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Singh NA, Sintini I. Editorial: New insights into atypical Alzheimer's disease: from clinical phenotype to biomarkers. Front Neurosci 2024; 18:1414443. [PMID: 38745936 PMCID: PMC11091363 DOI: 10.3389/fnins.2024.1414443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 04/16/2024] [Indexed: 05/16/2024] Open
Affiliation(s)
| | - Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
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Singh NA, Goodrich AW, Graff-Radford J, Machulda MM, Sintini I, Carlos AF, Robinson CG, Reid RI, Lowe VJ, Jack CR, Petersen RC, Boeve BF, Josephs KA, Kantarci K, Whitwell JL. Altered structural and functional connectivity in Posterior Cortical Atrophy and Dementia with Lewy bodies. Neuroimage 2024; 290:120564. [PMID: 38442778 PMCID: PMC11019668 DOI: 10.1016/j.neuroimage.2024.120564] [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: 02/12/2024] [Accepted: 03/03/2024] [Indexed: 03/07/2024] Open
Abstract
Posterior cortical atrophy (PCA) and dementia with Lewy bodies (DLB) show distinct atrophy and overlapping hypometabolism profiles, but it is unknown how disruptions in structural and functional connectivity compare between these disorders and whether breakdowns in connectivity relate to either atrophy or hypometabolism. Thirty amyloid-positive PCA patients, 24 amyloid-negative DLB patients and 30 amyloid-negative cognitively unimpaired (CU) healthy individuals were recruited at Mayo Clinic, Rochester, MN, and underwent a 3T head MRI, including structural MRI, resting state functional MRI (rsfMRI) and diffusion tensor imaging (DTI) sequences, as well as [18F] fluorodeoxyglucose (FDG) PET. We assessed functional connectivity within and between 12 brain networks using rsfMRI and the CONN functional connectivity toolbox and calculated regional DTI metrics using the Johns Hopkins atlas. Multivariate linear-regression models corrected for multiple comparisons and adjusted for age and sex compared DTI metrics and within-network and between-network functional connectivity across groups. Regional gray-matter volumes and FDG-PET standard uptake value ratios (SUVRs) were calculated and analyzed at the voxel-level using SPM12. We used univariate linear-regression models to investigate the relationship between connectivity measures, gray-matter volume, and FDG-PET SUVR. On DTI, PCA showed degeneration in occipito-parietal white matter, posterior thalamic radiations, splenium of the corpus collosum and sagittal stratum compared to DLB and CU, with greater degeneration in the temporal white matter and the fornix compared to CU. We observed no white-matter degeneration in DLB compared to CU. On rsfMRI, reduced within-network connectivity was present in dorsal and ventral default mode networks (DMN) and the dorsal-attention network in PCA compared to DLB and CU, with reduced within-network connectivity in the visual and sensorimotor networks compared to CU. DLB showed reduced connectivity in the cerebellar network compared to CU. Between-network analysis showed increased connectivity in both cerebellar-to-sensorimotor and cerebellar-to-dorsal attention network connectivity in PCA and DLB. PCA showed reduced anterior DMN-to-cerebellar and dorsal attention-to-sensorimotor connectivity, while DLB showed reduced posterior DMN-to-sensorimotor connectivity compared to CU. PCA showed reduced dorsal DMN-to-visual connectivity compared to DLB. The multimodal analysis revealed weak associations between functional connectivity and volume in PCA, and between functional connectivity and metabolism in DLB. These findings suggest that PCA and DLB have unique connectivity alterations, with PCA showing more widespread disruptions in both structural and functional connectivity; yet some overlap was observed with both disorders showing increased connectivity from the cerebellum.
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Affiliation(s)
| | - Austin W Goodrich
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | | | - Mary M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, United States
| | - Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Arenn F Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | | | - Robert I Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, United States; Department of Information Technology, Mayo Clinic, Rochester, MN, United States
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
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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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Hammers DB, Nemes S, Diedrich T, Eloyan A, Kirby K, Aisen P, Kramer J, Nudelman K, Foroud T, Rumbaugh M, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha SJ, Turner RS, Weintraub S, Wingo TS, Wolk DA, Wong B, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Learning slopes in early-onset Alzheimer's disease. Alzheimers Dement 2023; 19 Suppl 9:S19-S28. [PMID: 37243937 PMCID: PMC10806757 DOI: 10.1002/alz.13159] [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: 12/08/2022] [Revised: 02/16/2023] [Accepted: 02/16/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Investigation of learning slopes in early-onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early-onset dementia with and without β-amyloid positivity METHOD: Data from 310 participants in the Longitudinal Early-Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric-the learning ratio (LR)-outperformed other learning slope calculations across analyses CONCLUSIONS: Learning slopes appear to be sensitive to early-onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. HIGHLIGHTS Learning is impaired in amyloid-positive EOAD, beyond cognitive severity scores alone. Amyloid-positive EOAD participants perform worse on learning slopes than amyloid-negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sára Nemes
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Taylor Diedrich
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Joel Kramer
- Department of Neurology, University of California, San Francisco, California, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C. Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Steve Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon J. Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Sandra Weintraub
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bonnie Wong
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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Hammers DB, Eloyan A, Taurone A, Thangarajah M, Beckett L, Gao S, Kirby K, Aisen P, Dage JL, Foroud T, Griffin P, Grinberg LT, Jack CR, Kramer J, Koeppe R, Kukull WA, Mundada NS, Joie RL, Soleimani-Meigooni DN, Iaccarino L, Murray ME, Nudelman K, Polsinelli AJ, Rumbaugh M, Toga A, Touroutoglou A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez MF, Womack K, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha SJ, Turner RS, Wingo TS, Wolk DA, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Profiling baseline performance on the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort near the midpoint of data collection. Alzheimers Dement 2023; 19 Suppl 9:S8-S18. [PMID: 37256497 PMCID: PMC10806768 DOI: 10.1002/alz.13160] [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: 02/02/2023] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 06/01/2023]
Abstract
OBJECTIVE The Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early-onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data-collection mid-point. METHODS Data from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid-positive EOAD [n = 212], and amyloid-negative early-onset non-Alzheimer's disease [EOnonAD; n = 70]). RESULTS Cognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures. CONCLUSIONS We present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant. HIGHLIGHTS Findings represent the most comprehensive baseline characterization of sporadic early-onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups. EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group. Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Alexander Taurone
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Maryanne Thangarajah
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Laurel Beckett
- Department of Public Health Sciences, University of California – Davis, Davis, California, USA
| | - Sujuan Gao
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Lea T. Grinberg
- Department of Pathology, University of California – San Francisco, San Francisco, California, USA
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Joel Kramer
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Nidhi S Mundada
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Leonardo Iaccarino
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Angelina J. Polsinelli
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Steven Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon J. Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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Liu Z, Chao J, Wang C, Sun G, Roeth D, Liu W, Chen X, Li L, Tian E, Feng L, Davtyan H, Blurton-Jones M, Kalkum M, Shi Y. Astrocytic response mediated by the CLU risk allele inhibits OPC proliferation and myelination in a human iPSC model. Cell Rep 2023; 42:112841. [PMID: 37494190 PMCID: PMC10510531 DOI: 10.1016/j.celrep.2023.112841] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 05/05/2023] [Accepted: 07/05/2023] [Indexed: 07/28/2023] Open
Abstract
The C allele of rs11136000 variant in the clusterin (CLU) gene represents the third strongest known genetic risk factor for late-onset Alzheimer's disease. However, whether this single-nucleotide polymorphism (SNP) is functional and what the underlying mechanisms are remain unclear. In this study, the CLU rs11136000 SNP is identified as a functional variant by a small-scale CRISPR-Cas9 screen. Astrocytes derived from isogenic induced pluripotent stem cells (iPSCs) carrying the "C" or "T" allele of the CLU rs11136000 SNP exhibit different CLU expression levels. TAR DNA-binding protein-43 (TDP-43) preferentially binds to the "C" allele to promote CLU expression and exacerbate inflammation. The interferon response and CXCL10 expression are elevated in cytokine-treated C/C astrocytes, leading to inhibition of oligodendrocyte progenitor cell (OPC) proliferation and myelination. Accordingly, elevated CLU and CXCL10 but reduced myelin basic protein (MBP) expression are detected in human brains of C/C carriers. Our study uncovers a mechanism underlying reduced white matter integrity observed in the CLU rs11136000 risk "C" allele carriers.
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Affiliation(s)
- Zhenqing Liu
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Jianfei Chao
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Cheng Wang
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Guihua Sun
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Daniel Roeth
- Department of Molecular Imaging and Therapy, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Wei Liu
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA; Department of Immunology, Hebei Medical University, Shijiazhuang, Hebei 050017, China
| | - Xianwei Chen
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Li Li
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - E Tian
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Lizhao Feng
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Hayk Davtyan
- Department of Neurobiology & Behavior, Institute for Memory Impairments & Neurological Disorders and Sue & Bill Gross Stem Cell Research Center, University of California Irvine, Irvine, CA 92697, USA
| | - Mathew Blurton-Jones
- Department of Neurobiology & Behavior, Institute for Memory Impairments & Neurological Disorders and Sue & Bill Gross Stem Cell Research Center, University of California Irvine, Irvine, CA 92697, USA
| | - Markus Kalkum
- Department of Molecular Imaging and Therapy, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Yanhong Shi
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA.
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Graciani AL, Gutierre MU, Coppi AA, Arida RM, Gutierre RC. MYELIN, AGING, AND PHYSICAL EXERCISE. Neurobiol Aging 2023; 127:70-81. [PMID: 37116408 DOI: 10.1016/j.neurobiolaging.2023.03.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/22/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023]
Abstract
Myelin sheath is a structure in neurons fabricated by oligodendrocytes and Schwann cells responsible for increasing the efficiency of neural synapsis, impulse transmission, and providing metabolic support to the axon. They present morpho-functional changes during health aging as deformities of the sheath and its fragmentation, causing an increased load on microglial phagocytosis, with Alzheimer's disease aggravating. Physical exercise has been studied as a possible protective agent for the nervous system, offering benefits to neuroplasticity. In this regard, studies in animal models for Alzheimer's and depression reported the efficiency of physical exercise in protecting against myelin degeneration. A reduction of myelin damage during aging has also been observed in healthy humans. Physical activity promotes oligodendrocyte proliferation and myelin preservation during old age, although some controversies remain. In this review, we will address how effective physical exercise can be as a protective agent of the myelin sheath against the effects of aging in physiological and pathological conditions.
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8
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Increased Hippocampal-Inferior Temporal Gyrus White Matter Connectivity following Donepezil Treatment in Patients with Early Alzheimer's Disease: A Diffusion Tensor Probabilistic Tractography Study. J Clin Med 2023; 12:jcm12030967. [PMID: 36769615 PMCID: PMC9917574 DOI: 10.3390/jcm12030967] [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: 11/21/2022] [Revised: 01/17/2023] [Accepted: 01/21/2023] [Indexed: 01/31/2023] Open
Abstract
The incidence of Alzheimer's disease (AD) has been increasing each year, and a defective hippocampus has been primarily associated with an early stage of AD. However, the effect of donepezil treatment on hippocampus-related networks is unknown. Thus, in the current study, we evaluated the hippocampal white matter (WM) connectivity in patients with early-stage AD before and after donepezil treatment using probabilistic tractography, and we further determined the WM integrity and changes in brain volume. Ten patients with early-stage AD (mean age = 72.4 ± 7.9 years; seven females and three males) and nine healthy controls (HC; mean age = 70.7 ± 3.5 years; six females and three males) underwent a magnetic resonance (MR) examination. After performing the first MR examination, the patients received donepezil treatment for 6 months. The brain volumes and diffusion tensor imaging scalars of 11 regions of interest (the superior/middle/inferior frontal gyrus, the superior/middle/inferior temporal gyrus, the amygdala, the caudate nucleus, the hippocampus, the putamen, and the thalamus) were measured using MR imaging and DTI, respectively. Seed-based structural connectivity analyses were focused on the hippocampus. The patients with early AD had a lower hippocampal volume and WM connectivity with the superior frontal gyrus and higher mean diffusivity (MD) and radial diffusivity (RD) in the amygdala than HC (p < 0.05, Bonferroni-corrected). However, brain areas with a higher (or lower) brain volume and WM connectivity were not observed in the HC compared with the patients with early AD. After six months of donepezil treatment, the patients with early AD showed increased hippocampal-inferior temporal gyrus (ITG) WM connectivity (p < 0.05, Bonferroni-corrected).
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9
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Singh NA, Graff-Radford J, Machulda MM, Thu NT, Schwarz CG, Reid RI, Lowe VJ, Petersen RC, Jack CR, Josephs KA, Whitwell JL. Diffusivity Changes in Posterior Cortical Atrophy and Logopenic Progressive Aphasia: A Longitudinal Diffusion Tensor Imaging Study. J Alzheimers Dis 2023; 94:709-725. [PMID: 37302032 PMCID: PMC10785680 DOI: 10.3233/jad-221217] [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] [Indexed: 06/12/2023]
Abstract
BACKGROUND Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are associated with characteristic patterns of structural network degeneration. Little is known about longitudinal patterns of white matter tract degeneration in these phenotypes. OBJECTIVE To assess longitudinal patterns of white matter degeneration and identify phenotype specific cross-sectional and longitudinal diffusion tensor imaging (DTI) biomarkers in PCA and LPA. METHODS Twenty-five PCA, 22 LPA and 25 cognitively unimpaired (CU) individuals were recruited and underwent structural MRI that included a DTI sequence with a follow-up one year later. Cross-sectional and longitudinal mixed effects models were fit to assess the effects of diagnosis on baseline and annualized change in regional DTI metrics. Discriminatory power was investigated using the area under the receiver operating characteristic curves (AUROC). RESULTS PCA and LPA showed overlapping white matter degeneration profiles predominantly in the left occipital and temporal lobes, the posterior thalamic radiation and sagittal stratum at baseline, as well as the parietal lobe longitudinally. PCA showed degeneration in the occipital and parietal white matter, cross-sectionally and longitudinally, compared to CU, while LPA showed greater degeneration in the temporal and inferior parietal white matter and the inferior fronto-occipital fasciculus cross-sectionally, and in parietal white matter longitudinally compared to CU. Cross-sectionally, integrity of the inferior occipital white matter was best able to differentiate PCA from LPA, with an AUROC of 0.82. CONCLUSION These findings contribute to our understanding of white matter degeneration and support usage of DTI as a useful additional diagnostic biomarker for PCA and LPA.
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Affiliation(s)
| | | | - Mary M. Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Nha Trang Thu
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Robert I. Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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10
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Leo H, Kipp M. Remyelination in Multiple Sclerosis: Findings in the Cuprizone Model. Int J Mol Sci 2022; 23:ijms232416093. [PMID: 36555733 PMCID: PMC9783537 DOI: 10.3390/ijms232416093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
Remyelination therapies, which are currently under development, have a great potential to delay, prevent or even reverse disability in multiple sclerosis patients. Several models are available to study the effectiveness of novel compounds in vivo, among which is the cuprizone model. This model is characterized by toxin-induced demyelination, followed by endogenous remyelination after cessation of the intoxication. Due to its high reproducibility and ease of use, this model enjoys high popularity among various research and industrial groups. In this review article, we will summarize recent findings using this model and discuss the potential of some of the identified compounds to promote remyelination in multiple sclerosis patients.
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Affiliation(s)
| | - Markus Kipp
- Correspondence: ; Tel.: +49-(0)-381-494-8400
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11
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Pandey S, Shen K, Lee SH, Shen YAA, Wang Y, Otero-García M, Kotova N, Vito ST, Laufer BI, Newton DF, Rezzonico MG, Hanson JE, Kaminker JS, Bohlen CJ, Yuen TJ, Friedman BA. Disease-associated oligodendrocyte responses across neurodegenerative diseases. Cell Rep 2022; 40:111189. [PMID: 36001972 DOI: 10.1016/j.celrep.2022.111189] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 05/17/2022] [Accepted: 07/20/2022] [Indexed: 12/29/2022] Open
Abstract
Oligodendrocyte dysfunction has been implicated in the pathogenesis of neurodegenerative diseases, so understanding oligodendrocyte activation states would shed light on disease processes. We identify three distinct activation states of oligodendrocytes from single-cell RNA sequencing (RNA-seq) of mouse models of Alzheimer's disease (AD) and multiple sclerosis (MS): DA1 (disease-associated1, associated with immunogenic genes), DA2 (disease-associated2, associated with genes influencing survival), and IFN (associated with interferon response genes). Spatial analysis of disease-associated oligodendrocytes (DAOs) in the cuprizone model reveals that DA1 and DA2 are established outside of the lesion area during demyelination and that DA1 repopulates the lesion during remyelination. Independent meta-analysis of human single-nucleus RNA-seq datasets reveals that the transcriptional responses of MS oligodendrocytes share features with mouse models. In contrast, the oligodendrocyte activation signature observed in human AD is largely distinct from those observed in mice. This catalog of oligodendrocyte activation states (http://research-pub.gene.com/OligoLandscape/) will be important to understand disease progression and develop therapeutic interventions.
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Affiliation(s)
- Shristi Pandey
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
| | - Kimberle Shen
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Seung-Hye Lee
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Yun-An A Shen
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Yuanyuan Wang
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | | | | | - Stephen T Vito
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Benjamin I Laufer
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Dwight F Newton
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA; Roche Global IT Solution Centre, Hoffman-La Roche Canada, 7070 Mississauga Road, Mississauga, ON, Canada
| | - Mitchell G Rezzonico
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Jesse E Hanson
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Joshua S Kaminker
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Christopher J Bohlen
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Tracy J Yuen
- Department of Neuroscience, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
| | - Brad A Friedman
- Department of OMNI Bioinformatics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
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Early Changes in Transcriptomic Profiles in Synaptodendrosomes Reveal Aberrant Synaptic Functions in Alzheimer’s Disease. Int J Mol Sci 2022; 23:ijms23168888. [PMID: 36012153 PMCID: PMC9408306 DOI: 10.3390/ijms23168888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/29/2022] [Accepted: 08/04/2022] [Indexed: 11/16/2022] Open
Abstract
Alzheimer’s disease (AD) is one of the most prevalent neurodegenerative disorders characterized by the progressive decline of cognitive functions, and is closely associated with the dysfunction of synapses, which comprise the basic structure that mediates the communication between neurons. Although the protein architecture and machinery for protein translation at synapses are extensively studied, the impact that local changes in the mRNA reservoir have on AD progression is largely unknown. Here, we investigated the changes in transcriptomic profiles in the synaptodendrosomes purified from the cortices of AD mice at ages 3 and 6 months, a stage when early signatures of synaptic dysfunction are revealed. The transcriptomic profiles of synaptodendrosomes showed a greater number of localized differentially expressed genes (DEGs) in 6-month-old AD mice compared with mice 3 months of age. Gene Ontology (GO) analysis showed that these DEGs are majorly enriched in mitochondrial biogenesis and metabolic activity. More specifically, we further identified three representative DEGs in mitochondrial and metabolic pathways—Prnp, Cst3, and Cox6c—that regulate the dendritic spine density and morphology in neurons. Taken together, this study provides insights into the transcriptomic changes in synaptodendrosomes during AD progression, which may facilitate the development of intervention strategies targeting local translation to ameliorate the pathological progression of AD.
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13
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Sirkis DW, Bonham LW, Johnson TP, La Joie R, Yokoyama JS. Dissecting the clinical heterogeneity of early-onset Alzheimer's disease. Mol Psychiatry 2022; 27:2674-2688. [PMID: 35393555 PMCID: PMC9156414 DOI: 10.1038/s41380-022-01531-9] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 12/14/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.
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Affiliation(s)
- Daniel W Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Taylor P Johnson
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA.
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14
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Migliaccio R, Cacciamani F. The temporal lobe in typical and atypical Alzheimer disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 187:449-466. [PMID: 35964987 DOI: 10.1016/b978-0-12-823493-8.00004-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Alzheimer disease (AD) is defined neuropathologically by abnormal extra-cellular β-amyloid plaques combined with intraneuronal tau aggregation. Patients sharing the same neuropathological features but presenting different clinical manifestations and evolutions have led to the notion of AD spectrum. This spectrum encompasses typical and atypical forms of AD. For all of them, specific parts of the temporal lobes, as well as their structural and functional connections with other brain regions, are affected. In typical amnestic late-onset Alzheimer's disease (>65 years old; LOAD), tau pathology gradually spreads to the brain from the medial temporal lobe (MTL). MTL is an inhomogeneous structure consisting of several subregions densely connected to each other and to other cortical and subcortical brain regions. These regions play a crucial role in the storage of information in episodic memory. In less common early-onset AD (<65 years old; EOAD), a large proportion of patients presents atypical clinical manifestations, in which memory impairment is not inaugural and predominant. Instead, these patients have predominant and/or isolated deficits in language, visuospatial, motor, or executive/behavioral functions. In atypical variants, brain damage is mainly centered on the posterior regions, with relative sparing of the MTL. However, the temporal lobe also appears to be variably and specifically damaged in some subtypes of EOAD. For example, the left superior temporal gyrus is the core of brain damage in the language variant, as well as the ventral regions of the temporal lobe play an important role in the clinic of the visual variant.
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Affiliation(s)
- Raffaella Migliaccio
- Paris Brain Institute, INSERM U1127, Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurology, Institut de la mémoire et de la maladie d'Alzheimer, Hôpital de la Pitié-Salpêtrière, Paris, France.
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15
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Guo Q, Duan J, Cai S, Zhang J, Chen T, Yang H. Desynchronized white matter function and structure in drug-naive first-episode major depressive disorder patients. Front Psychiatry 2022; 13:1082052. [PMID: 36713909 PMCID: PMC9874158 DOI: 10.3389/fpsyt.2022.1082052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 12/21/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly prevalent mental disease. Using magnetic resonance imaging (MRI), although numerous studies have revealed the alterations in structure and function of grey matter (GM), few studies focused on the synchronization of white matter (WM) structure and function in MDD. The aim of this study was to investigate whether functional and structural abnormalities of WM play an essential role in the neurobiological mechanisms of MDD. METHODS Gradient-echo imaging sequences at 3.0T were used to gather resting state functional MRI (rsfMRI) data, which were performed on 33 drug-naive first-episode MDD patients and 34 healthy controls (HCs). After data preprocessed, amplitude of low frequency fluctuation (ALFF) of WM was calculated. ALFF values in different frequency bands were analyzed, including typical (0.01-0.15 Hz) band, slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands. In addition, the fractional anisotropy (FA) values in WM in 23 patients and 26 HCs were examined using tract-based spatial statistics (TBSS) and tractography based on diffusion tensor imaging (DTI). Pearson correlation analysis was applied to analyze the relationships between ALFF values and Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA). RESULTS Compared with the HCs, MDD patients showed decreased ALFF values in posterior thalamic radiation (PTR) and superior longitudinal fasciculus (SLF) in slow-5 frequency band, no significant differences of ALFF values were found in typical and slow-4 frequency bands. In addition, there were no significant differences in FA values with TBSS analysis as well as the number of fibers in PTR and SLF with tractography analysis between two groups. Further correlation analysis showed that the ALFF value in SLF was negatively correlated with HAMA-2 score (r = -0.548, p FDR = 0.037) in patients. CONCLUSION Our results indicated that WM dysfunction may be associated with the pathophysiological mechanism of depression. Our study also suggested that the functional damage of the WM may precedes the structural damage in first-episode MDD patients. Furthermore, for mental disorders, slow-5 frequency band may be a more sensitive functional indicator for early detection of abnormal spontaneous brain activity in WM.
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Affiliation(s)
- Qinger Guo
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jingfeng Duan
- Department of Psychiatry, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Shuyang Cai
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jiaxi Zhang
- School of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application of Zhejiang, Zhejiang Normal University, Jinhua, China
| | - Tao Chen
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Hong Yang
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
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16
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Blanchard JW, Victor MB, Tsai LH. Dissecting the complexities of Alzheimer disease with in vitro models of the human brain. Nat Rev Neurol 2021; 18:25-39. [PMID: 34750588 DOI: 10.1038/s41582-021-00578-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2021] [Indexed: 12/12/2022]
Abstract
Alzheimer disease (AD) is the most prevalent type of dementia. It is marked by severe memory loss and cognitive decline, and currently has limited effective treatment options. Although individuals with AD have common neuropathological hallmarks, emerging data suggest that the disease has a complex polygenic aetiology, and more than 25 genetic loci have been linked to an elevated risk of AD and dementia. Nevertheless, our ability to decipher the cellular and molecular mechanisms that underlie genetic susceptibility to AD, and its progression and severity, remains limited. Here, we discuss ongoing efforts to leverage genomic data from patients using cellular reprogramming technologies to recapitulate complex brain systems and build in vitro discovery platforms. Much attention has already been given to methodologies to derive major brain cell types from pluripotent stem cells. We therefore focus on technologies that combine multiple cell types to recreate anatomical and physiological properties of human brain tissue in vitro. We discuss the advances in the field for modelling four domains that have come into view as key contributors to the pathogenesis of AD: the blood-brain barrier, myelination, neuroinflammation and neuronal circuits. We also highlight opportunities for the field to further interrogate the complex genetic and environmental factors of AD using in vitro models.
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Affiliation(s)
- Joel W Blanchard
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Neuroscience, Black Family Stem Cell Institute, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mt. Sinai, New York, NY, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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17
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Qiu S, Palavicini JP, Wang J, Gonzalez NS, He S, Dustin E, Zou C, Ding L, Bhattacharjee A, Van Skike CE, Galvan V, Dupree JL, Han X. Adult-onset CNS myelin sulfatide deficiency is sufficient to cause Alzheimer's disease-like neuroinflammation and cognitive impairment. Mol Neurodegener 2021; 16:64. [PMID: 34526055 PMCID: PMC8442347 DOI: 10.1186/s13024-021-00488-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 08/26/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Human genetic association studies point to immune response and lipid metabolism, in addition to amyloid-beta (Aβ) and tau, as major pathways in Alzheimer's disease (AD) etiology. Accumulating evidence suggests that chronic neuroinflammation, mainly mediated by microglia and astrocytes, plays a causative role in neurodegeneration in AD. Our group and others have reported early and dramatic losses of brain sulfatide in AD cases and animal models that are mediated by ApoE in an isoform-dependent manner and accelerated by Aβ accumulation. To date, it remains unclear if changes in specific brain lipids are sufficient to drive AD-related pathology. METHODS To study the consequences of CNS sulfatide deficiency and gain insights into the underlying mechanisms, we developed a novel mouse model of adult-onset myelin sulfatide deficiency, i.e., tamoxifen-inducible myelinating glia-specific cerebroside sulfotransferase (CST) conditional knockout mice (CSTfl/fl/Plp1-CreERT), took advantage of constitutive CST knockout mice (CST-/-), and generated CST/ApoE double knockout mice (CST-/-/ApoE-/-), and assessed these mice using a broad range of methodologies including lipidomics, RNA profiling, behavioral testing, PLX3397-mediated microglia depletion, mass spectrometry (MS) imaging, immunofluorescence, electron microscopy, and Western blot. RESULTS We found that mild central nervous system (CNS) sulfatide losses within myelinating cells are sufficient to activate disease-associated microglia and astrocytes, and to increase the expression of AD risk genes (e.g., Apoe, Trem2, Cd33, and Mmp12), as well as previously established causal regulators of the immune/microglia network in late-onset AD (e.g., Tyrobp, Dock, and Fcerg1), leading to chronic AD-like neuroinflammation and mild cognitive impairment. Notably, neuroinflammation and mild cognitive impairment showed gender differences, being more pronounced in females than males. Subsequent mechanistic studies demonstrated that although CNS sulfatide losses led to ApoE upregulation, genetically-induced myelin sulfatide deficiency led to neuroinflammation independently of ApoE. These results, together with our previous studies (sulfatide deficiency in the context of AD is mediated by ApoE and accelerated by Aβ accumulation) placed both Aβ and ApoE upstream of sulfatide deficiency-induced neuroinflammation, and suggested a positive feedback loop where sulfatide losses may be amplified by increased ApoE expression. We also demonstrated that CNS sulfatide deficiency-induced astrogliosis and ApoE upregulation are not secondary to microgliosis, and that astrogliosis and microgliosis seem to be driven by activation of STAT3 and PU.1/Spi1 transcription factors, respectively. CONCLUSION Our results strongly suggest that sulfatide deficiency is an important contributor and driver of neuroinflammation and mild cognitive impairment in AD pathology.
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Affiliation(s)
- Shulan Qiu
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
| | - Juan Pablo Palavicini
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
- Division of Diabetes, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Jianing Wang
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
- Present Address: State Key Lab. of Environmental & Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hongkong, China
| | - Nancy S Gonzalez
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
| | - Sijia He
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
| | - Elizabeth Dustin
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, Virginia, 23284, USA
| | - Cheng Zou
- BRC Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, 14853, USA
| | - Lin Ding
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
- College of Food Science and Engineering, Ocean University of China, Qingdao, 266003, China
| | - Anindita Bhattacharjee
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
| | - Candice E Van Skike
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
- Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Veronica Galvan
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA
- Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Jeffrey L Dupree
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, Virginia, 23284, USA
- Research Division, McGuire Veterans Affairs Medical Center, Richmond, Virginia, 23249, USA
| | - Xianlin Han
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 4939 Charles Katz Drive, San Antonio, TX, 78229, USA.
- Division of Diabetes, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.
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18
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Overman MJ, Zamboni G, Butler C, Ahmed S. Splenial white matter integrity is associated with memory impairments in posterior cortical atrophy. Brain Commun 2021; 3:fcab060. [PMID: 34007964 PMCID: PMC8112963 DOI: 10.1093/braincomms/fcab060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/09/2020] [Accepted: 02/23/2021] [Indexed: 11/22/2022] Open
Abstract
Posterior cortical atrophy is an atypical form of Alzheimer’s disease characterized by visuospatial impairments and predominant tissue loss in the posterior parieto-occipital and temporo-occipital cortex. Whilst episodic memory is traditionally thought to be relatively preserved in posterior cortical atrophy, recent work indicates that memory impairments form a common clinical symptom in the early stages of the disease. Neuroimaging studies suggest that memory dysfunction in posterior cortical atrophy may originate from atrophy and functional hypoconnectivity of parietal cortex. The structural connectivity patterns underpinning these memory impairments, however, have not been investigated. This line of inquiry is of particular interest, as changes in white matter tracts of posterior cortical atrophy patients have been shown to be more extensive than expected based on posterior atrophy of grey matter. In this cross-sectional diffusion tensor imaging MRI study, we examine the relationship between white matter microstructure and verbal episodic memory in posterior cortical atrophy. We assessed episodic memory performance in a group of posterior cortical atrophy patients (n = 14) and a group of matched healthy control participants (n = 19) using the Free and Cued Selective Reminding Test with Immediate Recall. Diffusion tensor imaging measures were obtained for 13 of the posterior cortical atrophy patients and a second control group of 18 healthy adults. Patients and healthy controls demonstrated similar memory encoding performance, indicating that learning of verbal information was preserved in posterior cortical atrophy. However, retrieval of verbal items was significantly impaired in the patient group compared with control participants. As expected, tract-based spatial statistics analyses showed widespread reductions of white matter integrity in posterior cortical regions of patients compared with healthy adults. Correlation analyses indicated that poor verbal retrieval in the patient group was specifically associated with microstructural damage of the splenium of the corpus callosum. Post-hoc tractography analyses in healthy controls demonstrated that this splenial region was connected to thalamic radiations and the retrolenticular part of the internal capsule. These results provide insight into the brain circuits that underlie memory impairments in posterior cortical atrophy. From a cognitive perspective, we propose that the association between splenial integrity and memory dysfunction could arise indirectly via disruption of attentional processes. We discuss implications for the clinical phenotype and development of therapeutic aids for cognitive impairment in posterior cortical atrophy.
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Affiliation(s)
- Margot Juliëtte Overman
- Research Institute for the Care of Older People (RICE), Bath BA1 3NG, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Giovanna Zamboni
- Dipartimento di Scienze Biomediche, Metaboliche e Neuroscienze, Università di Modena e Reggio Emilia, Modena, Italy.,Center for Neuroscience and Neurotechnology, Università di Modena e Reggio Emilia, Modena, Italy.,Nuffield Department of Clinical Neuroscience, University of Oxford, Oxfordshire OX3 9DU, UK
| | - Christopher Butler
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxfordshire OX3 9DU, UK.,Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK.,Departamento de Neurología, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Samrah Ahmed
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxfordshire OX3 9DU, UK.,School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6ES, UK
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19
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Kim GW, Park SE, Park K, Jeong GW. White Matter Connectivity and Gray Matter Volume Changes Following Donepezil Treatment in Patients With Mild Cognitive Impairment: A Preliminary Study Using Probabilistic Tractography. Front Aging Neurosci 2021; 12:604940. [PMID: 33796017 PMCID: PMC8007874 DOI: 10.3389/fnagi.2020.604940] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/21/2020] [Indexed: 11/13/2022] Open
Abstract
The donepezil treatment is associated with improved cognitive performance in patients with mild cognitive impairment (MCI), and its clinical effectiveness is well-known. However, the impact of the donepezil treatment on the enhanced white matter connectivity in MCI is still unclear. The purpose of this study was to evaluate the thalamo-cortical white matter (WM) connectivity and cortical thickness and gray matter (GM) volume changes in the cortical regions following donepezil treatment in patients with MCI using probabilistic tractography and voxel-based morphometry. Patients with MCI underwent magnetic resonance examinations before and after 6-month donepezil treatment. Compared with healthy controls, patients with MCI showed decreased WM connectivity of the thalamo-lateral prefrontal cortex, as well as reduced thickness in the medial/lateral orbitofrontal cortices (p < 0.05). The thalamo-lateral temporal cortex connectivity in patients with MCI was negatively correlated with Alzheimer's disease assessment scale-cognitive subscale (ADAS-cog) (r = −0.76, p = 0.01). The average score of the Korean version of the mini-mental state examination (K-MMSE) in patients with MCI was improved by 7.9% after 6-months of donepezil treatment. However, the patterns of WM connectivity and brain volume change in untreated and treated patients were not significantly different from each other, resulting from multiple comparison corrections. These findings will be valuable in understanding the neurophysiopathological mechanism on MCI as a prodromal phase of Alzheimer's disease in connection with brain functional connectivity and morphometric change.
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Affiliation(s)
- Gwang-Won Kim
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Shin-Eui Park
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea
| | - Kwangsung Park
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea.,Department of Urology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
| | - Gwang-Woo Jeong
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
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20
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Meysami S, Raji CA, Merrill DA, Porter VR, Mendez MF. Quantitative MRI Differences Between Early versus Late Onset Alzheimer's Disease. Am J Alzheimers Dis Other Demen 2021; 36:15333175211055325. [PMID: 34814740 PMCID: PMC10623969 DOI: 10.1177/15333175211055325] [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] [Indexed: 11/16/2022]
Abstract
Investigators report greater parietal tau deposition and alternate frontoparietal network involvement in early onset Alzheimer's Disease (EOAD) with onset <65 years as compared with typical late onset AD (LOAD). To determine whether clinical brain MRI volumes reflect these differences in EOAD compared with LOAD. This study investigated the clinical MRI scans of 45 persons with Clinically Probable AD with onset <65 years, and compared them to 32 with Clinically Probable AD with onset ≥65 years. Brain volumes on their T1 MRI scans were quantified with a volumetric program. Receiver operating curve analyses were performed. Persons with EOAD had significantly smaller parietal lobes (volumetric percentiles) than LOAD. Late onset Alzheimer's Disease had a smaller left putamen and hippocampus. Area Under the Curve was 96.5% with brain region delineation of EOAD compared to LOAD. This study indicates parietal atrophy less than 30% of normal on clinical MRI scans is suggestive of EOAD compared to LOAD.
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Affiliation(s)
- Somayeh Meysami
- Department of Neurology, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
| | - Cyrus A. Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St Louis, St Louis, MO, USA
| | - David A. Merrill
- Department of Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
- Providence and St Johns Health Center, Pacific Neuroscience Institute, Santa Monica, CA, USA
| | - Verna R. Porter
- Department of Neurology, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
- Providence and St Johns Health Center, Pacific Neuroscience Institute, Santa Monica, CA, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
- Department of Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
- V.A. Greater Los Angeles Healthcare System, Los Angeles, CA, USA
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21
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Therapeutic potential of mangiferin in the treatment of various neuropsychiatric and neurodegenerative disorders. Neurochem Int 2020; 143:104939. [PMID: 33346032 DOI: 10.1016/j.neuint.2020.104939] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/02/2020] [Accepted: 12/12/2020] [Indexed: 12/19/2022]
Abstract
Xanthones are important chemical class of bioactive products that confers therapeutic benefits. Of several xanthones, mangiferin is known to be distributed widely across several fruits, vegetables and medicinal plants. Mangiferin has been shown to exert neuroprotective effects in both in-vitro and in-vivo models. Mangiferin attenuates cerebral infarction, cerebral edema, lipid peroxidation (MDA), neuronal damage, etc. Mangiferin further potentiate levels of endogenous antioxidants to confer protection against the oxidative stress inside the neurons. Mangiferin is involved in the regulation of various signaling pathways that influences the production and levels of proinflammatory cytokines in brain. Mangiferin cosunteracted the neurotoxic effect of amyloid-beta, MPTP, rotenone, 6-OHDA etc and confer protection to neurons. These evidence suggested that the mangiferin may be a potential therapeutic strategy for the treatment of various neurological disorders. The present review demonstrated the pharmacodynamics-pharmacokinetics of mangiferin and neurotherapeutic potential in several neurological disorders with underlying mechanisms.
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22
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Martini AC, Helman AM, McCarty KL, Lott IT, Doran E, Schmitt FA, Head E. Distribution of microglial phenotypes as a function of age and Alzheimer's disease neuropathology in the brains of people with Down syndrome. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12113. [PMID: 33088896 PMCID: PMC7560512 DOI: 10.1002/dad2.12113] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 09/02/2020] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Microglial cells play an important role in the development of Alzheimer's disease (AD). People with Down syndrome (DS) inevitably develop AD neuropathology (DSAD) by 40 years of age. We characterized the distribution of different microglial phenotypes in the brains of people with DS and DSAD. METHODS Autopsy tissue from the posterior cingulate cortex (PCC) from people with DS, DSAD, and neurotypical controls was immunostained with the microglial marker Iba1 to assess five microglia morphological types. RESULTS Individuals with DS have more hypertrophic microglial cells in their white matter. In the gray matter, individuals with DSAD had significantly fewer ramified microglia and more dystrophic microglia than controls and the younger individuals with DS. The DSAD group also exhibited more rod-shaped and amoeboid cells than the AD group. DISCUSSION Individuals with DS and DSAD show a microglial phenotype that distinguishes them from non-DS controls.
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Affiliation(s)
- Alessandra C. Martini
- Department of Pathology and Laboratory MedicineUniversity of California, IrvineIrvineCaliforniaUSA
| | - Alex M. Helman
- Department of Molecular and Cellular BiochemistryUniversity of KentuckyLexingtonKentuckyUSA
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
| | - Katie L. McCarty
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
| | - Ira T. Lott
- Department of PediatricsUniversity of California, IrvineIrvineCaliforniaUSA
- Department of NeurologyUniversity of California, IrvineIrvineCaliforniaUSA
| | - Eric Doran
- Department of PediatricsUniversity of California, IrvineIrvineCaliforniaUSA
| | - Frederick A. Schmitt
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of NeurologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Elizabeth Head
- Department of Pathology and Laboratory MedicineUniversity of California, IrvineIrvineCaliforniaUSA
- Department of NeurologyUniversity of KentuckyLexingtonKentuckyUSA
- Department of Pharmacology and Nutritional SciencesUniversity of KentuckyLexingtonKentuckyUSA
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23
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Glick-Shames H, Keadan T, Backner Y, Bick A, Levin N. Global Brain Involvement in Posterior Cortical Atrophy: Multimodal MR Imaging Investigation. Brain Topogr 2020; 33:600-612. [PMID: 32761400 DOI: 10.1007/s10548-020-00788-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 07/23/2020] [Indexed: 02/04/2023]
Abstract
Posterior cortical atrophy (PCA), considered a visual variant of Alzheimer's disease, has similar pathological characteristics yet shows a selective visual manifestation with relative preservation of other cortical areas, at least at early stages of disease. Using a gamut of imaging methods, we aim to evaluate the global aspect of this relatively local disease and describe the interplay of the involvement of the different brain components. Ten PCA patients and 14 age-matched controls underwent MRI scans. Cortical thickness was examined to identify areas of cortical thinning. Hippocampal volume was assessed using voxel-based morphometry. The integrity of 20 fiber tracts was assessed by Diffusion Tensor Imaging. Regions of difference in global functional connectivity were identified by resting-state fMRI, using multi-variant pattern analysis. Correlations were examined to evaluate the connection between grey matter atrophy, the network changes and the disease load. The patients presented bilateral cortical thinning, primarily in their brains' posterior segments. Impaired segments of white matter integrity were evident only within three fiber tracts in the left hemisphere. Four areas were identified as different in their global connectivity pattern. The visual network-related areas showed reduced connectivity and was correlated to atrophy. Right Broadman area 39 showed in addition increased connectivity to the frontal areas. Global structural and functional imaging pointed to the highly localized nature of PCA. Functional connectivity followed grey matter atrophy in visual regions. White matter involvement seemed less prominent, however damage is directly related to presence of disease and not mediated only by grey matter damage.
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Affiliation(s)
- Haya Glick-Shames
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Tarek Keadan
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Yael Backner
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Atira Bick
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Netta Levin
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel.
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24
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Mendoza-Léon R, Puentes J, Uriza LF, Hernández Hoyos M. Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders. Comput Biol Med 2019; 116:103527. [PMID: 31765915 DOI: 10.1016/j.compbiomed.2019.103527] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 10/23/2019] [Accepted: 10/28/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this article, we explore the application of Supervised Switching Autoencoders (SSAs) to perform AD classification using only one structural Magnetic Resonance Imaging (sMRI) slice. SSAs are revised supervised autoencoder architectures, combining unsupervised representation and supervised classification as one unified model. In this work, we study the capabilities of SSAs to capture complex visual neurodegeneration patterns, and fuse disease semantics simultaneously. We also examine how regions associated to disease state can be discovered by SSAs following a local patch-based approach. METHODS Patch-based SSAs models are trained on individual patches extracted from a single 2D slice, independently for Axial, Coronal, and Sagittal anatomical planes of the brain at selected informative locations, exploring different patch sizes and network parameterizations. Then, models perform binary class prediction - healthy (CDR = 0) or AD-demented (CDR > 0) - on test data at patch level. The final subject classification is performed employing a majority rule from the ensemble of patch predictions. In addition, relevant regions are identified, by computing accuracy densities from patch-level predictions, and analyzed, supported by Atlas-based regional definitions. RESULTS Our experiments employing a single 2D T1-w sMRI slice per subject show that SSAs perform similarly to previous proposals that rely on full volumetric information and feature-engineered representations. SSAs classification accuracy on slices extracted along the Axial, Coronal, and Sagittal anatomical planes from a balanced cohort of 40 independent test subjects was 87.5%, 90.0%, and 90.0%, respectively. A top sensitivity of 95.0% on both Coronal and Sagittal planes was also obtained. CONCLUSIONS SSAs provided well-ranked accuracy performance among previous classification proposals, including feature-engineered and feature learning based methods, using only one scan slice per subject, instead of the whole 3D volume, as it is conventionally done. In addition, regions identified as relevant by SSAs' were, in most part, coherent or partially coherent in regard to relevant regions reported on previous works. These regions were also associated with findings from medical knowledge, which gives value to our methodology as a potential analytical aid for disease understanding.
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Affiliation(s)
- Ricardo Mendoza-Léon
- Systems and Computing Engineering Department, School of Engineering, Universidad de los Andes, Bogotá, Colombia; IMT Atlantique, Lab-STICC, UMR CNRS 6285, F-29238, Brest, France.
| | - John Puentes
- IMT Atlantique, Lab-STICC, UMR CNRS 6285, F-29238, Brest, France
| | - Luis Felipe Uriza
- Departamento de Radiología e Imágenes Diagnósticas, Hospital Universitario de San Ignacio, Bogotá, Colombia; Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Marcela Hernández Hoyos
- Systems and Computing Engineering Department, School of Engineering, Universidad de los Andes, Bogotá, Colombia
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25
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Migliaccio R, Agosta F, Basaia S, Cividini C, Habert MO, Kas A, Montembeault M, Filippi M. Functional brain connectome in posterior cortical atrophy. Neuroimage Clin 2019; 25:102100. [PMID: 31865020 PMCID: PMC6931188 DOI: 10.1016/j.nicl.2019.102100] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 10/17/2019] [Accepted: 11/18/2019] [Indexed: 01/29/2023]
Abstract
This study investigated the functional brain connectome architecture in patients with Posterior Cortical Atrophy (PCA). Eighteen PCA patients and 29 age- and sex- matched healthy controls were consecutively recruited in a specialized referral center. Participants underwent neurologic examination, cerebrospinal fluid (CSF) examination for Alzheimer's disease (AD) biomarkers, cognitive assessment, and brain MRI. For a smaller subset of participants, FDG-PET examination was available. We assessed topological brain network properties and regional functional connectivity as well as intra- and inter-hemispheric connectivity, using graph analysis and connectomics. Supplementary analyses were performed to explore the association between the CSF AD profile and the connectome status, and taking into account hypometabolic, atrophic, and spared regions (nodes). PCA patients showed diffuse functional connectome alterations at both global and regional level, as well as a connectivity breakdown between the posterior brain nodes. They had a widespread loss of both intra- and inter-hemispheric connections, exceeding the structural damage, and including the frontal connections. In PCA, connectome alterations were identified in all the brain nodes irrespectively of their structural and metabolic classification and were associated with a connectivity breakdown between damaged and spared areas. Taken together, these findings suggest the potentially high sensitivity of graph-analysis and connectomic in capturing the progression and maybe early signs of neurodegeneration in PCA patients.
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Affiliation(s)
- Raffaella Migliaccio
- FrontLab, INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S1127, Institut du Cerveau et de la Moelle épinière (ICM), Pitié-Salpêtrière hospital, Paris, France; Institut de la mémoire et de la maladie d'Alzheimer, IM2A, Reference Centre for Rare dementias and Early Onset Alzheimer's disease, Neurology Departement, Pitié-Salpêtrière hospital, Paris, France.
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Marie-Odile Habert
- Department of Nuclear Medicine, Pitié-Salpêtrière hospital, Paris, France; LIB, Inserm U1146, Université Pierre et Marie Curie, Paris 6, Paris, France
| | - Aurélie Kas
- Department of Nuclear Medicine, Pitié-Salpêtrière hospital, Paris, France; LIB, Inserm U1146, Université Pierre et Marie Curie, Paris 6, Paris, France
| | - Maxime Montembeault
- Memory & Aging Center, Deparment of Neurology, University of California in San Francisco, San Francisco, United-States
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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26
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Jiang Y, Song L, Li X, Zhang Y, Chen Y, Jiang S, Hou C, Yao D, Wang X, Luo C. Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes. Hum Brain Mapp 2019; 40:3113-3124. [PMID: 30937973 PMCID: PMC6865396 DOI: 10.1002/hbm.24584] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/11/2019] [Accepted: 03/18/2019] [Indexed: 12/18/2022] Open
Abstract
Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white-matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white-matter structural architecture, it cannot detect neural activity or white-matter functions. Recent studies demonstrated the functional organization of white-matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white-matter dysfunctions in BECT. Resting-state fMRI data were collected from 24 new-onset drug-naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white-matter functional networks were obtained using a clustering analysis on voxel-by-voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub-bands (Slow-5:0.01-0.027, Slow-4:0.027-0.073, Slow-3:0.073-0.198, and Slow-2:0.198-0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white-matter networks based on their correlations with multiple gray-matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency-specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow-3 and Slow-4. This study provided further support on the existence of white-matter functional networks which exhibited frequency-specific properties, and extended abnormalities of rolandic area from the perspective of white-matter dysfunction in BECT.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Li Song
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Yaodan Zhang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
- Chengdu University of Traditional Chinese MedicineChengdu, SichuanChina
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Changyue Hou
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiaoming Wang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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27
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Chen Y, Liu P, Wang Y, Peng G. Neural Mechanisms of Visual Dysfunction in Posterior Cortical Atrophy. Front Neurol 2019; 10:670. [PMID: 31293507 PMCID: PMC6603128 DOI: 10.3389/fneur.2019.00670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 06/07/2019] [Indexed: 11/13/2022] Open
Abstract
Posterior cortical atrophy (PCA) is characterized predominantly by visual dysfunction that arises from bilateral impairments in occipital, parietal, and temporal regions of the brain. PCA is clinically identified based primarily on visual symptoms and neuroimaging findings. Region-specific gray and white matter deficits have been discussed in detail, and are associated with clinical manifestations that present with similar patterns of perfusion and metabolic findings. Here, we discuss both structural and functional changes in the ventral and dorsal visual streams along with their underlying relationships. We also discuss the most recent developments in neuroimaging characteristics and summarize correlations between distinct neuroimaging presentations.
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Affiliation(s)
- Yi Chen
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ping Liu
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yunyun Wang
- Department of Neurology, Shengzhou People's Hospital, Shengzhou, China
| | - Guoping Peng
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Guoping Peng
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28
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Single-cell transcriptomic analysis of Alzheimer's disease. Nature 2019; 570:332-337. [PMID: 31042697 DOI: 10.1038/s41586-019-1195-2] [Citation(s) in RCA: 1200] [Impact Index Per Article: 240.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 04/24/2019] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease is a pervasive neurodegenerative disorder, the molecular complexity of which remains poorly understood. Here, we analysed 80,660 single-nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer's disease pathology. Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival. The strongest disease-associated changes appeared early in pathological progression and were highly cell-type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response. Notably, we found that female cells were overrepresented in disease-associated subpopulations, and that transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes. Overall, myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology. Our single-cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer's disease.
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Jiang Y, Luo C, Li X, Li Y, Yang H, Li J, Chang X, Li H, Yang H, Wang J, Duan M, Yao D. White-matter functional networks changes in patients with schizophrenia. Neuroimage 2019; 190:172-181. [DOI: 10.1016/j.neuroimage.2018.04.018] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 03/26/2018] [Accepted: 04/09/2018] [Indexed: 10/17/2022] Open
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30
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Sintini I, Schwarz CG, Martin PR, Graff-Radford J, Machulda MM, Senjem ML, Reid RI, Spychalla AJ, Drubach DA, Lowe VJ, Jack CR, Josephs KA, Whitwell JL. Regional multimodal relationships between tau, hypometabolism, atrophy, and fractional anisotropy in atypical Alzheimer's disease. Hum Brain Mapp 2018; 40:1618-1631. [PMID: 30549156 DOI: 10.1002/hbm.24473] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 10/20/2018] [Accepted: 10/25/2018] [Indexed: 11/10/2022] Open
Abstract
Alzheimer's disease (AD) can present with atypical clinical forms where the prominent domain of deficit is not memory, that is, atypical AD. Atypical AD patients show cortical atrophy on MRI, hypometabolism on [18 F]fluorodeoxyglucose (FDG) PET, tau uptake on [18 F]AV-1451 PET, and white matter tract degeneration on diffusion tensor imaging (DTI). How these disease processes relate to each other locally and distantly remains unclear. We aimed to examine multimodal neuroimaging relationships in individuals with atypical AD, using univariate and multivariate techniques at region- and voxel-level. Forty atypical AD patients underwent MRI, FDG-PET, tau-PET, beta-amyloid PET, and DTI. Patients were all beta-amyloid positive. Partial Pearson's correlations were performed between tau and FDG standardized uptake value ratios, gray matter MRI-volumes and white matter tract fractional anisotropy. Sparse canonical correlation analysis was applied to identify multivariate relationships between the same quantities. Voxel-level associations across modalities were also assessed. Tau showed strong local negative correlations with FDG metabolism in the occipital and frontal lobes. Tau in frontal and parietal regions was negatively associated with temporoparietal gray matter MRI-volume. Fractional anisotropy in a set of posterior white matter tracts, including the splenium of the corpus callosum, cingulum, and posterior thalamic radiation, was negatively correlated with parietal and occipital tau, atrophy and, predominantly, with hypometabolism. These results support the view that tau is the driving force behind neurodegeneration in atypical AD, and that a breakdown in structural connectivity is related to cortical neurodegeneration, particularly hypometabolism.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | - Peter R Martin
- Department of Health Science Research (Biostatistics), Mayo Clinic, Rochester, Minnesota
| | | | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, Minnesota.,Department of Information Technology, Mayo Clinic, Rochester, Minnesota
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota
| | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
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31
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Sui X, Rajapakse JC. Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors. NEUROIMAGE-CLINICAL 2018; 20:1222-1232. [PMID: 30412925 PMCID: PMC6226553 DOI: 10.1016/j.nicl.2018.10.026] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/28/2018] [Accepted: 10/23/2018] [Indexed: 01/09/2023]
Abstract
The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Although white matter (WM) impairment also contributes to AD pathology, its heterogeneity remains unclear. The Latent Dirichlet Allocation (LDA) method is a suitable framework to study heterogeneity and allows to identify latent impairment factors of AD instead of simply mapping an overall disease effect. By exploring whole brain WM skeleton images by using LDA, three latent factors were revealed in AD: a temporal-frontal impairment factor (temporal and frontal lobes, especially hippocampus and para-hippocampus), a parietal factor (parietal lobe, especially precuneus), and a long fibre bundle factor (corpus callosum and superior longitudinal fasciculus). As revealed by longitudinal analysis, the latent factors have distinct impact on cognitive decline: for executive function (EF), the temporal-frontal factor was more strongly associated with baseline EF compared with the parietal factor, while the long-fibre bundle factor was most associated with decline rate of EF; for memory, the three factors showed almost equal effect on the baseline memory and decline rate. For each participant, LDA estimates his/her composition profile of latent impairment factors, which indicates disease subtype. We also found that the APOE genotype affects the AD subtype. Specifically, APOE ε4 was more associated with the long fibre bundle factor and APOE ε2 was more associated with temporal-frontal factor. By investigating heterogeneity and subtypes of AD through white matter impairment factors, our study could facilitate precision medicine. LDA revealed three latent white matter impairment factors in Alzheimer’s disease. Latent factors associate with executive function and memory decline differently. Individual factor composition indicates disease subtype. The APOE genotype is associated with the factor composition.
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Affiliation(s)
- Xiuchao Sui
- School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore
| | - Jagath C Rajapakse
- School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore.
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- School of Computer Science and Engineering, Nanyang Technological University, 639798, Singapore
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32
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Li KC, Luo X, Zeng QZ, Xu XJ, Huang PY, Shen ZJ, Xu JJ, Zhou J, Zhang MM. Distinct Patterns of Interhemispheric Connectivity in Patients With Early- and Late-Onset Alzheimer's Disease. Front Aging Neurosci 2018; 10:261. [PMID: 30237764 PMCID: PMC6136638 DOI: 10.3389/fnagi.2018.00261] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 08/14/2018] [Indexed: 12/18/2022] Open
Abstract
Background: Early-onset Alzheimer’s disease (EOAD) presents a different clinical profile than late-onset Alzheimer’s disease (LOAD). Neuroimaging studies have demonstrated that patients with EOAD present more atrophy and functional disconnection than LOAD patients. However, it remains unknown whether the interhemispheric functional disconnection or its underlying structural impairment contributes to the different clinical profiles of EOAD and LOAD. Methods: According to the arbitrary cut-off age of 65, we included 22 EOAD patients, 27 LOAD patients and 38 healthy controls (further divided into 21 relatively young and 17 old controls). Participants underwent resting-state functional MRI, diffusion tensor imaging (DTI) and comprehensive neuropsychological assessments. We used voxel-mirrored homotopic connectivity (VMHC) to examine interhemispheric functional connectivity. Then, we calculated the diffusion index based on tract-based spatial statistics (TBSS). Two-sample t-tests were used to assess the interhemispheric connectivity differences between each patient group and its corresponding control group. Results: We found that the EOAD patients had lower VMHC in the hippocampus, parahippocampal gyrus (PHG), superior temporal gyrus (STG) and inferior parietal cortex (IPC) than did controls. Consistently, the EOAD patients exhibited white matter (WM) tract impairment in the posterior regions. On the other hand, the LOAD patients displayed increased VMHC and impaired WM tracts in the frontal region. Correlation analyses showed that VMHC in the IPC was related to executive function in the EOAD patients (r = −0.67, P < 0.05). Conclusion: In contrast to the LOAD patients, patients with EOAD exhibited more widely disrupted interhemispheric functional and structural connectivity, which overlapped well across brain regions. In addition, for the EOAD patients, decreased interhemispheric connectivity related to executive deficits. Our study suggested that different interhemispheric connectivity damage patterns may contribute to the distinct clinical profiles in EOAD and LOAD.
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Affiliation(s)
- Kai-Cheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qing-Ze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao-Jun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Pei-Yu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhu-Jing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jing-Jing Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiong Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min-Ming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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33
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The impact of localized grey matter damage on neighboring connectivity: posterior cortical atrophy and the visual network. Brain Imaging Behav 2018; 13:1292-1301. [DOI: 10.1007/s11682-018-9952-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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34
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Ma M, Zhang J, Chen N, Guo J, Zhang Y, He L. Exploration of intrinsic brain activity in migraine with and without comorbid depression. J Headache Pain 2018; 19:48. [PMID: 29943098 PMCID: PMC6020083 DOI: 10.1186/s10194-018-0876-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 06/15/2018] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Major depressive disorder is a common comorbidity in migraineurs. Depression may affect the progression and prognosis of migraine. Few studies have examined the brain function in migraineurs that may cause this comorbidity. Here, we aimed to explore depression-related abnormalities in the intrinsic brain activity of interictal migraineurs with comorbid depression using resting-state functional magnetic resonance imaging. RESULTS Significant main effects of migraine and depression provided evidence that migraine and depression jointly affected the left medial prefrontal cortex, which was thought to be the neural basis of self-referential mental activity in previous studies. Abnormalities in this region may contribute to determining the common symptoms of migraine and depression and even result in comorbidity. Additionally, migraineurs with comorbid depression had different developmental trajectories in the right thalamus and fusiform, which were associated with recognizing, transmitting, controlling and remembering pain and emotion. CONCLUSIONS Based on our findings, the abnormal mPFC which may contribute to determining the common symptoms in migraine and depression and may be a therapeutic target for migraineurs comorbid depression. The different developmental trajectory in thalamus and fusiform indicates that the comorbidity may arise through a specific mechanism rather than simple superposition of migraine and depression.
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Affiliation(s)
- Mengmeng Ma
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Wainan Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Junran Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- Department of Medical Information Engineering, School of Electrical Engineering and Information, Sichuan University, Chengdu, China
| | - Ning Chen
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Wainan Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Jian Guo
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Wainan Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Yang Zhang
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Wainan Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Li He
- Department of Neurology, West China Hospital, Sichuan University, No. 37, Wainan Guoxue Xiang, Chengdu, 610041, Sichuan, China.
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35
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Agosta F, Mandic-Stojmenovic G, Canu E, Stojkovic T, Imperiale F, Caso F, Stefanova E, Copetti M, Kostic VS, Filippi M. Functional and structural brain networks in posterior cortical atrophy: A two-centre multiparametric MRI study. NEUROIMAGE-CLINICAL 2018; 19:901-910. [PMID: 30013929 PMCID: PMC6019262 DOI: 10.1016/j.nicl.2018.06.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 05/07/2018] [Accepted: 06/12/2018] [Indexed: 11/24/2022]
Abstract
This study identified structural and functional brain connectivity alterations in two independent samples of patients along the posterior cortical atrophy (PCA) disease course. Twenty-one PCA patients and 44 controls were recruited from two expert centres. Microstructural damage of white matter (WM) tracts was assessed using probabilistic tractography; resting state (RS) functional connectivity of brain networks was explored using a model free approach; grey matter (GM) atrophy was investigated using voxel-based morphometry. Compared with controls, common patterns of damage across PCA patients included: GM atrophy in the occipital-temporal-parietal regions; diffusion tensor (DT) MRI alterations of the corpus callosum and superior (SLF) and inferior longitudinal fasciculi (ILF) bilaterally; and decreased functional connectivity of the occipital gyri within the visual network and the precuneus and posterior cingulum within the default mode network (DMN). In PCA patients with longer disease duration and greater disease severity, WM damage extended to the cingulum and RS functional connectivity alterations spread within the frontal, dorsal attentive and salience networks. In PCA, reduced DMN functional connectivity was associated with SLF and ILF structural alterations. PCA patients showed distributed WM damage. Altered RS functional connectivity extends with disease worsening from occipital to temporo-parietal and frontostriatal regions, and this is likely to occur through WM connections. Future longitudinal studies are needed to establish trajectories of damage spreading in PCA and whether a combined DT MRI/RS functional MRI approach is promising in monitoring the disease progression. PCA patients showed distributed WM damage. In PCA, WM damage is associated with longer disease duration ad greater severity. In PCA, altered RS functional connectivity extends with disease worsening.
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Affiliation(s)
- Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - Gorana Mandic-Stojmenovic
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy; Clinic of Neurology, University of Belgrade, Dr Subotića 6, PO, Box 12, 11129, Belgrade 102, Serbia
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - Tanja Stojkovic
- Clinic of Neurology, University of Belgrade, Dr Subotića 6, PO, Box 12, 11129, Belgrade 102, Serbia
| | - Francesca Imperiale
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - Francesca Caso
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - Elka Stefanova
- Clinic of Neurology, University of Belgrade, Dr Subotića 6, PO, Box 12, 11129, Belgrade 102, Serbia
| | - Massimiliano Copetti
- Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, Viale Cappuccini, San Giovanni Rotondo 71013, Foggia, Italy
| | - Vladimir S Kostic
- Clinic of Neurology, University of Belgrade, Dr Subotića 6, PO, Box 12, 11129, Belgrade 102, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy; Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy.
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36
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Boccardi M, Gallo V, Yasui Y, Vineis P, Padovani A, Mosimann U, Giannakopoulos P, Gold G, Dubois B, Jack CR, Winblad B, Frisoni GB, Albanese E. The biomarker-based diagnosis of Alzheimer's disease. 2-lessons from oncology. Neurobiol Aging 2017; 52:141-152. [PMID: 28317645 DOI: 10.1016/j.neurobiolaging.2017.01.021] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 01/19/2017] [Accepted: 01/27/2017] [Indexed: 12/20/2022]
Abstract
Biomarkers for the diagnosis of Alzheimer's disease (AD) are not yet validated for use in clinical settings. We aim to provide a methodological framework for their systematic validation, by reference to that developed for oncology biomarkers. As for this discipline, the steps for the systematic validation of AD biomarkers need to target analytical validity, clinical validity, and clinical utility. However, the premises are different from oncology: the nature of disease (neurodegeneration vs. cancer), the purpose (improve diagnosis in clinically affected vs. screening preclinical individuals), and the target population (mild cognitive impairment patients referring to memory clinics vs. general population) lead to important differences, influencing both the design of validation studies and the use of selected biomarkers. This framework is applied within a wider initiative to assess the current available evidence on the clinical validity of biomarkers for AD, for the final aim to identify gaps and research priorities, and to inform coordinated research efforts boosting AD biomarkers research.
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Affiliation(s)
- Marina Boccardi
- Department of Psychiatry, LANVIE-Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS S.Giovanni di Dio-Fatebenefratelli, Brescia, Italy.
| | - Valentina Gallo
- Centre of Primary Care and Public Health, Queen Mary, University of London, Barts and the London School of Medicine, Blizard Institute, London, UK
| | - Yutaka Yasui
- School of Public Health, University of Alberta, Alberta, Canada; Department of Epidemiology & Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Paolo Vineis
- School of Public Health, Imperial College London, London, UK
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University Health and Wealth of Brescia, Brescia, Italy
| | - Urs Mosimann
- Gerontechnology & Rehabilitation Group, University of Bern, Bern, Switzerland; University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Gabriel Gold
- Department of Internal Medicine, Rehabilitation and Geriatrics, University Hospitals and University of Geneva, Thônex, Switzerland
| | - Bruno Dubois
- Dementia Research Center and Department of Neurology, Salpêtrière University Hospital, Paris University, Paris, France
| | | | - Bengt Winblad
- Center for Alzheimer Research, Division of Neurogeriatrics, Department of NVS, Karolinska Institutet, Huddinge, Sweden
| | - Giovanni B Frisoni
- Department of Psychiatry, LANVIE-Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS S.Giovanni di Dio-Fatebenefratelli, Brescia, Italy; Memory Clinic, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Emiliano Albanese
- Department of Psychiatry, WHO Collaborating Centre, University of Geneva, Geneva, Switzerland
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37
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Jacquemont T, De Vico Fallani F, Bertrand A, Epelbaum S, Routier A, Dubois B, Hampel H, Durrleman S, Colliot O. Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment. Neurobiol Aging 2017; 55:177-189. [DOI: 10.1016/j.neurobiolaging.2017.03.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 03/17/2017] [Accepted: 03/19/2017] [Indexed: 01/01/2023]
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38
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Raj D, Yin Z, Breur M, Doorduin J, Holtman IR, Olah M, Mantingh-Otter IJ, Van Dam D, De Deyn PP, den Dunnen W, Eggen BJL, Amor S, Boddeke E. Increased White Matter Inflammation in Aging- and Alzheimer's Disease Brain. Front Mol Neurosci 2017; 10:206. [PMID: 28713239 PMCID: PMC5492660 DOI: 10.3389/fnmol.2017.00206] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 06/12/2017] [Indexed: 11/13/2022] Open
Abstract
Chronic neuroinflammation, which is primarily mediated by microglia, plays an essential role in aging and neurodegeneration. It is still unclear whether this microglia-induced neuroinflammation occurs globally or is confined to distinct brain regions. In this study, we investigated microglia activity in various brain regions upon healthy aging and Alzheimer's disease (AD)-related pathology in both human and mouse samples. In purified microglia isolated from aging mouse brains, we found a profound gene expression pattern related to pro-inflammatory processes, phagocytosis, and lipid homeostasis. Particularly in white matter microglia of 24-month-old mice, abundant expression of phagocytic markers including Mac-2, Axl, CD16/32, Dectin1, CD11c, and CD36 was detected. Interestingly, in white matter of human brain tissue the first signs of inflammatory activity were already detected during middle age. Thus quantification of microglial proteins, such as CD68 (commonly associated with phagocytosis) and HLA-DR (associated with antigen presentation), in postmortem human white matter brain tissue showed an age-dependent increase in immunoreactivity already in middle-aged people (53.2 ± 2.0 years). This early inflammation was also detectable by non-invasive positron emission tomography imaging using [11C]-(R)-PK11195, a ligand that binds to activated microglia. Increased microglia activity was also prominently present in the white matter of human postmortem early-onset AD (EOAD) brain tissue. Interestingly, microglia activity in the white matter of late-onset AD (LOAD) CNS was similar to that of the aged clinically silent AD cases. These data indicate that microglia-induced neuroinflammation is predominant in the white matter of aging mice and humans as well as in EOAD brains. This white matter inflammation may contribute to the progression of neurodegeneration, and have prognostic value for detecting the onset and progression of aging and neurodegeneration.
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Affiliation(s)
- Divya Raj
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Zhuoran Yin
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands.,Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhan, China
| | - Marjolein Breur
- Department of Pathology, VU University Medical CenterAmsterdam, Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Inge R Holtman
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Marta Olah
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Ietje J Mantingh-Otter
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Debby Van Dam
- Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of AntwerpWilrijk, Belgium.,Department of Neurology and Alzheimer Research Center, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Peter P De Deyn
- Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of AntwerpWilrijk, Belgium.,Department of Neurology and Alzheimer Research Center, University Medical Center Groningen, University of GroningenGroningen, Netherlands.,Biobank, Institute Born-BungeWilrijk, Belgium
| | - Wilfred den Dunnen
- Department of Pathology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Bart J L Eggen
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
| | - Sandra Amor
- Department of Pathology, VU University Medical CenterAmsterdam, Netherlands.,Neuroimmunology Unit, Blizard Institute of Cell and Molecular Science, Barts and The London School of Medicine and DentistryLondon, United Kingdom
| | - Erik Boddeke
- Department of Neuroscience, Section Medical Physiology, University Medical Center Groningen, University of GroningenGroningen, Netherlands
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39
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Slattery CF, Zhang J, Paterson RW, Foulkes AJM, Carton A, Macpherson K, Mancini L, Thomas DL, Modat M, Toussaint N, Cash DM, Thornton JS, Henley SMD, Crutch SJ, Alexander DC, Ourselin S, Fox NC, Zhang H, Schott JM. ApoE influences regional white-matter axonal density loss in Alzheimer's disease. Neurobiol Aging 2017; 57:8-17. [PMID: 28578156 PMCID: PMC5538347 DOI: 10.1016/j.neurobiolaging.2017.04.021] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 04/14/2017] [Accepted: 04/22/2017] [Indexed: 01/10/2023]
Abstract
Mechanisms underlying phenotypic heterogeneity in young onset Alzheimer disease (YOAD) are poorly understood. We used diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI) with tract-based spatial statistics to investigate apolipoprotein (APOE) ε4 modulation of white-matter damage in 37 patients with YOAD (22, 59% APOE ε4 positive) and 23 age-matched controls. Correlation between neurite density index (NDI) and neuropsychological performance was assessed in 4 white-matter regions of interest. White-matter disruption was more widespread in ε4+ individuals but more focal (posterior predominant) in the absence of an ε4 allele. NODDI metrics indicate fractional anisotropy changes are underpinned by combinations of axonal loss and morphological change. Regional NDI in parieto-occipital white matter correlated with visual object and spatial perception battery performance (right and left, both p = 0.02), and performance (nonverbal) intelligence (WASI matrices, right, p = 0.04). NODDI provides tissue-specific microstructural metrics of white-matter tract damage in YOAD, including NDI which correlates with focal cognitive deficits, and APOEε4 status is associated with different patterns of white-matter neurodegeneration.
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Affiliation(s)
- Catherine F Slattery
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK.
| | - Jiaying Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Ross W Paterson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | | | - Amelia Carton
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Kirsty Macpherson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology, London, UK
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nicolas Toussaint
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - David M Cash
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK; Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Susie M D Henley
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Sebastian J Crutch
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Daniel C Alexander
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nick C Fox
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
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Abstract
Early-onset Alzheimer disease (EOAD), with onset in individuals younger than 65 years, although overshadowed by the more common late-onset AD (LOAD), differs significantly from LOAD. EOAD comprises approximately 5% of AD and is associated with delays in diagnosis, aggressive course, and age-related psychosocial needs. One source of confusion is that a substantial percentage of EOAD are phenotypic variants that differ from the usual memory-disordered presentation of typical AD. The management of EOAD is similar to that for LOAD, but special emphasis should be placed on targeting the specific cognitive areas involved and more age-appropriate psychosocial support and education.
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Affiliation(s)
- Mario F Mendez
- Behavioral Neurology Program, David Geffen School of Medicine at UCLA, 300 Westwood Plaza, Suite B-200, Box 956975, Los Angeles, CA 90095, USA; Neurobehavior Unit, VA Greater Los Angeles Healthcare System, 11301 Wilshire Boulevard, Building 206, Los Angeles, CA 90073, USA.
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41
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Leyton CE, Hodges JR, Piguet O, Ballard KJ. Common and divergent neural correlates of anomia in amnestic and logopenic presentations of Alzheimer's disease. Cortex 2017; 86:45-54. [DOI: 10.1016/j.cortex.2016.10.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 10/12/2016] [Accepted: 10/24/2016] [Indexed: 11/16/2022]
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42
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Ishiwata A, Kimura K. Homonymous Hemianopsia Associated with Probable Alzheimer's Disease. J NIPPON MED SCH 2016; 83:87-92. [PMID: 27180794 DOI: 10.1272/jnms.83.87] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Posterior cortical atrophy (PCA) is a rare neurodegenerative disorder that has cerebral atrophy in the parietal, occipital, or occipitotemporal cortices and is characterized by visuospatial and visuoperceptual impairments. The most cases are pathologically compatible with Alzheimer's disease (AD). We describe a case of PCA in which a combination of imaging methods, in conjunction with symptoms and neurological and neuropsychological examinations, led to its being diagnosed and to AD being identified as its probable cause. Treatment with donepezil for 6 months mildly improved alexia symptoms, but other symptoms remained unchanged. A 59-year-old Japanese woman with progressive alexia, visual deficit, and mild memory loss was referred to our neurologic clinic for the evaluation of right homonymous hemianopsia. Our neurological examination showed alexia, constructional apraxia, mild disorientation, short-term memory loss, and right homonymous hemianopsia. These findings resulted in a score of 23 (of 30) points on the Mini-Mental State Examination. Occipital atrophy was identified, with magnetic resonance imaging (MRI) showing left-side dominance. The MRI data were quantified with voxel-based morphometry, and PCA was diagnosed on the basis of these findings. Single photon emission computed tomography with (123)I-N-isopropyl-p-iodoamphetamine showed hypoperfusion in the corresponding voxel-based morphometry occipital lobes. Additionally, the finding of hypoperfusion in the posterior associate cortex, posterior cingulate gyrus, and precuneus was consistent with AD. Therefore, the PCA was considered to be a result of AD. We considered Lewy body dementia as a differential diagnosis because of the presence of hypoperfusion in the occipital lobes. However, the patient did not meet the criteria for Lewy body dementia during the course of the disease. We therefore consider including PCA in the differential diagnoses to be important for patients with visual deficit, cognitive impairment, and cerebral atrophy in the parietal, occipital, or occipitotemporal cortices. A combination of imaging methods, including MRI and single photon emission computed tomography, may help identify probable causes of PCA.
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Affiliation(s)
- Akiko Ishiwata
- Departments of Neurological Science, Graduate School of Medicine, Nippon Medical School
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43
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Migliaccio R, Gallea C, Kas A, Perlbarg V, Samri D, Trotta L, Michon A, Lacomblez L, Dubois B, Lehericy S, Bartolomeo P. Functional Connectivity of Ventral and Dorsal Visual Streams in Posterior Cortical Atrophy. J Alzheimers Dis 2016; 51:1119-30. [DOI: 10.3233/jad-150934] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Raffaella Migliaccio
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Department of Neurology, Institut de la mémoire et de la maladie d’Alzheimer, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Cécile Gallea
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Centre de Neuro-imagerie de Recherche (CENIR) de l’Institut du Cerveau et de la Moelle Epiniere (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France
- Equipe “Mouvements Anormaux et Ganglions de la Base”, Institut du Cerveau et de la Moëlle Epinière, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Aurélie Kas
- Service de médecine nucléaire, Hôpital Pitié-Salpêtrière, APHP, Paris, France
- INSERM U1146, CNRS UMR7371, laboratoire d’imagerie biomédicale, Sorbonne université, UPMC université, Paris 60 UMCR2, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Vincent Perlbarg
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- INSERM U1146, CNRS UMR7371, laboratoire d’imagerie biomédicale, Sorbonne université, UPMC université, Paris 60 UMCR2, Hôpital de la Pitié-Salpêtrière, Paris, France
- IHU-A-ICM, Bioinformatics/Biostatistis Plateform, Paris, France
| | - Dalila Samri
- Department of Neurology, Institut de la mémoire et de la maladie d’Alzheimer, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Laura Trotta
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Department of Neurology, Institut de la mémoire et de la maladie d’Alzheimer, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Agnès Michon
- Department of Neurology, Institut de la mémoire et de la maladie d’Alzheimer, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Lucette Lacomblez
- INSERM U1146, CNRS UMR7371, laboratoire d’imagerie biomédicale, Sorbonne université, UPMC université, Paris 60 UMCR2, Hôpital de la Pitié-Salpêtrière, Paris, France
- Department des maladies du système nerveux, CIC-CET, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
- Service de pharmacologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Bruno Dubois
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Department of Neurology, Institut de la mémoire et de la maladie d’Alzheimer, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - Stéphane Lehericy
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Centre de Neuro-imagerie de Recherche (CENIR) de l’Institut du Cerveau et de la Moelle Epiniere (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Paolo Bartolomeo
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), F-75013 Paris, France
- Department of Psychology, Catholic University, Milan, Italy
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Maye JE, Betensky RA, Gidicsin CM, Locascio J, Becker JA, Pepin L, Carmasin J, Rentz DM, Marshall GA, Blacker D, Sperling RA, Johnson KA. Maternal dementia age at onset in relation to amyloid burden in non-demented elderly offspring. Neurobiol Aging 2016; 40:61-67. [PMID: 26973104 PMCID: PMC4792089 DOI: 10.1016/j.neurobiolaging.2015.12.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 12/18/2015] [Accepted: 12/21/2015] [Indexed: 01/17/2023]
Abstract
Family history (FH) of dementia is a major risk factor for Alzheimer's disease, particularly when the FH is maternal and when the age of dementia onset (AO) is younger. This study tested whether brain amyloid-beta deposition, measured in vivo with (11)C-Pittsburgh compound B (PiB), was associated with parental dementia and/or younger parental AO. Detailed FH and positron emission tomography (PiB) data were acquired in 147 nondemented aging individuals (mean age 75 ± 8). No participant had both positive maternal and paternal FH. A series of analyses revealed that those with maternal, but not paternal, FH had greater levels of PiB retention in a global cortical region than those without FH. PiB retention in maternal FH was not significantly greater than paternal FH. Younger maternal dementia AO was related to greater PiB retention in offspring, whereas younger paternal dementia AO was not. Overall, results suggest that not only is amyloid-beta burden greater in individuals with maternal FH, but also that the burden is greater in association with younger maternal AO.
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Affiliation(s)
- Jacqueline E Maye
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Rebecca A Betensky
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christopher M Gidicsin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph Locascio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - J Alex Becker
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lesley Pepin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeremy Carmasin
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, USA
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Deborah Blacker
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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45
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Barha CK, Nagamatsu LS, Liu-Ambrose T. Basics of neuroanatomy and neurophysiology. HANDBOOK OF CLINICAL NEUROLOGY 2016; 138:53-68. [PMID: 27637952 DOI: 10.1016/b978-0-12-802973-2.00004-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
This chapter presents an overview of the anatomy and functioning of the central nervous system. We begin the discussion by first examining the cellular basis of neural transmission. Then we present a brief description of the brain's white and gray matter and associated diseases, including a discussion of white-matter lesions. Finally, we place this information into context by discussing how the central nervous system integrates complex information to guide key functional systems, including the visual, auditory, chemosensory, somatic, limbic, motor, and autonomic systems. Where appropriate, we have supplied information pertaining to pathologic and functional outcomes of damage to the central nervous system. Also included is a brief description of important tools and methods used in the study of neuroanatomy and neurophysiology. Overall, this chapter provides a basic review of the concepts required to understand and interpret the clinical disorders and related material presented in the subsequent chapters of this book.
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Affiliation(s)
- C K Barha
- Aging, Mobility, and Cognitive Neuroscience Laboratory, Department of Physical Therapy, Faculty of Medicine and Djavad Mowafaghian Centre for Brain Health, University of British Columbia Vancouver, BC, Canada
| | - L S Nagamatsu
- Exercise, Mobility and Brain Health Laboratory, School of Kinesiology, Faculty of Health Sciences, Western University, London, Ontario, Canada
| | - T Liu-Ambrose
- Aging, Mobility, and Cognitive Neuroscience Laboratory, Department of Physical Therapy, Faculty of Medicine and Djavad Mowafaghian Centre for Brain Health, University of British Columbia Vancouver, BC, Canada; Brain Research Centre, University of British Columbia Vancouver, BC, Canada.
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Caso F, Agosta F, Filippi M. Insights into White Matter Damage in Alzheimer's Disease: From Postmortem to in vivo Diffusion Tensor MRI Studies. NEURODEGENER DIS 2015; 16:26-33. [DOI: 10.1159/000441422] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 10/01/2015] [Indexed: 11/19/2022] Open
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47
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Agosta F, Weiler M, Filippi M. Propagation of pathology through brain networks in neurodegenerative diseases: from molecules to clinical phenotypes. CNS Neurosci Ther 2015; 21:754-67. [PMID: 26031656 DOI: 10.1111/cns.12410] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 04/29/2015] [Accepted: 04/30/2015] [Indexed: 12/11/2022] Open
Abstract
The cellular mechanisms underlying the stereotypical progression of pathology in neurodegenerative diseases are incompletely understood, but increasing evidence indicates that misfolded protein aggregates can spread by a self-perpetuating neuron-to-neuron transmission. Novel neuroimaging techniques can help elucidating how these disorders spread across brain networks. Recent knowledge from structural and functional connectivity studies suggests that the relation between neurodegenerative diseases and distinct brain networks is likely to be a strict consequence of diffuse network dynamics. Diffusion tensor magnetic resonance imaging also showed that measurement of white matter tract involvement can be a valid surrogate to assess the in vivo spreading of pathological proteins in these conditions. This review will introduce briefly the main molecular and pathological substrates of the most frequent neurodegenerative diseases and provide a comprehensive overview of neuroimaging findings that support the "network-based neurodegeneration" hypothesis in these disorders. Characterizing network breakdown in neurodegenerative diseases will help anticipate and perhaps prevent the devastating impact of these conditions.
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Affiliation(s)
- Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Marina Weiler
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Laboratory of Neuroimaging, University of Campinas, Campinas, Brazil
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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