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Wu S, Chen J. Is age-related myelinodegenerative change an initial risk factor of neurodegenerative diseases? Neural Regen Res 2026; 21:648-658. [PMID: 40326982 DOI: 10.4103/nrr.nrr-d-24-00848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 11/25/2024] [Indexed: 05/07/2025] Open
Abstract
Myelination, the continuous ensheathment of neuronal axons, is a lifelong process in the nervous system that is essential for the precise, temporospatial conduction of action potentials between neurons. Myelin also provides intercellular metabolic support to axons. Even minor disruptions in the integrity of myelin can impair neural performance and increase susceptibility to neurological diseases. In fact, myelin degeneration is a well-known neuropathological condition that is associated with normal aging and several neurodegenerative diseases, including multiple sclerosis and Alzheimer's disease. In the central nervous system, compact myelin sheaths are formed by fully mature oligodendrocytes. However, the entire oligodendrocyte lineage is susceptible to changes in the biological microenvironment and other risk factors that arise as the brain ages. In addition to their well-known role in action potential propagation, oligodendrocytes also provide intercellular metabolic support to axons by transferring energy metabolites and delivering exosomes. Therefore, myelin degeneration in the aging central nervous system is a significant contributor to the development of neurodegenerative diseases. Interventions that mitigate age-related myelin degeneration can improve neurological function in aging individuals. In this review, we investigate the changes in myelin that are associated with aging and their underlying mechanisms. We also discuss recent advances in understanding how myelin degeneration in the aging brain contributes to neurodegenerative diseases and explore the factors that can prevent, slow down, or even reverse age-related myelin degeneration. Future research will enhance our understanding of how reducing age-related myelin degeneration can be used as a therapeutic target for delaying or preventing neurodegenerative diseases.
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Affiliation(s)
- Shuangchan Wu
- Sanhang Institute for Brain Science and Technology (SiBST), School of Medical Research, Northwestern Polytechnical University, Xi'an, Shaanxi Province, China
- Shenzhen Research Institute of Northwestern Polytechnical University, Shenzhen, Guangdong Province, China
| | - Jun Chen
- Sanhang Institute for Brain Science and Technology (SiBST), School of Medical Research, Northwestern Polytechnical University, Xi'an, Shaanxi Province, China
- Institute for Biomedical Sciences of Pain, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi Province, China
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2
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Tremblay SA, Nathan Spreng R, Wearn A, Alasmar Z, Pirhadi A, Tardif CL, Chakravarty MM, Villeneuve S, Leppert IR, Carbonell F, Medina YI, Steele CJ, Gauthier CJ. Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer's disease. Neurobiol Aging 2025; 150:80-96. [PMID: 40086421 DOI: 10.1016/j.neurobiolaging.2025.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 02/11/2025] [Accepted: 03/02/2025] [Indexed: 03/16/2025]
Abstract
Early detection of pathological changes in Alzheimer's disease (AD) has garnered significant attention in the last few decades as interventions aiming to prevent progression will likely be most effective when initiated early. White matter (WM) alterations are among the earliest changes in AD, yet limited work has comprehensively characterized the effects of AD risk factors on WM. In older adults with a family history of AD, we investigated the sex-specific and APOE genotype-related relationships between WM microstructure and risk factors. Multiple MRI-derived metrics were integrated using a multivariate approach based on the Mahalanobis distance (D2). To uncover the specific biological underpinnings of these WM alterations, we then extracted the contribution of each MRI feature to D2 in significant clusters. Lastly, the links between WM D2 and cognition were explored. WM D2 in several regions was associated with high systolic blood pressure, BMI, and glycated hemoglobin, and low cholesterol, in both males and females. APOE4 + displayed a distinct risk pattern, with LDL-cholesterol having a detrimental effect only in carriers, and this pattern was linked to immediate memory performance. Myelination was the main mechanism underlying WM alterations. Our findings reveal that combined exposure to multiple cardiometabolic risk factors negatively impacts microstructural health, which may subsequently affect cognition. Notably, APOE4 carriers exhibited a different risk pattern, especially in the role of LDL, suggesting distinct underlying mechanisms in this group.
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Affiliation(s)
- Stefanie A Tremblay
- Physics department, Concordia University, 7141 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada; Montreal Heart Institute, 5000 Rue Bélanger, Montréal, QC H1T 1C8, Canada; School of Health, Concordia University, 7200 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada.
| | - R Nathan Spreng
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; Department of Psychiatry, McGill University, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; StoP-AD Centre, Douglas Mental Health Institute Research Centre, 6875 Blvd. LaSalle, Verdun, QC H4H 1R3, Canada
| | - Alfie Wearn
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada
| | - Zaki Alasmar
- School of Health, Concordia University, 7200 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada; Psychology department, Concordia University, 7141 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada
| | - Amir Pirhadi
- Electrical Engineering department, Concordia University, 1455 De Maisonneuve Blvd. W, Montreal, QC H3G 1M8, Canada; ViTAA Medical Solutions, 400 Rue Montfort, Montréal, QC H3C 4J9, Canada
| | - Christine L Tardif
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; Department of Biomedical Engineering, McGill University, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada
| | - Mallar M Chakravarty
- Department of Psychiatry, McGill University, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; Department of Biomedical Engineering, McGill University, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; StoP-AD Centre, Douglas Mental Health Institute Research Centre, 6875 Blvd. LaSalle, Verdun, QC H4H 1R3, Canada
| | - Sylvia Villeneuve
- Department of Psychiatry, McGill University, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; StoP-AD Centre, Douglas Mental Health Institute Research Centre, 6875 Blvd. LaSalle, Verdun, QC H4H 1R3, Canada
| | - Ilana R Leppert
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada
| | | | - Yasser Iturria Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, 845 Rue Sherbrooke W, Montréal, QC H3A 0G4, Canada; Ludmer Center for NeuroInformatics and Mental Health, 1010 rue Sherbrooke W, Montreal, Canada
| | - Christopher J Steele
- School of Health, Concordia University, 7200 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada; Psychology department, Concordia University, 7141 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada; Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, Leipzig 04103, Germany
| | - Claudine J Gauthier
- Physics department, Concordia University, 7141 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada; Montreal Heart Institute, 5000 Rue Bélanger, Montréal, QC H1T 1C8, Canada; School of Health, Concordia University, 7200 Rue Sherbrooke W, Montréal, QC H4B 1R6, Canada.
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3
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Li Z, Martens YA, Ren Y, Jin Y, Sekiya H, Doss SV, Kouri N, Castanedes-Casey M, Christensen TA, Miller Nevalainen LB, Takegami N, Chen K, Liu CC, Soto-Beasley A, Boon BDC, Labuzan SA, Ikezu TC, Chen Y, Bartkowiak AD, Xhafkollari G, Wetmore AM, Bennett DA, Reichard RR, Petersen RC, Kanekiyo T, Ross OA, Murray ME, Dickson DW, Bu G, Zhao N. APOE genotype determines cell-type-specific pathological landscape of Alzheimer's disease. Neuron 2025; 113:1380-1397.e7. [PMID: 40112813 DOI: 10.1016/j.neuron.2025.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 11/21/2024] [Accepted: 02/18/2025] [Indexed: 03/22/2025]
Abstract
The apolipoprotein E (APOE) gene is the strongest genetic risk modifier for Alzheimer's disease (AD), with the APOE4 allele increasing risk and APOE2 decreasing it compared with the common APOE3 allele. Using single-nucleus RNA sequencing of the temporal cortex from APOE2 carriers, APOE3 homozygotes, and APOE4 carriers, we found that AD-associated transcriptomic changes were highly APOE genotype dependent. Comparing AD with controls, APOE2 carriers showed upregulated synaptic and myelination-related pathways, preserving synapses and myelination at the protein level. Conversely, these pathways were downregulated in APOE3 homozygotes, resulting in reduced synaptic and myelination proteins. In APOE4 carriers, excitatory neurons displayed reduced synaptic pathways similar to APOE3, but oligodendrocytes showed upregulated myelination pathways like APOE2. However, their synaptic and myelination protein levels remained unchanged or increased. APOE4 carriers also showed increased pro-inflammatory signatures in microglia but reduced responses to amyloid-β pathology. These findings reveal APOE genotype-specific molecular alterations in AD across cell types.
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Affiliation(s)
- Zonghua Li
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Yuka A Martens
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Yingxue Ren
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Yunjung Jin
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Hiroaki Sekiya
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Sydney V Doss
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | | | | | - Nanaka Takegami
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Kai Chen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Chia-Chen Liu
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - Baayla D C Boon
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Sydney A Labuzan
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Tadafumi C Ikezu
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Yixing Chen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | | | - Allison M Wetmore
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Ross R Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Takahisa Kanekiyo
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA.
| | - Na Zhao
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA.
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4
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Du L, Planalp EM, Betthauser TJ, Jonaitis EM, Hermann BP, Rivera-Rivera LA, Cody KA, Chin NA, Cadman RV, Johnson KM, Field A, Rowley HA, Mueller KD, Asthana S, Eisenmenger L, Christian BT, Johnson SC, Langhough RE. Onset ages of cerebrovascular disease and amyloid and effects on cognition in risk-enriched cohorts. Brain Commun 2025; 7:fcaf158. [PMID: 40337464 PMCID: PMC12056727 DOI: 10.1093/braincomms/fcaf158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 03/20/2025] [Accepted: 04/18/2025] [Indexed: 05/09/2025] Open
Abstract
The temporal relationship between cerebrovascular disease (V), indicated by white matter hyperintensities, and beta-amyloid (A) in Alzheimer's disease remains unclear, prompting speculation about their potential interdependence. Longitudinal data were employed to estimate onset ages and corresponding disease chronicity for A and V (where disease chronicity is calculated as age at measurement minus estimated age of biomarker abnormality onset). In a large, predominantly cognitively unimpaired dataset (n = 877, ages 43-93 years), a V+ threshold was identified, and Sampled Iterative Local Approximation (SILA) was utilized to illustrate the predictable accumulation trajectory of V post-onset. Investigating the temporal association between A and V onset ages and accumulation trajectories in preclinical years, four operationalizations of time were examined across two initially cognitively unimpaired samples (n = 240 primary sample from Wisconsin Registry for Alzheimer's Prevention; n = 123 replication sample from Wisconsin Alzheimer's Disease Research Center): (i) chronological age, (ii) estimated V+ chronicity, (iii) years since baseline scan, and (iv) estimated A+ chronicity. Results indicated that while both diseases are age-related, their onsets and trajectories are independent of each other. In addition, results indicated that V and A accumulation trajectories were highly predictable relative to onset of positivity for each biomarker. Cognitive decline across multiple cognitive domains was fastest when both V and A were present based on last available amyloid PET and MRI scan, with greater A chronicity being a more salient predictor of cognitive decline in these samples.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Elizabeth M Planalp
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Tobey J Betthauser
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo A Rivera-Rivera
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly A Cody
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA 94304, USA
| | - Nathaniel A Chin
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Robert V Cadman
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Howard A Rowley
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Kimberly D Mueller
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Sanjay Asthana
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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Ziar R, Tesar PJ, Clayton BLL. Astrocyte and oligodendrocyte pathology in Alzheimer's disease. Neurotherapeutics 2025; 22:e00540. [PMID: 39939240 PMCID: PMC12047399 DOI: 10.1016/j.neurot.2025.e00540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Revised: 01/10/2025] [Accepted: 01/24/2025] [Indexed: 02/14/2025] Open
Abstract
Astrocytes and oligodendrocytes, once considered passive support cells, are now recognized as active participants in the pathogenesis of Alzheimer's disease. Emerging evidence highlights the critical role that these glial cells play in the pathological features of Alzheimer's, including neuroinflammation, excitotoxicity, synaptic dysfunction, and myelin degeneration, which contribute to neurodegeneration and cognitive decline. Here, we review the current understanding of astrocyte and oligodendrocyte pathology in Alzheimer's disease and highlight research that supports the therapeutic potential of modulating astrocyte and oligodendrocyte functions to treat Alzheimer's disease.
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Affiliation(s)
- Rania Ziar
- Institute for Glial Sciences, Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Paul J Tesar
- Institute for Glial Sciences, Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
| | - Benjamin L L Clayton
- Institute for Glial Sciences, Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
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Peterson AJ, Sun Y, Archer DB, Adegboye HA, Moore EE, Deberghes I, Pechman KR, Shashikumar N, Robb WH, Workmeister AW, Jackson TB, Liu D, Dumitrescu L, Davis LT, Landman BA, Blennow K, Zetterberg H, Hohman TJ, Jefferson AL. Cerebrospinal fluid YKL-40 relates to white matter hyperintensity progression in females but not males over a 6-year period. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2025; 17:e70110. [PMID: 40352684 PMCID: PMC12064334 DOI: 10.1002/dad2.70110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 03/19/2025] [Accepted: 03/20/2025] [Indexed: 05/14/2025]
Abstract
INTRODUCTION Neuroinflammation may have sex-specific effects on white matter injury and impact the development of dementia. METHODS Human chitinase-3-like protein-1 (YKL-40) concentrations at baseline were related to white matter hyperintensity (WMH) volume, free water (FW), and FW-corrected fractional anisotropy using linear effects models (for cross-sectional outcomes) and linear mixed-effects models (for longitudinal outcomes), adjusting for demographic and medical risk factors. Models were repeated with a sex-interaction term and then stratified by sex. RESULTS In stratified analyses, greater baseline YKL-40 concentrations were associated with increased WMHs in females but not males in the parietal (females p = 0.04; males p = .34) and temporal lobes (females p = 0.005; males = p = 0.71) longitudinally. YKL-40 associations with FW and FW-corrected fractional anisotropy were null. DISCUSSION Results suggest that neuroinflammation is a sex-specific driver of WMHs (but not FW) in females. Differential sequelae of neuroinflammation may be one reason that females have a greater burden of WMHs. Highlights ·Cerebrospinal fluid YKL-40 is associated with white matter hyperintensities in females but not males cross-sectionally and longitudinally.·Longitudinally, cerebrospinal fluid YKL-40 is associated with white matter hyperintensities in the parietal and temporal lobes, regions that exhibit early pathological changes in Alzheimer's disease .·Cerebrospinal fluid YKL-40 is not associated with white matter microstructural measures.
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Affiliation(s)
- Amalia J. Peterson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Yunyi Sun
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Hailey A. Adegboye
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Elizabeth E. Moore
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyMass General BrighamBostonMassachusettsUSA
| | - Isabella Deberghes
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - W. Hudson Robb
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Abigail W. Workmeister
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - T. Bryan Jackson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Dandan Liu
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - L. Taylor Davis
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Bennett A. Landman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Electrical Engineering and Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LabSahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LabSahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public Health, University of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
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7
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Li Y, Tian T, Qin Y, Zhang S, Liu C, Zhu W. White matter injuries mediate brain age effects on cognitive function in cerebral small vessel disease. Neuroradiology 2025; 67:613-622. [PMID: 39960532 PMCID: PMC12003548 DOI: 10.1007/s00234-025-03568-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Accepted: 02/09/2025] [Indexed: 04/17/2025]
Abstract
PURPOSE This study aims to investigate the potential effect of compromised structural integrity on cerebral aging and cognitive function in cerebral small vessel disease (CSVD). METHODS Fifty-five CSVD patients and 42 controls underwent three-dimensional T1-weighted imaging and diffusion tensor imaging. Relative brain age (RBA) was computed to assess cerebral aging. Variables of structural integrity included cortical thickness, cortical volume, white matter hyperintensity (WMH) volume, peak width of skeletonized mean diffusivity (PSMD), ventricular volume, and choroid plexus volume. Mini-Mental State Examination (MMSE) was conducted to assess general cognition. Trail Making Test (TMT) and Auditory Verbal Learning Test were administered to evaluate executive function and episodic memory, respectively. Mediation analysis and multivariate linear regression with interaction terms were performed to explore the differential impacts of RBA on cognitive function and structural integrity between CSVD patients and controls. RESULTS RBA was significantly increased in CSVD patients compared to controls (p < 0.001). White matter injuries as assessed with PSMD (mediation magnitude: 41.1%) and WMH volume (mediation magnitude: 56.9%) significantly mediated the relationship between CSVD pathologies and RBA (p < 0.001). Higher RBA was significantly correlated with poorer scores of MMSE, TMT-A, and TMT-B in CSVD patients (p < 0.01). Additionally, PSMD (mediation magnitude: 57.8% in MMSE, 48.3% in TMT-A, and 28.8% in TMT-B) and WMH volume (mediation magnitude: 55.1% in MMSE) significantly mediated the relationship between RBA and cognitive function (p < 0.05). CONCLUSION White matter injuries play a critical role in the cerebral aging and cognitive decline in CSVD patients.
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Affiliation(s)
- Yuanhao Li
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China
| | - Tian Tian
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China
| | - Chengxia Liu
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China.
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Jiefang Road 1095, Wuhan, China.
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8
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Kedia S, Simons M. Oligodendrocytes in Alzheimer's disease pathophysiology. Nat Neurosci 2025; 28:446-456. [PMID: 39881195 DOI: 10.1038/s41593-025-01873-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Accepted: 12/19/2024] [Indexed: 01/31/2025]
Abstract
Our understanding of Alzheimer's disease (AD) has transformed from a purely neuronal perspective to one that acknowledges the involvement of glial cells. Despite remarkable progress in unraveling the biology of microglia, astrocytes and vascular elements, the exploration of oligodendrocytes in AD is still in its early stages. Contrary to the traditional notion of oligodendrocytes as passive bystanders in AD pathology, emerging evidence indicates their active participation in and reaction to amyloid and tau pathology. Oligodendrocytes undergo a functional transition to a disease-associated state, engaging in immune modulation, stress responses and cellular survival. Far from being inert players, they appear to serve a dual role in AD pathogenesis, potentially offering defense mechanisms against pathology while also contributing to disease progression. This Review explores recent advancements in understanding the roles of oligodendrocytes and their myelin sheaths in the context of AD, shedding light on their complex interactions within the disease pathology.
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Affiliation(s)
- Shreeya Kedia
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Mikael Simons
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
- Munich Cluster of Systems Neurology (SyNergy), Munich, Germany.
- Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, Munich, Germany.
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9
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Xu Y, Wei H, Du R, Wang R, Zhu Y, Zhao T, Zhu X, Li Y. Hippocampal vascularization pattern and cerebral blood flow cooperatively modulate hippocampal tolerable amount of Aβ deposition in the occurrence of MCI. Fluids Barriers CNS 2025; 22:22. [PMID: 39994752 PMCID: PMC11854383 DOI: 10.1186/s12987-025-00635-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2024] [Accepted: 02/17/2025] [Indexed: 02/26/2025] Open
Abstract
BACKGROUND Aβ deposition in the brain does not necessarily lead to cognitive impairment, and that blood supply may have other unexplained regulatory effects on Aβ. Therefore, there appears to be a more complex relationship between blood supply, Aβ deposition, and cognitive impairment that warrants further exploration. METHODS This cohort study collected four longitudinal follow-up datasets, including a total of 281 subjects, followed for four years. Three-dimensional time-of-flight angiography and pseudo-continuous arterial spin labeling were used to assess hippocampal vascularization pattern (VP) and hippocampal cerebral blood flow (CBF). 11 C-Pittsburgh compound B (PiB)-PET/CT-based spatial measurements were used detect hippocampal PiB uptake as a reflection of hippocampal Aβ deposition. We explored the relationships between hippocampal blood supply (VP and CBF), hippocampal PiB uptake, and the occurrence of mild cognitive impairment (MCI) using a generalized nonlinear model. RESULTS We demonstrated the synergistic effect of hippocampal VP and CBF on predicting the occurrence of MCI. We conducted confirmation and quantification of the relationship between hippocampal blood supply and hippocampal PiB uptake. Additionally, the predicted value of PiB uptake based on hippocampal blood supply not only exhibited strong predictive efficacy for the occurrence of MCI (AUC = 0.831, p < 0.001), but was also validated in cerebral small vessel disease cohorts (AUC = 0.792, p < 0.001) and well validated in an independent cohort (Kappa = 0.741, p < 0.001). CONCLUSIONS Overall, we reveal that hippocampal blood supply at baseline can regulate hippocampal PiB uptake, which reflects hippocampal tolerable amount of Aβ deposition and serves as an effective predictor for the occurrence of MCI, providing an important extension on the relationship between hippocampal blood supply and Aβ deposition.
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Affiliation(s)
- Yuhao Xu
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212001, China
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
- Department of Neurology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, China
| | - Hong Wei
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
- Department of Neurology, The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212001, China
- Central Laboratory of the Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212001, China
| | - Rui Du
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
| | - Ranchao Wang
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
| | - Yan Zhu
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
- Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, China
| | - Tian Zhao
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
- Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, China
| | - Xiaolan Zhu
- Central Laboratory of the Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212001, China.
- Reproductive Center, The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212001, China.
| | - Yuefeng Li
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212001, China.
- Department of Neuroimaging Laboratory, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
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10
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Zheng Q, Wang X. Alzheimer's disease: insights into pathology, molecular mechanisms, and therapy. Protein Cell 2025; 16:83-120. [PMID: 38733347 PMCID: PMC11786724 DOI: 10.1093/procel/pwae026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024] Open
Abstract
Alzheimer's disease (AD), the leading cause of dementia, is characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. This condition casts a significant shadow on global health due to its complex and multifactorial nature. In addition to genetic predispositions, the development of AD is influenced by a myriad of risk factors, including aging, systemic inflammation, chronic health conditions, lifestyle, and environmental exposures. Recent advancements in understanding the complex pathophysiology of AD are paving the way for enhanced diagnostic techniques, improved risk assessment, and potentially effective prevention strategies. These discoveries are crucial in the quest to unravel the complexities of AD, offering a beacon of hope for improved management and treatment options for the millions affected by this debilitating disease.
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Affiliation(s)
- Qiuyang Zheng
- Shenzhen Research Institute of Xiamen University, Shenzhen 518057, China
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Department of Neurology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Xin Wang
- Shenzhen Research Institute of Xiamen University, Shenzhen 518057, China
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Department of Neurology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen 361005, China
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11
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Peterson A, Sathe A, Zaras D, Yang Y, Durant A, Deters KD, Shashikumar N, Pechman KR, Kim ME, Gao C, Mohd Khairi N, Li Z, Yao T, Huo Y, Dumitrescu L, Gifford KA, Wilson JE, Cambronero FE, Risacher SL, Beason‐Held LL, An Y, Arfanakis K, Erus G, Davatzikos C, Tosun D, Toga AW, Thompson PM, Mormino EC, Habes M, Wang D, Zhang P, Schilling K, Albert M, Kukull W, Biber SA, Landman BA, Johnson SC, Schneider J, Barnes LL, Bennett DA, Jefferson AL, Resnick SM, Saykin AJ, Hohman TJ, Archer DB. Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease. Alzheimers Dement 2025; 21:e14343. [PMID: 39711105 PMCID: PMC11781133 DOI: 10.1002/alz.14343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 09/08/2024] [Accepted: 09/27/2024] [Indexed: 12/24/2024]
Abstract
INTRODUCTION The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized. METHODS Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status. RESULTS Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. HIGHLIGHTS Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstructural integrity. Females generally have lower free water-corrected fractional anisotropy compared to males. APOE ε4 carriers tended to have higher free water than non-carriers.
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Affiliation(s)
- Amalia Peterson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Aditi Sathe
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Dimitrios Zaras
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Yisu Yang
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Alaina Durant
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kacie D. Deters
- Department of Integrative Biology and PhysiologyUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Michael E. Kim
- Department of Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
| | - Chenyu Gao
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Nazirah Mohd Khairi
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Zhiyuan Li
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Tianyuan Yao
- Department of Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
| | - Yuankai Huo
- Department of Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Brain InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jo Ellen Wilson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of Psychiatry and Behavioral SciencesCenter for Cognitive Medicine, Vanderbilt University Medical CenterNashvilleTennesseeUSA
- Veteran's Affairs, Geriatric Research, Education and Clinical CenterTennessee Valley Healthcare SystemNashvilleTennesseeUSA
| | - Francis E. Cambronero
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Shannon L. Risacher
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
| | - Lori L. Beason‐Held
- Laboratory for Behavioral NeuroscienceNational Institute on Aging, National Institutes of HealthBaltimoreMarylandUSA
| | - Yang An
- Laboratory for Behavioral NeuroscienceNational Institute on Aging, National Institutes of HealthBaltimoreMarylandUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Diagnostic RadiologyRush University Medical CenterChicagoIllinoisUSA
| | - Guray Erus
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Christos Davatzikos
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Duygu Tosun
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and InformaticsKeck School of Medicine, University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and InformaticsKeck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative DisordersUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Di Wang
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative DisordersUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Panpan Zhang
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Kurt Schilling
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
| | | | | | | | - Marilyn Albert
- Department of NeurologyJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Walter Kukull
- National Alzheimer's Coordinating CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Sarah A. Biber
- National Alzheimer's Coordinating CenterUniversity of WashingtonSeattleWashingtonUSA
| | - Bennett A. Landman
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
- Vanderbilt Brain InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Julie Schneider
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Lisa L. Barnes
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - David A. Bennett
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Computer ScienceVanderbilt UniversityNashvilleTennesseeUSA
| | - Susan M. Resnick
- Laboratory for Behavioral NeuroscienceNational Institute on Aging, National Institutes of HealthBaltimoreMarylandUSA
| | - Andrew J. Saykin
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Brain InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Brain InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
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12
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Lim D, Matute C, Cavaliere F, Verkhratsky A. Neuroglia in neurodegeneration: Alzheimer, Parkinson, and Huntington disease. HANDBOOK OF CLINICAL NEUROLOGY 2025; 210:9-44. [PMID: 40148060 DOI: 10.1016/b978-0-443-19102-2.00012-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/29/2025]
Abstract
The conspicuous rise of chronic neurodegenerative diseases, including Alzheimer (AD), Parkinson (PD), and Huntington (HD) diseases, is currently without disease-modifying therapies and accompanied by an excessive rate of unsuccessful clinical trials. This reflects a profound lack of understanding of the pathogenesis of these diseases, indicating that the current paradigms guiding disease modeling and drug development are in need of reconsideration. The role of neuroglia, namely astrocytes, microglial cells, and oligodendrocytes, in the pathogenesis of neurodegenerative diseases emerged during the last decades. This chapter provides the state-of-the-art update on the changes of astrocytes, microglial cells, and oligodendrocytes in AD, PD, and HD. A growing body of evidence suggests that homeostatic and defensive functions of glial cells are compromised at different disease stages, leading to increased susceptibility of neurons to noxious stimuli, eventually resulting in their malfunction and degeneration. Investments are needed in the generation of novel preclinical models suitable for studying glial pathology, in "humanizing" research, and in-depth investigation of glial cell alterations to slow down and, possibly, halt and prevent the rise of neurodegenerative disease. Targeting glial cells opens new therapeutic avenues to treat AD, PD, and HD.
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Affiliation(s)
- Dmitry Lim
- Department of Pharmaceutical Sciences, Università del Piemonte Orientale "Amedeo Avogadro", Novara, Italy.
| | - Carlos Matute
- Department of Neurosciences, University of the Basque Country UPV/EHU and CIBERNED, Leioa, Bizkaia, Spain
| | - Fabio Cavaliere
- The Basque Biomodels Platform for Human Research (BBioH), Achucarro Basque Center for Neuroscience & Fundación Biofisica Bizkaia, Leioa, Spain
| | - Alexei Verkhratsky
- Department of Neurosciences, University of the Basque Country UPV/EHU and CIBERNED, Leioa, Bizkaia, Spain; Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
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13
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Lopez-Lee C, Kodama L, Fan L, Zhu D, Zhu J, Wong MY, Ye P, Norman K, Foxe NR, Ijaz L, Yu F, Chen H, Carling GK, Torres ER, Kim RD, Dubal DB, Liddelow SA, Sinha SC, Luo W, Gan L. Tlr7 drives sex differences in age- and Alzheimer's disease-related demyelination. Science 2024; 386:eadk7844. [PMID: 39607927 DOI: 10.1126/science.adk7844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 06/30/2024] [Accepted: 10/10/2024] [Indexed: 11/30/2024]
Abstract
Alzheimer's disease (AD) and other age-related disorders associated with demyelination exhibit sex differences. In this work, we used single-nuclei transcriptomics to dissect the contributions of sex chromosomes and gonads in demyelination and AD. In a mouse model of demyelination, we identified the roles of sex chromosomes and gonads in modifying microglia and oligodendrocyte responses before and after myelin loss. In an AD-related mouse model expressing APOE4, XY sex chromosomes heightened interferon (IFN) response and tau-induced demyelination. The X-linked gene, Toll-like receptor 7 (Tlr7), regulated sex-specific IFN response to myelin. Deletion of Tlr7 dampened sex differences while protecting against demyelination. Administering TLR7 inhibitor mitigated tau-induced motor impairment and demyelination in male mice, indicating that Tlr7 plays a role in the male-biased type I Interferon IFN response in aging- and AD-related demyelination.
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Affiliation(s)
- Chloe Lopez-Lee
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY, USA
| | - Lay Kodama
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Neuroscience Graduate Program, University of California San Francisco, San Francisco, CA, USA
| | - Li Fan
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Daphne Zhu
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Jingjie Zhu
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Man Ying Wong
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Pearly Ye
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Kendra Norman
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Nessa R Foxe
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Laraib Ijaz
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Fangmin Yu
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Hao Chen
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Gillian K Carling
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY, USA
| | - Eileen R Torres
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Rachel D Kim
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Dena B Dubal
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Shane A Liddelow
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neuroscience & Physiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Ophthalmology, NYU Grossman School of Medicine, New York, NY, USA
- Parekh Center for Interdisciplinary Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Subhash C Sinha
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Wenjie Luo
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Li Gan
- Helen and Robert Appel Institute for Alzheimer's Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY, USA
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14
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Salian VS, Tang X, Thompson KJ, Curan GL, Lowe VJ, Li L, Kalari KR, Kandimalla KK. Molecular Mechanisms Underlying Amyloid Beta Peptide Mediated Upregulation of Vascular Cell Adhesion Molecule-1 in Alzheimer Disease. J Pharmacol Exp Ther 2024; 391:430-440. [PMID: 39455283 PMCID: PMC11585316 DOI: 10.1124/jpet.124.002280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 09/30/2024] [Accepted: 10/08/2024] [Indexed: 10/28/2024] Open
Abstract
Amyloid β(Aβ) deposition and neurofibrillary tangles are widely considered the primary pathological hallmarks of familial and sporadic forms of Alzheimer disease (AD). However, cerebrovascular inflammation, which is prevalent in 70% of AD patients, is emerging as another core feature of AD pathology. In our current work, we investigated the hypothesis that Aβ42 exposure drives an increase in vascular cell adhesion molecule-1 (VCAM-1) expression, a cerebrovascular inflammatory marker expressed on the blood-brain barrier (BBB) endothelium in humans and murine models. We have demonstrated that the inflammation signaling pathway is upregulated in AD patient brains, and VCAM-1 expression is increased in AD patients compared with healthy controls. Furthermore, dynamic SPEC/CT imaging in APP,PS1 transgenic mice (a mouse model that overexpresses Aβ42) demonstrated VCAM-1 upregulation at the BBB. Although there is a strong association between Aβ42 exposure and an increase in VCAM-1 expression, the underlying mechanisms remain partially understood. Molecular mechanisms driving VCAM-1 expression at the BBB were investigated in polarized human cerebral microvascular endothelial cell monolayers. Moreover, by employing reverse-phase protein array assays and immunocytochemistry we demonstrated that Aβ42 increases VCAM-1 expression via the Src/p38/MEK signaling pathway. Therefore, targeting the Src/p38/MEK pathway may help modulate VCAM-1 expression at the BBB and help mitigate cerebrovascular inflammation in Alzheimer disease. SIGNIFICANCE STATEMENT: Although considered a core pathological feature of Alzheimer disease, molecular pathways leading to cerebrovascular inflammation remain only partially understood. Moreover, clinical diagnostic methods for detecting cerebrovascular inflammation are underdeveloped. This study demonstrated the detection of VCAM-1 using radio-iodinated VCAM-1 antibody and single-photon emission computed tomography/computed tomography imaging. Additionally, exposure to Aβ42 increases VCAM-1 expression on the blood-brain barrier endothelium via the Src/p38/MEK pathway. These findings are expected to aid in the development of diagnostic and therapeutic approaches for addressing cerebrovascular inflammation in AD.
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Affiliation(s)
- Vrishali S Salian
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Xiaojia Tang
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Kevin J Thompson
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Geoffry L Curan
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Val J Lowe
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Ling Li
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Krishna R Kalari
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
| | - Karunya K Kandimalla
- Department of Pharmaceutics and Brain Barriers Research Center, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (V.S.S., K.K.K.); Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota (G.L.C., V.J.L.); Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (X.T., K.J.T., K.R.K.); and Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota (L.L.)
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15
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Shao Y, Li F, Zou B, Jin Y, Wang X, Wang L, Huang Y, Xie Y, Sun W, Kang JX, Liu K, Huang Y, Huang W, Wang B. Up-regulation of myelin-associated glycoprotein is associated with the ameliorating effect of omega-3 polyunsaturated fatty acids on Alzheimer's disease progression in APP-PS1 transgenic mice. Food Funct 2024; 15:11236-11251. [PMID: 39453315 DOI: 10.1039/d4fo03355h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2024]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive behavioral and cognitive impairments. Despite growing evidence of the neuroprotective action of omega-3 polyunsaturated fatty acids (PUFAs), the effects and mechanism of omega-3 PUFAs on AD control are yet to be clarified. By crossing male heterozygous fat-1 mice with female APP/PS1 mice, we assessed whether elevated tissue omega-3 PUFA levels could alleviate AD progression and their underlying mechanism among the offspring WT, APP/PS1 and APP/PS1 × fat-1 groups at various stages. We found that the fat-1 transgene significantly increased brain omega-3 PUFA and docosahexaenoic acid (DHA) levels, and cognitive deficits together with brain Aβ-40 and Aβ-42 levels in 6-month-old APP/PS1 × fat-1 mice were significantly lower than those in APP/PS1 mice. Subsequently, the tandem mass tag (TMT) method revealed the elevated expression of cortex and hippocampus myelin-associated glycoprotein (MAG) in APP/PS1 × fat-1 mice at 2-6 months. Furthermore, GO and KEGG pathway enrichment analysis suggested that the MAG-related myelin sheath pathway and its interaction with AD were regulated by omega-3 PUFAs. Moreover, subsequent western blot assays showed that both increased endogenous omega-3 levels and in vitro supplemented DHA up-regulated MAG expression, and the AD-protective effects of DHA on LPS-induced BV2 cells were significantly weakened when MAG was inhibited by si-RNA transfection. In summary, our study suggested that omega-3 PUFAs might protect against AD by up-regulating MAG expression.
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Affiliation(s)
- Yan Shao
- Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, China
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Fei Li
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Bo Zou
- Department of Clinical Nutrition, Shenzhen Longgang Central Hospital, Shenzhen 518116, China.
| | - Yanling Jin
- Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, China
| | - Xiaoyang Wang
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Liting Wang
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Youying Huang
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Yu Xie
- Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, China
| | - Wei Sun
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Jing X Kang
- Laboratory for Lipid Medicine and Technology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02129, USA
- Omega-3 and Global Health Institute, Boston, MA 02129, USA
| | - Kai Liu
- Department of Endocrinology, General Hospital of Northern Theater Command, Shenyang 110016, P. R. China
- Department of Disease Surveillance, Center for Disease Control and Prevention of Northern Theater Command, Shenyang 110034, P.R. China
| | - Yi Huang
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Wei Huang
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China.
| | - Bin Wang
- Department of Clinical Nutrition, Shenzhen Longgang Central Hospital, Shenzhen 518116, China.
- Research Center for Nutrition and Food Safety, Chongqing Key Laboratory of Nutrition and Food Safety, Institute of Military Preventive Medicine, Army Medical University, Chongqing 400038, China
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16
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Rosas HD, Mercaldo ND, Hasimoglu Y, Petersen M, Lewis LR, Lai F, Powell D, Dhungana A, Demir A, Keater D, Yassa M, Brickman AM, O'Bryant S. Association of plasma neurofilament light chain with microstructural white matter changes in Down syndrome. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e70023. [PMID: 39583646 PMCID: PMC11582681 DOI: 10.1002/dad2.70023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 09/10/2024] [Accepted: 09/13/2024] [Indexed: 11/26/2024]
Abstract
INTRODUCTION Both micro- and macrostructural white matter (WM) abnormalities, particularly those related to axonal degeneration, are associated with cognitive decline in adults with Down syndrome (DS) prior to a diagnosis of Alzheimer disease. Neurofilament light chain (NfL) is a support protein within myelinated axons released into blood following axonal damage. In this study we investigated cross-sectional relationships between WM microstructural changes as measured by diffusion tensor imaging (DTI) and plasma NfL concentration in adults with DS without dementia. METHODS Thirty cognitively stable (CS) adults with DS underwent diffusion-weighted MRI scanning and plasma NfL measurement. DTI measures of select WM tracts were derived using automatic fiber tracking, and associations with plasma NfL were assessed using Spearman correlation coefficients. RESULTS Higher Plasma NfL was associated with greater altered diffusion measures of select tracts. DISCUSSION Early increases in plasma NfL may reflect early white matter microstructural changes prior to dementia in DS. Highlights The onset of such WM changes in DS has not yet been widely studied.WM microstructural properties correlated with plasma neurofilament light chain (NfL).NfL may reflect early, selective WM changes in adults with DS at high risk of developing AD.
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Affiliation(s)
- Herminia Diana Rosas
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Nathaniel David Mercaldo
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Yasemin Hasimoglu
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Melissa Petersen
- Department of Family MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Lydia R. Lewis
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Florence Lai
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - David Powell
- Magnetic Resonance Imaging and Spectroscopy CenterUniversity of KentuckyLexingtonKentuckyUSA
| | - Asim Dhungana
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Ali Demir
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Neuroimaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalCharlestownMassachusettsUSA
| | - David Keater
- Department of Neurobiology and BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Michael Yassa
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's disease and the Aging Brain Department of NeurologyVagelos College of Physicians and Surgeons, Columbia UniversityNew YorkUSA
| | - Sid O'Bryant
- Department of Family MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
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17
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Chen YY, Chang CJ, Liang YW, Tseng HY, Li SJ, Chang CW, Wu YT, Shao HH, Chen PC, Lai ML, Deng WC, Hsu R, Lo YC. Utilizing diffusion tensor imaging as an image biomarker in exploring the therapeutic efficacy of forniceal deep brain stimulation in a mice model of Alzheimer's disease. J Neural Eng 2024; 21:056003. [PMID: 39230033 DOI: 10.1088/1741-2552/ad7322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 08/15/2024] [Indexed: 09/05/2024]
Abstract
Objective.With prolonged life expectancy, the incidence of memory deficits, especially in Alzheimer's disease (AD), has increased. Although multiple treatments have been evaluated, no promising treatment has been found to date. Deep brain stimulation (DBS) of the fornix area was explored as a possible treatment because the fornix is intimately connected to memory-related areas that are vulnerable in AD; however, a proper imaging biomarker for assessing the therapeutic efficiency of forniceal DBS in AD has not been established.Approach.This study assessed the efficacy and safety of DBS by estimating the optimal intersection volume between the volume of tissue activated and the fornix. Utilizing a gold-electroplating process, the microelectrode's surface area on the neural probe was increased, enhancing charge transfer performance within potential water window limits. Bilateral fornix implantation was conducted in triple-transgenic AD mice (3 × Tg-AD) and wild-type mice (strain: B6129SF1/J), with forniceal DBS administered exclusively to 3 × Tg-AD mice in the DBS-on group. Behavioral tasks, diffusion tensor imaging (DTI), and immunohistochemistry (IHC) were performed in all mice to assess the therapeutic efficacy of forniceal DBS.Main results.The results illustrated that memory deficits and increased anxiety-like behavior in 3 × Tg-AD mice were rescued by forniceal DBS. Furthermore, forniceal DBS positively altered DTI indices, such as increasing fractional anisotropy (FA) and decreasing mean diffusivity (MD), together with reducing microglial cell and astrocyte counts, suggesting a potential causal relationship between revised FA/MD and reduced cell counts in the anterior cingulate cortex, hippocampus, fornix, amygdala, and entorhinal cortex of 3 × Tg-AD mice following forniceal DBS.Significance.The efficacy of forniceal DBS in AD can be indicated by alterations in DTI-based biomarkers reflecting the decreased activation of glial cells, suggesting reduced neural inflammation as evidenced by improvements in memory and anxiety-like behavior.
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Affiliation(s)
- You-Yin Chen
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, 12F., Education & Research Building, Shuang-Ho Campus, No. 301, Yuantong Rd., New Taipei City 23564, Taiwan, Republic of China
| | - Chih-Ju Chang
- Department of Neurosurgery, Cathay General Hospital, No. 280, Sec. 4, Renai Rd., Taipei 10629, Taiwan, Republic of China
- School of Medicine, Fu Jen Catholic University, No.510, Zhongzheng Rd., New Taipei City 242062, Taiwan, Republic of China
| | - Yao-Wen Liang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
| | - Hsin-Yi Tseng
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University and National Health Research Institutes, 12F., Education & Research Building, Shuang-Ho Campus, No. 301, Yuantong Rd., New Taipei City 23564, Taiwan, Republic of China
| | - Ssu-Ju Li
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
| | - Ching-Wen Chang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
| | - Yen-Ting Wu
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
| | - Huai-Hsuan Shao
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong St., Taipei 11221, Taiwan, Republic of China
| | - Po-Chun Chen
- Department of Materials and Mineral Resources Engineering, National Taipei University of Technology, No. 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan, Republic of China
| | - Ming-Liang Lai
- Graduate Institute of Intellectual Property, National Taipei University of Technology, No. 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan, Republic of China
| | - Wen-Chun Deng
- Departments of Neurosurgery, Keelung Chang Gung Memorial Hospital, Chang Gung University, No.222, Maijin Rd., Keelung 20400, Taiwan, Republic of China
| | - RuSiou Hsu
- Department of Ophthalmology, Stanford University, 1651 Page Mill Rd., Palo Alto, CA 94304, United States of America
| | - Yu-Chun Lo
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, 12F., Education & Research Building, Shuang-Ho Campus, No. 301, Yuantong Rd., New Taipei City 23564, Taiwan, Republic of China
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18
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Charisis S, Short MI, Bernal R, Kautz TF, Treviño HA, Mathews J, Dediós AGV, Muhammad JAS, Luckey AM, Aslam A, Himali JJ, Shipp EL, Habes M, Beiser AS, DeCarli C, Scarmeas N, Ramachandran VS, Seshadri S, Maillard P, Satizabal CL. Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age. Alzheimers Dement 2024; 20:5849-5860. [PMID: 39132759 PMCID: PMC11497668 DOI: 10.1002/alz.13879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/01/2024] [Accepted: 03/24/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults. METHODS We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols. RESULTS Higher sOB-R was associated with lower fractional anisotropy (FA, β = -0.114 ± 0.02, p < 0.001), and higher free water (FW, β = 0.091 ± 0.022, p < 0.001) and peak-width skeletonized mean diffusivity (PSMD, β = 0.078 ± 0.021, p < 0.001). Correspondingly, higher FLI was associated with higher FA (β = 0.115 ± 0.027, p < 0.001) and lower FW (β = -0.096 ± 0.029, p = 0.001) and PSMD (β = -0.085 ± 0.028, p = 0.002). DISCUSSION Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk. HIGHLIGHTS Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.
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Affiliation(s)
- Sokratis Charisis
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Meghan I. Short
- Institute for Clinical Research and Health Policy StudiesTufts Medical CenterBostonMassachusettsUSA
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Tiffany F. Kautz
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Hector A. Treviño
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Julia Mathews
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | | | - Jazmyn A. S. Muhammad
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Alison M. Luckey
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Asra Aslam
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Jayandra J. Himali
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Eric L. Shipp
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Alexa S. Beiser
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Charles DeCarli
- Department of NeurologyUniversity of California, DavisSacramentoCaliforniaUSA
| | - Nikolaos Scarmeas
- 1st Department of NeurologyNational and Kapodistrian University of AthensAthensGreece
- Taub Institute for Research in Alzheimer's Disease and the Aging Brainthe Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
| | - Vasan S. Ramachandran
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Pauline Maillard
- Department of NeurologyUniversity of California, DavisSacramentoCaliforniaUSA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
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19
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Rivier CA, Singh S, Senff J, Tack RW, Marini S, Clocchiatti-Tuozzo S, Huo S, Renedo D, Papier K, Conroy M, Littlejohns TJ, Chemali Z, Kourkoulis C, Payabvash S, Newhouse A, Westover MB, Lazar RM, Pikula A, Ibrahim S, Howard VJ, Howard G, Brouwers HB, Van Duijn CM, Fricchione G, Tanzi RE, Yechoor N, Sheth KN, Anderson CD, Rosand J, Falcone GJ. Brain Care Score and Neuroimaging Markers of Brain Health in Asymptomatic Middle-Age Persons. Neurology 2024; 103:e209687. [PMID: 39052961 PMCID: PMC11760050 DOI: 10.1212/wnl.0000000000209687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 05/29/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVES To investigate associations between health-related behaviors as measured using the Brain Care Score (BCS) and neuroimaging markers of white matter injury. METHODS This prospective cohort study in the UK Biobank assessed the BCS, a novel tool designed to empower patients to address 12 dementia and stroke risk factors. The BCS ranges from 0 to 21, with higher scores suggesting better brain care. Outcomes included white matter hyperintensities (WMH) volume, fractional anisotropy (FA), and mean diffusivity (MD) obtained during 2 imaging assessments, as well as their progression between assessments, using multivariable linear regression adjusted for age and sex. RESULTS We included 34,509 participants (average age 55 years, 53% female) with no stroke or dementia history. At first and repeat imaging assessments, every 5-point increase in baseline BCS was linked to significantly lower WMH volumes (25% 95% CI [23%-27%] first, 33% [27%-39%] repeat) and higher FA (18% [16%-20%] first, 22% [15%-28%] repeat), with a decrease in MD (9% [7%-11%] first, 10% [4%-16%] repeat). In addition, a higher baseline BCS was associated with a 10% [3%-17%] reduction in WMH progression and FA decline over time. DISCUSSION This study extends the impact of the BCS to neuroimaging markers of clinically silent cerebrovascular disease. Our results suggest that improving one's BCS could be a valuable intervention to prevent early brain health decline.
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Affiliation(s)
- Cyprien A Rivier
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sanjula Singh
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Jasper Senff
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Reinier W Tack
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sandro Marini
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Santiago Clocchiatti-Tuozzo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Shufan Huo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Daniela Renedo
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Keren Papier
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Megan Conroy
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Thomas J Littlejohns
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Zeina Chemali
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Christina Kourkoulis
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Seyedmehdi Payabvash
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Amy Newhouse
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - M Brandon Westover
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Ronald M Lazar
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Aleksandra Pikula
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Sarah Ibrahim
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Virginia J Howard
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - George Howard
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - H Bart Brouwers
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Cornelia M Van Duijn
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Gregory Fricchione
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Rudolph E Tanzi
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Nirupama Yechoor
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Kevin N Sheth
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Christopher D Anderson
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Jonathan Rosand
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
| | - Guido J Falcone
- From the Department of Neurology (C.A.R., S.C.-T., S.H., D.R., K.N.S., G.J.F.), Yale School of Medicine, New Haven, CT; Yale Center for Brain and Mind Health (C.A.R., S.C.-T., S.H., D.R., S.P., K.N.S., G.J.F.); Henry and Allison McCance Center for Brain Health (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., G.F., R.E.T., N.Y., C.D.A., J.R.); Departments of Neurology (S.S., J.S., R.W.T., S.M., Z.C., C.K., M.B.W., N.Y., C.D.A., J.R.), Psychiatry (A.N.), and Medicine (A.N.), Massachusetts General Hospital, Boston; Broad Institute of MIT and Harvard (S.S., J.S., R.W.T., S.M., C.K., N.Y., C.D.A., J.R.), Cambridge, MA; Department of Neurology (S.S., J.S., R.W.T., H.B.B.), Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, the Netherlands; Cancer Epidemiology Unit (K.P.), Nuffield Department of Population Health (M.C., T.J.L., C.M.V.D.), Big Data Institute, University of Oxford, United Kingdom; UAB McKnight Brain Institute (R.M.L.), Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham; Department of Medicine (Neurology) (A.P.), University of Toronto; Krembil Brain Institute (A.P.), Toronto, Ontario, Canada; Program for Health System and Technology Evaluation (S.I.); Toronto General Hospital Research Institute; The Jay and Sari Sonshine Centre for Stroke Prevention & Cerebrovascular Brain Health (A.P., S.I.), University Health Network, Toronto; Centre for Advancing Collaborative Healthcare & Education (CACHE) and Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health (S.I.), University of Toronto, Ontario, Canada; Departments of Epidemiology (V.J.H.) and Biostatistics (G.H.), School of Public Health, University of Alabama at Birmingham; Department of Neurosurgery (H.B.B.), Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands; Benson-Henry Institute for Mind Body Medicine (G.F.), Massachusetts General Hospital; and Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA
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20
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Daniels AJ, McDade E, Llibre-Guerra JJ, Xiong C, Perrin RJ, Ibanez L, Supnet-Bell C, Cruchaga C, Goate A, Renton AE, Benzinger TL, Gordon BA, Hassenstab J, Karch C, Popp B, Levey A, Morris J, Buckles V, Allegri RF, Chrem P, Berman SB, Chhatwal JP, Farlow MR, Fox NC, Day GS, Ikeuchi T, Jucker M, Lee JH, Levin J, Lopera F, Takada L, Sosa AL, Martins R, Mori H, Noble JM, Salloway S, Huey E, Rosa-Neto P, Sánchez-Valle R, Schofield PR, Roh JH, Bateman RJ. 15 Years of Longitudinal Genetic, Clinical, Cognitive, Imaging, and Biochemical Measures in DIAN. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.08.24311689. [PMID: 39148846 PMCID: PMC11326320 DOI: 10.1101/2024.08.08.24311689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.
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Affiliation(s)
- Alisha J. Daniels
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Eric McDade
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | | | - Chengjie Xiong
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Richard J. Perrin
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Laura Ibanez
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | | | - Carlos Cruchaga
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Alison Goate
- Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Alan E. Renton
- Icahn School of Medicine at Mount Sinai, New York, NY USA
| | | | - Brian A. Gordon
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Jason Hassenstab
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Celeste Karch
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Brent Popp
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Allan Levey
- Goizueta Alzheimer’s Disease Research Center, Emory University, Atlanta, GA, USA
| | - John Morris
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | - Virginia Buckles
- Washington University School of Medicine, St Louis, St Louis, MO, USA
| | | | - Patricio Chrem
- Institute of Neurological Research FLENI, Buenos Aires, Argentina
| | | | - Jasmeer P. Chhatwal
- Massachusetts General and Brigham & Women’s Hospitals, Harvard Medical School, Boston MA, USA
| | | | - Nick C. Fox
- UK Dementia Research Institute at University College London, London, United Kingdom
- University College London, London, United Kingdom
| | | | - Takeshi Ikeuchi
- Brain Research Institute, Niigata University, Niigata, Japan
| | - Mathias Jucker
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany
| | | | - Johannes Levin
- DZNE, German Center for Neurodegenerative Diseases, Munich, Germany
- Ludwig-Maximilians-Universität München, Munich, Germany
| | | | | | - Ana Luisa Sosa
- Instituto Nacional de Neurologia y Neurocirugla Innn, Mexico City, Mexico
| | - Ralph Martins
- Edith Cowan University, Western Australia, Australia
| | | | - James M. Noble
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, and GH Sergievsky Center, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Edward Huey
- Brown University, Butler Hospital, Providence, RI, USA
| | - Pedro Rosa-Neto
- Centre de Recherche de L’hopital Douglas and McGill University, Montreal, Quebec
| | - Raquel Sánchez-Valle
- Hospital Clínic de Barcelona. IDIBAPS. University of Barcelona, Barcelona, Spain
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jee Hoon Roh
- Korea University, Korea University Anam Hospital, Seoul, South Korea
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Naveed K, Rashidi-Ranjbar N, Kumar S, Zomorrodi R, Blumberger DM, Fischer CE, Sanches M, Mulsant BH, Pollock BG, Voineskos AN, Rajji TK. Effect of dorsolateral prefrontal cortex structural measures on neuroplasticity and response to paired-associative stimulation in Alzheimer's dementia. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230233. [PMID: 38853564 PMCID: PMC11343312 DOI: 10.1098/rstb.2023.0233] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 12/04/2023] [Accepted: 01/15/2024] [Indexed: 06/11/2024] Open
Abstract
Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)-a tract important to induce PAS-LTP-were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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Affiliation(s)
- K. Naveed
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - N. Rashidi-Ranjbar
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, 209 Victoria Street, Toronto, OntarioM5B 1T8, Canada
| | - S. Kumar
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - R. Zomorrodi
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
| | - D. M. Blumberger
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - C. E. Fischer
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, 209 Victoria Street, Toronto, OntarioM5B 1T8, Canada
| | - M. Sanches
- Biostatistics Core, Centre for Addiction and Mental Health, 60 White Squirrel Way, Toronto, OntarioM6J 1H4, Canada
| | - B. H. Mulsant
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - B. G. Pollock
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - A. N. Voineskos
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - T. K. Rajji
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
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22
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Korbmacher M, van der Meer D, Beck D, Askeland-Gjerde DE, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100323. [PMID: 39132576 PMCID: PMC11313202 DOI: 10.1016/j.bpsgos.2024.100323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 03/24/2024] [Accepted: 04/16/2024] [Indexed: 08/13/2024] Open
Abstract
Background During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging. Methods We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer's disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data. Results Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages. Conclusions We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.
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Affiliation(s)
- Max Korbmacher
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Daniel E. Askeland-Gjerde
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
| | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ole A. Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ivan I. Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
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23
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Qiu T, Liu Z, Rheault F, Legarreta JH, Valcourt Caron A, St‐Onge F, Strikwerda‐Brown C, Metz A, Dadar M, Soucy J, Pichet Binette A, Spreng RN, Descoteaux M, Villeneuve S. Structural white matter properties and cognitive resilience to tau pathology. Alzheimers Dement 2024; 20:3364-3377. [PMID: 38561254 PMCID: PMC11095478 DOI: 10.1002/alz.13776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 01/11/2024] [Accepted: 02/07/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-β/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS Aβ and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.
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Affiliation(s)
- Ting Qiu
- Douglas Mental Health University InstituteMontrealCanada
| | - Zhen‐Qi Liu
- Montreal Neurological InstituteDepartment of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
| | - François Rheault
- Medical Imaging and NeuroInformatics LabUniversité de SherbrookeSherbrookeCanada
| | - Jon Haitz Legarreta
- Department of RadiologyBrigham and Women's HospitalMass General Brigham/Harvard Medical SchoolBostonMassachusettsUSA
| | - Alex Valcourt Caron
- Sherbrooke Connectivity Imaging LaboratoryUniversité de SherbrookeSherbrookeCanada
| | | | - Cherie Strikwerda‐Brown
- Douglas Mental Health University InstituteMontrealCanada
- School of Psychological ScienceThe University of Western AustraliaPerthAustralia
| | - Amelie Metz
- Douglas Mental Health University InstituteMontrealCanada
| | - Mahsa Dadar
- Douglas Mental Health University InstituteMontrealCanada
- Department of PsychiatryMcGill UniversityMontrealCanada
| | - Jean‐Paul Soucy
- Montreal Neurological InstituteDepartment of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
| | | | - R. Nathan Spreng
- Douglas Mental Health University InstituteMontrealCanada
- Montreal Neurological InstituteDepartment of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
- Department of PsychiatryMcGill UniversityMontrealCanada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging LaboratoryUniversité de SherbrookeSherbrookeCanada
| | - Sylvia Villeneuve
- Douglas Mental Health University InstituteMontrealCanada
- Department of PsychiatryMcGill UniversityMontrealCanada
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24
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Phillips JS, Adluru N, Chung MK, Radhakrishnan H, Olm CA, Cook PA, Gee JC, Cousins KAQ, Arezoumandan S, Wolk DA, McMillan CT, Grossman M, Irwin DJ. Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease. Front Neurosci 2024; 18:1353306. [PMID: 38567286 PMCID: PMC10986184 DOI: 10.3389/fnins.2024.1353306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.
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Affiliation(s)
- Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Moo K. Chung
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Hamsanandini Radhakrishnan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip A. Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - James C. Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A. Q. Cousins
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanaz Arezoumandan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Memory Center, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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25
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Yang DX, Sun Z, Yu MM, Zou QQ, Li PY, Zhang JK, Wu X, Li YH, Wang ML. Associations of MRI-Derived Glymphatic System Impairment With Global White Matter Damage and Cognitive Impairment in Mild Traumatic Brain Injury: A DTI-ALPS Study. J Magn Reson Imaging 2024; 59:639-647. [PMID: 37276070 DOI: 10.1002/jmri.28797] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND Assessing the glymphatic function using diffusion tensor image analysis along the perivascular space (DTI-ALPS) may be helpful for mild traumatic brain injury (mTBI) management. PURPOSE To assess glymphatic function using DTI-ALPS and its associations with global white matter damage and cognitive impairment in mTBI. STUDY TYPE Prospective. POPULATION Thirty-four controls (44.1% female, mean age 49.2 years) and 58 mTBI subjects (43.1% female, mean age 48.7 years), including uncomplicated mTBI (N = 32) and complicated mTBI (N = 26). FIELD STRENGTH/SEQUENCE 3-T, single-shot echo-planar imaging sequence. ASSESSMENT Magnetic resonance imaging (MRI) was done within 1 month since injury. DTI-ALPS was performed to assess glymphatic function, and peak width of skeletonized mean diffusivity (PSMD) was used to assess global white matter damage. Cognitive tests included Auditory Verbal Learning Test and Digit Span Test (forward and backward). STATISTICAL TESTS Neuroimaging findings comparisons were done between mTBI and control groups. Partial correlation and multivariable linear regression assessed the associations between DTI-ALPS, PSMD, and cognitive impairment. Mediation effects of PSMD on the relationship between DTI-ALPS and cognitive impairment were explored. P-value <0.05 was considered statistically significant, except for cognitive correlational analyses with a Bonferroni-corrected P-value set at 0.05/3 ≈ 0.017. RESULTS mTBI showed lower DTI-ALPS and higher PSMD, especially in complicated mTBI. DTI-ALPS was significantly correlated with verbal memory (r = 0.566), attention abilities (r = 0.792), executive function (r = 0.618), and PSMD (r = -0.533). DTI-ALPS was associated with verbal memory (β = 8.77, 95% confidence interval [CI] 5.00, 12.54), attention abilities (β = 5.67, 95% CI 4.56, 6.97), executive function (β = 2.34, 95% CI 1.49, 3.20), and PSMD (β = -0.79, 95% CI -1.15, -0.43). PSMD mediated 46.29%, 20.46%, and 24.36% of the effects for the relationship between DTI-ALPS and verbal memory, attention abilities, and executive function. DATA CONCLUSION Glymphatic function may be impaired in mTBI reflected by DTI-ALPS. Glymphatic dysfunction may cause cognitive impairment related to global white matter damage after mTBI. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Dian-Xu Yang
- Department of Neurosurgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zheng Sun
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Meng-Meng Yu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China
| | - Qiao-Qiao Zou
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Peng-Yang Li
- Division of Cardiology, Pauley Heart Center, Virginia Commonwealth, University, Richmond, Virginia, USA
| | - Jing-Kun Zhang
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, California, USA
| | - Xue Wu
- Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA
| | - Yue-Hua Li
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming-Liang Wang
- Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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26
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Ruiz-Rizzo AL, Finke K, Archila-Meléndez ME. Diffusion Tensor Imaging in Alzheimer's Studies. Methods Mol Biol 2024; 2785:105-113. [PMID: 38427191 DOI: 10.1007/978-1-0716-3774-6_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
In this chapter, we describe the use of quantitative metrics of white matter obtained from the diffusion tensor model based on diffusion-weighted imaging in Alzheimer's disease (AD). Our description synthesizes insights not only from patient populations with AD dementia but also from participants at risk for AD dementia (e.g., amnestic mild cognitive impairment, subjective cognitive decline, or familial AD mutation carriers). A reference to studies examining correlations with behavioral variables is also included. Our main message is to caution against the overinterpretation of diffusion metrics and to favor analyses that focus on regions of interest or major white matter tracts for biomarker studies in AD.
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Affiliation(s)
| | - Kathrin Finke
- Department of Neurology, Jena University Hospital, Jena, Germany
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27
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Groechel RC, Alosco ML, Dixon D, Tripodis Y, Mez J, Goldstein L, Budson AE, Qiu WQ, Killiany RJ. Associations between white matter integrity of the cingulum bundle, surrounding gray matter regions, and cognition across the dementia continuum. J Comp Neurol 2023; 531:2162-2171. [PMID: 38010204 PMCID: PMC10841586 DOI: 10.1002/cne.25564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 10/19/2023] [Accepted: 10/21/2023] [Indexed: 11/29/2023]
Abstract
INTRODUCTION Previous Alzheimer's disease and related dementias (AD/ADRD) research studies have illustrated the significance of studying alterations in white matter (WM). Fewer studies have examined how WM integrity, measured with diffusion tensor imaging (DTI), is associated with volume of gray matter (GM) regions and measures of cognitive function in aged participants spanning the dementia continuum. METHODS Magnetic resonance imaging and cognitive data were collected from 241 Boston University Alzheimer's Disease Research Center participants who spanned from cognitively normal controls to amnestic mild cognitive impairment to having dementia. Primary DTI tracts of interest were the cingulum ventral (CV) and cingulum dorsal (CD) pathways. GM regions of interest (ROIs) were in the medial temporal lobe (MTL), prefrontal cortex, and retrosplenial cortex. Analyses of covariance models were used to assess differences in WM integrity across groups (control, amnestic mild cognitive impairment, and dementia). Multiple linear regression models were used to assess associations between WM integrity and GM volume, and with measures of memory and executive function. RESULTS Differences in WM integrity were shown in both cingulum pathways in participants across the dementia continuum. Associations between WM integrity of both cingulum pathways and volume of selected GM ROIs were widespread. Functionally significant associations were found between WM of the CV pathway and memory, independent of MTL GM volume. DISCUSSION Differences in WM integrity of the cingulum bundle and surrounding GM ROI are likely related to the progression of AD/ADRD. Such differences should continue to be studied, particularly in association with memory performance.
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Affiliation(s)
- Renée C. Groechel
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine
- National Institute of Neurological Disorders & Stroke Intramural Research Program
| | - Michael L. Alosco
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Chronic Traumatic Encephalopathy Center
| | - Diane Dixon
- Boston University Alzheimer’s Disease Research Center
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Research Center
- Department of Biostatistics, Boston University School of Public Health
| | - Jesse Mez
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Chronic Traumatic Encephalopathy Center
| | - Lee Goldstein
- Boston University Alzheimer’s Disease Research Center
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine
| | - Andrew E. Budson
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Neurology Service, VA Boston Healthcare System
| | - Wei Qiao Qiu
- Boston University Alzheimer’s Disease Research Center
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine
| | - Ronald J. Killiany
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine
- Department of Environmental Health, Boston University School of Public Health
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28
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Shirzadi Z, Schultz SA, Yau WYW, Joseph-Mathurin N, Fitzpatrick CD, Levin R, Kantarci K, Preboske GM, Jack CR, Farlow MR, Hassenstab J, Jucker M, Morris JC, Xiong C, Karch CM, Levey AI, Gordon BA, Schofield PR, Salloway SP, Perrin RJ, McDade E, Levin J, Cruchaga C, Allegri RF, Fox NC, Goate A, Day GS, Koeppe R, Chui HC, Berman S, Mori H, Sanchez-Valle R, Lee JH, Rosa-Neto P, Ruthirakuhan M, Wu CY, Swardfager W, Benzinger TLS, Sohrabi HR, Martins RN, Bateman RJ, Johnson KA, Sperling RA, Greenberg SM, Schultz AP, Chhatwal JP. Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease. JAMA Neurol 2023; 80:1353-1363. [PMID: 37843849 PMCID: PMC10580156 DOI: 10.1001/jamaneurol.2023.3618] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 06/26/2023] [Indexed: 10/17/2023]
Abstract
Importance Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors. Objective To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes. Design, Setting, and Participants This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers-the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer's Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019). Main Outcome and Measures The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH. Results Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = -3.1 [P = .002]; ADNI: t = -5.6 [P < .001]; HABS: t = -2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001). Conclusions and Relevance The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.
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Affiliation(s)
- Zahra Shirzadi
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Stephanie A. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Wai-Ying W. Yau
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | | | - Colleen D. Fitzpatrick
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Raina Levin
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Jason Hassenstab
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Tübingen, Germany
| | - John C. Morris
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Chengjie Xiong
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Celeste M. Karch
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Brian A. Gordon
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | | | - Richard J. Perrin
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Eric McDade
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, German Center for Neurodegenerative Diseases, site Munich, Munich Cluster for Systems Neurology, Munich, Germany
| | - Carlos Cruchaga
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | | | - Nick C. Fox
- UK Dementia Research Institute, University College London, London, United Kingdom
| | - Alison Goate
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor
| | - Helena C. Chui
- Keck School of Medicine, University of Southern California, Los Angeles
| | - Sarah Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Hiroshi Mori
- Osaka Metropolitan University Medical School, Osaka, Nagaoka Sutoku University, Osaka City, Niigata, Japan
| | | | - Jae-Hong Lee
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Pedro Rosa-Neto
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Myuri Ruthirakuhan
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Che-Yuan Wu
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Walter Swardfager
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | | | - Hamid R. Sohrabi
- Centre for Healthy Ageing, School of Psychology, Health Future Institute, Murdoch University, Perth, Western Australia, Australia
| | - Ralph N. Martins
- School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
| | - Randall J. Bateman
- Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Keith A. Johnson
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Reisa A. Sperling
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Steven M. Greenberg
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Aaron P. Schultz
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Jasmeer P. Chhatwal
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston
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Diao Y, Lanz B, Jelescu IO. Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer's using machine learning. Alzheimers Res Ther 2023; 15:193. [PMID: 37936236 PMCID: PMC10629161 DOI: 10.1186/s13195-023-01328-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 10/09/2023] [Indexed: 11/09/2023]
Abstract
BACKGROUND The pathological process of Alzheimer's disease (AD) typically takes decades from onset to clinical symptoms. Early brain changes in AD include MRI-measurable features such as altered functional connectivity (FC) and white matter degeneration. The ability of these features to discriminate between subjects without a diagnosis, or their prognostic value, is however not established. METHODS The main trigger mechanism of AD is still debated, although impaired brain glucose metabolism is taking an increasingly central role. Here, we used a rat model of sporadic AD, based on impaired brain glucose metabolism induced by an intracerebroventricular injection of streptozotocin (STZ). We characterized alterations in FC and white matter microstructure longitudinally using functional and diffusion MRI. Those MRI-derived measures were used to classify STZ from control rats using machine learning, and the importance of each individual measure was quantified using explainable artificial intelligence methods. RESULTS Overall, combining all the FC and white matter metrics in an ensemble way was the best strategy to discriminate STZ rats, with a consistent accuracy over 0.85. However, the best accuracy early on was achieved using white matter microstructure features, and later on using FC. This suggests that consistent damage in white matter in the STZ group might precede FC. For cross-timepoint prediction, microstructure features also had the highest performance while, in contrast, that of FC was reduced by its dynamic pattern which shifted from early hyperconnectivity to late hypoconnectivity. CONCLUSIONS Our study highlights the MRI-derived measures that best discriminate STZ vs control rats early in the course of the disease, with potential translation to humans.
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Affiliation(s)
- Yujian Diao
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Bernard Lanz
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ileana Ozana Jelescu
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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30
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Schlepckow K, Morenas-Rodríguez E, Hong S, Haass C. Stimulation of TREM2 with agonistic antibodies-an emerging therapeutic option for Alzheimer's disease. Lancet Neurol 2023; 22:1048-1060. [PMID: 37863592 DOI: 10.1016/s1474-4422(23)00247-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 06/29/2023] [Accepted: 06/29/2023] [Indexed: 10/22/2023]
Abstract
Neurodegenerative disorders, including Alzheimer's disease, are associated with microgliosis. Microglia have long been considered to have detrimental roles in Alzheimer's disease. However, functional analyses of genes encoding risk factors that are linked to late-onset Alzheimer's disease, and that are enriched or exclusively expressed in microglia, have revealed unexpected protective functions. One of the major risk genes for Alzheimer's disease is TREM2. Risk variants of TREM2 are loss-of-function mutations affecting chemotaxis, phagocytosis, lipid and energy metabolism, and survival and proliferation. Agonistic anti-TREM2 antibodies have been developed to boost these protective functions in patients with intact TREM2 alleles. Several anti-TREM2 antibodies are in early clinical trials, and current efforts aim to achieve more efficient transport of these antibodies across the blood-brain barrier. PET imaging could be used to monitor target engagement. Data from animal models, and biomarker studies in patients, further support a rationale for boosting TREM2 functions during the preclinical stage of Alzheimer's disease.
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Affiliation(s)
- Kai Schlepckow
- German Centre for Neurodegenerative Diseases, Munich, Germany
| | - Estrella Morenas-Rodríguez
- Memory Unit, Department of Neurology, Hospital Universitario 12 de Octubre, Madrid, Spain; Group of Neurogenerative Diseases, Hospital Universitario 12 de Octubre Research Institute (imas12), Madrid, Spain
| | - Soyon Hong
- UK Dementia Research Institute, Institute of Neurology, University College London, London, UK
| | - Christian Haass
- German Centre for Neurodegenerative Diseases, Munich, Germany; Metabolic Biochemistry, Biomedical Centre, Faculty of Medicine, Ludwig-Maximilians University, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
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31
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Chen H, Fan L, Guo Q, Wong MY, Yu F, Foxe N, Wang W, Nessim A, Carling G, Liu B, Lopez-Lee C, Huang Y, Amin S, Patel T, Mok SA, Song WM, Zhang B, Ma Q, Fu H, Gan L, Luo W. DAP12 deficiency alters microglia-oligodendrocyte communication and enhances resilience against tau toxicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.563970. [PMID: 37961594 PMCID: PMC10634844 DOI: 10.1101/2023.10.26.563970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Pathogenic tau accumulation fuels neurodegeneration in Alzheimer's disease (AD). Enhancing aging brain's resilience to tau pathology would lead to novel therapeutic strategies. DAP12 (DNAX-activation protein 12) is critically involved in microglial immune responses. Previous studies have showed that mice lacking DAP12 in tauopathy mice exhibit higher tau pathology but are protected from tau-induced cognitive deficits. However, the exact mechanism remains elusive. Our current study uncovers a novel resilience mechanism via microglial interaction with oligodendrocytes. Despite higher tau inclusions, Dap12 deletion curbs tau-induced brain inflammation and ameliorates myelin and synapse loss. Specifically, removal of Dap12 abolished tau-induced disease-associated clusters in microglia (MG) and intermediate oligodendrocytes (iOli), which are spatially correlated with tau pathology in AD brains. Our study highlights the critical role of interactions between microglia and oligodendrocytes in tau toxicity and DAP12 signaling as a promising target for enhancing resilience in AD.
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Affiliation(s)
- Hao Chen
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Li Fan
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Qi Guo
- Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Man Ying Wong
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Fangmin Yu
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Nessa Foxe
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | | | - Aviram Nessim
- The State University of New York at Stony Brook, Long Island, New York, USA
| | - Gillian Carling
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Bangyan Liu
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Chloe Lopez-Lee
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Yige Huang
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Sadaf Amin
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Tark Patel
- Department of Biochemistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB Canada
| | - Sue-Ann Mok
- Department of Biochemistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB Canada
| | - Won-min Song
- Department of Genetics and Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Hongjun Fu
- Department of Neuroscience, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Li Gan
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Millburn High School, New Jersey, NJ, USA
| | - Wenjie Luo
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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32
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Chen H, Fan L, Guo Q, Wong MY, Yu F, Foxe N, Wang W, Nessim A, Carling G, Liu B, Lopez-Lee C, Huang Y, Amin S, Mok SA, Song WM, Zhang B, Ma Q, Fu H, Gan L, Luo W. DAP12 deficiency alters microglia-oligodendrocyte communication and enhances resilience against tau toxicity. RESEARCH SQUARE 2023:rs.3.rs-3454358. [PMID: 37961627 PMCID: PMC10635319 DOI: 10.21203/rs.3.rs-3454358/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Pathogenic tau accumulation fuels neurodegeneration in Alzheimer's disease (AD). Enhancing aging brain's resilience to tau pathology would lead to novel therapeutic strategies. DAP12 (DNAX-activation protein 12) is critically involved in microglial immune responses. Previous studies have showed that mice lacking DAP12 in tauopathy mice exhibit higher tau pathology but are protected from tau-induced cognitive deficits. However, the exact mechanism remains elusive. Our current study uncovers a novel resilience mechanism via microglial interaction with oligodendrocytes. Despite higher tau inclusions, Dap12 deletion curbs tau-induced brain inflammation and ameliorates myelin and synapse loss. Specifically, removal of Dap12 abolished tau-induced disease-associated clusters in microglia (MG) and intermediate oligodendrocytes (iOli), which are spatially correlated with tau pathology in AD brains. Our study highlights the critical role of interactions between microglia and oligodendrocytes in tau toxicity and DAP12 signaling as a promising target for enhancing resilience in AD.
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Affiliation(s)
- Hao Chen
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Li Fan
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Qi Guo
- Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Man Ying Wong
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Fangmin Yu
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Nessa Foxe
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | | | - Aviram Nessim
- The State University of New York at Stony Brook, Long Island, New York, USA
| | - Gillian Carling
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Bangyan Liu
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Chloe Lopez-Lee
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Yige Huang
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Program of Neuroscience, Weill Graduate School of Medical Sciences of Cornell University, New York, NY, USA
| | - Sadaf Amin
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Sue-Ann Mok
- Department of Biochemistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB Canada
| | - Won-min Song
- Department of Genetics and Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Hongjun Fu
- Department of Neuroscience, College of Medicine, Ohio State University, Columbus, OH 43210 USA
| | - Li Gan
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Millburn High School, New Jersey, NJ, USA
| | - Wenjie Luo
- Helen and Robert Appel Alzheimer Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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33
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Cerneckis J, Shi Y. Myelin organoids for the study of Alzheimer's disease. Front Neurosci 2023; 17:1283742. [PMID: 37942133 PMCID: PMC10628225 DOI: 10.3389/fnins.2023.1283742] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023] Open
Affiliation(s)
- Jonas Cerneckis
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA, United States
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA, United States
| | - Yanhong Shi
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA, United States
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA, United States
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34
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Gallagher RL, Koscik RL, Moody JF, Vogt NM, Adluru N, Kecskemeti SR, Van Hulle CA, Chin NA, Asthana S, Kollmorgen G, Suridjan I, Carlsson CM, Johnson SC, Dean DC, Zetterberg H, Blennow K, Alexander AL, Bendlin BB. Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status. Alzheimers Res Ther 2023; 15:180. [PMID: 37848950 PMCID: PMC10583332 DOI: 10.1186/s13195-023-01281-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 07/27/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. METHODS Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). RESULTS Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. CONCLUSION Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.
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Affiliation(s)
- Rigina L Gallagher
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Rebecca Langhough Koscik
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Jason F Moody
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Nicholas M Vogt
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nagesh Adluru
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | | | - Carol A Van Hulle
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nathaniel A Chin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | | | | | - Cynthia M Carlsson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Sterling C Johnson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Douglas C Dean
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Henrik Zetterberg
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrew L Alexander
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Barbara B Bendlin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA.
- Wisconsin Alzheimer's Institute, Madison, WI, USA.
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Ali DG, Bahrani AA, El Khouli RH, Gold BT, Jiang Y, Zachariou V, Wilcock DM, Jicha GA. White matter hyperintensities influence distal cortical β-amyloid accumulation in default mode network pathways. Brain Behav 2023; 13:e3209. [PMID: 37534614 PMCID: PMC10570488 DOI: 10.1002/brb3.3209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). Yet, the role of SVD in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that WMHs influence amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults. METHODS Regional standard uptake value ratios (SUVr) from Aβ-PET and white matter hyperintensity (WMH) volumes from three-dimensional magnetic resonance imaging FLAIR images were analyzed across a sample of 72 clinically unimpaired (mini-mental state examination ≥26), older adults (mean age 74.96 and standard deviation 8.13) from the Alzheimer's Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ-PET SUVr in the connected cortical DMN regions was analyzed using linear regression models adjusted for age, sex, ApoE, and total brain volumes. RESULTS The regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus were associated with increased regional SUVr in the inferior parietal lobule (p = .011). CONCLUSION The findings suggest that the relation between Aβ in parietal cortex is associated with SVD in downstream white matter (WM) pathways in preclinical AD. The biological relationships and interplay between Aβ and WM microstructure alterations that precede overt WMH development across the continuum of AD progression warrant further study.
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Affiliation(s)
- Doaa G. Ali
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Ahmed A. Bahrani
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Riham H. El Khouli
- Department of Radiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Brian T. Gold
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Yang Jiang
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Valentinos Zachariou
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Physiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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36
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Qu Y, Wang P, Yao H, Wang D, Song C, Yang H, Zhang Z, Chen P, Kang X, Du K, Fan L, Zhou B, Han T, Yu C, Zhang X, Zuo N, Jiang T, Zhou Y, Liu B, Han Y, Lu J, Liu Y. Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease. Neurosci Bull 2023; 39:1533-1543. [PMID: 37014553 PMCID: PMC10533766 DOI: 10.1007/s12264-023-01041-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/29/2022] [Indexed: 04/05/2023] Open
Abstract
Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.
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Affiliation(s)
- Yida Qu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Hongxiang Yao
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Dawei Wang
- Department of Radiology, Department of Epidemiology and Health Statistics, School of Public Health, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Chengyuan Song
- Department of Neurology, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Hongwei Yang
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Zengqiang Zhang
- Branch of Chinese, PLA General Hospital, Sanya, 572022, China
| | - Pindong Chen
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaopeng Kang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kai Du
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, 300222, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuying Zhou
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Bing Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Lab of Cognition Neuroscience & Learning, Beijing Normal University, Beijing, 100091, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- Beijing Institute of Geriatrics, Beijing, 100053, China
- National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
| | - Yong Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
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Lopez-Lee C, Kodama L, Fan L, Wong MY, Foxe NR, Jiaz L, Yu F, Ye P, Zhu J, Norman K, Torres ER, Kim RD, Mousa GA, Dubal D, Liddelow S, Luo W, Gan L. Sex Chromosomes and Gonads Shape the Sex-Biased Transcriptomic Landscape in Tlr7-Mediated Demyelination During Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.19.558439. [PMID: 37781600 PMCID: PMC10541118 DOI: 10.1101/2023.09.19.558439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Demyelination occurs in aging and associated diseases, including Alzheimer's disease. Several of these diseases exhibit sex differences in prevalence and severity. Biological sex primarily stems from sex chromosomes and gonads releasing sex hormones. To dissect mechanisms underlying sex differences in demyelination of aging brains, we constructed a transcriptomic atlas of cell type-specific responses to illustrate how sex chromosomes, gonads, and their interaction shape responses to demyelination. We found that sex-biased oligodendrocyte and microglial responses are driven by interaction of sex chromosomes and gonads prior to myelin loss. Post demyelination, sex chromosomes mainly guide microglial responses, while gonadal composition influences oligodendrocyte signaling. Significantly, ablation of the X-linked gene Toll-like receptor 7 (Tlr7), which exhibited sex-biased expression during demyelination, abolished the sex-biased responses and protected against demyelination.
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Affiliation(s)
- Chloe Lopez-Lee
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY
| | - Lay Kodama
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, University of California San Francisco, San Francisco, CA
| | - Li Fan
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Man Ying Wong
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Nessa R. Foxe
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Laraib Jiaz
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Fangmin Yu
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Pearly Ye
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Jingjie Zhu
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Kendra Norman
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Eileen Ruth Torres
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Rachel D. Kim
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY
| | - Gergey Alzaem Mousa
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Dena Dubal
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA
| | - Shane Liddelow
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY
- Department of Neuroscience & Physiology, NYU Grossman School of Medicine, New York, NY
- Department of Ophthalmology, NYU Grossman School of Medicine, New York, NY
- Parekh Center for Interdisciplinary Neurology, NYU Grossman School of Medicine, New York, NY
| | - Wenjie Luo
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Li Gan
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY
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38
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Yang S, Park JH, Lu HC. Axonal energy metabolism, and the effects in aging and neurodegenerative diseases. Mol Neurodegener 2023; 18:49. [PMID: 37475056 PMCID: PMC10357692 DOI: 10.1186/s13024-023-00634-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 06/08/2023] [Indexed: 07/22/2023] Open
Abstract
Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.
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Affiliation(s)
- Sen Yang
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Jung Hyun Park
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Hui-Chen Lu
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA.
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39
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Byun MS, Chang M, Yi D, Ahn H, Han D, Jeon S, Jang H, Lee DY, Oh SH. Association of Central Auditory Processing Dysfunction With Preclinical Alzheimer's Disease. Otolaryngol Head Neck Surg 2023; 169:112-119. [PMID: 36939433 PMCID: PMC10846842 DOI: 10.1002/ohn.228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/13/2022] [Accepted: 11/21/2022] [Indexed: 01/30/2023]
Abstract
OBJECTIVE To investigate whether central auditory processing dysfunction measured by the dichotic digit test-1 digit (DDT1) is present in preclinical Alzheimer's disease (AD) individuals who are cognitively normal (CN) older adults with the cerebral beta-amyloid (Aβ) deposition and to explore the potential of the DDT1 as a screening test for preclinical AD. STUDY DESIGN Cross-sectional design. SETTING A prospective observational cohort study. METHODS CN older adults with a global clinical dementia rating score of 0 were included. The hearing test battery including pure-tone audiometry, speech audiometry, distortion product otoacoustic emission, and DDT1 was administered to participants. RESULTS Fifty CN older adults were included. Among them, 38 individuals were included in the Aβ deposition negative (AN) group and 12 were included in the Aβ deposition positive (AP) group. The DDT1 scores of both the better and worse ears were significantly lower in the AP group than in the AN group (p = .008 and p = .015, respectively). No significant differences were observed between the groups in tests of the peripheral auditory pathways. In multivariable logistic regression analysis adjusted for apolipoprotein E4 positivity, the DDT1 better ear score predicted the AP group (p = .036, odds ratio = 0.892, 95% confidence interval: 0.780-0.985) with relatively high diagnostic accuracy. CONCLUSION Our findings suggest that Aβ deposition may affect the central auditory pathway even before cognitive decline appears. DDT1, which can easily be applied to the old-age population, may have the potential as a screening tool for preclinical AD.
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Affiliation(s)
- Min Soo Byun
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Munyoung Chang
- Department of Otolaryngology–Head and Neck Surgery, Chung-Ang University College of Medicine, Seoul, South Korea
- Department of Otolaryngology–Head and Neck Surgery, Chung-Ang University Hospital, Seoul, South Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Centre, Seoul National University, Seoul, South Korea
| | - Hyejin Ahn
- Interdisciplinary Program of Cognitive Science, Seoul National University College of Humanities, Seoul, South Korea
| | - Dongkyun Han
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Seulki Jeon
- Department of Otolaryngology–Head and Neck Surgery, Seoul National University Hospital, Seoul, South Korea
| | - Hyunsook Jang
- Division of Speech Pathology and Audiology, Research Institute of Audiology & Speech Pathology, Hallym University, Chuncheon-si, Gangwon-do, South Korea
| | - Dong Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Institute of Human Behavioral Medicine, Medical Research Centre, Seoul National University, Seoul, South Korea
| | - Seung Ha Oh
- Department of Otolaryngology–Head and Neck Surgery, Seoul National University Hospital, Seoul, South Korea
- Department of Otolaryngology–Head and Neck Surgery, Seoul National University College of Medicine, Seoul, South Korea
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40
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Liu H, Cai H, Yang D, Zhu W, Wu G, Chen J. Learning pyramidal multi-scale harmonic wavelets for identifying the neuropathology propagation patterns of Alzheimer's disease. Med Image Anal 2023; 87:102812. [PMID: 37196535 PMCID: PMC10503391 DOI: 10.1016/j.media.2023.102812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 02/25/2023] [Accepted: 04/07/2023] [Indexed: 05/19/2023]
Abstract
Previous studies have established that neurodegenerative disease such as Alzheimer's disease (AD) is a disconnection syndrome, where the neuropathological burdens often propagate across the brain network to interfere with the structural and functional connections. In this context, identifying the propagation patterns of neuropathological burdens sheds new light on understanding the pathophysiological mechanism of AD progression. However, little attention has been paid to propagation pattern identification by fully considering the intrinsic properties of brain-network organization, which plays an important role in improving the interpretability of the identified propagation pathways. To this end, we propose a novel harmonic wavelet analysis approach to construct a set of region-specific pyramidal multi-scale harmonic wavelets, it allows us to characterize the propagation patterns of neuropathological burdens from multiple hierarchical modules across the brain network. Specifically, we first extract underlying hub nodes through a series of network centrality measurements on the common brain network reference generated from a population of minimum spanning tree (MST) brain networks. Then, we propose a manifold learning method to identify the region-specific pyramidal multi-scale harmonic wavelets corresponding to hub nodes by seamlessly integrating the hierarchically modular property of the brain network. We estimate the statistical power of our proposed harmonic wavelet analysis approach on synthetic data and large-scale neuroimaging data from ADNI. Compared with the other harmonic analysis techniques, our proposed method not only effectively predicts the early stage of AD but also provides a new window to capture the underlying hub nodes and the propagation pathways of neuropathological burdens in AD.
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Affiliation(s)
- Huan Liu
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guandong 510006, China
| | - Hongmin Cai
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guandong 510006, China
| | - Defu Yang
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Wentao Zhu
- Zhejiang Lab, Hangzhou, Zhejiang 311121, China
| | - Guorong Wu
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiazhou Chen
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guandong 510006, China.
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41
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Depp C, Sun T, Sasmita AO, Spieth L, Berghoff SA, Nazarenko T, Overhoff K, Steixner-Kumar AA, Subramanian S, Arinrad S, Ruhwedel T, Möbius W, Göbbels S, Saher G, Werner HB, Damkou A, Zampar S, Wirths O, Thalmann M, Simons M, Saito T, Saido T, Krueger-Burg D, Kawaguchi R, Willem M, Haass C, Geschwind D, Ehrenreich H, Stassart R, Nave KA. Myelin dysfunction drives amyloid-β deposition in models of Alzheimer's disease. Nature 2023; 618:349-357. [PMID: 37258678 PMCID: PMC10247380 DOI: 10.1038/s41586-023-06120-6] [Citation(s) in RCA: 178] [Impact Index Per Article: 89.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 04/21/2023] [Indexed: 06/02/2023]
Abstract
The incidence of Alzheimer's disease (AD), the leading cause of dementia, increases rapidly with age, but why age constitutes the main risk factor is still poorly understood. Brain ageing affects oligodendrocytes and the structural integrity of myelin sheaths1, the latter of which is associated with secondary neuroinflammation2,3. As oligodendrocytes support axonal energy metabolism and neuronal health4-7, we hypothesized that loss of myelin integrity could be an upstream risk factor for neuronal amyloid-β (Aβ) deposition, the central neuropathological hallmark of AD. Here we identify genetic pathways of myelin dysfunction and demyelinating injuries as potent drivers of amyloid deposition in mouse models of AD. Mechanistically, myelin dysfunction causes the accumulation of the Aβ-producing machinery within axonal swellings and increases the cleavage of cortical amyloid precursor protein. Suprisingly, AD mice with dysfunctional myelin lack plaque-corralling microglia despite an overall increase in their numbers. Bulk and single-cell transcriptomics of AD mouse models with myelin defects show that there is a concomitant induction of highly similar but distinct disease-associated microglia signatures specific to myelin damage and amyloid plaques, respectively. Despite successful induction, amyloid disease-associated microglia (DAM) that usually clear amyloid plaques are apparently distracted to nearby myelin damage. Our data suggest a working model whereby age-dependent structural defects of myelin promote Aβ plaque formation directly and indirectly and are therefore an upstream AD risk factor. Improving oligodendrocyte health and myelin integrity could be a promising target to delay development and slow progression of AD.
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Affiliation(s)
- Constanze Depp
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
| | - Ting Sun
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Andrew Octavian Sasmita
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Lena Spieth
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Stefan A Berghoff
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Taisiia Nazarenko
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Katharina Overhoff
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Agnes A Steixner-Kumar
- Clinical Neuroscience, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Swati Subramanian
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Sahab Arinrad
- Clinical Neuroscience, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Torben Ruhwedel
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Wiebke Möbius
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Sandra Göbbels
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Gesine Saher
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Hauke B Werner
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Alkmini Damkou
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Silvia Zampar
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Oliver Wirths
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Maik Thalmann
- Department of German Philology, Georg-August University, Göttingen, Germany
| | - Mikael Simons
- Institute of Neuronal Cell Biology, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster of Systems Neurology (SyNergy), Munich, Germany
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, Japan
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Takaomi Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Dilja Krueger-Burg
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
- Department of Molecular Neurobiology, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael Willem
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster of Systems Neurology (SyNergy), Munich, Germany
- Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Christian Haass
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster of Systems Neurology (SyNergy), Munich, Germany
- Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Hannelore Ehrenreich
- Clinical Neuroscience, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Ruth Stassart
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Paul-Flechsig-Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Klaus-Armin Nave
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
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42
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Zanon Zotin MC, Yilmaz P, Sveikata L, Schoemaker D, van Veluw SJ, Etherton MR, Charidimou A, Greenberg SM, Duering M, Viswanathan A. Peak Width of Skeletonized Mean Diffusivity: A Neuroimaging Marker for White Matter Injury. Radiology 2023; 306:e212780. [PMID: 36692402 PMCID: PMC9968775 DOI: 10.1148/radiol.212780] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 10/01/2022] [Accepted: 10/14/2022] [Indexed: 01/25/2023]
Abstract
A leading cause of white matter (WM) injury in older individuals is cerebral small vessel disease (SVD). Cerebral SVD is the most prevalent vascular contributor to cognitive impairment and dementia. Therapeutic progress for cerebral SVD and other WM disorders depends on the development and validation of neuroimaging markers suitable as outcome measures in future interventional trials. Diffusion-tensor imaging (DTI) is one of the best-suited MRI techniques for assessing the extent of WM damage in the brain. But the optimal method to analyze individual DTI data remains hindered by labor-intensive and time-consuming processes. Peak width of skeletonized mean diffusivity (PSMD), a recently developed fast, fully automated DTI marker, was designed to quantify the WM damage secondary to cerebral SVD and reflect related cognitive impairment. Despite its promising results, knowledge about PSMD is still limited in the radiologic community. This focused review provides an overview of the technical details of PSMD while synthesizing the available data on its clinical and neuroimaging associations. From a critical expert viewpoint, the authors discuss the limitations of PSMD and its current validation status as a neuroimaging marker for vascular cognitive impairment. Finally, they point out the gaps to be addressed to further advance the field.
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Affiliation(s)
| | | | - Lukas Sveikata
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Dorothee Schoemaker
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Susanne J. van Veluw
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Mark R. Etherton
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Andreas Charidimou
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Steven M. Greenberg
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Marco Duering
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Anand Viswanathan
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
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43
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Quan M, Wang Q, Qin W, Wang W, Li F, Zhao T, Li T, Qiu Q, Cao S, Wang S, Wang Y, Jin H, Zhou A, Fang J, Jia L, Jia J. Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease. Alzheimers Res Ther 2023; 15:40. [PMID: 36850008 PMCID: PMC9972804 DOI: 10.1186/s13195-023-01192-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023]
Abstract
BACKGROUND Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD. METHODS One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation. RESULTS Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups. CONCLUSIONS There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.
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Affiliation(s)
- Meina Quan
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qi Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Qin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Fangyu Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Tan Zhao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Tingting Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qiongqiong Qiu
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shuman Cao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shiyuan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Yan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Hongmei Jin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Aihong Zhou
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jiliang Fang
- grid.464297.aGuang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Longfei Jia
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. .,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China. .,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China. .,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China. .,Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
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44
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Sharp FR, DeCarli CS, Jin LW, Zhan X. White matter injury, cholesterol dysmetabolism, and APP/Abeta dysmetabolism interact to produce Alzheimer's disease (AD) neuropathology: A hypothesis and review. Front Aging Neurosci 2023; 15:1096206. [PMID: 36845656 PMCID: PMC9950279 DOI: 10.3389/fnagi.2023.1096206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/30/2023] [Indexed: 02/12/2023] Open
Abstract
We postulate that myelin injury contributes to cholesterol release from myelin and cholesterol dysmetabolism which contributes to Abeta dysmetabolism, and combined with genetic and AD risk factors, leads to increased Abeta and amyloid plaques. Increased Abeta damages myelin to form a vicious injury cycle. Thus, white matter injury, cholesterol dysmetabolism and Abeta dysmetabolism interact to produce or worsen AD neuropathology. The amyloid cascade is the leading hypothesis for the cause of Alzheimer's disease (AD). The failure of clinical trials based on this hypothesis has raised other possibilities. Even with a possible new success (Lecanemab), it is not clear whether this is a cause or a result of the disease. With the discovery in 1993 that the apolipoprotein E type 4 allele (APOE4) was the major risk factor for sporadic, late-onset AD (LOAD), there has been increasing interest in cholesterol in AD since APOE is a major cholesterol transporter. Recent studies show that cholesterol metabolism is intricately involved with Abeta (Aβ)/amyloid transport and metabolism, with cholesterol down-regulating the Aβ LRP1 transporter and upregulating the Aβ RAGE receptor, both of which would increase brain Aβ. Moreover, manipulating cholesterol transport and metabolism in rodent AD models can ameliorate pathology and cognitive deficits, or worsen them depending upon the manipulation. Though white matter (WM) injury has been noted in AD brain since Alzheimer's initial observations, recent studies have shown abnormal white matter in every AD brain. Moreover, there is age-related WM injury in normal individuals that occurs earlier and is worse with the APOE4 genotype. Moreover, WM injury precedes formation of plaques and tangles in human Familial Alzheimer's disease (FAD) and precedes plaque formation in rodent AD models. Restoring WM in rodent AD models improves cognition without affecting AD pathology. Thus, we postulate that the amyloid cascade, cholesterol dysmetabolism and white matter injury interact to produce and/or worsen AD pathology. We further postulate that the primary initiating event could be related to any of the three, with age a major factor for WM injury, diet and APOE4 and other genes a factor for cholesterol dysmetabolism, and FAD and other genes for Abeta dysmetabolism.
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Affiliation(s)
- Frank R. Sharp
- Department of Neurology, The MIND Institute, University of California at Davis Medical Center, Sacramento, CA, United States
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45
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Chen Q, Abrigo J, Deng M, Shi L, Wang YX, Chu WCW. Diffusion Changes in Hippocampal Cingulum in Early Biologically Defined Alzheimer's Disease. J Alzheimers Dis 2023; 91:1007-1017. [PMID: 36530082 DOI: 10.3233/jad-220671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Diagnosis of Alzheimer's disease (AD) was recently shifted from clinical to biological construct to reflect underlying neuropathological status, where amyloid deposition designated patients to the Alzheimer's continuum, and additional tau positivity represented AD. OBJECTIVE To investigate white matter (WM) alteration in the brain of patients in the Alzheimer's continuum. METHODS A total of 236 subjects across the clinical and biological spectra of AD were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding five groups: A-T-cognitively normal (CN), A+T-CN, A+T+ CN, A+T+ mild cognitive impairment, and A+T+ AD. WM alteration was measured by diffusion tensor imaging (DTI). Group differences, correlation of DTI measures with amyloid and tau, and diagnostic performance of such measures were evaluated. RESULTS Compared with A-T-CN, widespread WM alteration was observed in the Alzheimer's continuum, including hippocampal cingulum (CGH), cingulum of the cingulate gyrus, and uncinate fasciculus. Diffusion changes measured by regional mean fractional anisotropy (FA) in the bilateral CGH were first detected in the A+T+ CN group and associated with tau burden in the Alzheimer's continuum (p < 0.001). For discrimination between A+T+ CN and A-T-CN groups, CGH FA achieved accuracy, sensitivity, and specificity of 74%, 58%, and 78% for right CGH and 57%, 83%, and 47% respectively for left CGH. CONCLUSION WM alteration is widespread in the Alzheimer's continuum. Diffusion alteration in CGH occurred early and was correlated with tau pathology, thus may be a promising biomarker in preclinical AD.
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Affiliation(s)
- Qianyun Chen
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jill Abrigo
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Min Deng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yi-Xiang Wang
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Winnie Chiu Wing Chu
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
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46
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Marcolini S, Rojczyk P, Seitz-Holland J, Koerte IK, Alosco ML, Bouix S. Posttraumatic Stress and Traumatic Brain Injury: Cognition, Behavior, and Neuroimaging Markers in Vietnam Veterans. J Alzheimers Dis 2023; 95:1427-1448. [PMID: 37694363 PMCID: PMC10578246 DOI: 10.3233/jad-221304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/24/2023] [Indexed: 09/12/2023]
Abstract
BACKGROUND Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are common in Veterans and linked to behavioral disturbances, increased risk of cognitive decline, and Alzheimer's disease. OBJECTIVE We studied the synergistic effects of PTSD and TBI on behavioral, cognitive, and neuroimaging measures in Vietnam war Veterans. METHODS Data were acquired at baseline and after about one-year from male Veterans categorized into: PTSD, TBI, PTSD+TBI, and Veteran controls without PTSD or TBI. We applied manual tractography to examine white matter microstructure of three fiber tracts: uncinate fasciculus (N = 91), cingulum (N = 87), and inferior longitudinal fasciculus (N = 95). ANCOVAs were used to compare Veterans' baseline behavioral and cognitive functioning (N = 285), white matter microstructure, amyloid-β (N = 230), and tau PET (N = 120). Additional ANCOVAs examined scores' differences from baseline to follow-up. RESULTS Veterans with PTSD and PTSD+TBI, but not Veterans with TBI only, exhibited poorer behavioral and cognitive functioning at baseline than controls. The groups did not differ in baseline white matter, amyloid-β, or tau, nor in behavioral and cognitive functioning, and tau accumulation change. Progression of white matter abnormalities of the uncinate fasciculus in Veterans with PTSD compared to controls was observed; analyses in TBI and PTSD+TBI were not run due to insufficient sample size. CONCLUSIONS PTSD and PTSD+TBI negatively affect behavioral and cognitive functioning, while TBI does not contribute independently. Whether progressive decline in uncinate fasciculus microstructure in Veterans with PTSD might account for cognitive decline should be further studied. Findings did not support an association between PTSD, TBI, and Alzheimer's disease pathology based on amyloid and tau PET.
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Affiliation(s)
- Sofia Marcolini
- Department of Neurology and Alzheimer Center, University Medical Center Groningen, Groningen, The Netherlands
| | - Philine Rojczyk
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, Germany
| | - Johanna Seitz-Holland
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Inga K. Koerte
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, Germany
| | - Michael L. Alosco
- Department of Neurology, Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Software Engineering and Information Technology, École de Technologie Supe´rieure, Montre´al, Canada
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47
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Han S, Gim Y, Jang EH, Hur EM. Functions and dysfunctions of oligodendrocytes in neurodegenerative diseases. Front Cell Neurosci 2022; 16:1083159. [PMID: 36605616 PMCID: PMC9807813 DOI: 10.3389/fncel.2022.1083159] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Neurodegenerative diseases (NDDs) are characterized by the progressive loss of selectively vulnerable populations of neurons, which is responsible for the clinical symptoms. Although degeneration of neurons is a prominent feature that undoubtedly contributes to and defines NDD pathology, it is now clear that neuronal cell death is by no means mediated solely by cell-autonomous mechanisms. Oligodendrocytes (OLs), the myelinating cells of the central nervous system (CNS), enable rapid transmission of electrical signals and provide metabolic and trophic support to neurons. Recent evidence suggests that OLs and their progenitor population play a role in the onset and progression of NDDs. In this review, we discuss emerging evidence suggesting a role of OL lineage cells in the pathogenesis of age-related NDDs. We start with multiple system atrophy, an NDD with a well-known oligodendroglial pathology, and then discuss Alzheimer's disease (AD) and Parkinson's disease (PD), NDDs which have been thought of as neuronal origins. Understanding the functions and dysfunctions of OLs might lead to the advent of disease-modifying strategies against NDDs.
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Affiliation(s)
- Seungwan Han
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, South Korea
- BK21 Four Future Veterinary Medicine Leading Education and Research Center, College of Veterinary Medicine, Seoul National University, Seoul, South Korea
| | - Yunho Gim
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, South Korea
- BK21 Four Future Veterinary Medicine Leading Education and Research Center, College of Veterinary Medicine, Seoul National University, Seoul, South Korea
| | - Eun-Hae Jang
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, South Korea
- Comparative Medicine Disease Research Center, Seoul National University, Seoul, South Korea
| | - Eun-Mi Hur
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, South Korea
- BK21 Four Future Veterinary Medicine Leading Education and Research Center, College of Veterinary Medicine, Seoul National University, Seoul, South Korea
- Comparative Medicine Disease Research Center, Seoul National University, Seoul, South Korea
- Interdisciplinary Program in Neuroscience, College of Natural Sciences, Seoul National University, Seoul, South Korea
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48
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Schoemaker D, Zanon Zotin MC, Chen K, Igwe KC, Vila-Castelar C, Martinez J, Baena A, Fox-Fuller JT, Lopera F, Reiman EM, Brickman AM, Quiroz YT. White matter hyperintensities are a prominent feature of autosomal dominant Alzheimer’s disease that emerge prior to dementia. Alzheimers Res Ther 2022; 14:89. [PMID: 35768838 PMCID: PMC9245224 DOI: 10.1186/s13195-022-01030-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/06/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
To promote the development of effective therapies, there is an important need to characterize the full spectrum of neuropathological changes associated with Alzheimer’s disease. In line with this need, this study examined white matter abnormalities in individuals with early-onset autosomal dominant Alzheimer’s disease, in relation to age and symptom severity.
Methods
This is a cross-sectional analysis of data collected in members of a large kindred with a PSEN1 E280A mutation. Participants were recruited between September 2011 and July 2012 from the Colombian Alzheimer’s Prevention Initiative registry. The studied cohort comprised 50 participants aged between 20 and 55 years, including 20 cognitively unimpaired mutation carriers, 9 cognitively impaired mutation carriers, and 21 non-carriers. Participants completed an MRI, a lumbar puncture for cerebrospinal fluid collection, a florbetapir PET scan, and neurological and neuropsychological examinations. The volume of white matter hyperintensities (WMH) was compared between cognitively unimpaired carriers, cognitively impaired carriers, and non-carriers. Relationships between WMH, age, and cognitive performance were further examined in mutation carriers.
Results
The mean (SD) age of participants was 35.8 (9.6) years and 64% were women. Cardiovascular risk factors were uncommon and did not differ across groups. Cognitively impaired carriers [median, 6.37; interquartile range (IQR), 9.15] had an increased volume of WMH compared to both cognitively unimpaired carriers [median, 0.85; IQR, 0.79] and non-carriers [median, 1.07; IQR, 0.71]. In mutation carriers, the volume of WMH strongly correlated with cognition and age, with evidence for an accelerated rate of changes after the age of 43 years, 1 year earlier than the estimated median age of symptom onset. In multivariable regression models including cortical amyloid retention, superior parietal lobe cortical thickness, and cerebrospinal fluid phospho-tau, the volume of WMH was the only biomarker independently and significantly contributing to the total explained variance in cognitive performance.
Conclusions
The volume of WMH is increased among individuals with symptomatic autosomal-dominant Alzheimer’s disease, begins to increase prior to clinical symptom onset, and is an independent determinant of cognitive performance in this group. These findings suggest that WMH are a key component of autosomal-dominant Alzheimer’s disease that is closely related to the progression of clinical symptoms.
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49
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Littau JL, Velilla L, Hase Y, Villalba‐Moreno ND, Hagel C, Drexler D, Osorio Restrepo S, Villegas A, Lopera F, Vargas S, Glatzel M, Krasemann S, Quiroz YT, Arboleda‐Velasquez JF, Kalaria R, Sepulveda‐Falla D. Evidence of beta amyloid independent small vessel disease in familial Alzheimer's disease. Brain Pathol 2022; 32:e13097. [PMID: 35695802 PMCID: PMC9616091 DOI: 10.1111/bpa.13097] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 05/24/2022] [Indexed: 12/04/2022] Open
Abstract
We studied small vessel disease (SVD) pathology in Familial Alzheimer's disease (FAD) subjects carrying the presenilin 1 (PSEN1) p.Glu280Ala mutation in comparison to those with sporadic Alzheimer's disease (SAD) as a positive control for Alzheimer's pathology and Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) bearing different NOTCH3 mutations, as positive controls for SVD pathology. Upon magnetic resonance imaging (MRI) in life, some FAD showed mild white matter hyperintensities and no further radiologic evidence of SVD. In post-mortem studies, total SVD pathology in cortical areas and basal ganglia was similar in PSEN1 FAD and CADASIL subjects, except for the feature of arteriosclerosis which was higher in CADASIL subjects than in PSEN1 FAD subjects. Further only a few SAD subjects showed a similar degree of SVD pathology as observed in CADASIL. Furthermore, we found significantly enlarged perivascular spaces in vessels devoid of cerebral amyloid angiopathy in FAD compared with SAD and CADASIL subjects. As expected, there was greater fibrinogen-positive perivascular reactivity in CADASIL but similar reactivity in PSEN1 FAD and SAD groups. Fibrinogen immunoreactivity correlated with onset age in the PSEN1 FAD cases, suggesting increased vascular permeability may contribute to cognitive decline. Additionally, we found reduced perivascular expression of PDGFRβ AQP4 in microvessels with enlarged PVS in PSEN1 FAD cases. We demonstrate that there is Aβ-independent SVD pathology in PSEN1 FAD, that was marginally lower than that in CADASIL subjects although not evident by MRI. These observations suggest presence of covert SVD even in PSEN1, contributing to disease progression. As is the case in SAD, these consequences may be preventable by early recognition and actively controlling vascular disease risk, even in familial forms of dementia.
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Affiliation(s)
- Jessica Lisa Littau
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Lina Velilla
- Neuroscience Group of AntioquiaUniversity of AntioquiaMedellín
| | - Yoshiki Hase
- Neurovascular Research GroupTranslational and Clinical Research Institute, Newcastle UniversityNewcastle upon Tyne
| | | | - Christian Hagel
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Dagmar Drexler
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | | | - Andres Villegas
- Neuroscience Group of AntioquiaUniversity of AntioquiaMedellín
| | | | - Sergio Vargas
- Department of Radiology, Neuroradiology SectionUniversidad de AntioquiaMedellínColombia
| | - Markus Glatzel
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Susanne Krasemann
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Yakeel T. Quiroz
- Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Joseph F. Arboleda‐Velasquez
- Schepens Eye Research Institute of Mass Eye and Ear and the Department of Ophthalmology at Harvard Medical SchoolBostonMassachusetts
| | - Rajesh Kalaria
- Neurovascular Research GroupTranslational and Clinical Research Institute, Newcastle UniversityNewcastle upon Tyne
| | - Diego Sepulveda‐Falla
- Institute of NeuropathologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Neuroscience Group of AntioquiaUniversity of AntioquiaMedellín
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50
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Ruiz-Rizzo AL, Viviano RP, Daugherty AM, Finke K, Müller HJ, Damoiseaux JS. Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor: Cingulo-opercular network in SCD. Neuroimage 2022; 263:119662. [PMID: 36198354 DOI: 10.1016/j.neuroimage.2022.119662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/19/2022] [Accepted: 10/01/2022] [Indexed: 11/18/2022] Open
Abstract
Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 ± 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.
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Affiliation(s)
- Adriana L Ruiz-Rizzo
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany; Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena 07747, Germany.
| | - Raymond P Viviano
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Ana M Daugherty
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Kathrin Finke
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany; Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena 07747, Germany
| | - Hermann J Müller
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich 80802, Germany
| | - Jessica S Damoiseaux
- Department of Psychology and Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
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