cognitively Normal Older Adult APOEɛ4 Carriers. J Alzheimers Dis 2021; 73:87-101. [PMID: 31743999 DOI: 10.3233/jad-190504] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Evidence suggests the ɛ4 allele of the apolipoprotein E (APOE) gene may accelerate an age-related process of cortical thickening and cerebral blood flow (CBF) reduction in the anterior cingulate cortex (ACC). Although the neural basis of this association remains unclear, evidence suggests it might reflect early neurodegenerative processes. However, to date, associations between cerebrospinal fluid (CSF) biomarkers of neurodegeneration, such as CSF tau, and APOE-related alterations in ACC cortical thickness (CTH) and CBF have yet to be explored. The current study explored the interaction of CSF tau and APOE genotype (ɛ4+, ɛ4-) on FreeSurfer-derived CTH and arterial spin labeling MRI-measured resting CBF in the ACC (caudal ACC [cACC] and rostral ACC [rACC]) among a sample of 45 cognitively normal older adults. Secondary analyses also examined associations between APOE, CTH/CBF, and cognitive performance. In the cACC, higher CSF tau was associated with higher CTH and lower CBF in ɛ4+, whereas these relationships were not evident in ɛ4-. In the rACC, higher CSF tau was associated with higher CTH for both ɛ4+ and ɛ4-, and with lower CBF only in ɛ4+. Significant interactions of CSF tau and APOE on CTH/CBF were not observed in two posterior reference regions implicated in Alzheimer's disease. Secondary analyses revealed a negative relationship between cACC CTH and executive functioning in ɛ4+ and a positive relationship in ɛ4-. Findings suggest the presence of an ɛ4-related pattern of increased CTH and reduced CBF in the ACC that is associated with biomarkers of neurodegeneration and subtle decrements in cognition.
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Affiliation(s)
- Chelsea C Hays
- VA San Diego Healthcare System, San Diego, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Zvinka Z Zlatar
- Department of Psychiatry, UC San Diego, La Jolla, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - M J Meloy
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Jessica Osuna
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, UC San Diego, La Jolla, CA, USA
| | - Thomas T Liu
- Department of Radiology, UC San Diego, La Jolla, CA, USA
| | - Douglas R Galasko
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Neurosciences, UC San Diego, La Jolla, CA, USA
| | - Christina E Wierenga
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, UC San Diego, La Jolla, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
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30
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Montal V, Vilaplana E, Pegueroles J, Bejanin A, Alcolea D, Carmona-Iragui M, Clarimón J, Levin J, Cruchaga C, Graff-Radford NR, Noble JM, Lee JH, Allegri R, Karch CM, Laske C, Schofield P, Salloway S, Ances B, Benzinger T, McDale E, Bateman R, Blesa R, Sánchez-Valle R, Lleó A, Fortea J. Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease. Alzheimers Dement 2021; 17:618-628. [PMID: 33196147 PMCID: PMC8043974 DOI: 10.1002/alz.12224] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/20/2020] [Accepted: 10/09/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials. METHODS In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network. RESULTS In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations. DISCUSSION These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.
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Affiliation(s)
- Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alex Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - María Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
| | - Jordi Clarimón
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | | | - James M Noble
- Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, BuenosAires, Argentina
| | - Celeste M. Karch
- Department of Psychiatry, Washington University School of Medicine, Saint Lous, MO, USA
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Stephen Salloway
- Neurology and the Memory and Aging Program, Butler Hospital, Providence, RI, USA
| | - Beau Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Tammie Benzinger
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Eric McDale
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Randall Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Raquel Sánchez-Valle
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
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Diao Y, Yin T, Gruetter R, Jelescu IO. PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain. Front Neurosci 2021; 15:602170. [PMID: 33841071 PMCID: PMC8032956 DOI: 10.3389/fnins.2021.602170] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/26/2021] [Indexed: 01/12/2023] Open
Abstract
Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as physiology. Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artifacts from rs-fMRI signals through optimized data processing methods. However, existing tools that correct for these effects have been developed for human brain and are not readily transposable to rat data. Therefore, the aim of the present study was to establish a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data. It includes a novel denoising approach based on the Marchenko-Pastur Principal Component Analysis (MP-PCA) method, FMRIB's ICA-based Xnoiseifier (FIX) for automatic artifact classification and cleaning, and global signal regression (GSR). Our results show that: (I) MP-PCA denoising substantially improves the temporal signal-to-noise ratio, (II) the pre-trained FIX classifier achieves a high accuracy in artifact classification, and (III) both independent component analysis (ICA) cleaning and GSR are essential steps in correcting for possible artifacts and minimizing the within-group variability in control animals while maintaining typical connectivity patterns. Reduced within-group variability also facilitates the exploration of potential between-group FC changes, as illustrated here in a rat model of sporadic Alzheimer's disease.
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Affiliation(s)
- Yujian Diao
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Laboratoire d’Imagerie Fonctionnelle et Métabolique, EPFL, Lausanne, Switzerland
| | - Ting Yin
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Rolf Gruetter
- Laboratoire d’Imagerie Fonctionnelle et Métabolique, EPFL, Lausanne, Switzerland
| | - Ileana O. Jelescu
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
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Abstract
The loss of proteostasis over the life course is associated with a wide range of debilitating degenerative diseases and is a central hallmark of human aging. When left unchecked, proteins that are intrinsically disordered can pathologically aggregate into highly ordered fibrils, plaques, and tangles (termed amyloids), which are associated with countless disorders such as Alzheimer's disease, Parkinson's disease, type II diabetes, cancer, and even certain viral infections. However, despite significant advances in protein folding and solution biophysics techniques, determining the molecular cause of these conditions in humans has remained elusive. This has been due, in part, to recent discoveries showing that soluble protein oligomers, not insoluble fibrils or plaques, drive the majority of pathological processes. This has subsequently led researchers to focus instead on heterogeneous and often promiscuous protein oligomers. Unfortunately, significant gaps remain in how to prepare, model, experimentally corroborate, and extract amyloid oligomers relevant to human disease in a systematic manner. This Review will report on each of these techniques and their successes and shortcomings in an attempt to standardize comparisons between protein oligomers across disciplines, especially in the context of neurodegeneration. By standardizing multiple techniques and identifying their common overlap, a clearer picture of the soluble neuropathological aggresome can be constructed and used as a baseline for studying human disease and aging.
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Affiliation(s)
- Gregory-Neal Gomes
- Department of Pathology, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511, USA
| | - Zachary A. Levine
- Department of Pathology, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511, USA
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André C, Rehel S, Kuhn E, Landeau B, Moulinet I, Touron E, Ourry V, Le Du G, Mézenge F, Tomadesso C, de Flores R, Bejanin A, Sherif S, Delcroix N, Manrique A, Abbas A, Marchant NL, Lutz A, Klimecki OM, Collette F, Arenaza-Urquijo EM, Poisnel G, Vivien D, Bertran F, de la Sayette V, Chételat G, Rauchs G. Association of Sleep-Disordered Breathing With Alzheimer Disease Biomarkers in Community-Dwelling Older Adults: A Secondary Analysis of a Randomized Clinical Trial. JAMA Neurol 2021; 77:716-724. [PMID: 32202593 DOI: 10.1001/jamaneurol.2020.0311] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Importance Increasing evidence suggests that sleep-disordered breathing (SDB) increases the risk of developing Alzheimer clinical syndrome. However, the brain mechanisms underlying the link between SDB and Alzheimer disease are still unclear. Objective To determine which brain changes are associated with the presence of SDB in older individuals who are cognitively unimpaired, including changes in amyloid deposition, gray matter volume, perfusion, and glucose metabolism. Design, Setting, and Participants This cross-sectional study was conducted using data from the Age-Well randomized clinical trial of the Medit-Ageing European project, acquired between 2016 and 2018 at Cyceron Center in Caen, France. Community-dwelling older adults were assessed for eligibility and were enrolled in the Age-Well clinical trial if they did not meet medical or cognitive exclusion criteria and were willing to participate. Participants who completed a detailed neuropsychological assessment, polysomnography, a magnetic resonance imaging, and florbetapir and fluorodeoxyglucose positron emission tomography scans were included in the analyses. Main Outcomes and Measures Based on an apnea-hypopnea index cutoff of 15 events per hour, participants were classified as having SDB or not. Voxelwise between-group comparisons were performed for each neuroimaging modality, and secondary analyses aimed at identifying which SDB parameter (sleep fragmentation, hypoxia severity, or frequency of respiratory disturbances) best explained the observed brain changes and assessing whether SDB severity and/or SDB-associated brain changes are associated with cognitive and behavioral changes. Results Of 157 participants initially assessed, 137 were enrolled in the Age-Well clinical trial, and 127 were analyzed in this study. The mean (SD) age of the 127 participants was 69.1 (3.9) years, and 80 (63.0%) were women. Participants with SDB showed greater amyloid burden (t114 = 4.51; familywise error-corrected P = .04; Cohen d, 0.83), gray matter volume (t119 = 4.12; familywise error-corrected P = .04; Cohen d, 0.75), perfusion (t116 = 4.62; familywise error-corrected P = .001; Cohen d, 0.86), and metabolism (t79 = 4.63; familywise error-corrected P = .001; Cohen d, 1.04), overlapping mainly over the posterior cingulate cortex and precuneus. No association was found with cognition, self-reported cognitive and sleep difficulties, or excessive daytime sleepiness symptoms. Conclusions and Relevance The SDB-associated brain changes in older adults who are cognitively unimpaired include greater amyloid deposition and neuronal activity in Alzheimer disease-sensitive brain regions, notably the posterior cingulate cortex and precuneus. These results support the need to screen and treat for SDB, especially in asymptomatic older populations, to reduce Alzheimer disease risk. Trial Registration ClinicalTrials.gov Identifier: NCT02977819.
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Affiliation(s)
- Claire André
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France.,Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France
| | - Stéphane Rehel
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France.,Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France
| | - Elizabeth Kuhn
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Brigitte Landeau
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Inès Moulinet
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Edelweiss Touron
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Valentin Ourry
- Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France
| | - Gwendoline Le Du
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Florence Mézenge
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Clémence Tomadesso
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Robin de Flores
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Alexandre Bejanin
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Siya Sherif
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Nicolas Delcroix
- Centre National de la Recherche Scientifique, Unité Mixte de Service 3048, GIP Cyceron, Caen, France
| | - Alain Manrique
- Normandie Université, Université de Caen, EA 4650 "Signalisation, Électrophysiologie et Imagerie des Lésions d'Ischémie-Reperfusion Myocardique", GIP Cyceron, Caen, France
| | - Ahmed Abbas
- Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France
| | - Natalie L Marchant
- Division of Psychiatry, University College London, London, United Kingdom
| | - Antoine Lutz
- Lyon Neuroscience Research Center, Institut National de la Santé et de la Recherche Médicale Unité 1028, Centre National de la Recherche Scientifique Unité Mixte de Recherche 5292, Lyon University, Lyon, France
| | - Olga M Klimecki
- Swiss Center for Affective Sciences, Department of Medicine, University of Geneva, Geneva, Switzerland
| | - Fabienne Collette
- GIGA-Cyclotron Research Centre, In Vivo Imaging and Psychology and Cognitive Neuroscience Unit, Liège University, Liège, Belgium
| | - Eider M Arenaza-Urquijo
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Géraldine Poisnel
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Denis Vivien
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France.,Département de Recherche Clinique, Centre Hospitalier Universitaire de Caen-Normandie, Caen, France
| | - Françoise Bertran
- Unité d'Exploration et de Traitement des Troubles du Sommeil, Centre Hospitalier Universitaire de Caen, Caen, France
| | - Vincent de la Sayette
- Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France.,Service de Neurologie, Centre Hospitalier Universitaire de Caen, Caen, France
| | - Gaël Chételat
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237 "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Géraldine Rauchs
- Normandie Université, Université de Caen, Paris Sciences & Lettres Université, École Pratique des Hautes Études, Institut National de la Santé et de la Recherche Médicale, Unité 1077 "Neuropsychologie et Imagerie de la Mémoire Humaine," Centre Hospitalier Universitaire de Caen, GIP Cyceron, Caen, France
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Wu Z, Peng Y, Hong M, Zhang Y. Gray Matter Deterioration Pattern During Alzheimer's Disease Progression: A Regions-of-Interest Based Surface Morphometry Study. Front Aging Neurosci 2021; 13:593898. [PMID: 33613265 PMCID: PMC7886803 DOI: 10.3389/fnagi.2021.593898] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 01/13/2021] [Indexed: 11/17/2022] Open
Abstract
Accurate detection of the regions of Alzheimer's disease (AD) lesions is critical for early intervention to effectively slow down the progression of the disease. Although gray matter volumetric abnormalities are commonly detected in patients with mild cognition impairment (MCI) and patients with AD, the gray matter surface-based deterioration pattern associated with the progression of the disease from MCI to AD stages is largely unknown. To identify group differences in gray matter surface morphometry, including cortical thickness, the gyrification index (GI), and the sulcus depth, 80 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were split into healthy controls (HCs; N = 20), early MCIs (EMCI; N = 20), late MCIs (LMCI; N = 20), and ADs (N = 20). Regions-of-interest (ROI)-based surface morphometry was subsequently studied and compared across the four stage groups to characterize the gray matter deterioration during AD progression. Co-alteration patterns (Spearman's correlation coefficient) across the whole brain were also examined. Results showed that patients with MCI and AD exhibited a significant reduction in cortical thickness (p < 0.001) mainly in the cingulate region (four subregions) and in the temporal (thirteen subregions), parietal (five subregions), and frontal (six subregions) lobes compared to HCs. The sulcus depth of the eight temporal, four frontal, four occipital, and eight parietal subregions were also significantly affected (p < 0.001) by the progression of AD. The GI was shown to be insensitive to AD progression (only three subregions were detected with a significant difference, p < 0.001). Moreover, Spearman's correlation analysis confirmed that the co-alteration pattern of the cortical thickness and sulcus depth indices is predominant during AD progression. The findings highlight the relevance between gray matter surface morphometry and the stages of AD, laying the foundation for in vivo tracking of AD progression. The co-alteration pattern of surface-based morphometry would improve the researchers' knowledge of the underlying pathologic mechanisms in AD.
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Affiliation(s)
- Zhanxiong Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China.,Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Yun Peng
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Ming Hong
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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Harrison TM, Du R, Klencklen G, Baker SL, Jagust WJ. Distinct effects of beta-amyloid and tau on cortical thickness in cognitively healthy older adults. Alzheimers Dement 2020; 17:1085-1096. [PMID: 33325068 PMCID: PMC8203764 DOI: 10.1002/alz.12249] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 10/22/2020] [Accepted: 11/01/2020] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Published reports of associations between β-amyloid (Aβ) and cortical integrity conflict. Tau biomarkers may help elucidate the complex relationship between pathology and neurodegeneration in aging. METHODS We measured cortical thickness using magnetic resonance imaging, Aβ using Pittsburgh compound B positron emission tomography (PiB-PET), and tau using flortaucipir (FTP)-PET in 125 cognitively normal older adults. We examined relationships among PET measures, cortical thickness, and cognition. RESULTS Cortical thickness was reduced in PiB+/FTP+ participants compared to the PiB+/FTP- and PiB-/FTP- groups. Continuous PiB associations with cortical thickness were weak but positive in FTP- participants and negative in FTP+. FTP strongly negatively predicted thickness regardless of PiB status. FTP was associated with memory and cortical thickness, and mediated the association of PiB with memory. DISCUSSION Past findings linking Aβ and cortical thickness are likely weak due to opposing effects of Aβ on cortical thickness relative to tau burden. Tau, in contrast to Aβ, is strongly related to cortical thickness and memory.
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Affiliation(s)
- Theresa M Harrison
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, California, USA
| | - Richard Du
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, California, USA
| | - Giuliana Klencklen
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, California, USA
| | - Suzanne L Baker
- Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, California, USA.,Lawrence Berkeley National Laboratory, Berkeley, California, USA
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Ozzoude M, Ramirez J, Raamana PR, Holmes MF, Walker K, Scott CJM, Gao F, Goubran M, Kwan D, Tartaglia MC, Beaton D, Saposnik G, Hassan A, Lawrence-Dewar J, Dowlatshahi D, Strother SC, Symons S, Bartha R, Swartz RH, Black SE. Cortical Thickness Estimation in Individuals With Cerebral Small Vessel Disease, Focal Atrophy, and Chronic Stroke Lesions. Front Neurosci 2020; 14:598868. [PMID: 33381009 PMCID: PMC7768006 DOI: 10.3389/fnins.2020.598868] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/24/2020] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Regional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases (CVD) can be estimated using specialized neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures. PURPOSE The main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer's (FS's) cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and CVD, with varying degrees of neurovascular lesions and brain atrophy. METHODS In 155 CVD participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FS outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures. RESULTS Corrected procedures increased "Acceptable" QC ratings from 18 to 76% for the cortical ribbon and from 38 to 92% for tissue segmentation. Corrected procedures reduced "Fail" ratings from 11 to 0% for the cortical ribbon and 62 to 8% for tissue segmentation. FS-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8 mL vs. 15.9 mL, p < 0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p = 0.018) and left insula (p = 0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p < 0.001). CONCLUSION These findings suggest that correction procedures which account for brain atrophy and neurovascular lesions can significantly improve FS's segmentation results and reduce failure rates, thus maximizing power by preventing the loss of our important study participants. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and cognitive dysfunction due to neurodegenerative disease in the ONDRI study.
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Affiliation(s)
- Miracle Ozzoude
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | - Melissa F. Holmes
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Kirstin Walker
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J. M. Scott
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queens University, Kingston, ON, Canada
| | - Maria C. Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Gustavo Saposnik
- Stroke Outcomes and Decision Neuroscience Research Unit, Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | | | - Dariush Dowlatshahi
- Department of Medicine (Neurology), Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Richard H. Swartz
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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Sur C, Kost J, Scott D, Adamczuk K, Fox NC, Cummings JL, Tariot PN, Aisen PS, Vellas B, Voss T, Mahoney E, Mukai Y, Kennedy ME, Lines C, Michelson D, Egan MF. BACE inhibition causes rapid, regional, and non-progressive volume reduction in Alzheimer's disease brain. Brain 2020; 143:3816-3826. [PMID: 33253354 PMCID: PMC8453290 DOI: 10.1093/brain/awaa332] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 07/22/2020] [Accepted: 08/10/2020] [Indexed: 01/26/2023] Open
Abstract
In the phase 3 EPOCH trial (Clinicaltrials.gov; NCT01739348), treatment with the BACE inhibitor verubecestat failed to improve cognition in patients with mild-to-moderate Alzheimer's disease, but was associated with reduced hippocampal volume after 78 weeks as assessed by MRI. The aims of the present exploratory analyses were to: (i) characterize the effect of verubecestat on brain volume by evaluating the time course of volumetric MRI changes for a variety of brain regions; and (ii) understand the mechanism through which verubecestat might cause hippocampal (and other brain region) volume loss by assessing its relationship to measures of amyloid, neurodegeneration, and cognition. Participants were aged 55-85 years with probable Alzheimer's disease dementia and a Mini Mental State Examination score ≥15 and ≤26. MRIs were obtained at baseline and at Weeks 13, 26, 52 and 78 of treatment. MRIs were segmented using Freesurfer and analysed using a tensor-based morphometry method. PET amyloid data were obtained with 18F-flutemetamol (Vizamyl®) at baseline and Week 78. Standardized uptake value ratios were generated with subcortical white matter as a reference region. Neurofilament light chain in the CSF was assessed as a biomarker of neurodegeneration. Compared with placebo, verubecestat showed increased MRI brain volume loss at Week 13 with no evidence of additional loss through Week 78. The verubecestat-related volumetric MRI loss occurred predominantly in amyloid-rich brain regions. Correlations between amyloid burden at baseline and verubecestat-related volumetric MRI reductions were not significant (r = 0.05 to 0.26, P-values > 0.27). There were no significant differences between verubecestat and placebo in changes from baseline in CSF levels of neurofilament light chain at Week 78 (increases of 7.2 and 14.6 pg/ml for verubecestat versus 19.7 pg/ml for placebo, P-values ≥ 0.1). There was a moderate correlation between volumetric MRI changes and cognitive decline in all groups including placebo at Week 78 (e.g. r = -0.45 to -0.55, P < 0.001 for whole brain), but the correlations were smaller at Week 13 and significant only for the verubecestat groups (e.g. r = -0.15 and -0.11, P < 0.04 for whole brain). Our results suggest that the verubecestat-associated MRI brain volume loss is not due to generalized, progressive neurodegeneration, but may be mediated by specific effects on BACE-related amyloid processes.
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Affiliation(s)
| | - James Kost
- Merck and Co., Inc., Kenilworth, NJ, USA
| | | | | | - Nick C Fox
- Institute of Neurology and UK Dementia Research Institute, University College London, London, UK
| | - Jeffrey L Cummings
- University of Nevada Las Vegas (UNLV) School of Integrated Health Sciences, Las Vegas, NV, USA
- UNLV Department of Brain Health, Las Vegas, NV, USA
- UNLV, Chambers-Grundy Center for Transformative Neuroscience, Las Vegas, NV, USA
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Pierre N Tariot
- Banner Alzheimer’s Institute, University of Arizona College of Medicine, Phoenix, AZ, USA
| | - Paul S Aisen
- University of Southern California, San Diego, CA, USA
| | - Bruno Vellas
- Gerontopole, INSERM U 1027, Alzheimer’s Disease Research and Clinical Center, Toulouse University Hospital, Toulouse, France
| | | | | | - Yuki Mukai
- Merck and Co., Inc., Kenilworth, NJ, USA
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Chhatwal JP, Schultz AP, Dang Y, Ostaszewski B, Liu L, Yang HS, Johnson KA, Sperling RA, Selkoe DJ. Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals. Nat Commun 2020; 11:6024. [PMID: 33247134 PMCID: PMC7695712 DOI: 10.1038/s41467-020-19543-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 10/12/2020] [Indexed: 02/06/2023] Open
Abstract
The availability of blood-based assays detecting Alzheimer's disease (AD) pathology should greatly accelerate AD therapeutic development and improve clinical care. This is especially true for markers that capture the risk of decline in pre-symptomatic stages of AD, as this would allow one to focus interventions on participants maximally at risk and at a stage prior to widespread synapse loss and neurodegeneration. Here we quantify plasma concentrations of an N-terminal fragment of tau (NT1) in a large, well-characterized cohort of clinically normal elderly who were followed longitudinally. Plasma NT1 levels at study entry (when all participants were unimpaired) were highly predictive of future cognitive decline, pathological tau accumulation, neurodegeneration, and transition to a diagnosis of MCI/AD. These predictive effects were particularly strong in participants with even modestly elevated brain β-amyloid burden at study entry, suggesting plasma NT1 levels capture very early cognitive, pathologic and neurodegenerative changes along the AD trajectory.
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Affiliation(s)
- Jasmeer P Chhatwal
- Massachusetts General Hospital, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Aaron P Schultz
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yifan Dang
- Brigham and Women's Hospital, Boston, MA, USA
| | | | - Lei Liu
- Brigham and Women's Hospital, Boston, MA, USA
| | - Hyun-Sik Yang
- Massachusetts General Hospital, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Boston, MA, USA.
- Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
| | - Dennis J Selkoe
- Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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39
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Tristão Pereira C, Diao Y, Yin T, da Silva AR, Lanz B, Pierzchala K, Poitry-Yamate C, Jelescu IO. Synchronous nonmonotonic changes in functional connectivity and white matter integrity in a rat model of sporadic Alzheimer's disease. Neuroimage 2020; 225:117498. [PMID: 33164858 DOI: 10.1016/j.neuroimage.2020.117498] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 09/16/2020] [Accepted: 10/18/2020] [Indexed: 12/17/2022] Open
Abstract
Brain glucose hypometabolism has been singled out as an important contributor and possibly main trigger to Alzheimer's disease (AD). Intracerebroventricular injections of streptozotocin (icv-STZ) cause brain glucose hypometabolism without systemic diabetes. Here, a first-time longitudinal study of brain glucose metabolism, functional connectivity and white matter microstructure was performed in icv-STZ rats using PET and MRI. Histological markers of pathology were tested at an advanced stage of disease. STZ rats exhibited altered functional connectivity and intra-axonal damage and demyelination in brain regions typical of AD, in a temporal pattern of acute injury, transient recovery/compensation and chronic degeneration. In the context of sustained glucose hypometabolism, these nonmonotonic trends - also reported in behavioral studies of this animal model as well as in human AD - suggest a compensatory mechanism, possibly recruiting ketone bodies, that allows a partial and temporary repair of brain structure and function. The early acute phase could thus become a valuable therapeutic window to strengthen the recovery phase and prevent or delay chronic degeneration, to be considered both in preclinical and clinical studies of AD. In conclusion, this work reveals the consequences of brain insulin resistance on structure and function, highlights signature nonmonotonic trajectories in their evolution and proposes potent MRI-derived biomarkers translatable to human AD and diabetic populations.
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Affiliation(s)
- Catarina Tristão Pereira
- Centre d'Imagerie Biomédicale, EPFL, Station 6, Lausanne 1015, Switzerland; Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
| | - Yujian Diao
- Centre d'Imagerie Biomédicale, EPFL, Station 6, Lausanne 1015, Switzerland; Laboratoire d'Imagerie Fonctionnelle et Métabolique, EPFL, Lausanne, Switzerland
| | - Ting Yin
- Centre d'Imagerie Biomédicale, EPFL, Station 6, Lausanne 1015, Switzerland
| | - Analina R da Silva
- Centre d'Imagerie Biomédicale, EPFL, Station 6, Lausanne 1015, Switzerland
| | - Bernard Lanz
- Laboratoire d'Imagerie Fonctionnelle et Métabolique, EPFL, Lausanne, Switzerland
| | | | | | - Ileana O Jelescu
- Centre d'Imagerie Biomédicale, EPFL, Station 6, Lausanne 1015, Switzerland.
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40
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Li K, Wang S, Luo X, Zeng Q, Jiaerken Y, Xu X, Wang C, Liu X, Li Z, Zhao S, Zhang T, Fu Y, Chen Y, Liu Z, Zhou J, Huang P, Zhang M. Progressive Memory Circuit Impairments along with Alzheimer's Disease Neuropathology Spread: Evidence from in vivo Neuroimaging. Cereb Cortex 2020; 30:5863-5873. [PMID: 32537637 DOI: 10.1093/cercor/bhaa162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 05/04/2020] [Accepted: 05/21/2020] [Indexed: 01/04/2023] Open
Abstract
During the progression of Alzheimer's disease (AD), neuropathology may propagate transneuronally, cause disruption in memory circuit, and lead to memory impairment. However, there is a lack of in vivo evidence regarding this process. Thus, we aim to simulate and observe the progression of neuropathology in AD continuum. We included cognitively normal (CN), mild cognitive impairments (MCI), and AD subjects, and further classified them using the A/T/N scheme (Group 0: CN, A - T-; Group 1: CN, A + T-; Group 2: CN, A + T+; Group 3: MCI, A + T+; Group 4: AD, A + T+). We investigated alterations of three core memory circuit structures: hippocampus (HP) subfields volume, cingulum-angular bundles (CAB) fiber integrity, and precuneus cortex volume. HP subfields volume showed the trend of initially increased and then decreased (starting from Group 2), while precuneus volume decreased in Groups 3 and 4. The CAB integrity degenerated in Groups 3 and 4 and aggravated with higher disease stages. Further, memory circuit impairments were correlated with neuropathology biomarkers and memory performance. Conclusively, our results demonstrated a pattern of memory circuit impairments along with AD progression: starting from the HP, then propagating to the downstream projection fiber tract and cortex. These findings support the tau propagation theory to some extent.
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Affiliation(s)
- Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Chao Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Zheyu Li
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Shuai Zhao
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Tianyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yanv Fu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Zhirong Liu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Jiong Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
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Buckley RF, Scott MR, Jacobs HIL, Schultz AP, Properzi MJ, Amariglio RE, Hohman TJ, Mayblyum DV, Rubinstein ZB, Manning L, Hanseeuw BJ, Mormino EC, Rentz DM, Johnson KA, Sperling RA. Sex Mediates Relationships Between Regional Tau Pathology and Cognitive Decline. Ann Neurol 2020; 88:921-932. [PMID: 32799367 DOI: 10.1002/ana.25878] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 08/13/2020] [Accepted: 08/13/2020] [Indexed: 12/18/2022]
Abstract
OBJECTIVE The goal of this study was to examine sex differences in tau distribution across the brain of older adults, using positron emission tomography (PET), and investigate how these differences might associate with cognitive trajectories. METHODS Participants were 343 clinically normal individuals (women, 58%; 73.8 [8.5] years) and 55 individuals with mild cognitive impairment (MCI; women, 38%; 76.9 [7.3] years) from the Harvard Aging Brain Study and the Alzheimer's Disease Neuroimaging Initiative. We examined 18 F-Flortaucipir (FTP)-positron emission tomography (PET) signal across 41 cortical and subcortical regions of interest (ROIs). Linear regression models estimated the effect of sex on FTP-signal for each ROI after adjusting for age and cohort. We also examined interactions between sex*Aβ-PET positive / negative (+ / -) and sex*apolipoprotein ε4 (APOEε4) status. Linear mixed models estimated the moderating effect of sex on the relationship between a composite of sex-differentiated tau ROIs and cognitive decline. RESULTS Women showed significantly higher FTP-signals than men across multiple regions of the cortical mantle (p < 0.007). β-amyloid (Aβ)-moderated sex differences in tau signal were localized to medial and inferio-lateral temporal regions (p < 0.007); Aβ + women exhibited greater FTP-signal than other groups. APOEε4-moderated sex differences in FTP-signal were only found in the lateral occipital lobe. Women with higher FTP-signals in composite ROI exhibited faster cognitive decline than men (p = 0.04). INTERPRETATION Tau vulnerability in women is not just limited to the medial temporal lobe and significantly contributed to greater risk of faster cognitive decline. Interactive effects of sex and Aβ were predominantly localized in the temporal lobe, however, sex differences in extra-temporal tau highlights the possibility of accelerated tau proliferation in women with the onset of clinical symptomatology. ANN NEUROL 2020;88:921-932.
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Affiliation(s)
- Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Department of Neurology, Center for Alzheimer Research and Treatment, Boston, MA, USA.,Melbourne School of Psychological Science, University of Melbourne, Melbourne, VIC, Australia
| | - Matthew R Scott
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Heidi I L Jacobs
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael J Properzi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Department of Neurology, Center for Alzheimer Research and Treatment, Boston, MA, USA
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Danielle V Mayblyum
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Zoe B Rubinstein
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Lyssa Manning
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Bernard J Hanseeuw
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Department of Neurology, Cliniques Universitaires Saint-Luc, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | | | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Department of Neurology, Center for Alzheimer Research and Treatment, Boston, MA, USA
| | - Keith A Johnson
- Brigham and Women's Hospital, Department of Neurology, Center for Alzheimer Research and Treatment, Boston, MA, USA.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Department of Neurology, Center for Alzheimer Research and Treatment, Boston, MA, USA
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Xie L, Wisse LEM, Das SR, Vergnet N, Dong M, Ittyerah R, de Flores R, Yushkevich PA, Wolk DA. Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease. Hum Brain Mapp 2020; 41:4704-4717. [PMID: 32845545 PMCID: PMC7555086 DOI: 10.1002/hbm.25151] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/10/2020] [Accepted: 07/18/2020] [Indexed: 01/01/2023] Open
Abstract
A major focus of Alzheimer's disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1-weighted MRI of 337 participants were included, divided into amyloid-β negative (Aβ-) controls, cerebral spinal fluid p-tau positive (T+) and negative (T-) preclinical AD (Aβ+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2-year-follow-up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T- preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the cross-sectional MTL measures, longitudinal cognitive measures (PACC, ADAS-Cog) and cross-sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and thus are more directly linked to active disease progression than cross-sectional measurements. Moreover, accelerated atrophy in preclinical AD seems to occur only in the presence of concomitant tau pathology. The proposed longitudinal measurements may serve as efficient outcome measures in clinical trials.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicolas Vergnet
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mengjin Dong
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Wang H, Shen X, Li J, Suckling J, Tan C, Wang Y, Feng L, Zhang C, Tan L, Dong Q, Touchon J, Gauthier S, Yu J. Clinical and biomarker trajectories in sporadic Alzheimer's disease: A longitudinal study. Alzheimers Dement (Amst) 2020; 12:e12095. [PMID: 32793801 PMCID: PMC7421532 DOI: 10.1002/dad2.12095] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 07/22/2020] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Amyloid beta (Aβ) deposition was identified to precede tau pathology and neurodegeneration in familial Alzheimer's disease (AD). But the divergence between sporadic and familial AD limits the extension of these findings to sporadic AD. METHODS Longitudinal changes of biomarkers among different stages were assessed using linear mixed-effects models. The slopes of the models were used to estimate rates of change to calculate the biomarker trajectories in sporadic AD. RESULTS Cerebrospinal fluid (CSF) Aβ was estimated to decline 45.2 years (abnormal: 27.8 years) before dementia, and Aβ deposition seemed to increase 31.7 years (abnormal: 26.7 years) before dementia. It was estimated to take 29.0 years (CSF t-tau), 12.2 years (memory), 11.6 years (hippocampus), 9.3 years (hypometabolism), and 6.1 years (cognition) to move from normal to dementia. DISCUSSION The trajectory in sporadic AD is led by Aβ accumulation, followed by CSF t-tau increase, memory deficits, brain atrophy, hypometabolism, and cognitive decline.
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Affiliation(s)
- Hui‐Fu Wang
- Department of NeurologyQingdao Municipal HospitalQingdao UniversityQingdaoChina
| | - Xue‐Ning Shen
- Department of Neurology and Institute of NeurologyHuashan HospitalShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Jie‐Qiong Li
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdaoChina
| | - John Suckling
- Department of PsychiatryUniversity of CambridgeCambridgeUK
- Medical Research Council and Wellcome Trust Behavioural and Clinical Neuroscience InstituteUniversity of CambridgeCambridge, UK; Cambridgeshire and Peterborough NHS TrustUK
| | - Chen‐Chen Tan
- Department of NeurologyQingdao Municipal HospitalQingdao UniversityQingdaoChina
| | - Yan‐Jiang Wang
- Department of NeurologyDaping HospitalThird Military Medical UniversityChongqingChina
| | - Lei Feng
- Department of Psychological MedicineYong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
| | - Can Zhang
- Genetics and Aging Research UnitMcCance Center for Brain HealthMassGeneral Institute for Neurodegenerative Diseases (MIND)Department of NeurologyMassachusetts General Hospital and Harvard Medical SchoolCharlestownMassachusettsUSA
| | - Lan Tan
- Department of NeurologyQingdao Municipal HospitalQingdao UniversityQingdaoChina
| | - Qiang Dong
- Department of Neurology and Institute of NeurologyHuashan HospitalShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Jacques Touchon
- Memory Research and Resource Center for Alzheimer's DiseaseDepartment of NeurologyUniversity Hospital of MontpellierUniversity of MontpellierMontpellierFrance
| | - Serge Gauthier
- McGill Center for Studies in AgingMcGill UniversityMontrealCanada
| | - Jin‐Tai Yu
- Department of Neurology and Institute of NeurologyHuashan HospitalShanghai Medical CollegeFudan UniversityShanghaiChina
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Abstract
Patients with Alzheimer's disease (AD) present with both extracellular amyloid-β (Aβ) plaques and intracellular tau-containing neurofibrillary tangles in the brain. For many years, the prevailing view of AD pathogenesis has been that changes in Aβ precipitate the disease process and initiate a deleterious cascade involving tau pathology and neurodegeneration. Beyond this 'triggering' function, it has been typically presumed that Aβ and tau act independently and in the absence of specific interaction. However, accumulating evidence now suggests otherwise and contends that both pathologies have synergistic effects. This could not only help explain negative results from anti-Aβ clinical trials but also suggest that trials directed solely at tau may need to be reconsidered. Here, drawing from extensive human and disease model data, we highlight the latest evidence base pertaining to the complex Aβ-tau interaction and underscore its crucial importance to elucidating disease pathogenesis and the design of next-generation AD therapeutic trials.
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Affiliation(s)
- Marc Aurel Busche
- UK Dementia Research Institute at UCL, University College London, London, UK.
| | - Bradley T Hyman
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Boston, USA
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Pegueroles J, Pané A, Vilaplana E, Montal V, Bejanin A, Videla L, Carmona‐Iragui M, Barroeta I, Ibarzabal A, Casajoana A, Alcolea D, Valldeneu S, Altuna M, de Hollanda A, Vidal J, Ortega E, Osorio R, Convit A, Blesa R, Lleó A, Fortea J, Jiménez A. Obesity impacts brain metabolism and structure independently of amyloid and tau pathology in healthy elderly. Alzheimers Dement (Amst) 2020; 12:e12052. [PMID: 32743041 PMCID: PMC7385480 DOI: 10.1002/dad2.12052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/22/2020] [Accepted: 05/26/2020] [Indexed: 12/16/2022]
Abstract
AIMS/HYPOTHESIS Midlife obesity is a risk factor for dementia. We investigated the impact of obesity on brain structure, metabolism, and cerebrospinal fluid (CSF) core Alzheimer's disease (AD) biomarkers in healthy elderly. METHODS We selected controls from ADNI2 with CSF AD biomarkers and/or fluorodeoxyglucose positron emission tomography (FDG-PET) and 3T-MRI. We measured cortical thickness, FDG uptake, and CSF amyloid beta (Aβ)1-42, p-tau, and t-tau levels. We performed regression analyses between these biomarkers and body mass index (BMI). RESULTS We included 201 individuals (mean age 73.5 years, mean BMI 27.4 kg/m2). Higher BMI was related to less cortical thickness and higher metabolism in brain areas typically not involved in AD (family-wise error [FWE] <0.05), but not to AD CSF biomarkers. It is notable that the impact of obesity on brain metabolism and structure was also found in amyloid negative individuals. CONCLUSIONS/INTERPRETATION In the cognitively unimpaired elderly, obesity has differential effects on brain metabolism and structure independent of an underlying AD pathophysiology.
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Affiliation(s)
- Jordi Pegueroles
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Adriana Pané
- Obesity Unit, Endocrinology and Diabetes DepartmentHospital Clinic Universitari de BarcelonaBarcelonaSpain
| | - Eduard Vilaplana
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Víctor Montal
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alexandre Bejanin
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Laura Videla
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - María Carmona‐Iragui
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Isabel Barroeta
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Ainitze Ibarzabal
- Obesity Unit, Gastrointestinal Surgery DepartmentHospital Clínic de BarcelonaBarcelonaSpain
| | - Anna Casajoana
- Department of Bariatric SurgeryBellvitge University HospitalBarcelonaSpain
| | - Daniel Alcolea
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Silvia Valldeneu
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Miren Altuna
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Ana de Hollanda
- Obesity Unit, Endocrinology and Diabetes DepartmentHospital Clinic Universitari de BarcelonaBarcelonaSpain
- Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)BarcelonaSpain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN)MadridSpain
| | - Josep Vidal
- Obesity Unit, Endocrinology and Diabetes DepartmentHospital Clinic Universitari de BarcelonaBarcelonaSpain
- Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)MadridSpain
| | - Emilio Ortega
- Obesity Unit, Endocrinology and Diabetes DepartmentHospital Clinic Universitari de BarcelonaBarcelonaSpain
- Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)BarcelonaSpain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN)MadridSpain
| | - Ricardo Osorio
- Brain, Obesity, and Diabetes Laboratory (BODyLab)New York University School of MedicineNew YorkUSA
| | - Antonio Convit
- Brain, Obesity, and Diabetes Laboratory (BODyLab)New York University School of MedicineNew YorkUSA
| | - Rafael Blesa
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alberto Lleó
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Juan Fortea
- Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Amanda Jiménez
- Obesity Unit, Endocrinology and Diabetes DepartmentHospital Clinic Universitari de BarcelonaBarcelonaSpain
- Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)BarcelonaSpain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN)MadridSpain
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Popescu SG, Whittington A, Gunn RN, Matthews PM, Glocker B, Sharp DJ, Cole JH. Nonlinear biomarker interactions in conversion from mild cognitive impairment to Alzheimer's disease. Hum Brain Mapp 2020; 41:4406-4418. [PMID: 32643852 PMCID: PMC7502835 DOI: 10.1002/hbm.25133] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 06/11/2020] [Accepted: 06/25/2020] [Indexed: 12/20/2022] Open
Abstract
Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid‐β42, total tau, phosphorylated tau), [18F]florbetapir, hippocampal volume and brain‐age. We examined: (a) the independent value of each biomarker; and (b) whether modelling nonlinear interactions between biomarkers improved predictions. Each measured added complementary information when predicting conversion to Alzheimer's. A linear model classifying stable from progressive MCI explained over half the variance (R2 = 0.51, p < .001); the strongest independently contributing biomarker was hippocampal volume (R2 = 0.13). When comparing sensitivity of different models to progressive MCI (independent biomarker models, additive models, nonlinear interaction models), we observed a significant improvement (p < .001) for various two‐way interaction models. The best performing model included an interaction between amyloid‐β‐PET and P‐tau, while accounting for hippocampal volume (sensitivity = 0.77, AUC = 0.826). Closely related biomarkers contributed uniquely to predict conversion to Alzheimer's. Nonlinear biomarker interactions were also implicated, and results showed that although for some patients adding additional biomarkers may add little value (i.e., when hippocampal volume is high), for others (i.e., with low hippocampal volume) further invasive and expensive examination may be warranted. Our framework enables visualisation of these interactions, in individual patient biomarker ‘space', providing information for personalised or stratified healthcare or clinical trial design.
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Affiliation(s)
- Sebastian G Popescu
- Computational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.,Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
| | - Alex Whittington
- Computational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.,Invicro Ltd, London, UK
| | - Roger N Gunn
- Invicro Ltd, London, UK.,Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, UK.,Department of Brain Sciences, Imperial College London, London, UK
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, UK.,Care Research & Technology Centre, UK Dementia Research Institute, London, UK
| | - Ben Glocker
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
| | - David J Sharp
- Computational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.,Care Research & Technology Centre, UK Dementia Research Institute, London, UK
| | - James H Cole
- Computational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.,Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Centre for Medical Imaging Computing, Computer Science, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
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Dong JW, Jelescu IO, Ades-Aron B, Novikov DS, Friedman K, Babb JS, Osorio RS, Galvin JE, Shepherd TM, Fieremans E. Diffusion MRI biomarkers of white matter microstructure vary nonmonotonically with increasing cerebral amyloid deposition. Neurobiol Aging 2020; 89:118-128. [PMID: 32111392 PMCID: PMC7314576 DOI: 10.1016/j.neurobiolaging.2020.01.009] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 12/14/2019] [Accepted: 01/14/2020] [Indexed: 01/27/2023]
Abstract
Beta amyloid (Aβ) accumulation is the earliest pathological marker of Alzheimer's disease (AD), but early AD pathology also affects white matter (WM) integrity. We performed a cross-sectional study including 44 subjects (23 healthy controls and 21 mild cognitive impairment or early AD patients) who underwent simultaneous PET-MR using 18F-Florbetapir, and were categorized into 3 groups based on Aβ burden: Aβ- [mean mSUVr ≤1.00], Aβi [1.00 < mSUVr <1.17], Aβ+ [mSUVr ≥1.17]. Intergroup comparisons of diffusion MRI metrics revealed significant differences across multiple WM tracts. Aβi group displayed more restricted diffusion (higher fractional anisotropy, radial kurtosis, axonal water fraction, and lower radial diffusivity) than both Aβ- and Aβ+ groups. This nonmonotonic trend was confirmed by significant continuous correlations between mSUVr and diffusion metrics going in opposite direction for 2 cohorts: pooled Aβ-/Aβi and pooled Aβi/Aβ+. The transient period of increased diffusion restriction may be due to inflammation that accompanies rising Aβ burden. In the later stages of Aβ accumulation, neurodegeneration is the predominant factor affecting diffusion.
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Affiliation(s)
- Jian W Dong
- Department of Radiology, New York University School of Medicine, New York, NY, USA; Department of Radiology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ileana O Jelescu
- Department of Radiology, New York University School of Medicine, New York, NY, USA; Centre d'Imagerie Biomédicale, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Benjamin Ades-Aron
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Dmitry S Novikov
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Kent Friedman
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - James S Babb
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Ricardo S Osorio
- Center for Sleep and Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - James E Galvin
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Boca-Raton, FL, USA
| | - Timothy M Shepherd
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Els Fieremans
- Department of Radiology, New York University School of Medicine, New York, NY, USA.
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Parker TD, Cash DM, Lane CA, Lu K, Malone IB, Nicholas JM, James S, Keshavan A, Murray‐Smith H, Wong A, Buchanan SM, Keuss SE, Sudre CH, Thomas DL, Crutch SJ, Fox NC, Richards M, Schott JM. Amyloid β influences the relationship between cortical thickness and vascular load. Alzheimers Dement (Amst) 2020; 12:e12022. [PMID: 32313829 PMCID: PMC7163924 DOI: 10.1002/dad2.12022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/30/2019] [Accepted: 01/02/2020] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear. METHODS We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness. RESULTS Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region. DISCUSSION WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms.
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Affiliation(s)
- Thomas D. Parker
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - David M. Cash
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Christopher A. Lane
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Kirsty Lu
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Ian B. Malone
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Jennifer M. Nicholas
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- Department of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUK
| | | | - Ashvini Keshavan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Heidi Murray‐Smith
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCLLondonUK
| | - Sarah M. Buchanan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Sarah E. Keuss
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Carole H. Sudre
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringUCLLondonUK
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Queen Square Institute of NeurologyUCLLondonUK
- Neuroradiological Academic Unit, Department of Brain Repair and RehabilitationUCL Queen Square Institute of NeurologyLondonUK
| | - Sebastian J. Crutch
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Nick C. Fox
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | | | - Jonathan M. Schott
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
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Vilaplana E, Rodriguez-Vieitez E, Ferreira D, Montal V, Almkvist O, Wall A, Lleó A, Westman E, Graff C, Fortea J, Nordberg A. Cortical microstructural correlates of astrocytosis in autosomal-dominant Alzheimer disease. Neurology 2020; 94:e2026-e2036. [PMID: 32291295 PMCID: PMC7282881 DOI: 10.1212/wnl.0000000000009405] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 11/18/2019] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE To study the macrostructural and microstructural MRI correlates of brain astrocytosis, measured with 11C-deuterium-L-deprenyl (11C-DED)-PET, in familial autosomal-dominant Alzheimer disease (ADAD). METHODS The total sample (n = 31) comprised ADAD mutation carriers (n = 10 presymptomatic, 39.2 ± 10.6 years old; n = 3 symptomatic, 55.5 ± 2.0 years old) and noncarriers (n = 18, 44.0 ± 13.7 years old) belonging to families with mutations in either the presenilin-1 or amyloid precursor protein genes. All participants underwent structural and diffusion MRI and neuropsychological assessment, and 20 participants (6 presymptomatic and 3 symptomatic mutation carriers and 11 noncarriers) also underwent 11C-DED-PET. RESULTS Vertex-wise interaction analyses revealed a differential relationship between carriers and noncarriers in the association between 11C-DED binding and estimated years to onset (EYO) and between cortical mean diffusivity (MD) and EYO. These differences were due to higher 11C-DED binding in presymptomatic carriers, with lower binding in symptomatic carriers compared to noncarriers, and to lower cortical MD in presymptomatic carriers, with higher MD in symptomatic carriers compared to noncarriers. Using a vertex-wise local correlation approach, 11C-DED binding was negatively correlated with cortical MD and positively correlated with cortical thickness. CONCLUSIONS Our proof-of-concept study is the first to show that microstructural and macrostructural changes can reflect underlying neuroinflammatory mechanisms in early stages of Alzheimer disease (AD). The findings support a role for neuroinflammation in AD pathogenesis, with potential implications for the correct interpretation of neuroimaging biomarkers as surrogate endpoints in clinical trials.
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Affiliation(s)
- Eduard Vilaplana
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Elena Rodriguez-Vieitez
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Daniel Ferreira
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Victor Montal
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Ove Almkvist
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Anders Wall
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Alberto Lleó
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Eric Westman
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Caroline Graff
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Juan Fortea
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Agneta Nordberg
- From the Memory Unit, Department of Neurology (E.V., V.M., A.L., J.F.), Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED (E.V., V.M., A.L., J.F.), Madrid, Spain; Department of Neurobiology (E.R.-V., D.F., O.A., E.W., A.N.), Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, and Division of Neurogeriatrics (C.G.), Karolinska Institutet, Stockholm Department of Psychology (O.A.), Stockholm University; The Aging Brain Unit (O.A., A.N.) and Unit for Hereditary Dementias (C.G.), Theme Aging, Karolinska University Hospital, Stockholm; Department of Surgical Sciences, Section of Nuclear Medicine & PET (A.W.), Uppsala University, Sweden; and Department of Neuroimaging (E.W.), Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
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Lewandowski CT, Maldonado Weng J, LaDu MJ. Alzheimer's disease pathology in APOE transgenic mouse models: The Who, What, When, Where, Why, and How. Neurobiol Dis 2020; 139:104811. [PMID: 32087290 DOI: 10.1016/j.nbd.2020.104811] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/01/2020] [Accepted: 02/18/2020] [Indexed: 02/07/2023] Open
Abstract
The focus on amyloid plaques and neurofibrillary tangles has yielded no Alzheimer's disease (AD) modifying treatments in the past several decades, despite successful studies in preclinical mouse models. This inconsistency has caused a renewed focus on improving the fidelity and reliability of AD mouse models, with disparate views on how this improvement can be accomplished. However, the interactive effects of the universal biological variables of AD, which include age, APOE genotype, and sex, are often overlooked. Age is the greatest risk factor for AD, while the ε4 allele of the human APOE gene, encoding apolipoprotein E, is the greatest genetic risk factor. Sex is the final universal biological variable of AD, as females develop AD at almost twice the rate of males and, importantly, female sex exacerbates the effects of APOE4 on AD risk and rate of cognitive decline. Therefore, this review evaluates the importance of context for understanding the role of APOE in preclinical mouse models. Specifically, we detail how human AD pathology is mirrored in current transgenic mouse models ("What") and describe the critical need for introducing human APOE into these mouse models ("Who"). We next outline different methods for introducing human APOE into mice ("How") and highlight efforts to develop temporally defined and location-specific human apoE expression models ("When" and "Where"). We conclude with the importance of choosing the human APOE mouse model relevant to the question being addressed, using the selection of transgenic models for testing apoE-targeted therapeutics as an example ("Why").
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Affiliation(s)
- Cutler T Lewandowski
- Department of Pharmaceutical Sciences, University of Illinois at Chicago, 833 S. Wood St., Chicago, IL 60612, USA.
| | - Juan Maldonado Weng
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, 808 S. Wood St., Chicago, IL 60612, USA.
| | - Mary Jo LaDu
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, 808 S. Wood St., Chicago, IL 60612, USA.
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