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Luo N, Lin K, Cai Y, Zhang Z, Sui X, Han Z, Yuan W, Xing J, Gui Z, Liu G, Wang J, Xu F. An engineered adeno-associated virus mediates efficient blood-brain barrier penetration with enhanced neurotropism and reduced hepatotropism. J Control Release 2025; 379:303-315. [PMID: 39798705 DOI: 10.1016/j.jconrel.2025.01.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 12/22/2024] [Accepted: 01/08/2025] [Indexed: 01/15/2025]
Abstract
The blood-brain barrier (BBB) is a formidable barrier that restricts the entry of substances into the brain, complicating the study of brain function and the treatment of neurological conditions. Traditional methods of delivering genes from the periphery to the central nervous system (CNS) using adeno-associated viruses (AAVs) often require high doses, which can trigger immune responses and hepatotoxicity. Here, we developed a new AAV variant named AAVhu.32-PLUS based on a rational strategy. Following intravenous injection, AAVhu.32-PLUS can cross the BBB and exhibits higher efficiency and specificity in transducing neurons and significantly reduced hepatotropism compared to the extensively used AAV-PHP.eB. Furthermore, through in vitro cell experiments, we identified that AAVhu.32-PLUS may rely on the LY6A receptor for crossing the BBB. Finally, our research indicates that AAVhu.32-PLUS, while having lower transduction efficiency in astrocytes compared to AAV-PHP.eB, is still capable of efficiently transducing glioblastoma after intravenous injection. These properties make AAVhu.32-PLUS a promising tool for neuroscience research and targeted therapies of brain disease.
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Affiliation(s)
- Nengsong Luo
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, 430074 Wuhan, PR China; Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China; Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, 430071 Wuhan, PR China
| | - Kunzhang Lin
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China; Key Laboratory of Quality Control Technology for Virus-Based Therapeutics, Guangdong Provincial Medical Products Administration, NMPA Key Laboratory for Research and Evaluation of Viral Vector Technology in Cell and Gene Therapy Medicinal Products, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China.
| | - Yuxiang Cai
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, 430074 Wuhan, PR China
| | - Zilian Zhang
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China; Key Laboratory of Quality Control Technology for Virus-Based Therapeutics, Guangdong Provincial Medical Products Administration, NMPA Key Laboratory for Research and Evaluation of Viral Vector Technology in Cell and Gene Therapy Medicinal Products, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China
| | - Xiaokai Sui
- Zhongnan Hospital, Wuhan University, 430072 Wuhan, PR China
| | - Zengpeng Han
- Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Wenjia Yuan
- Brain Case Biotechnology Co., Ltd., 518107 Shenzhen, PR China
| | - Jiayong Xing
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China
| | - Zhu Gui
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, 430071 Wuhan, PR China; University of Chinese Academy of Sciences, 100049 Beijing, PR China
| | - Gangning Liu
- College of Life Sciences, Wuhan University, 430072 Wuhan, PR China
| | - Jie Wang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, 430071 Wuhan, PR China; University of Chinese Academy of Sciences, 100049 Beijing, PR China
| | - Fuqiang Xu
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, 430074 Wuhan, PR China; Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China; Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, 430071 Wuhan, PR China; Key Laboratory of Quality Control Technology for Virus-Based Therapeutics, Guangdong Provincial Medical Products Administration, NMPA Key Laboratory for Research and Evaluation of Viral Vector Technology in Cell and Gene Therapy Medicinal Products, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055 Shenzhen, PR China; University of Chinese Academy of Sciences, 100049 Beijing, PR China; Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 200031 Shanghai, PR China.
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Phan TX, Mullins WA, Tetrault AM, Shibata K, Lee JL, Hett K, Considine CM, Darby RR. Transdiagnostic Network Localization of Social, Language, and Motor Symptoms in Patients With Frontotemporal Lobar Degeneration. Neurology 2024; 103:e210108. [PMID: 39586043 PMCID: PMC11590234 DOI: 10.1212/wnl.0000000000210108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 10/10/2024] [Indexed: 11/27/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Frontotemporal lobar degeneration (FTLD) includes different clinical syndromes with distinct patterns of symptoms and neuroanatomical locations of neurodegeneration. However, FTLD is clinically heterogeneous (with overlapping symptoms across several domains) and neuroanatomically heterogeneous (with brain atrophy in different locations in different patients). Traditional methods struggle to fully account for this heterogeneity. In this study, we use a relatively new neuroimaging approach, atrophy network mapping, to localize clinical symptoms in patients with FTLD to specific brain networks transdiagnostically. METHODS Data were obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative and 4-Repeat Tauopathy Neuroimaging Initiative. Inclusion required T1-weighted MRI and a diagnosis of behavioral-variant frontotemporal dementia (bvFTD), semantic-variant primary progressive aphasia (svPPA), nonfluent primary progressive aphasia (nfvPPA), progressive supranuclear palsy Richardson syndrome (PSP-rs), corticobasal syndrome (CBS), or normal cognition. Measures of social cognition (Interpersonal Reactivity Index, Revised Self-Monitoring Scale), language (Boston Naming Test, Animal Fluency), and motor function (Unified Parkinson Disease Rating Scale Part III, PSP Rating Scale) were correlated with neuroimaging measures, including cortical thickness, volume, and atrophy network mapping, a newer method that localizes regions connected to brain atrophy using a functional connectome from cognitively normal persons (n = 1,000). RESULTS Fifty-seven patients with bvFTD (age 61.2 ± 6.8 years, 35% female), 41 PSP-rs (age 69.7 ± 7.4 years, 54% female), 39 CBS (age 66.2 ± 6.2 years, 51% female), 37 svPPA (age 63.0 ± 6.0 years, 46% female), and 36 nfvPPA (age 68.3 ± 7.3 years, 53% female) and 135 healthy age-matched controls (age 63.3 ± 7.4 years, 58% female) were included. Compared with atrophy alone, atrophy network mapping showed more consistent neuroimaging results across patients with the same clinical syndrome (Dice index mean 0.68 vs 0.11, paired t = 263.1, df = 4,452, p < 0.001), more strongly explained social cognition (F(1, 84) = 10.2, p = 0.002) and motor symptoms (F(1, 185) = 91.3, p < 0.001) across different syndromes, and showed novel neuroanatomical associations, with the temporal parietal junction relating to social cognition; Wernicke area relating to language symptoms; and association sensorimotor cortex, thalamus, and cerebellum relating to motor symptoms. DISCUSSION Atrophy network mapping can improve understanding of brain-behavior relationships in clinically and neuroanatomically heterogeneous disorders such as FTLD.
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Affiliation(s)
- Tony X Phan
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - W Andrew Mullins
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Aaron M Tetrault
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Kiiya Shibata
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Jayden L Lee
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Kilian Hett
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Ciaran M Considine
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - R Ryan Darby
- From the Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
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Gkintoni E, Michou E. Advancing Neuropsychological Rehabilitation in Primary Progressive Aphasia Based on Principles of Cognitive Neuroscience: A Scoping Review and Systematic Analysis of the Data. Brain Sci 2024; 14:1234. [PMID: 39766433 PMCID: PMC11727489 DOI: 10.3390/brainsci14121234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2024] [Revised: 12/03/2024] [Accepted: 12/06/2024] [Indexed: 01/15/2025] Open
Abstract
Background/Objectives: This systematic review of neuropsychological rehabilitation strategies for primary progressive aphasia will consider recent developments in cognitive neuroscience, especially neuroimaging techniques such as EEG and fMRI, to outline how these tools might be integrated into clinical practice to maximize treatment outcomes. Methods: A systematic search of peer-reviewed literature from the last decade was performed following the PRISMA guidelines across multiple databases. A total of 63 studies were included, guided by predefined inclusion and exclusion criteria, with a focus on cognitive and language rehabilitation in PPA, interventions guided by neuroimaging, and mechanisms of neuroplasticity. Results: Integration of neuroimaging techniques contributes to the increase in the efficacy of interventions with critical information about the neural mechanisms underlying language deficits in the aphasias. Traditional rehabilitation strategies, technology-assisted interventions, and non-invasive brain stimulation techniques hold considerable promise for language improvement. Neuroimaging was also found to be necessary in subtype-specific differentiation toward tailoring therapeutic intervention. Evidence also shows that directed and sustained interventions using neuroplasticity can have long-term effects in managing the symptoms of PPA. Conclusions: The present review underlines the necessity of including cognitive neuroscience techniques within neuropsychological rehabilitation to enhance therapeutic outcomes in PPA. In addition, neuroimaging modalities such as EEG and fMRI are also of great importance in understanding the underlying neurobiology of language disturbances and guiding tailored interventions. Long-term benefits of these approaches should be evaluated, including their applicability in routine clinical practice.
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Affiliation(s)
- Evgenia Gkintoni
- Department of Psychiatry, University General Hospital of Patras, 26504 Patras, Greece
| | - Emilia Michou
- Department of Speech and Language Therapy, University of Patras, 26504 Patras, Greece;
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Lavanya M, Namasivayam SKR, Priyanka S, Abiraamavalli T. Microencapsulation and nanoencapsulation of bacterial probiotics: new frontiers in Alzheimer's disease treatment. 3 Biotech 2024; 14:313. [PMID: 39611008 PMCID: PMC11599650 DOI: 10.1007/s13205-024-04158-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Accepted: 11/08/2024] [Indexed: 11/30/2024] Open
Abstract
Alzheimer's disease, a progressive neurodegenerative disorder marked by cognitive decline, affects millions worldwide. The presence of amyloid plaques and neurofibrillary tangles in the brain is the key pathological feature, leading to neuronal dysfunction and cell death. Current treatment options include pharmacological approaches such as cholinesterase inhibitors, as well as non-pharmacological strategies like cognitive training and lifestyle modifications. Recently, the potential role of probiotics, particularly strains, such as Lactobacillus and Bifidobacterium, in managing neurodegenerative diseases through the gut-brain axis has garnered significant attention. Probiotics can modulate inflammation, produce neurotransmitters, and support neuronal health, potentially slowing disease progression and alleviating symptoms, such as stress and anxiety. Optimizing the pharmacotherapeutic effects of probiotics is critical and involves advanced formulation techniques, such as microencapsulation and nanoencapsulation. Microencapsulation employs natural or synthetic polymers to protect probiotic cells, enhancing their viability and stability against environmental stressors. Methods like extrusion, emulsion, and spray-drying are used to create microcapsules suited for various applications. Nanoencapsulation, on the other hand, operates at the nanoscale, utilizing polymeric or lipid-based nanoparticles to improve the bioavailability and shelf life of probiotics. Techniques, such as nanoprecipitation and emulsification, are employed to ensure stable nanocapsule formation, thereby augmenting the therapeutic potential of probiotics as nutraceutical agents. This study delves into the essential formulation aspects of microencapsulation and nanoencapsulation for beneficial probiotic strains, aimed at managing Alzheimer's disease by optimizing the gut-brain axis. The insights gained from these advanced techniques promise to enhance probiotic delivery efficacy, potentially leading to improved health outcomes for patients suffering from neurodegenerative disorders.
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Affiliation(s)
- M. Lavanya
- Centre for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu 602105 India
| | - S. Karthick Raja Namasivayam
- Centre for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu 602105 India
| | - S. Priyanka
- Centre for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu 602105 India
| | - T. Abiraamavalli
- Centre for Applied Research, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu 602105 India
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Firdaus Z, Li X. Epigenetic Explorations of Neurological Disorders, the Identification Methods, and Therapeutic Avenues. Int J Mol Sci 2024; 25:11658. [PMID: 39519209 PMCID: PMC11546397 DOI: 10.3390/ijms252111658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 10/26/2024] [Accepted: 10/26/2024] [Indexed: 11/16/2024] Open
Abstract
Neurodegenerative disorders are major health concerns globally, especially in aging societies. The exploration of brain epigenomes, which consist of multiple forms of DNA methylation and covalent histone modifications, offers new and unanticipated perspective into the mechanisms of aging and neurodegenerative diseases. Initially, chromatin defects in the brain were thought to be static abnormalities from early development associated with rare genetic syndromes. However, it is now evident that mutations and the dysregulation of the epigenetic machinery extend across a broader spectrum, encompassing adult-onset neurodegenerative diseases. Hence, it is crucial to develop methodologies that can enhance epigenetic research. Several approaches have been created to investigate alterations in epigenetics on a spectrum of scales-ranging from low to high-with a particular focus on detecting DNA methylation and histone modifications. This article explores the burgeoning realm of neuroepigenetics, emphasizing its role in enhancing our mechanistic comprehension of neurodegenerative disorders and elucidating the predominant techniques employed for detecting modifications in the epigenome. Additionally, we ponder the potential influence of these advancements on shaping future therapeutic approaches.
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Affiliation(s)
- Zeba Firdaus
- Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA;
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA
| | - Xiaogang Li
- Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA;
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA
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Kumar S, Earnest T, Yang B, Kothapalli D, Aschenbrenner AJ, Hassenstab J, Xiong C, Ances B, Morris J, Benzinger TLS, Gordon BA, Payne P, Sotiras A, Alzheimer’s Disease Neuroimaging Initiative. Analyzing heterogeneity in Alzheimer Disease using multimodal normative modeling on imaging-based ATN biomarkers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.15.553412. [PMID: 37662280 PMCID: PMC10473626 DOI: 10.1101/2023.08.15.553412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
INTRODUCTION Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer Disease (AD) heterogeneity. We employed a deep learning-based multimodal normative framework to analyze individual-level variation across ATN (amyloid-tau-neurodegeneration) imaging biomarkers. METHODS We selected cross-sectional discovery (n = 665) and replication cohorts (n = 430) with available T1-weighted MRI, amyloid and tau PET. Normative modeling estimated individual-level abnormal deviations in amyloid-positive individuals compared to amyloid-negative controls. Regional abnormality patterns were mapped at different clinical group levels to assess intra-group heterogeneity. An individual-level disease severity index (DSI) was calculated using both the spatial extent and magnitude of abnormal deviations across ATN. RESULTS Greater intra-group heterogeneity in ATN abnormality patterns was observed in more severe clinical stages of AD. Higher DSI was associated with worse cognitive function and increased risk of disease progression. DISCUSSION Subject-specific abnormality maps across ATN reveal the heterogeneous impact of AD on the brain.
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Affiliation(s)
- Sayantan Kumar
- Department of Computer Science and Engineering, Washington University in St Louis; 1 Brookings Drive, Saint Louis, MO 63130
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St Louis; 660 S. Euclid Ave, Campus Box 8132, Saint Louis, MO 63110
| | - Tom Earnest
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Braden Yang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Deydeep Kothapalli
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Andrew J. Aschenbrenner
- Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8111, St louis, MO 63110
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8111, St louis, MO 63110
| | - Chengie Xiong
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St Louis; 660 S. Euclid Ave, Campus Box 8132, Saint Louis, MO 63110
| | - Beau Ances
- Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8111, St louis, MO 63110
| | - John Morris
- Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8111, St louis, MO 63110
| | - Tammie L. S. Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Brian A. Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Philip Payne
- Department of Computer Science and Engineering, Washington University in St Louis; 1 Brookings Drive, Saint Louis, MO 63130
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St Louis; 660 S. Euclid Ave, Campus Box 8132, Saint Louis, MO 63110
| | - Aristeidis Sotiras
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St Louis; 660 S. Euclid Ave, Campus Box 8132, Saint Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
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Mannone M, Fazio P, Marwan N. Modeling a neurological disorder as the result of an operator acting on the brain: A first sketch based on network channel modeling. CHAOS (WOODBURY, N.Y.) 2024; 34:053133. [PMID: 38781106 DOI: 10.1063/5.0199988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 05/06/2024] [Indexed: 05/25/2024]
Abstract
The brain is a complex network, and diseases can alter its structures and connections between regions. Therefore, we can try to formalize the action of diseases by using operators acting on the brain network. Here, we propose a conceptual model of the brain, seen as a multilayer network, whose intra-lobe interactions are formalized as the diagonal blocks of an adjacency matrix. We propose a general and abstract definition of disease as an operator altering the weights of the connections between neural agglomerates, that is, the elements of the brain matrix. As models, we consider examples from three neurological disorders: epilepsy, Alzheimer-Perusini's disease, and schizophrenia. The alteration of neural connections can be seen as alterations of communication pathways, and thus, they can be described with a new channel model.
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Affiliation(s)
- Maria Mannone
- Institute of Physics and Astronomy, University of Potsdam, 14476 Potsdam, Germany
- DSMN, Ca' Foscari University of Venice, 30170 Venezia Mestre Italy
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, 14473 Potsdam, Germany
| | - Peppino Fazio
- DSMN, Ca' Foscari University of Venice, 30170 Venezia Mestre Italy
- VSB, Technical University of Ostrava, 708 00 Ostrava, Czechia
| | - Norbert Marwan
- Institute of Physics and Astronomy, University of Potsdam, 14476 Potsdam, Germany
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, 14473 Potsdam, Germany
- Institute of Geosciences Potsdam, University of Potsdam, 14473 Potsdam, Germany
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Whiteside DJ, Holland N, Tsvetanov KA, Mak E, Malpetti M, Savulich G, Jones PS, Naessens M, Rouse MA, Fryer TD, Hong YT, Aigbirhio FI, Mulroy E, Bhatia KP, Rittman T, O'Brien JT, Rowe JB. Synaptic density affects clinical severity via network dysfunction in syndromes associated with frontotemporal lobar degeneration. Nat Commun 2023; 14:8458. [PMID: 38114493 PMCID: PMC10730886 DOI: 10.1038/s41467-023-44307-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 12/07/2023] [Indexed: 12/21/2023] Open
Abstract
There is extensive synaptic loss from frontotemporal lobar degeneration, in preclinical models and human in vivo and post mortem studies. Understanding the consequences of synaptic loss for network function is important to support translational models and guide future therapeutic strategies. To examine this relationship, we recruited 55 participants with syndromes associated with frontotemporal lobar degeneration and 24 healthy controls. We measured synaptic density with positron emission tomography using the radioligand [11C]UCB-J, which binds to the presynaptic vesicle glycoprotein SV2A, neurite dispersion with diffusion magnetic resonance imaging, and network function with task-free magnetic resonance imaging functional connectivity. Synaptic density and neurite dispersion in patients was associated with reduced connectivity beyond atrophy. Functional connectivity moderated the relationship between synaptic density and clinical severity. Our findings confirm the importance of synaptic loss in frontotemporal lobar degeneration syndromes, and the resulting effect on behaviour as a function of abnormal connectivity.
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Affiliation(s)
- David J Whiteside
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - Negin Holland
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kamen A Tsvetanov
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Maura Malpetti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - George Savulich
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Michelle Naessens
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Matthew A Rouse
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Young T Hong
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Eoin Mulroy
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Kailash P Bhatia
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - John T O'Brien
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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9
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Kim H, Zhu X, Zhao Y, Bell SA, Gehrman PR, Cohen D, Devanand DP, Goldberg TE, Lee S. Resting-state functional connectivity changes in older adults with sleep disturbance and the role of amyloid burden. Mol Psychiatry 2023; 28:4399-4406. [PMID: 37596355 PMCID: PMC10842478 DOI: 10.1038/s41380-023-02214-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 07/19/2023] [Accepted: 08/02/2023] [Indexed: 08/20/2023]
Abstract
Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using the linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β = 0.11, P = 0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.
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Affiliation(s)
- Hyun Kim
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA.
| | - Xi Zhu
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Division of Anxiety, Mood, Eating, and Related Disorders, New York State Psychiatric Institute, New York, NY, USA
| | - Yiming Zhao
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Sophie A Bell
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
| | - Philip R Gehrman
- Department of Psychiatry, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, PA, USA
- Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Daniel Cohen
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
| | - D P Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Terry E Goldberg
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Seonjoo Lee
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
- Division of Mental Health Data Science, New York State Psychiatric Institute, New York, NY, USA
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10
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Vogel JW, Corriveau-Lecavalier N, Franzmeier N, Pereira JB, Brown JA, Maass A, Botha H, Seeley WW, Bassett DS, Jones DT, Ewers M. Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight. Nat Rev Neurosci 2023; 24:620-639. [PMID: 37620599 DOI: 10.1038/s41583-023-00731-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/26/2023] [Indexed: 08/26/2023]
Abstract
Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.
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Affiliation(s)
- Jacob W Vogel
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden.
| | - Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Acadamy, University of Gothenburg, Mölndal and Gothenburg, Sweden
| | - Joana B Pereira
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institute, Stockholm, Sweden
| | - Jesse A Brown
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Dani S Bassett
- Departments of Bioengineering, Electrical and Systems Engineering, Physics and Astronomy, Neurology and Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany.
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11
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Giannini LA, Mol MO, Rajicic A, van Buuren R, Sarkar L, Arezoumandan S, Ohm DT, Irwin DJ, Rozemuller AJ, van Swieten JC, Seelaar H. Presymptomatic and early pathological features of MAPT-associated frontotemporal lobar degeneration. Acta Neuropathol Commun 2023; 11:126. [PMID: 37533060 PMCID: PMC10394953 DOI: 10.1186/s40478-023-01588-9] [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: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 08/04/2023] Open
Abstract
Early pathological features of frontotemporal lobar degeneration (FTLD) due to MAPT pathogenic variants (FTLD-MAPT) are understudied, since early-stage tissue is rarely available. Here, we report unique pathological data from three presymptomatic/early-stage MAPT variant carriers (FTLD Clinical Dementia Rating [FTLD-CDR] = 0-1). We examined neuronal degeneration semi-quantitatively and digitally quantified tau burden in 18 grey matter (9 cortical, 9 subcortical) and 13 white matter (9 cortical, 4 subcortical) regions. We compared presymptomatic/early-stage pathology to an intermediate/end-stage cohort (FTLD-CDR = 2-3) with the same variants (2 L315R, 10 P301L, 6 G272V), and developed a clinicopathological staging model for P301L and G272V variants. The 68-year-old presymptomatic L315R carrier (FTLD-CDR = 0) had limited tau burden morphologically similar to L315R end-stage carriers in middle frontal, antero-inferior temporal, amygdala, (para-)hippocampus and striatum, along with age-related Alzheimer's disease neuropathological change. The 59-year-old prodromal P301L carrier (FTLD-CDR = 0.5) had highest tau burden in anterior cingulate, anterior temporal, middle/superior frontal, and fronto-insular cortex, and amygdala. The 45-year-old early-stage G272V carrier (FTLD-CDR = 1) had highest tau burden in superior frontal and anterior cingulate cortex, subiculum and CA1. The severity and distribution of tau burden showed some regional variability between variants at presymptomatic/early-stage, while neuronal degeneration, mild-to-moderate, was similarly distributed in frontotemporal regions. Early-stage tau burden and neuronal degeneration were both less severe than in intermediate-/end-stage cases. In a subset of regions (10 GM, 8 WM) used for clinicopathological staging, clinical severity correlated strongly with neuronal degeneration (rho = 0.72, p < 0.001), less strongly with GM tau burden (rho = 0.57, p = 0.006), and did not with WM tau burden (p = 0.9). Clinicopathological staging showed variant-specific patterns of early tau pathology and progression across stages. These unique data demonstrate that tau pathology and neuronal degeneration are present already at the presymptomatic/early-stage of FTLD-MAPT, though less severely compared to intermediate/end-stage disease. Moreover, early pathological patterns, especially of tau burden, differ partly between specific MAPT variants.
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Affiliation(s)
- Lucia Aa Giannini
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Merel O Mol
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Ana Rajicic
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Renee van Buuren
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Lana Sarkar
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Sanaz Arezoumandan
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel T Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Annemieke Jm Rozemuller
- Department of Pathology, Amsterdam Neuroscience, Amsterdam University Medical Center, location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - John C van Swieten
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Harro Seelaar
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands.
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12
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Chen M, Burke S, Olm CA, Irwin DJ, Massimo L, Lee EB, Trojanowski JQ, Gee JC, Grossman M. Antemortem network analysis of spreading pathology in autopsy-confirmed frontotemporal degeneration. Brain Commun 2023; 5:fcad147. [PMID: 37223129 PMCID: PMC10202556 DOI: 10.1093/braincomms/fcad147] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 03/15/2023] [Accepted: 05/10/2023] [Indexed: 05/25/2023] Open
Abstract
Despite well-articulated hypotheses of spreading pathology in animal models of neurodegenerative disease, the basis for spreading neurodegenerative pathology in humans has been difficult to ascertain. In this study, we used graph theoretic analyses of structural networks in antemortem, multimodal MRI from autopsy-confirmed cases to examine spreading pathology in sporadic frontotemporal lobar degeneration. We defined phases of progressive cortical atrophy on T1-weighted MRI using a published algorithm in autopsied frontotemporal lobar degeneration with tau inclusions or with transactional DNA binding protein of ∼43 kDa inclusions. We studied global and local indices of structural networks in each of these phases, focusing on the integrity of grey matter hubs and white matter edges projecting between hubs. We found that global network measures are compromised to an equal degree in patients with frontotemporal lobar degeneration with tau inclusions and frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions compared to healthy controls. While measures of local network integrity were compromised in both frontotemporal lobar degeneration with tau inclusions and frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, we discovered several important characteristics that distinguished between these groups. Hubs identified in controls were degraded in both patient groups, but degraded hubs were associated with the earliest phase of cortical atrophy (i.e. epicentres) only in frontotemporal lobar degeneration with tau inclusions. Degraded edges were significantly more plentiful in frontotemporal lobar degeneration with tau inclusions than in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, suggesting that the spread of tau pathology involves more significant white matter degeneration. Weakened edges were associated with degraded hubs in frontotemporal lobar degeneration with tau inclusions more than in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, particularly in the earlier phases of the disease, and phase-to-phase transitions in frontotemporal lobar degeneration with tau inclusions were characterized by weakened edges in earlier phases projecting to diseased hubs in subsequent phases of the disease. When we examined the spread of pathology from a region diseased in an earlier phase to physically adjacent regions in subsequent phases, we found greater evidence of disease spreading to adjacent regions in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions than in frontotemporal lobar degeneration with tau inclusions. We associated evidence of degraded grey matter hubs and weakened white matter edges with quantitative measures of digitized pathology from direct observations of patients' brain samples. We conclude from these observations that the spread of pathology from diseased regions to distant regions via weakened long-range edges may contribute to spreading disease in frontotemporal dementia-tau, while spread of pathology to physically adjacent regions via local neuronal connectivity may play a more prominent role in spreading disease in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions.
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Affiliation(s)
- Min Chen
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah Burke
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christopher A Olm
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David J Irwin
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lauren Massimo
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James C Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
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13
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Kim H, Zhu X, Zhao Y, Bell S, Gehrman P, Cohen D, Devanand D, Goldberg T, Lee S. Resting-State Functional Connectivity Changes in Older Adults with Sleep Disturbance and the Role of Amyloid Burden. RESEARCH SQUARE 2023:rs.3.rs-2547880. [PMID: 36798352 PMCID: PMC9934741 DOI: 10.21203/rs.3.rs-2547880/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β=0.11, P=0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.
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Affiliation(s)
| | - Xi Zhu
- Columbia University Medical Center
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14
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Abbate C. Research on Alzheimer's syndromes is critical to improve diagnosis, patient management and non-pharmacological treatments, but is under-pursued. Front Aging Neurosci 2022; 14:1039899. [PMID: 36325192 PMCID: PMC9618725 DOI: 10.3389/fnagi.2022.1039899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/03/2022] [Indexed: 11/18/2022] Open
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15
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Chen M, Ohm DT, Phillips JS, McMillan CT, Capp N, Peterson C, Xie E, Wolk DA, Trojanowski JQ, Lee EB, Gee J, Grossman M, Irwin DJ. Divergent Histopathological Networks of Frontotemporal Degeneration Proteinopathy Subytpes. J Neurosci 2022; 42:3868-3877. [PMID: 35318284 PMCID: PMC9087810 DOI: 10.1523/jneurosci.2061-21.2022] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/22/2022] [Accepted: 03/01/2022] [Indexed: 11/21/2022] Open
Abstract
Network analyses inform complex systems such as human brain connectivity, but this approach is seldom applied to gold-standard histopathology. Here, we use two complimentary computational approaches to model microscopic progression of the main subtypes of tauopathy versus TDP-43 proteinopathy in the human brain. Digital histopathology measures were obtained in up to 13 gray matter (GM) and adjacent white matter (WM) cortical brain regions sampled from 53 tauopathy and 66 TDP-43 proteinopathy autopsy patients. First, we constructed a weighted non-directed graph for each group, where nodes are defined as GM and WM regions sampled and edges in the graph are weighted using the group-level Pearson's correlation coefficient for each pairwise node comparison. Additionally, we performed mediation analyses to test mediation effects of WM pathology between anterior frontotemporal and posterior parietal GM nodes. We find greater correlation (i.e., edges) between GM and WM node pairs in tauopathies compared with TDP-43 proteinopathies. Moreover, WM pathology strongly correlated with a graph metric of pathology spread (i.e., node-strength) in tauopathies (r = 0.60, p < 0.03) but not in TDP-43 proteinopathies (r = 0.03, p = 0.9). Finally, we found mediation effects for WM pathology on the association between anterior and posterior GM pathology in FTLD-Tau but not in FTLD-TDP. These data suggest distinct tau and TDP-43 proteinopathies may have divergent patterns of cellular propagation in GM and WM. More specifically, axonal spread may be more influential in FTLD-Tau progression. Network analyses of digital histopathological measurements can inform models of disease progression of cellular degeneration in the human brain.SIGNIFICANCE STATEMENT In this study, we uniquely perform two complimentary computational approaches to model and contrast microscopic disease progression between common frontotemporal lobar degeneration (FTLD) proteinopathy subtypes with similar clinical syndromes during life. Our models suggest white matter (WM) pathology influences cortical spread of disease in tauopathies that is less evident in TDP-43 proteinopathies. These data support the hypothesis that there are neuropathologic signatures of cellular degeneration within neurocognitive networks for specific protienopathies. These distinctive patterns of cellular pathology can guide future efforts to develop tissue-sensitive imaging and biological markers with diagnostic and prognostic utility for FTLD. Moreover, our novel computational approach can be used in future work to model various neurodegenerative disorders with mixed proteinopathy within the human brain connectome.
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Affiliation(s)
- Min Chen
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Daniel T Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Jeffrey S Phillips
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Noah Capp
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Claire Peterson
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Emily Xie
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David A Wolk
- Alzheimer's Disease Research Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Edward B Lee
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - James Gee
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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16
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Stocks J, Popuri K, Heywood A, Tosun D, Alpert K, Beg MF, Rosen H, Wang L, for the Alzheimer's Disease Neuroimaging Initiative. Network-wise concordance of multimodal neuroimaging features across the Alzheimer's disease continuum. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12304. [PMID: 35496375 PMCID: PMC9043119 DOI: 10.1002/dad2.12304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/17/2022] [Accepted: 02/25/2022] [Indexed: 01/18/2023]
Abstract
Background Concordance between cortical atrophy and cortical glucose hypometabolism within distributed brain networks was evaluated among cerebrospinal fluid (CSF) biomarker-defined amyloid/tau/neurodegeneration (A/T/N) groups. Method We computed correlations between cortical thickness and fluorodeoxyglucose metabolism within 12 functional brain networks. Differences among A/T/N groups (biomarker normal [BN], Alzheimer's disease [AD] continuum, suspected non-AD pathologic change [SNAP]) in network concordance and relationships to longitudinal change in cognition were assessed. Results Network-wise markers of concordance distinguish SNAP subjects from BN subjects within the posterior multimodal and language networks. AD-continuum subjects showed increased concordance in 9/12 networks assessed compared to BN subjects, as well as widespread atrophy and hypometabolism. Baseline network concordance was associated with longitudinal change in a composite memory variable in both SNAP and AD-continuum subjects. Conclusions Our novel study investigates the interrelationships between atrophy and hypometabolism across brain networks in A/T/N groups, helping disentangle the structure-function relationships that contribute to both clinical outcomes and diagnostic uncertainty in AD.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral SciencesFeinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Karteek Popuri
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Ashley Heywood
- Department of Psychiatry and Behavioral SciencesFeinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Duygu Tosun
- School of MedicineUniversity of CaliforniaSan Francisco, CaliforniaUSA
| | - Kate Alpert
- Department of Psychiatry and Behavioral SciencesFeinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Mirza Faisal Beg
- School of Engineering ScienceSimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Howard Rosen
- School of MedicineUniversity of CaliforniaSan Francisco, CaliforniaUSA
| | - Lei Wang
- Department of Psychiatry and Behavioral SciencesFeinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
- Department of Psychiatry and Behavioral HealthOhio State University Wexner Medical CenterColumbusOhioUSA
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17
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Jenkins LM, Wang L, Rosen H, Weintraub S. A transdiagnostic review of neuroimaging studies of apathy and disinhibition in dementia. Brain 2022; 145:1886-1905. [PMID: 35388419 PMCID: PMC9630876 DOI: 10.1093/brain/awac133] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 01/18/2022] [Accepted: 03/13/2022] [Indexed: 11/12/2022] Open
Abstract
Apathy and disinhibition are common and highly distressing neuropsychiatric symptoms associated with negative outcomes in persons with dementia. This paper is a critical review of functional and structural neuroimaging studies of these symptoms transdiagnostically in dementia of the Alzheimer type, which is characterized by prominent amnesia early in the disease course, and behavioural variant frontotemporal dementia, characterized by early social-comportmental deficits. We describe the prevalence and clinical correlates of these symptoms and describe methodological issues, including difficulties with symptom definition and different measurement instruments. We highlight the heterogeneity of findings, noting however, a striking similarity of the set of brain regions implicated across clinical diagnoses and symptoms. These regions involve several key nodes of the salience network, and we describe the functions and anatomical connectivity of these brain areas, as well as present a new theoretical account of disinhibition in dementia. Future avenues for research are discussed, including the importance of transdiagnostic studies, measuring subdomains of apathy and disinhibition, and examining different units of analysis for deepening our understanding of the networks and mechanisms underlying these extremely distressing symptoms.
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Affiliation(s)
- Lisanne M Jenkins
- Correspondence to: Lisanne Jenkins 710 N Lakeshore Drive, Suite 1315 Chicago, IL 60611, USA E-mail:
| | - Lei Wang
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH 43210, USA
| | - Howie Rosen
- Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, CA, USA 94158
| | - Sandra Weintraub
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA,Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
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18
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Cao M, Liu J, Zhang X, Yang T, Wang Y, Hou Y, Song Q, Cui Y, Wang Y, Wang P. ABI3 Is a Novel Early Biomarker of Alzheimer's Disease. J Alzheimers Dis 2022; 87:335-344. [PMID: 35275543 DOI: 10.3233/jad-215635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The Abi3 gene has been suggested to be an important regulator of microglia during Alzheimer's disease (AD), but the diagnostic power of ABI3 in neurodegenerative disease has rarely been reported. OBJECTIVE The aim of this study was to evaluate the diagnostic value of ABI3 in AD patients. METHODS ELISAs were used to measure the ABI3 level in the serum and cerebrospinal fluid (CSF) of AD patients as well as in the serum of APP/PS1 mice. RT-PCR and western blot were further performed to detect the expression levels of ABI3 in peripheral blood mononuclear cells (PBMCs) of AD subjects as well as in the hippocampus and cortical tissue of APP/PS1 mice. The correlation of cognitive ability with ABI3 level was estimated by linear regression analysis. Moreover, the diagnostic value of ABI3 for AD was assessed with ROC analysis. RESULTS The ABI3 levels all decreased significantly in the serum, CSF, and PBMCs of AD patients and showed a good diagnostic performance. In addition, the ABI3 levels were observed to decrease markedly in the hippocampus from 5-month-old mice, but the dramatic change only appeared in the cortical tissue in the 9-month-old APP/PS1 mice. The ABI3 levels in the PBMCs of AD patients and in the hippocampus of APP/PS1 mice were all positively correlated with cognitive capacity. CONCLUSION These results demonstrated that ABI3 in serum, CSF, and PBMCs could be a novel early diagnostic biomarker of AD. Moreover, ABI3 had potential to be a novel tracer marker in hippocampus of early AD.
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Affiliation(s)
- Min Cao
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China.,Department of Clinical Laboratory, Beijing Huairou Hospital, Beijing, People's Republic of China
| | - Jing Liu
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Xiaomin Zhang
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Tingting Yang
- Department of Clinical Laboratory, the Hospital of Shunyi District Beijing, Beijing, People's Republic of China
| | - Yaqi Wang
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Yuli Hou
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Qiao Song
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Yuting Cui
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Yifei Wang
- Department of Laboratory Technology, Capital Medical University, Beijing, People's Republic of China
| | - Peichang Wang
- Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China
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19
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Ushizima D, Chen Y, Alegro M, Ovando D, Eser R, Lee W, Poon K, Shankar A, Kantamneni N, Satrawada S, Junior EA, Heinsen H, Tosun D, Grinberg LT. Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation. Neuroimage 2022; 248:118790. [PMID: 34933123 PMCID: PMC8983026 DOI: 10.1016/j.neuroimage.2021.118790] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 11/30/2021] [Accepted: 12/04/2021] [Indexed: 01/16/2023] Open
Abstract
Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.
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Affiliation(s)
- Daniela Ushizima
- Bakar Institute for Computational Health Sciences, University of California San Francisco, CA, USA; Berkeley Institute for Data Science, University of California Berkeley, CA, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Yuheng Chen
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maryana Alegro
- Bakar Institute for Computational Health Sciences, University of California San Francisco, CA, USA; Berkeley Institute for Data Science, University of California Berkeley, CA, USA; Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Dulce Ovando
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Rana Eser
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - WingHung Lee
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Kinson Poon
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Anubhav Shankar
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Namrata Kantamneni
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Shruti Satrawada
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | | | - Helmut Heinsen
- University of Sao Paulo Medical School, Sao Paulo, Brazil; Julius-Maximilians University Würzburg, Würzburg, Germany
| | - Duygu Tosun
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA; Veterans Affairs San Francisco, CA, USA
| | - Lea T Grinberg
- Bakar Institute for Computational Health Sciences, University of California San Francisco, CA, USA; Department of Neurology, University of California San Francisco, San Francisco, CA, USA; University of Sao Paulo Medical School, Sao Paulo, Brazil; Department of Pathology, University of California San Francisco, San Francisco, CA, USA.
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20
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Signature laminar distributions of pathology in frontotemporal lobar degeneration. Acta Neuropathol 2022; 143:363-382. [PMID: 34997851 PMCID: PMC8858288 DOI: 10.1007/s00401-021-02402-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 12/11/2021] [Accepted: 12/28/2021] [Indexed: 12/24/2022]
Abstract
Frontotemporal lobar degeneration (FTLD) with either tau (FTLD-tau) or TDP-43 (FTLD-TDP) inclusions are distinct proteinopathies that frequently cause similar frontotemporal dementia (FTD) clinical syndromes. FTD syndromes often display macroscopic signatures of neurodegeneration at the level of regions and networks, but it is unclear if subregional laminar pathology display patterns unique to proteinopathy or clinical syndrome. We hypothesized that FTLD-tau and FTLD-TDP accumulate pathology in relatively distinct cortical layers independent of clinical syndrome, with greater involvement of lower layers in FTLD-tau. The current study examined 170 patients with either FTLD-tau (n = 73) or FTLD-TDP (n = 97) spanning dementia and motor phenotypes in the FTD spectrum. We digitally measured the percent area occupied by tau and TDP-43 pathology in upper layers (I-III), lower layers (IV-VI), and juxtacortical white matter (WM) from isocortical regions in both hemispheres where available. Linear mixed-effects models compared ratios of upper to lower layer pathology between FTLD groups and investigated relationships with regions, WM pathology, and global cognitive impairment while adjusting for demographics. We found lower ratios of layer pathology in FTLD-tau and higher ratios of layer pathology in FTLD-TDP, reflecting lower layer-predominant tau pathology and upper layer-predominant TDP-43 pathology, respectively (p < 0.001). FTLD-tau displayed lower ratios of layer pathology related to greater WM tau pathology (p = 0.002) and to earlier involved/severe pathology regions (p = 0.007). In contrast, FTLD-TDP displayed higher ratios of layer pathology not related to either WM pathology or regional severity. Greater cognitive impairment was associated with higher ratios of layer pathology in FTLD-tau (p = 0.018), but was not related to ratios of layer pathology in FTLD-TDP. Lower layer-predominant tau pathology and upper layer-predominant TDP-43 pathology are proteinopathy-specific, regardless of clinical syndromes or regional networks that define these syndromes. Thus, patterns of laminar change may provide a useful anatomical framework for investigating how degeneration of select cells and corresponding laminar circuits influence large-scale networks and clinical symptomology in FTLD.
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21
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Shafiei G, Bazinet V, Dadar M, Manera AL, Collins DL, Dagher A, Borroni B, Sanchez-Valle R, Moreno F, Laforce R, Graff C, Synofzik M, Galimberti D, Rowe JB, Masellis M, Tartaglia MC, Finger E, Vandenberghe R, de Mendonça A, Tagliavini F, Santana I, Butler C, Gerhard A, Danek A, Levin J, Otto M, Sorbi S, Jiskoot LC, Seelaar H, van Swieten JC, Rohrer JD, Misic B, Ducharme S, Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI)
RosenHowardDickersonBradford CDomoto-ReillyKimokoKnopmanDavidBoeveBradley FBoxerAdam LKornakJohnMillerBruce LSeeleyWilliam WGorno-TempiniMaria-LuisaMcGinnisScottMandelliMaria Luisa, GENetic Frontotemporal dementia Initiative (GENFI)
EsteveAitana SogorbNelsonAnnabelBouziguesArabellaHellerCarolinGreavesCaroline VCashDavidThomasDavid LToddEmilyBenotmaneHanyaZetterbergHenrikSwiftImogen JNicholasJenniferSamraKiranRussellLucy LBocchettaMartinaShafeiRachelleConveryRhian STimberlakeCarolynCopeThomasRittmanTimothyBenussiAlbertoPremiEnricoGasparottiRobertoArchettiSilvanaGazzinaStefanoCantoniValentinaArighiAndreaFenoglioChiaraScarpiniElioFumagalliGiorgioBorracciVittoriaRossiGiacominaGiacconeGiorgioFedeGiuseppe DiCaroppoPaolaTiraboschiPietroPrioniSaraRedaelliVeronicaTang-WaiDavidRogaevaEkaterinaCastelo-BrancoMiguelFreedmanMorrisKerenRonBlackSandraMitchellSaraShoesmithChristenBarthaRobartRademakersRosavan der EndeEmmaPoosJackiePapmaJanne MGianniniLuciavan MinkelenRickPijnenburgYolandeNacmiasBenedettaFerrariCamillaPolitoCristinaLombardiGemmaBessiValentinaVeldsmanMicheleAnderssonChristinThonbergHakanÖijerstedtLinnJelicVesnaThompsonPaulLangheinrichTobiasLladóAlbertAntonellAnnaOlivesJaumeBalasaMirceaBargallóNuriaBorrego-EcijaSergiVerdelhoAnaMarutaCarolinaFerreiraCatarina BMiltenbergerGabrieldo CoutoFrederico SimõesGabilondoAlazneGorostidiAnaVillanuaJorgeCañadaMartaTaintaMikelZulaicaMirenBarandiaranMyriamAlvesPatriciaBenderBenjaminWilkeCarloGrafLisaVogelsAnnickVandenbulckeMathieuVan DammePhilipBruffaertsRoseRosa-NetoPedroGauthierSergeCamuzatAgnèsBriceAlexisBertrandAnneFunkiewiezAurélieRinaldiDaisySaracinoDarioColliotOlivierSayahSabrinaPrixCatharinaWlasichElisabethWagemannOliviaLoosliSandraSchöneckerSonjaHoegenTobiasLombardiJolinaAnderl-StraubSarahRollinAdelineKuchcinskiGregoryBertouxMaximeLebouvierThibaudDeramecourtVincentSantiagoBeatrizDuroDianaLeitãoMaria JoãoAlmeidaMaria RosarioTábuas-PereiraMiguelAfonsoSóniaEngelAnnerosePolyakovaMaryna. Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia. Brain 2022; 146:321-336. [PMID: 35188955 PMCID: PMC9825569 DOI: 10.1093/brain/awac069] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/14/2021] [Accepted: 01/30/2022] [Indexed: 01/13/2023] Open
Abstract
Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.
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Affiliation(s)
| | | | - Mahsa Dadar
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Radiology and Nuclear Medicine, Laval University, Quebec City, QC, Canada
| | - Ana L Manera
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Raquel Sanchez-Valle
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d’Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain,Neuroscience Area, Biodonostia Health Research Institute, San Sebastian, Gipuzkoa, Spain
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, Quebec, QC, Canada
| | - Caroline Graff
- Department of Geriatric Medicine, Karolinska University Hospital-Huddinge, Stockholm, Sweden,Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany,Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Daniela Galimberti
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy,Department of Biomedical, Surgical and Dental Sciences, University of Milan, Dino Ferrari Center, Milan, Italy
| | - James B Rowe
- University of Cambridge, Department of Clinical Neurosciences, Cambridge University Hospitals NHS Trust, and MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Toronto Western Hospital, Tanz Centre for Research in Neurodegenerative Disease, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium,Neurology Service, University Hospitals Leuven, Leuven, Belgium,Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | | | - Fabrizio Tagliavini
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologico Carlo Besta, Milan, Italy
| | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal,Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Chris Butler
- Department of Clinical Neurology, University of Oxford, Oxford, UK,Department of Brain Sciences, Imperial College London, London, UK
| | - Alex Gerhard
- Division of Neuroscience and Experimental Psychology, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK,Department of Geriatric Medicine and Nuclear Medicine, University of Duisburg-Essen, Duisburg and Essen, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany,Clinical Research Unit, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany,Munich Cluster of Systems Neurology (SyNergy), Munich, Germany
| | - Markus Otto
- Department of Neurology, University Hospital Ulm, Ulm, Germany
| | - Sandro Sorbi
- Department of Neurofarba, University of Florence, Florence, Italy,IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Lize C Jiskoot
- Department of Neurology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Harro Seelaar
- Department of Neurology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Bratislav Misic
- Correspondence to: Bratislav Misic 3801 Rue University Webster 211, Montreal QC H3A 2B4, Canada E-mail:
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22
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Meier EL. The role of disrupted functional connectivity in aphasia. HANDBOOK OF CLINICAL NEUROLOGY 2022; 185:99-119. [PMID: 35078613 DOI: 10.1016/b978-0-12-823384-9.00005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Language is one of the most complex and specialized higher cognitive processes. Brain damage to the distributed, primarily left-lateralized language network can result in aphasia, a neurologic disorder characterized by receptive and/or expressive deficits in spoken and/or written language. Most often, aphasia is the consequence of stroke-termed poststroke aphasia (PSA)-yet, aphasia can also manifest due to neurodegenerative disease, specifically, a disorder called primary progressive aphasia (PPA). In recent years, functional connectivity neuroimaging studies have provided emerging evidence supporting theories regarding the relationships between language impairments, structural brain damage, and functional network properties in these two disorders. This chapter reviews the current evidence for the "network phenotype of stroke injury" hypothesis (Siegel et al., 2016) as it pertains to PSA and the "network degeneration hypothesis" (Seeley et al., 2009) as it pertains to PPA. Methodologic considerations for functional connectivity studies, limitations of the current functional connectivity literature in aphasia, and future directions are also discussed.
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Affiliation(s)
- Erin L Meier
- Department of Communication Sciences and Disorders, Northeastern University, Boston, MA, United States.
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23
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Ebrahimi V, Tarhriz V, Talebi M, Rasouli A, Farjami A, Razi Soofiyani S, Soleimanian A, Forouhandeh H. A new insight on feasibility of pre-, pro-, and synbiotics-based therapies in Alzheimer’s disease. JOURNAL OF REPORTS IN PHARMACEUTICAL SCIENCES 2022. [DOI: 10.4103/jrptps.jrptps_170_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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24
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Zalyalova Z, Munasipova S. Frontotemporal dementia with cortico-basal syndrome. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:107-114. [DOI: 10.17116/jnevro2022122021107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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25
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Haber SN, Liu H, Seidlitz J, Bullmore E. Prefrontal connectomics: from anatomy to human imaging. Neuropsychopharmacology 2022; 47:20-40. [PMID: 34584210 PMCID: PMC8617085 DOI: 10.1038/s41386-021-01156-6] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 07/23/2021] [Accepted: 08/02/2021] [Indexed: 12/22/2022]
Abstract
The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic "hard wiring" first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.
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Affiliation(s)
- Suzanne N. Haber
- grid.412750.50000 0004 1936 9166Department of Pharmacology and Physiology, University of Rochester School of Medicine & Dentistry, Rochester, NY 14642 USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA 02478 USA
| | - Hesheng Liu
- grid.259828.c0000 0001 2189 3475Department of Neuroscience, Medical University of South Carolina, Charleston, SC USA ,grid.38142.3c000000041936754XDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Jakob Seidlitz
- grid.25879.310000 0004 1936 8972Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
| | - Ed Bullmore
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, CB2 0SZ UK
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26
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Costigan A, Umla-Runge K, Evans C, Raybould R, Graham K, Lawrence A. Evidence against altered excitatory/inhibitory balance in the posteromedial cortex of young adult APOE E4 carriers: A resting state 1H-MRS study. NEUROIMAGE. REPORTS 2021; 1:100059. [PMID: 36896169 PMCID: PMC9986794 DOI: 10.1016/j.ynirp.2021.100059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/09/2021] [Accepted: 10/04/2021] [Indexed: 11/20/2022]
Abstract
A strategy to gain insight into early changes that may predispose people to Alzheimer's disease (AD) is to study the brains of younger cognitively healthy people that are at increased genetic risk of AD. The Apolipoprotein (APOE) E4 allele is the strongest genetic risk factor for AD, and several neuroimaging studies comparing APOE E4 carriers with non-carriers at age ∼20-30 years have detected hyperactivity (or reduced deactivation) in posteromedial cortex (PMC), a key hub of the default network (DN), which has a high susceptibility to early amyloid deposition in AD. Transgenic mouse models suggest such early network activity alterations may result from altered excitatory/inhibitory (E/I) balance, but this is yet to be examined in humans. Here we test the hypothesis that PMC fMRI hyperactivity could be underpinned by altered levels of excitatory (glutamate) and/or inhibitory (GABA) neurotransmitters in this brain region. Forty-seven participants (20 APOE E4 carriers and 27 non-carriers) aged 18-25 years underwent resting-state proton magnetic resonance spectroscopy (1H-MRS), a non-invasive neuroimaging technique to measure glutamate and GABA in vivo. Metabolites were measured in a PMC voxel of interest and in a comparison voxel in the occipital cortex (OCC). There was no difference in either glutamate or GABA between the E4 carriers and non-carriers in either MRS voxel, or in the ratio of glutamate to GABA, a measure of E/I balance. Default Bayesian t-tests revealed evidence in support of this null finding. Our findings suggest that PMC hyperactivity in APOE E4 carriers is unlikely to be associated with, or possibly may precede, alterations in local resting-state PMC neurotransmitters, thus informing our understanding of the spatio-temporal sequence of early network alterations underlying APOE E4 related AD risk.
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Affiliation(s)
- A.G. Costigan
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - K. Umla-Runge
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - C.J. Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - R. Raybould
- UK Dementia Research Institute, Cardiff, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - K.S. Graham
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - A.D. Lawrence
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
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27
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Chu M, Liu L, Wang J, Liu L, Kong Y, Jing D, Xie K, Cui Y, Cui B, Zhang J, Ye H, Li J, Wang L, Rosa-Neto P, Gauthier S, Wu L. Investigating the Roles of Anterior Cingulate in Behavioral Variant Frontotemporal Dementia: A PET/MRI Study. J Alzheimers Dis 2021; 84:1771-1779. [PMID: 34719498 PMCID: PMC8764589 DOI: 10.3233/jad-215127] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Background: The anterior cingulate cortex (ACC) seems to play an important role in behavioral deficits and executive dysfunctions in patients with behavioral variant frontotemporal dementia (bvFTD), while its specific and independent contribution requires clarification. Objective: To identify whether ACC abnormalities in gray matter (GM) volume and standardized uptake value ratio (SUVR) images are associated with disease severity of bvFTD, by analyzing hybrid T1 and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET). Methods: We enrolled 21 bvFTD patients and 21 healthy controls in the study. Each subject underwent a hybrid PET/MRI study and a standardized neuropsychologic assessment battery. GM volume and SUVR are voxel-wise calculated and compared. Then we estimate the mean value inside ACC for further partial Pearson’s correlation to explore the association between GM volume/SUVR of the ACC and severity of behavioral deficit as well as executive dysfunction. Results: ACC was shown to be involved in both atrophy and hypometabolism patterns. The partial Pearson’s correlation analysis showed that the SUVR of the ACC was strongly correlated with frontal behavior inventory total score (left r = –0.85, right r = –0.85, p < 0.0001), disinhibition subscale score (left r = –0.72, p = 0.002; right = –0.75, p < 0.0001), and apathy subscale score (left = –0.87, right = –0.85, p < 0.0001). Conclusion: These findings demonstrated decreased ACC activity contributes to behavioral disturbances of both apathetic and disinhibition syndromes of bvFTD, which can be sensitively detected using 18F-FDG PET.
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Affiliation(s)
- Min Chu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Li Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Department of Neurology, Shenyang Fifth People Hospital, Shenyang, China
| | - Jingjuan Wang
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lin Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Department of Neurology, Second Hospital of ShanXi Medical University, Taiyuan, China
| | - Yu Kong
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Donglai Jing
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Department of Neurology, Rongcheng People's Hospital, Hebei, China
| | - Kexin Xie
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yue Cui
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Bo Cui
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hong Ye
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Junjie Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lin Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Pedro Rosa-Neto
- McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Montreal, Canada
| | - Serge Gauthier
- McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Montreal, Canada
| | - Liyong Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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28
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Arnatkeviciute A, Fulcher BD, Bellgrove MA, Fornito A. Imaging Transcriptomics of Brain Disorders. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:319-331. [PMID: 36324650 PMCID: PMC9616271 DOI: 10.1016/j.bpsgos.2021.10.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/06/2021] [Accepted: 10/11/2021] [Indexed: 01/05/2023] Open
Abstract
Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.
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Affiliation(s)
- Aurina Arnatkeviciute
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
- Address correspondence to Aurina Arnatkeviciute, Ph.D
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Camperdown, New South Wales, Australia
| | - Mark A. Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
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29
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Cui W, Fu W, Lin Y, Zhang T. Application of Nanomaterials in Neurodegenerative Diseases. Curr Stem Cell Res Ther 2021; 16:83-94. [PMID: 32213159 DOI: 10.2174/1574888x15666200326093410] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 01/07/2020] [Accepted: 02/04/2020] [Indexed: 02/08/2023]
Abstract
Neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and Huntington's disease are very harmful brain lesions. Due to the difficulty in obtaining therapeutic drugs, the best treatment for neurodegenerative diseases is often not available. In addition, the bloodbrain barrier can effectively prevent the transfer of cells, particles and macromolecules (such as drugs) in the brain, resulting in the failure of the traditional drug delivery system to provide adequate cellular structure repair and connection modes, which are crucial for the functional recovery of neurodegenerative diseases. Nanomaterials are designed to carry drugs across the blood-brain barrier for targets. Nanotechnology uses engineering materials or equipment to interact with biological systems at the molecular level to induce physiological responses through stimulation, response and target site interactions, while minimizing the side effects, thus revolutionizing the treatment and diagnosis of neurodegenerative diseases. Some magnetic nanomaterials play a role as imaging agents or nanoprobes for Magnetic Resonance Imaging to assist in the diagnosis of neurodegenerative diseases. Although the current research on nanomaterials is not as useful as expected in clinical applications, it achieves a major breakthrough and guides the future development direction of nanotechnology in the application of neurodegenerative diseases. This review briefly discusses the application and advantages of nanomaterials in neurodegenerative diseases. Data for this review were identified by searches of PubMed, and references from relevant articles published in English between 2015 and 2019 using the search terms "nanomaterials", "neurodegenerative diseases" and "blood-brain barrier".
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Affiliation(s)
- Weitong Cui
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Wei Fu
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, China
| | - Yunfeng Lin
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Tianxu Zhang
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China
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30
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Cicardi ME, Marrone L, Azzouz M, Trotti D. Proteostatic imbalance and protein spreading in amyotrophic lateral sclerosis. EMBO J 2021; 40:e106389. [PMID: 33792056 PMCID: PMC8126909 DOI: 10.15252/embj.2020106389] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 11/18/2020] [Accepted: 02/25/2021] [Indexed: 12/11/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder whose exact causative mechanisms are still under intense investigation. Several lines of evidence suggest that the anatomical and temporal propagation of pathological protein species along the neural axis could be among the main driving mechanisms for the fast and irreversible progression of ALS pathology. Many ALS-associated proteins form intracellular aggregates as a result of their intrinsic prion-like properties and/or following impairment of the protein quality control systems. During the disease course, these mutated proteins and aberrant peptides are released in the extracellular milieu as soluble or aggregated forms through a variety of mechanisms. Internalization by recipient cells may seed further aggregation and amplify existing proteostatic imbalances, thus triggering a vicious cycle that propagates pathology in vulnerable cells, such as motor neurons and other susceptible neuronal subtypes. Here, we provide an in-depth review of ALS pathology with a particular focus on the disease mechanisms of seeding and transmission of the most common ALS-associated proteins, including SOD1, FUS, TDP-43, and C9orf72-linked dipeptide repeats. For each of these proteins, we report historical, biochemical, and pathological evidence of their behaviors in ALS. We further discuss the possibility to harness pathological proteins as biomarkers and reflect on the implications of these findings for future research.
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Affiliation(s)
- Maria Elena Cicardi
- Department of NeuroscienceWeinberg ALS CenterVickie and Jack Farber Institute for NeuroscienceThomas Jefferson UniversityPhiladelphiaPAUSA
| | - Lara Marrone
- Department of NeuroscienceSheffield Institute for Translational Neuroscience (SITraN)University of SheffieldSheffieldUK
| | - Mimoun Azzouz
- Department of NeuroscienceSheffield Institute for Translational Neuroscience (SITraN)University of SheffieldSheffieldUK
| | - Davide Trotti
- Department of NeuroscienceWeinberg ALS CenterVickie and Jack Farber Institute for NeuroscienceThomas Jefferson UniversityPhiladelphiaPAUSA
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31
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Raj A, Powell F. Network model of pathology spread recapitulates neurodegeneration and selective vulnerability in Huntington's Disease. Neuroimage 2021; 235:118008. [PMID: 33789134 DOI: 10.1016/j.neuroimage.2021.118008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/16/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Huntington's Disease (HD), an autosomal dominant genetic disorder caused by a mutation in the Huntingtin gene (HTT), displays a stereotyped topography in the human brain and a stereotyped progression, initially appearing in the striatum. Like other degenerative diseases, spatial topography of HD is divorced from where implicated genes are expressed, a dissociation whose mechanistic underpinning is not currently understood. Cell autonomous molecular factors characterized by gene expression signatures, including proteolytic and post translational modifications, play a role in vulnerability to disease. Non-autonomous mechanisms, likely involving the brain's anatomic or functional connectivity patterns, might also be responsible for selective vulnerability in HD. Leveraging a large dataset of 635 subjects from a multinational study, this paper tests various cell-autonomous and non-autonomous models that can explain HD topography. We test whether the expression patterns of implicated genes is sufficient to explain regional HD atrophy, or whether the network transmission of protein products is required to explain them. We find that network models are capable of predicting, to a high degree, observed atrophy in human subjects. Lastly, we propose a model of anterograde network transmission, and show that it is the most parsimonious yet most likely to explain observed atrophy patterns in HD. Collectively, these data indicate that pathology spread in HD may be mediated by the brain's intrinsic structural network organization. This is the first study to systematically and quantitatively test multiple hypotheses of pathology spread in living human subjects with HD.
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Affiliation(s)
- Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, USA; UCSF-UC Berkeley Graduate Program in BioEngineering, University of California at San Francisco, USA; Department of Radiology, Weill Cornell Medical College of Cornell University, 407 E. 61 Street, RR106, New York, NY 10065, USA.
| | - Fon Powell
- Department of Radiology, Weill Cornell Medical College of Cornell University, 407 E. 61 Street, RR106, New York, NY 10065, USA
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32
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Carli G, Tondo G, Boccalini C, Perani D. Brain Molecular Connectivity in Neurodegenerative Conditions. Brain Sci 2021; 11:brainsci11040433. [PMID: 33800680 PMCID: PMC8067093 DOI: 10.3390/brainsci11040433] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 03/15/2021] [Accepted: 03/23/2021] [Indexed: 12/28/2022] Open
Abstract
Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.
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Affiliation(s)
- Giulia Carli
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Giacomo Tondo
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Cecilia Boccalini
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
- Nuclear Medicine Unit, San Raffaele Hospital, 20121 Milan, Italy
- Correspondence: ; Tel.: +39-02-26432224
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33
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Waugh RE, Danielian LE, Shoukry RFS, Floeter MK. Longitudinal changes in network homogeneity in presymptomatic C9orf72 mutation carriers. Neurobiol Aging 2021; 99:1-10. [PMID: 33421737 PMCID: PMC11428095 DOI: 10.1016/j.neurobiolaging.2020.11.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/04/2020] [Accepted: 11/22/2020] [Indexed: 12/11/2022]
Abstract
The risk for carriers of repeat expansion mutations in C9orf72 to develop amyotrophic lateral sclerosis and frontotemporal dementia increases with age. Functional magnetic resonance imaging studies have shown reduced connectivity in symptomatic carriers, but it is not known whether connectivity declines throughout life as an acceleration of the normal aging pattern. In this study, we examined intra-network homogeneity (NeHo) in 5 functional networks in 15 presymptomatic C9+ carriers over an 18-month period and compared to repeated scans in 34 healthy controls and 27 symptomatic C9+ carriers. The longitudinal trajectory of NeHo in the somatomotor, dorsal attention, and default mode networks in presymptomatic carriers differed from aging controls and symptomatic carriers. In somatomotor networks, NeHo increased over time in regions adjacent to regions where symptomatic carriers had reduced NeHo. In the default network, the posterior cingulate exhibited age-dependent increases in NeHo. These findings are evidence against the proposal that the decline in functional connectivity seen in symptomatic carriers represents a lifelong acceleration of the healthy aging process.
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Affiliation(s)
- Rebecca E Waugh
- Motor Neuron Disorders Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Laura E Danielian
- Motor Neuron Disorders Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Rachel F Smallwood Shoukry
- Motor Neuron Disorders Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Mary Kay Floeter
- Motor Neuron Disorders Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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34
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Giannini LAA, Peterson C, Ohm D, Xie SX, McMillan CT, Raskovsky K, Massimo L, Suh E, Van Deerlin VM, Wolk DA, Trojanowski JQ, Lee EB, Grossman M, Irwin DJ. Frontotemporal lobar degeneration proteinopathies have disparate microscopic patterns of white and grey matter pathology. Acta Neuropathol Commun 2021; 9:30. [PMID: 33622418 PMCID: PMC7901087 DOI: 10.1186/s40478-021-01129-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 02/07/2021] [Indexed: 01/10/2023] Open
Abstract
Frontotemporal lobar degeneration proteinopathies with tau inclusions (FTLD-Tau) or TDP-43 inclusions (FTLD-TDP) are associated with clinically similar phenotypes. However, these disparate proteinopathies likely differ in cellular severity and regional distribution of inclusions in white matter (WM) and adjacent grey matter (GM), which have been understudied. We performed a neuropathological study of subcortical WM and adjacent GM in a large autopsy cohort (n = 92; FTLD-Tau = 37, FTLD-TDP = 55) using a validated digital image approach. The antemortem clinical phenotype was behavioral-variant frontotemporal dementia (bvFTD) in 23 patients with FTLD-Tau and 42 with FTLD-TDP, and primary progressive aphasia (PPA) in 14 patients with FTLD-Tau and 13 with FTLD-TDP. We used linear mixed-effects models to: (1) compare WM pathology burden between proteinopathies; (2) investigate the relationship between WM pathology burden and WM degeneration using luxol fast blue (LFB) myelin staining; (3) study regional patterns of pathology burden in clinico-pathological groups. WM pathology burden was greater in FTLD-Tau compared to FTLD-TDP across regions (beta = 4.21, SE = 0.34, p < 0.001), and correlated with the degree of WM degeneration in both FTLD-Tau (beta = 0.32, SE = 0.10, p = 0.002) and FTLD-TDP (beta = 0.40, SE = 0.08, p < 0.001). WM degeneration was greater in FTLD-Tau than FTLD-TDP particularly in middle-frontal and anterior cingulate regions (p < 0.05). Distinct regional patterns of WM and GM inclusions characterized FTLD-Tau and FTLD-TDP proteinopathies, and associated in part with clinical phenotype. In FTLD-Tau, WM pathology was particularly severe in the dorsolateral frontal cortex in nonfluent-variant PPA, and GM pathology in dorsolateral and paralimbic frontal regions with some variation across tauopathies. Differently, FTLD-TDP had little WM regional variability, but showed severe GM pathology burden in ventromedial prefrontal regions in both bvFTD and PPA. To conclude, FTLD-Tau and FTLD-TDP proteinopathies have distinct severity and regional distribution of WM and GM pathology, which may impact their clinical presentation, with overall greater severity of WM pathology as a distinguishing feature of tauopathies.
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Affiliation(s)
- Lucia A A Giannini
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
- Department of Neurology, Alzheimer Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Claire Peterson
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - Daniel Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Corey T McMillan
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - Katya Raskovsky
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - Lauren Massimo
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - EunRah Suh
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David A Wolk
- Department of Pathology and Laboratory Medicine, Alzheimer's Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Alzheimer's Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Alzheimer's Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Murray Grossman
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Neurology, Perelman School of Medicine, Penn Frontotemporal Degeneration Center (FTDC), Hospital of the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA, 19104, USA.
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35
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Nigro S, Tafuri B, Urso D, De Blasi R, Frisullo ME, Barulli MR, Capozzo R, Cedola A, Gigli G, Logroscino G. Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia. Brain Sci 2021; 11:brainsci11020192. [PMID: 33557411 PMCID: PMC7915789 DOI: 10.3390/brainsci11020192] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 11/17/2022] Open
Abstract
Recent research on behavioral variant frontotemporal dementia (bvFTD) has shown that personality changes and executive dysfunctions are accompanied by a disease-specific anatomical pattern of cortical and subcortical atrophy. We investigated the structural topological network changes in patients with bvFTD in comparison to healthy controls. In particular, 25 bvFTD patients and 20 healthy controls underwent structural 3T MRI. Next, bilaterally averaged values of 34 cortical surface areas, 34 cortical thickness values, and six subcortical volumes were used to capture single-subject anatomical connectivity and investigate network organization using a graph theory approach. Relative to controls, bvFTD patients showed altered small-world properties and decreased global efficiency, suggesting a reduced ability to combine specialized information from distributed brain regions. At a local level, patients with bvFTD displayed lower values of local efficiency in the cortical thickness of the caudal and rostral middle frontal gyrus, rostral anterior cingulate, and precuneus, cuneus, and transverse temporal gyrus. A significant correlation was also found between the efficiency of caudal anterior cingulate thickness and Mini-Mental State Examination (MMSE) scores in bvFTD patients. Taken together, these findings confirm the selective disruption in structural brain networks of bvFTD patients, providing new insights on the association between cognitive decline and graph properties.
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Affiliation(s)
- Salvatore Nigro
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Benedetta Tafuri
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Daniele Urso
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Neurosciences, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London SE5 8AF, UK
| | - Roberto De Blasi
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Radiology, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy
| | - Maria Elisa Frisullo
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Maria Rosaria Barulli
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Rosa Capozzo
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Alessia Cedola
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
| | - Giuseppe Gigli
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
- Department of Mathematics and Physics “Ennio De Giorgi”, University of Salento, Campus Ecotekne, 73100 Lecce, Italy
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari ‘Aldo Moro’, 70124 Bari, Italy
- Correspondence: or giancarlo.; Tel.: +39-0833/773904
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36
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Pasquini L, Nana AL, Toller G, Brown JA, Deng J, Staffaroni A, Kim EJ, Hwang JHL, Li L, Park Y, Gaus SE, Allen I, Sturm VE, Spina S, Grinberg LT, Rankin KP, Kramer JH, Rosen HJ, Miller BL, Seeley WW. Salience Network Atrophy Links Neuron Type-Specific Pathobiology to Loss of Empathy in Frontotemporal Dementia. Cereb Cortex 2020; 30:5387-5399. [PMID: 32500143 PMCID: PMC7566683 DOI: 10.1093/cercor/bhaa119] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/21/2020] [Accepted: 04/16/2020] [Indexed: 12/12/2022] Open
Abstract
Each neurodegenerative syndrome reflects a stereotyped pattern of cellular, regional, and large-scale brain network degeneration. In behavioral variant of frontotemporal dementia (bvFTD), a disorder of social-emotional function, von Economo neurons (VENs), and fork cells are among the initial neuronal targets. These large layer 5 projection neurons are concentrated in the anterior cingulate and frontoinsular (FI) cortices, regions that anchor the salience network, a large-scale system linked to social-emotional function. Here, we studied patients with bvFTD, amyotrophic lateral sclerosis (ALS), or both, given that these syndromes share common pathobiological and genetic factors. Our goal was to determine how neuron type-specific TAR DNA-binding protein of 43 kDa (TDP-43) pathobiology relates to atrophy in specific brain structures and to loss of emotional empathy, a cardinal feature of bvFTD. We combined questionnaire-based empathy assessments, in vivo structural MR imaging, and quantitative histopathological data from 16 patients across the bvFTD/ALS spectrum. We show that TDP-43 pathobiology within right FI VENs and fork cells is associated with salience network atrophy spanning insular, medial frontal, and thalamic regions. Gray matter degeneration within these structures mediated loss of emotional empathy, suggesting a chain of influence linking the cellular, regional/network, and behavioral levels in producing signature bvFTD clinical features.
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Affiliation(s)
- Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Alissa L Nana
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Gianina Toller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Jesse A Brown
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Jersey Deng
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Adam Staffaroni
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Eun-Joo Kim
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Ji-Hye L Hwang
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Libo Li
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
- Department of Psychopharmacology, Qiqihar Medical University, 333 Bukui N St, Qiqihar 161006, China
| | - Youngsoon Park
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Stephanie E Gaus
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Isabel Allen
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Virginia E Sturm
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
- Department of Pathology, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Katherine P Rankin
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
- Department of Pathology, University of California San Francisco, 675 Nelson Rising Lane, San Francisco, California 94158, USA
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37
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Abstract
Frontotemporal dementia (FTD) encompasses a group of clinical syndromes, including behavioral-variant FTD, nonfluent variant primary progressive aphasia, semantic variant primary progressive aphasia, FTD motor neuron disease, progressive supranuclear palsy syndrome, and corticobasal syndrome. Early on in its course, FTD is commonly seen in psychiatric clinics. We review the clinical features and diagnostic criteria in FTD spectrum disorders.
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Affiliation(s)
- Kyan Younes
- UCSF Memory and Aging Center, Box 1207, 675 Nelson Rising Lane, Suite 190, San Francisco, CA 94143, USA.
| | - Bruce L Miller
- UCSF Memory and Aging Center, Box 1207, 675 Nelson Rising Lane, Suite 190, San Francisco, CA 94143, USA. https://twitter.com/brucemillerucsf
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Tetreault AM, Phan T, Orlando D, Lyu I, Kang H, Landman B, Darby RR, on behalf of Alzheimer’s Disease Neuroimaging Initiative. Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer's disease. Brain 2020; 143:1249-1260. [PMID: 32176777 PMCID: PMC7174048 DOI: 10.1093/brain/awaa058] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/10/2020] [Accepted: 01/20/2020] [Indexed: 12/14/2022] Open
Abstract
There is both clinical and neuroanatomical variability at the single-subject level in Alzheimer's disease, complicating our understanding of brain-behaviour relationships and making it challenging to develop neuroimaging biomarkers to track disease severity, progression, and response to treatment. Prior work has shown that both group-level atrophy in clinical dementia syndromes and complex neurological symptoms in patients with focal brain lesions localize to brain networks. Here, we use a new technique termed 'atrophy network mapping' to test the hypothesis that single-subject atrophy maps in patients with a clinical diagnosis of Alzheimer's disease will also localize to syndrome-specific and symptom-specific brain networks. First, we defined single-subject atrophy maps by comparing cortical thickness in each Alzheimer's disease patient versus a group of age-matched, cognitively normal subjects across two independent datasets (total Alzheimer's disease patients = 330). No more than 42% of Alzheimer's disease patients had atrophy at any given location across these datasets. Next, we determined the network of brain regions functionally connected to each Alzheimer's disease patient's location of atrophy using seed-based functional connectivity in a large (n = 1000) normative connectome. Despite the heterogeneity of atrophied regions at the single-subject level, we found that 100% of patients with a clinical diagnosis of Alzheimer's disease had atrophy functionally connected to the same brain regions in the mesial temporal lobe, precuneus cortex, and angular gyrus. Results were specific versus control subjects and replicated across two independent datasets. Finally, we used atrophy network mapping to define symptom-specific networks for impaired memory and delusions, finding that our results matched symptom networks derived from patients with focal brain lesions. Our study supports atrophy network mapping as a method to localize clinical, cognitive, and neuropsychiatric symptoms to brain networks, providing insight into brain-behaviour relationships in patients with dementia.
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Affiliation(s)
- Aaron M Tetreault
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Tony Phan
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dana Orlando
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ilwoo Lyu
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - R Ryan Darby
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
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39
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Kagerer SM, van Bergen JMG, Li X, Quevenco FC, Gietl AF, Studer S, Treyer V, Meyer R, Kaufmann PA, Nitsch RM, van Zijl PCM, Hock C, Unschuld PG. APOE4 moderates effects of cortical iron on synchronized default mode network activity in cognitively healthy old-aged adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12002. [PMID: 32211498 PMCID: PMC7085281 DOI: 10.1002/dad2.12002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 10/21/2019] [Accepted: 11/01/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Apolipoprotein E ε4 (APOE4)-related genetic risk for sporadic Alzheimer's disease is associated with an early impairment of cognitive brain networks. The current study determines relationships between APOE4 carrier status, cortical iron, and cortical network-functionality. METHODS Sixty-nine cognitively healthy old-aged individuals (mean age [SD] 66.1 [± 7.2] years; Mini-Mental State Exam [MMSE] 29.3 ± 1.1) were genotyped for APOE4 carrier-status and received 3 Tesla magnetic resonance imaging (MRI) for blood oxygen level-dependent functional magnetic resonance imaging (MRI) at rest, three-dimensional (3D)-gradient echo (six echoes) for cortical gray-matter, non-heme iron by quantitative susceptibility mapping, and 18F-flutemetamol positron emission tomography for amyloid-β. RESULTS A spatial pattern consistent with the default mode network (DMN) could be identified by independent component analysis. DMN activity was enhanced in APOE4 carriers and related to cortical iron burden. APOE4 and cortical iron synergistically interacted with DMN activity. Secondary analysis revealed a positive, APOE4 associated, relationship between cortical iron and DMN connectivity. DISCUSSION Our findings suggest that APOE4 moderates effects of iron on brain functionality prior to manifestation of cognitive impairment.
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Affiliation(s)
- Sonja M. Kagerer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | | | - Xu Li
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | | | - Anton F. Gietl
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Sandro Studer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
| | - Valerie Treyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Rafael Meyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Philipp A. Kaufmann
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Roger M. Nitsch
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Peter C. M. van Zijl
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | - Christoph Hock
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Paul G. Unschuld
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
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40
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Kim EJ, Hwang JHL, Gaus SE, Nana AL, Deng J, Brown JA, Spina S, Lee MJ, Ramos EM, Grinberg LT, Kramer JH, Boxer AL, Gorno-Tempini ML, Rosen HJ, Miller BL, Seeley WW. Evidence of corticofugal tau spreading in patients with frontotemporal dementia. Acta Neuropathol 2020; 139:27-43. [PMID: 31542807 DOI: 10.1007/s00401-019-02075-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 08/10/2019] [Accepted: 08/11/2019] [Indexed: 01/09/2023]
Abstract
Common neurodegenerative diseases feature progressive accumulation of disease-specific protein aggregates in selectively vulnerable brain regions. Increasing experimental evidence suggests that misfolded disease proteins exhibit prion-like properties, including the ability to seed corruptive templating and self-propagation along axons. Direct evidence for transneuronal spread in patients, however, remains limited. To test predictions made by the transneuronal spread hypothesis in human tissues, we asked whether tau deposition within axons of the corticospinal and corticopontine pathways can be predicted based on clinical syndromes and cortical atrophy patterns seen in frontotemporal lobar degeneration (FTLD). Sixteen patients with Pick's disease, 21 with corticobasal degeneration, and 3 with FTLD-MAPT were included, spanning a range of clinical syndromes across the frontotemporal dementia (FTD) spectrum. Cortical involvement was measured using a neurodegeneration score, a tau score, and a composite score based on semiquantitative ratings and complemented by an MRI-based cortical atrophy W-map based on antemortem imaging. Midbrain cerebral peduncle and pontine base descending fibers were divided into three subregions, representing prefrontopontine, corticospinal, and parieto-temporo-occipital fiber pathways. Tau area fraction was calculated in each subregion and related to clinical syndrome and cortical measures. Within each clinical syndrome, there were predicted relationships between cortical atrophy patterns and axonal tau deposition in midbrain cerebral peduncle and pontine base. Between syndromes, contrasting and predictable patterns of brainstem axonal tau deposition emerged, with, for example, greater tau in prefrontopontine fibers in behavioral variant FTD and in corticospinal fibers in corticobasal syndrome. Finally, semiquantitative and quantitative cortical degeneration scores predicted brainstem axonal tau deposition based on anatomical principles. Taken together, these findings provide important human evidence in support of axonal tau spreading in patients with specific forms of tau-related neurodegeneration.
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Affiliation(s)
- Eun-Joo Kim
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Ji-Hye L Hwang
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Stephanie E Gaus
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Alissa L Nana
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Jersey Deng
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Jesse A Brown
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Myung Jun Lee
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Eliana Marisa Ramos
- Department of Psychiatry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
- Department of Pathology, University of California, San Francisco, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California, 675 Nelson Rising Lane, San Francisco, CA, 94158, USA.
- Department of Pathology, University of California, San Francisco, USA.
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41
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Brown JA, Deng J, Neuhaus J, Sible IJ, Sias AC, Lee SE, Kornak J, Marx GA, Karydas AM, Spina S, Grinberg LT, Coppola G, Geschwind DH, Kramer JH, Gorno-Tempini ML, Miller BL, Rosen HJ, Seeley WW. Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy. Neuron 2019; 104:856-868.e5. [PMID: 31623919 DOI: 10.1016/j.neuron.2019.08.037] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 06/12/2019] [Accepted: 08/22/2019] [Indexed: 12/16/2022]
Abstract
Neurodegenerative diseases appear to progress by spreading via brain connections. Here we evaluated this transneuronal degeneration hypothesis by attempting to predict future atrophy in a longitudinal cohort of patients with behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA). We determined patient-specific "epicenters" at baseline, located each patient's epicenters in the healthy functional connectome, and derived two region-wise graph theoretical metrics to predict future atrophy: (1) shortest path length to the epicenter and (2) nodal hazard, the cumulative atrophy of a region's first-degree neighbors. Using these predictors and baseline atrophy, we could accurately predict longitudinal atrophy in most patients. The regions most vulnerable to subsequent atrophy were functionally connected to the epicenter and had intermediate levels of baseline atrophy. These findings provide novel, longitudinal evidence that neurodegeneration progresses along connectional pathways and, further developed, could lead to network-based clinical tools for prognostication and disease monitoring.
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Affiliation(s)
- Jesse A Brown
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Jersey Deng
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - John Neuhaus
- University of California, San Francisco, Department of Epidemiology and Biostatistics, San Francisco, CA, USA
| | - Isabel J Sible
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Ana C Sias
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Suzee E Lee
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - John Kornak
- University of California, San Francisco, Department of Epidemiology and Biostatistics, San Francisco, CA, USA
| | - Gabe A Marx
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Anna M Karydas
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Salvatore Spina
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Lea T Grinberg
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Giovanni Coppola
- University of California, Los Angeles, Department of Neurology and Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - Dan H Geschwind
- University of California, Los Angeles, Department of Neurology and Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - Joel H Kramer
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Bruce L Miller
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Howard J Rosen
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - William W Seeley
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA.
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42
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Staffaroni AM, Ljubenkov PA, Kornak J, Cobigo Y, Datta S, Marx G, Walters SM, Chiang K, Olney N, Elahi FM, Knopman DS, Dickerson BC, Boeve BF, Gorno-Tempini ML, Spina S, Grinberg LT, Seeley WW, Miller BL, Kramer JH, Boxer AL, Rosen HJ. Longitudinal multimodal imaging and clinical endpoints for frontotemporal dementia clinical trials. Brain 2019; 142:443-459. [PMID: 30698757 DOI: 10.1093/brain/awy319] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 11/02/2018] [Indexed: 12/22/2022] Open
Abstract
Frontotemporal dementia refers to a group of progressive neurodegenerative syndromes usually caused by the accumulation of pathological tau or TDP-43 proteins. The effects of these proteins in the brain are complex, and each can present with several different clinical syndromes. Clinical efficacy trials of drugs targeting these proteins must use endpoints that are meaningful to all participants despite the variability in symptoms across patients. There are many candidate clinical measures, including neuropsychological scores and functional measures. Brain imaging is another potentially attractive outcome that can be precisely quantified and provides evidence of disease modification. Most imaging studies in frontotemporal dementia have been cross-sectional, and few have compared longitudinal changes in cortical volume with changes in other measures such as perfusion and white matter integrity. The current study characterized longitudinal changes in 161 patients with three frontotemporal dementia syndromes: behavioural variant frontotemporal dementia (n = 77) and the semantic (n = 45) and non-fluent (n = 39) variants of primary progressive aphasia. Visits included comprehensive neuropsychological and functional assessment, structural MRI (3 T), diffusion tensor imaging, and arterial spin labelled perfusion imaging. The goal was to identify measures that are appropriate as clinical trial outcomes for each group, as well as those that might be appropriate for trials that would include more than one of these groups. Linear mixed effects models were used to estimate changes in each measure, and to examine the correlation between imaging and clinical changes. Sample sizes were estimated based on the observed effects for theoretical clinical trials using bootstrapping techniques to provide 95% confidence intervals for these estimates. Declines in functional and neuropsychological measures, as well as frontal and temporal cortical volumes and white matter microstructure were detected in all groups. Imaging changes were statistically significantly correlated with, and explained a substantial portion of variance in, the change in most clinical measures. Perfusion and diffusion tensor imaging accounted for variation in clinical decline beyond volume alone. Sample size estimates for atrophy and diffusion imaging were comparable to clinical measures. Corpus callosal fractional anisotropy led to the lowest sample size estimates for all three syndromes. These findings provide further guidance on selection of trial endpoints for studies in frontotemporal dementia and support the use of neuroimaging, particularly structural and diffusion weighted imaging, as biomarkers. Diffusion and perfusion imaging appear to offer additional utility for explaining clinical change beyond the variance explained by volume alone, arguing for considering multimodal imaging in treatment trials.
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Affiliation(s)
- Adam M Staffaroni
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Peter A Ljubenkov
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Yann Cobigo
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Samir Datta
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Gabe Marx
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Samantha M Walters
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Kevin Chiang
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Nick Olney
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Fanny M Elahi
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - David S Knopman
- Department of Neurology, College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, Minnesota USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charleston, MA, USA
| | - Bradley F Boeve
- Department of Neurology, College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, Minnesota USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA.,Department of Pathology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA.,Department of Pathology - LIM 22, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA.,Department of Pathology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California at San Francisco (UCSF), San Francisco, CA, USA
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43
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Sala A, Caminiti SP, Iaccarino L, Beretta L, Iannaccone S, Magnani G, Padovani A, Ferini-Strambi L, Perani D. Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies. Hum Brain Mapp 2019; 40:4537-4550. [PMID: 31322307 DOI: 10.1002/hbm.24719] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 06/01/2019] [Accepted: 06/19/2019] [Indexed: 01/08/2023] Open
Abstract
Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.
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Affiliation(s)
- Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Beretta
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology, IRCCS San Raffaele Hospital, Milan, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Luigi Ferini-Strambi
- Vita-Salute San Raffaele University, Milan, Italy.,Department of Clinical Neurosciences, San Raffaele Scientific Institute, Neurology, Sleep Disorders Center, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
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44
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Ahn JH, Kim M, Kim JS, Youn J, Jang W, Oh E, Lee PH, Koh SB, Ahn TB, Cho JW. Midbrain atrophy in patients with presymptomatic progressive supranuclear palsy-Richardson's syndrome. Parkinsonism Relat Disord 2019; 66:80-86. [PMID: 31307918 DOI: 10.1016/j.parkreldis.2019.07.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 06/27/2019] [Accepted: 07/07/2019] [Indexed: 10/26/2022]
Abstract
INTRODUCTION In the present study, midbrain atrophy and the pons-to-midbrain area ratio (P/M ratio) were investigated as diagnostic markers for presymptomatic progressive supranuclear palsy-Richardson's syndrome (Pre-PSP-RS). METHODS The present study included 27 patients with probable PSP-RS who underwent brain MRI at least twice before and after the development of clinical symptoms, age- and sex-matched participants with Parkinson's disease (PD, n = 27), and healthy controls (n = 27). The midbrain area, pons area, and P/M ratio of the Pre-PSP-RS, PD, and control subjects were measured using midsagittal images from brain MRI, and the parameters were compared among the groups. RESULTS The midbrain area decreased and the P/M ratio increased significantly in the Pre-PSP-RS patients compared with both the PD and control subjects (midbrain, Pre-PSP-RS vs. PD = 1.01 cm2vs. 1.29 cm2, p < 0.001, Pre-PSP-RS vs. controls = 1.01 cm2vs. 1.29 cm2, p < 0.001; P/M ratio, Pre-PSP-RS vs. PD = 5.27 vs. 4.03, p < 0.001, Pre-PSP-RS vs. controls = 5.27 cm2vs. 4.06 cm2, p < 0.001). The P/M ratio had high sensitivity (vs. PD, 96.3%, vs. control, 88.9%) and specificity (vs. PD, 81.5%, vs. control, 96.3%) in differentiating Pre-PSP-RS patients from PD and control subjects. CONCLUSION Midbrain atrophy precedes the clinical symptoms of PSP-RS and could be a useful diagnostic imaging biomarker for Pre-PSP-RS. Furthermore, this information could play an important role in the development of future treatment strategies.
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Affiliation(s)
- Jong Hyeon Ahn
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Minkyeong Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Ji Sun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Jinyoung Youn
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Wooyoung Jang
- Department of Neurology, Gangneung Asan Hospital, University of Ulsan College of Medicine, 38 Bangdong-gil, Sacheon, Gangneung, 25440, Republic of Korea
| | - Eungseok Oh
- Department of Neurology, Chungnam National University Hospital, College of Medicine, 282 Munhwa-ro, Jung-Gu, Daejun, 35015, Republic of Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Seong-Beom Koh
- Departments of Neurology, Korea University College of Medicine, Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Republic of Korea
| | - Tae-Beom Ahn
- Department of Neurology, Kyung Hee University College of Medicine, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea
| | - Jin Whan Cho
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
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45
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Nascimento C, Nunes VP, Diehl Rodriguez R, Takada L, Suemoto CK, Grinberg LT, Nitrini R, Lafer B. A review on shared clinical and molecular mechanisms between bipolar disorder and frontotemporal dementia. Prog Neuropsychopharmacol Biol Psychiatry 2019; 93:269-283. [PMID: 31014945 PMCID: PMC6994228 DOI: 10.1016/j.pnpbp.2019.04.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 04/15/2019] [Accepted: 04/18/2019] [Indexed: 12/12/2022]
Abstract
Mental disorders are highly prevalent and important causes of medical burden worldwide. Co-occurrence of neurological and psychiatric symptoms are observed among mental disorders, representing a challenge for their differential diagnosis. Psychiatrists and neurologists have faced challenges in diagnosing old adults presenting behavioral changes. This is the case for early frontotemporal dementia (FTD) and bipolar disorder. In its initial stages, FTD is characterized by behavioral or language disturbances in the absence of cognitive symptoms. Consequently, patients with the behavioral subtype of FTD (bv-FTD) can be initially misdiagnosed as having a psychiatric disorder, typically major depression disorder (MDD) or bipolar disorder (BD). Bipolar disorder is associated with a higher risk of dementia in older adults and with cognitive impairment, with a subset of patients presents a neuroprogressive pattern during the disease course. No mendelian mutations were identified in BD, whereas three major genetic causes of FTD have been identified. Clinical similarities between BD and bv-FTD raise the question whether common molecular pathways might explain shared clinical symptoms. Here, we reviewed existing data on clinical and molecular similarities between BD and FTD to propose biological pathways that can be further investigated as common or specific markers of BD and FTD.
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Affiliation(s)
- Camila Nascimento
- Bipolar Disorder Program (PROMAN), Department of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil.
| | - Villela Paula Nunes
- Bipolar Disorder Program (PROMAN), Department of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil.
| | - Roberta Diehl Rodriguez
- Behavioral and Cognitive Neurology Unit, Department of Neurology and LIM 22, University of São Paulo, São Paulo 05403-900, Brazil
| | - Leonel Takada
- Behavioral and Cognitive Neurology Unit, Department of Neurology, University of São Paulo, São Paulo 05403-900, Brazil
| | - Cláudia Kimie Suemoto
- Division of Geriatrics, LIM-22, University of São Paulo Medical School, São Paulo 01246-90, Brazil
| | - Lea Tenenholz Grinberg
- Department of Pathology, LIM-22, University of São Paulo Medical School, São Paulo 01246-90, Brazil; Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA 94143-120, USA.
| | - Ricardo Nitrini
- Behavioral and Cognitive Neurology Unit, Department of Neurology, University of São Paulo, São Paulo 05403-900, Brazil
| | - Beny Lafer
- Bipolar Disorder Program (PROMAN), Department of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
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46
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Sala A, Perani D. Brain Molecular Connectivity in Neurodegenerative Diseases: Recent Advances and New Perspectives Using Positron Emission Tomography. Front Neurosci 2019; 13:617. [PMID: 31258466 PMCID: PMC6587303 DOI: 10.3389/fnins.2019.00617] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 05/29/2019] [Indexed: 12/12/2022] Open
Abstract
Positron emission tomography (PET) represents a unique molecular tool to get in vivo access to a wide spectrum of biological and neuropathological processes, of crucial relevance for neurodegenerative conditions. Although most PET findings are based on massive univariate approaches, in the last decade the increasing interest in multivariate methods has paved the way to the assessment of unexplored cerebral features, spanning from resting state brain networks to whole-brain connectome properties. Currently, the combination of molecular neuroimaging techniques with multivariate connectivity methods represents one of the most powerful, yet still emerging, approach to achieve novel insights into the pathophysiology of neurodegenerative diseases. In this review, we will summarize the available evidence in the field of PET molecular connectivity, with the aim to provide an overview of how these studies may increase the understanding of the pathogenesis of neurodegenerative diseases, over and above "traditional" structural/functional connectivity studies. Considering the available evidence, a major focus will be represented by molecular connectivity studies using [18F]FDG-PET, today applied in the major neuropathological spectra, from amyloidopathies and tauopathies to synucleinopathies and beyond. Pioneering studies using PET tracers targeting brain neuropathology and neurotransmission systems for connectivity studies will be discussed, their strengths and limitations highlighted with reference to both applied methodology and results interpretation. The most common methods for molecular connectivity assessment will be reviewed, with particular emphasis on the available strategies to investigate molecular connectivity at the single-subject level, of potential relevance for not only research but also diagnostic purposes. Finally, we will highlight possible future perspectives in the field, with reference in particular to newly available PET tracers, which will expand the application of molecular connectivity to new, exciting, unforeseen possibilities.
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Affiliation(s)
- Arianna Sala
- Faculty of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy.,Division of Neuroscience, Faculty of Psychology, San Raffaele Scientific Institute (IRCCS), Milan, Italy
| | - Daniela Perani
- Division of Neuroscience, Faculty of Psychology, San Raffaele Scientific Institute (IRCCS), Milan, Italy.,Faculty of Psychology, Vita-Salute San Raffaele University, Milan, Italy.,Nuclear Medicine Unit, Faculty of Psychology, San Raffaele Hospital (IRCCS), Milan, Italy
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47
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Butler PM, Chiong W, Perry DC, Miller ZA, Gennatas ED, Brown JA, Pasquini L, Karydas A, Dokuru D, Coppola G, Sturm VE, Boxer AL, Gorno-Tempini ML, Rosen HJ, Kramer JH, Miller BL, Seeley WW. Dopamine receptor D 4 (DRD 4) polymorphisms with reduced functional potency intensify atrophy in syndrome-specific sites of frontotemporal dementia. Neuroimage Clin 2019; 23:101822. [PMID: 31003069 PMCID: PMC6475809 DOI: 10.1016/j.nicl.2019.101822] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 04/04/2019] [Accepted: 04/09/2019] [Indexed: 11/23/2022]
Abstract
OBJECTIVE We aimed to understand the impact of dopamine receptor D4 (DRD4) polymorphisms on neurodegeneration in patients with dementia. We hypothesized that DRD4dampened-variants with reduced functional potency would be associated with greater atrophy in regions with higher receptor density. Given that DRD4 is concentrated in anterior regions of the limbic and cortical forebrain we anticipated genotype effects in patients with a more rostral pattern of neurodegeneration. METHODS 337 subjects, including healthy controls, patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD) underwent genotyping, structural MRI, and cognitive/behavioral testing. We conducted whole-brain voxel-based morphometry to examine the relationship between DRD4 genotypes and brain atrophy patterns within and across groups. General linear modeling was used to evaluate relationships between genotype and cognitive/behavioral measures. RESULTS DRD4 dampened-variants predicted gray matter atrophy in disease-specific regions of FTD in anterior cingulate, ventromedial prefrontal, orbitofrontal and insular cortices on the right greater than the left. Genotype predicted greater apathy and repetitive motor disturbance in patients with FTD. These results covaried with frontoinsular cortical atrophy. Peak atrophy patterned along regions of neuroanatomic vulnerability in FTD-spectrum disorders. In AD subjects and controls, genotype did not impact gray matter intensity. CONCLUSIONS We conclude that DRD4 polymorphisms with reduced functional potency exacerbate neuronal injury in sites of higher receptor density, which intersect with syndrome-specific regions undergoing neurodegeneration in FTD.
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Affiliation(s)
- P M Butler
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA.
| | - W Chiong
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - D C Perry
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Z A Miller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - E D Gennatas
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - J A Brown
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - L Pasquini
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - A Karydas
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - D Dokuru
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - G Coppola
- Departments of Psychiatry and Neurology, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - V E Sturm
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - A L Boxer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - M L Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - H J Rosen
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - J H Kramer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - B L Miller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - W W Seeley
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
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48
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Quevenco FC, Schreiner SJ, Preti MG, van Bergen JMG, Kirchner T, Wyss M, Steininger SC, Gietl A, Leh SE, Buck A, Pruessmann KP, Hock C, Nitsch RM, Henning A, Van De Ville D, Unschuld PG. GABA and glutamate moderate beta-amyloid related functional connectivity in cognitively unimpaired old-aged adults. NEUROIMAGE-CLINICAL 2019; 22:101776. [PMID: 30927605 PMCID: PMC6439267 DOI: 10.1016/j.nicl.2019.101776] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 02/03/2019] [Accepted: 03/10/2019] [Indexed: 02/08/2023]
Abstract
Background Effects of beta-amyloid accumulation on neuronal function precede the clinical manifestation of Alzheimer's disease (AD) by years and affect distinct cognitive brain networks. As previous studies suggest a link between beta-amyloid and dysregulation of excitatory and inhibitory neurotransmitters, we aimed to investigate the impact of GABA and glutamate on beta-amyloid related functional connectivity. Methods 29 cognitively unimpaired old-aged adults (age = 70.03 ± 5.77 years) were administered 11C-Pittsburgh Compound B (PiB) positron-emission tomography (PET), and MRI at 7 Tesla (7T) including blood oxygen level dependent (BOLD) functional MRI (fMRI) at rest for measuring static and dynamic functional connectivity. An advanced 7T MR spectroscopic imaging (MRSI) sequence based on the free induction decay acquisition localized by outer volume suppression’ (FIDLOVS) technology was used for gray matter specific measures of GABA and glutamate in the posterior cingulate and precuneus (PCP) region. Results GABA and glutamate MR-spectra indicated significantly higher levels in gray matter than in white matter. A global effect of beta-amyloid on functional connectivity in the frontal, occipital and inferior temporal lobes was observable. Interactive effects of beta-amyloid with gray matter GABA displayed positive PCP connectivity to the frontomedial regions, and the interaction of beta-amyloid with gray matter glutamate indicated positive PCP connectivity to frontal and cerebellar regions. Furthermore, decreased whole-brain but increased fronto-occipital and temporo-parietal dynamic connectivity was found, when GABA interacted with regional beta-amyloid deposits in the amygdala, frontal lobe, hippocampus, insula and striatum. Conclusions GABA, and less so glutamate, may moderate beta-amyloid related functional connectivity. Additional research is needed to better characterize their interaction and potential impact on AD. Combined ultra-high fieldstrength FIDLOVS MRSI at 7 Tesla with 11C-PIB PET. Assessment of gray matter specific levels of GABA and glutamate. Identification of interactive effects of GABA, glutamate and beta-Amyloid. GABA may moderate dysfunctional beta-Amyloid effects on pre-clinical brain pathology.
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Affiliation(s)
- F C Quevenco
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - S J Schreiner
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - M G Preti
- Department of Radiology and Medical Informatics, Université de Genève, Switzerland; Institute of Bioengineering, École polytechnique fédérale de Lausanne, Switzerland
| | - J M G van Bergen
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - T Kirchner
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - M Wyss
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - S C Steininger
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - A Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - S E Leh
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - A Buck
- Division of Nuclear Medicine, University Hospital Zurich (USZ), Zurich, Switzerland
| | - K P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| | - C Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| | - R M Nitsch
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| | - A Henning
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland; Max Planck Institute for Biological Cybernetics, Tubingen, Germany
| | - D Van De Ville
- Department of Radiology and Medical Informatics, Université de Genève, Switzerland; Institute of Bioengineering, École polytechnique fédérale de Lausanne, Switzerland
| | - P G Unschuld
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland.
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Costa AS, Dogan I, Schulz JB, Reetz K. Going beyond the mean: Intraindividual variability of cognitive performance in prodromal and early neurodegenerative disorders. Clin Neuropsychol 2019; 33:369-389. [PMID: 30663511 DOI: 10.1080/13854046.2018.1533587] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Intraindividual variability (IIV), generally defined as short-term variations in behavior, has been proposed as a sign of subtle early impairment in neurodegenerative disorders, presumably associated with the disintegration of neuronal network connectivity. We aim to provide a review of IIV as a sensitive cognitive marker in prodromal neurodegenerative disorders. METHOD A narrative review focusing not only on theoretical and methodological definitions, including an overview on the neural correlates of IIV, but mainly on results from population-based and clinical-based studies on the role of IIV as a reliable predictor of mild cognitive impairment (MCI) and conversion to dementia in neurodegenerative disorders, mostly Alzheimer's and Parkinson's disease. RESULTS Most studies focus on MCI and Alzheimer's disease and demonstrate that IIV is a reliable cognitive marker. IIV is partly more sensitive than mean performance in the prediction of cognitive impairment or progressive deterioration and is independent of socio-demographic variables and disease mediators (e.g., genetic susceptibility). Neuroimaging data, mostly from healthy subjects, suggest a relationship between IIV and dysfunction of the default mode network, presumably mediated by white matter disintegration in frontal and parietal areas. CONCLUSIONS IIV measures may provide valuable information about diagnosis and progression in prodromal stages of neurodegenerative disorders. Thus, further conceptual and methodological clarifications are needed to justify the inclusion of IIV as a sensible cognitive marker in routine clinical neuropsychological assessment.
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Affiliation(s)
- Ana Sofia Costa
- a Neurocognition Unit, Department of Neurology , Hospital de Braga , Braga , Portugal.,b Department of Neurology , RWTH Aachen University , Aachen , Germany.,c JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University , Aachen , Germany
| | - Imis Dogan
- b Department of Neurology , RWTH Aachen University , Aachen , Germany.,c JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University , Aachen , Germany
| | - Jörg B Schulz
- b Department of Neurology , RWTH Aachen University , Aachen , Germany.,c JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University , Aachen , Germany
| | - Kathrin Reetz
- b Department of Neurology , RWTH Aachen University , Aachen , Germany.,c JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University , Aachen , Germany
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50
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Butler PM, Chiong W. Neurodegenerative disorders of the human frontal lobes. HANDBOOK OF CLINICAL NEUROLOGY 2019; 163:391-410. [PMID: 31590743 DOI: 10.1016/b978-0-12-804281-6.00021-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The frontal lobes play an integral role in human socioemotional and cognitive function. Sense of self, moral decisions, empathy, and behavioral monitoring of goal-states all depend on key nodes within frontal cortex. While several neurodegenerative diseases can affect frontal function, frontotemporal dementia (FTD) has particularly serious and specific effects, which thus provide insights into the role of frontal circuits in homeostasis and adaptive behavior. FTD represents a collection of disorders with specific clinical-pathologic correlates, imaging, and genetics. Patients with FTD and initial prefrontal degeneration often present with neuropsychiatric symptoms such as loss of social decorum, new obsessions, or lack of empathy. In those patients with early anterior temporal degeneration, language (particularly in patients with left-predominant disease) and socioemotional changes (particularly in patients with right-predominant disease) precede eventual frontal dysregulation. Herein, we review a brief history of FTD, initial clinical descriptions, and the evolution of nomenclature. Next, we consider clinical features, neuropathology, imaging, and genetics in FTD-spectrum disorders in relation to the integrity of frontal circuits. In particular, we focus our discussion on behavioral variant FTD given its profound impact on cortical and subcortical frontal structures. This review highlights the clinical heterogeneity of behavioral phenotypes as well as the clinical-anatomic convergence of varying proteinopathies at the neuronal, regional, and network level. Recent neuroimaging and modeling approaches in FTD reveal varying network dysfunction centered on frontal-insular cortices, which underscores the role of the human frontal lobes in complex behaviors. We conclude the chapter reviewing the cognitive and behavioral neuroscience findings furnished from studies in FTD related to executive and socioemotional function, reward-processing, decision-making, and sense of self.
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Affiliation(s)
- P Monroe Butler
- Department of Neurology, UCSF Memory and Aging Center, UCSF School of Medicine, San Francisco, CA, United States
| | - Winston Chiong
- Department of Neurology, UCSF Memory and Aging Center, UCSF School of Medicine, San Francisco, CA, United States.
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