1
|
Tang H, Ma G, Guo L, Fu X, Huang H, Zhan L. Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:7363-7375. [PMID: 36374890 PMCID: PMC10183052 DOI: 10.1109/tnnls.2022.3220220] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Recently, brain networks have been widely adopted to study brain dynamics, brain development, and brain diseases. Graph representation learning techniques on brain functional networks can facilitate the discovery of novel biomarkers for clinical phenotypes and neurodegenerative diseases. However, current graph learning techniques have several issues on brain network mining. First, most current graph learning models are designed for unsigned graph, which hinders the analysis of many signed network data (e.g., brain functional networks). Meanwhile, the insufficiency of brain network data limits the model performance on clinical phenotypes' predictions. Moreover, few of the current graph learning models are interpretable, which may not be capable of providing biological insights for model outcomes. Here, we propose an interpretable hierarchical signed graph representation learning (HSGPL) model to extract graph-level representations from brain functional networks, which can be used for different prediction tasks. To further improve the model performance, we also propose a new strategy to augment functional brain network data for contrastive learning. We evaluate this framework on different classification and regression tasks using data from human connectome project (HCP) and open access series of imaging studies (OASIS). Our results from extensive experiments demonstrate the superiority of the proposed model compared with several state-of-the-art techniques. In addition, we use graph saliency maps, derived from these prediction tasks, to demonstrate detection and interpretation of phenotypic biomarkers.
Collapse
|
2
|
Miskovic R, Ljubicic J, Bonaci-Nikolic B, Petkovic A, Markovic V, Rankovic I, Djordjevic J, Stankovic A, Klaassen K, Pavlovic S, Stojanovic M. Case report: Rapidly progressive neurocognitive disorder with a fatal outcome in a patient with PU.1 mutated agammaglobulinemia. Front Immunol 2024; 15:1324679. [PMID: 38500873 PMCID: PMC10945545 DOI: 10.3389/fimmu.2024.1324679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/19/2024] [Indexed: 03/20/2024] Open
Abstract
Introduction PU.1-mutated agammaglobulinemia (PU.MA) represents a recently described autosomal-dominant form of agammaglobulinemia caused by mutation of the SPI1 gene. This gene codes for PU.1 pioneer transcription factor important for the maturation of monocytes, B lymphocytes, and conventional dendritic cells. Only six cases with PU.MA, presenting with chronic sinopulmonary and systemic enteroviral infections, have been previously described. Accumulating literature evidence suggests a possible relationship between SPI1 mutation, microglial phagocytic dysfunction, and the development of Alzheimer's disease (AD). Case description We present a Caucasian female patient born from a non-consanguineous marriage, who was diagnosed with agammaglobulinemia at the age of 15 years when the immunoglobulin replacement therapy was started. During the following seventeen years, she was treated for recurrent respiratory and intestinal infections. At the age of 33 years, the diagnosis of celiac-like disease was established. Five years later progressive cognitive deterioration, unstable gait, speech disturbances, and behavioral changes developed. Comprehensive microbiological investigations were negative, excluding possible infective etiology. Brain MRI, 18FDG-PET-CT, and neuropsychological testing were suggestive for a diagnosis of a frontal variant of AD. Clinical exome sequencing revealed the presence of a novel frameshift heterozygous variant c.441dup in exon 4 of the SPI1 gene. Despite intensive therapy, the patient passed away a few months after the onset of the first neurological symptoms. Conclusion We describe the first case of PU.MA patient presenting with a rapidly progressive neurocognitive deterioration. The possible role of microglial dysfunction in patients with SPI1 mutation could explain their susceptibility to neurodegenerative diseases thus highlighting the importance of genetic testing in patients with inborn errors of immunity. Since PU.MA represents a newly described form of agammaglobulinemia, our case expands the spectrum of manifestations associated with SPI1 mutation.
Collapse
Affiliation(s)
- Rada Miskovic
- Clinic of Allergy and Immunology, University Clinical Center of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Jelena Ljubicic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Branka Bonaci-Nikolic
- Clinic of Allergy and Immunology, University Clinical Center of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Ana Petkovic
- Diagnostic Department, Center of Sterotaxic Radiosurgery, Clinic of Neurosurgery, University Clinical Center of Serbia, Belgrade, Serbia
| | - Vladana Markovic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
- Clinic of Neurology, University Clinical Center of Serbia, Belgrade, Serbia
| | - Ivan Rankovic
- Department of Gastroenterology and Liver Unit, Royal Cornwall Hospitals NHS Trust, University of Exeter, Truro, United Kingdom
| | - Jelena Djordjevic
- Clinic of Neurology and Psychiatry for Children and Youth, Belgrade, Serbia
- Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia
| | - Ana Stankovic
- Center for Radiology, University Clinical Center of Serbia, Belgrade, Serbia
| | - Kristel Klaassen
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Sonja Pavlovic
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Maja Stojanovic
- Clinic of Allergy and Immunology, University Clinical Center of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| |
Collapse
|
3
|
Olmos-Villaseñor R, Sepulveda-Silva C, Julio-Ramos T, Fuentes-Lopez E, Toloza-Ramirez D, Santibañez RA, Copland DA, Mendez-Orellana C. Phonological and Semantic Fluency in Alzheimer's Disease: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2023; 95:1-12. [PMID: 37482994 PMCID: PMC10578227 DOI: 10.3233/jad-221272] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/21/2023] [Indexed: 07/25/2023]
Abstract
BACKGROUND Semantic and Phonological fluency (SF and PF) are routinely evaluated in patients with Alzheimer's disease (AD). There are disagreements in the literature regarding which fluency task is more affected while developing AD. Most studies focus on SF assessment, given its connection with the temporoparietal amnesic system. PF is less reported, it is related to working memory, which is also impaired in probable and diagnosed AD. Differentiating between performance on these tasks might be informative in early AD diagnosis, providing an accurate linguistic profile. OBJECTIVE Compare SF and PF performance in healthy volunteers, volunteers with probable AD, and patients with AD diagnosis, considering the heterogeneity of age, gender, and educational level variables. METHODS A total of 8 studies were included for meta-analysis, reaching a sample size of 1,270 individuals (568 patients diagnosed with AD, 340 with probable AD diagnosis, and 362 healthy volunteers). RESULTS The three groups consistently performed better on SF than PF. When progressing to a diagnosis of AD, we observed a significant difference in SF and PF performance across our 3 groups of interest (p = 0.04). The age variable explained a proportion of this difference in task performance across the groups, and as age increases, both tasks equally worsen. CONCLUSION The performance of SF and PF might play a differential role in early AD diagnosis. These tasks rely on partially different neural bases of language processing. They are thus worth exploring independently in diagnosing normal aging and its transition to pathological stages, including probable and diagnosed AD.
Collapse
Affiliation(s)
- Rocio Olmos-Villaseñor
- Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Laboratory of Language Rehabilitation and Stimulation (LARES), Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Consuelo Sepulveda-Silva
- Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Laboratory of Language Rehabilitation and Stimulation (LARES), Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Teresa Julio-Ramos
- Laboratory of Language Rehabilitation and Stimulation (LARES), Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Eduardo Fuentes-Lopez
- Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - David Toloza-Ramirez
- Exercise and Rehabilitation Sciences Institute, School of Speech Therapy, Faculty of Rehabilitation Sciences, Universidad Andres Bello, Santiago, Chile
| | - Rodrigo A. Santibañez
- Neurology Department, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Neurology Service, Complejo Asistencial Doctor Sótero del Río, Santiago, Chile
| | - David A. Copland
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, Australia
| | - Carolina Mendez-Orellana
- Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Laboratory of Language Rehabilitation and Stimulation (LARES), Speech and Language Therapy School, Health Sciences Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
| |
Collapse
|
4
|
Burkett BJ, Babcock JC, Lowe VJ, Graff-Radford J, Subramaniam RM, Johnson DR. PET Imaging of Dementia: Update 2022. Clin Nucl Med 2022; 47:763-773. [PMID: 35543643 DOI: 10.1097/rlu.0000000000004251] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
ABSTRACT PET imaging plays an essential role in achieving earlier and more specific diagnoses of dementia syndromes, important for clinical prognostication and optimal medical management. This has become especially vital with the recent development of pathology-specific disease-modifying therapy for Alzheimer disease, which will continue to evolve and require methods to select appropriate treatment candidates. Techniques that began as research tools such as amyloid and tau PET have now entered clinical use, making nuclear medicine physicians and radiologists essential members of the care team. This review discusses recent changes in the understanding of dementia and examines the roles of nuclear medicine imaging in clinical practice. Within this framework, multiple cases will be shown to illustrate a systematic approach of FDG PET interpretation and integration of PET imaging of specific molecular pathology including dopamine transporters, amyloid, and tau. The approach presented here incorporates contemporary understanding of both common and uncommon dementia syndromes, intended as an updated practical guide to assist with the sophisticated interpretation of nuclear medicine examinations in the context of this rapidly and continually developing area of imaging.
Collapse
|
5
|
Perez SD, Phillips JS, Norise C, Kinney NG, Vaddi P, Halpin A, Rascovsky K, Irwin DJ, McMillan CT, Xie L, Wisse LE, Yushkevich PA, Kallogjeri D, Grossman M, Cousins KA. Neuropsychological and Neuroanatomical Features of Patients with Behavioral/Dysexecutive Variant Alzheimer’s disease (AD): A Comparison to Behavioral Variant Frontotemporal Dementia and Amnestic AD Groups. J Alzheimers Dis 2022; 89:641-658. [PMID: 35938245 PMCID: PMC10117623 DOI: 10.3233/jad-215728] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: An understudied variant of Alzheimer’s disease (AD), the behavioral/dysexecutive variant of AD (bvAD), is associated with progressive personality, behavior, and/or executive dysfunction and frontal atrophy. Objective: This study characterizes the neuropsychological and neuroanatomical features associated with bvAD by comparing it to behavioral variant frontotemporal dementia (bvFTD), amnestic AD (aAD), and subjects with normal cognition. Methods: Subjects included 16 bvAD, 67 bvFTD, and 18 aAD patients, and 26 healthy controls. Neuropsychological assessment and MRI data were compared between these groups. Results: Compared to bvFTD, bvAD showed more significant visuospatial impairments (Rey Figure copy and recall), more irritability (Neuropsychological Inventory), and equivalent verbal memory (Philadelphia Verbal Learning Test). Compared to aAD, bvAD indicated more executive dysfunction (F-letter fluency) and better visuospatial performance. Neuroimaging analysis found that bvAD showed cortical thinning relative to bvFTD posteriorly in left temporal-occipital regions; bvFTD had cortical thinning relative to bvAD in left inferior frontal cortex. bvAD had cortical thinning relative to aAD in prefrontal and anterior temporal regions. All patient groups had lower volumes than controls in both anterior and posterior hippocampus. However, bvAD patients had higher average volume than aAD patients in posterior hippocampus and higher volume than bvFTD patients in anterior hippocampus after adjustment for age and intracranial volume. Conclusion: Findings demonstrated that underlying pathology mediates disease presentation in bvAD and bvFTD.
Collapse
Affiliation(s)
- Sophia Dominguez Perez
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Catherine Norise
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nikolas G. Kinney
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Prerana Vaddi
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy Halpin
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, University of Maine, Orono, ME, USA
| | - Katya Rascovsky
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E.M. Wisse
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Paul A. Yushkevich
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dorina Kallogjeri
- Department of Otolaryngology, Washington University, St. Louis, MO, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katheryn A.Q. Cousins
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
6
|
Sirkis DW, Bonham LW, Johnson TP, La Joie R, Yokoyama JS. Dissecting the clinical heterogeneity of early-onset Alzheimer's disease. Mol Psychiatry 2022; 27:2674-2688. [PMID: 35393555 PMCID: PMC9156414 DOI: 10.1038/s41380-022-01531-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 12/14/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.
Collapse
Affiliation(s)
- Daniel W Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Taylor P Johnson
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA.
| |
Collapse
|
7
|
Faruk EM, Fouad H, Hasan RAA, Taha NM, El-Shazly AM. Inhibition of gene expression and production of iNOS and TNF-α in experimental model of neurodegenerative disorders stimulated microglia by Soy nano-isoflavone/stem cell-exosomes. Tissue Cell 2022; 76:101758. [PMID: 35182987 DOI: 10.1016/j.tice.2022.101758] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 02/02/2022] [Accepted: 02/09/2022] [Indexed: 12/16/2022]
Abstract
The present study evaluated the therapeutic potential of soybean nano-isoflavone extract versus bone marrow mesenchymal stem cells derived extracellular exosomes (BMSCs-EXs) in experimentally induced neurodegenerative diseases in rats (ND). In this study, 36 albino male rats were divided into four groups: Group I (control rats); Group II (induced neurodegenerative disease in rats by intraperitoneal injection of d-galactose (120 mg/kg/day for 2 months); Group III (ND-induced rats treated with nano-isoflavone in doses of 10 mg/kg by oral gavage for 3 months); and Group IV (ND-induced rats treated with a single dose injection of BMSCs-EXs. The effect of BMSCs-EXs was evaluated by cerebral oxidant/antioxidant biomarkers, and mRNA gene expression quantitation for cerebral tumor necrosis factor α (TNF-α), inducible nitric oxide synthase (i-NOS) and GAPDH pathway-encoding genes by real time reverse transcription polymerase chain reaction (RT-PCR) techniques. Then, histopathological examination of the cerebral cortical tissues. Our results showed that BMSC-EXs were successfully isolated and characterized. d-galactose produced a significant rise in the number of damaged neurons, decreased cerebral superoxide dismutase and catalase activities, increased cerebral malondialdehyde levels, downregulated the cerebral TNF-α, and i-NOS pathway-encoding genes. Furthermore, BMSC-EXs and nano-isoflavone treatments repaired damaged cerebral tissue and recovered its function greatly following induction of neurodegenerative disease. Treatment with either MSCs-EXs or nano-isoflavones led to significant improvement in the histological findings, reversed the degenerative effect of d-galactose, and had a favorable therapeutic utility against d- galactose-induced neurodegenerative disease.
Collapse
Affiliation(s)
- Eman Mohamed Faruk
- Department of Anatomy, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia; Department of Histology & Cell Biology, Faculty of Medicine, Benha University, Egypt.
| | - Hanan Fouad
- Medical Biochemistry & Molecular Biology, Faculty of Medicine, Cairo University, Egypt; Galala University, Faculty of medicine, Suez Governorate, Egypt
| | - Rehab Abd Allah Hasan
- Department of Histology & Cell Biology, Faculty of Medicine for Girls; AFMG, Al-Azhar University Egypt
| | | | | |
Collapse
|
8
|
Henríquez F, Cabello V, Baez S, de Souza LC, Lillo P, Martínez-Pernía D, Olavarría L, Torralva T, Slachevsky A. Multidimensional Clinical Assessment in Frontotemporal Dementia and Its Spectrum in Latin America and the Caribbean: A Narrative Review and a Glance at Future Challenges. Front Neurol 2022; 12:768591. [PMID: 35250791 PMCID: PMC8890568 DOI: 10.3389/fneur.2021.768591] [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: 08/31/2021] [Accepted: 12/13/2021] [Indexed: 12/14/2022] Open
Abstract
Frontotemporal dementia (FTD) is the third most common form of dementia across all age groups and is a leading cause of early-onset dementia. The Frontotemporal dementia (FTD) includes a spectrum of diseases that are classified according to their clinical presentation and patterns of neurodegeneration. There are two main types of FTD: behavioral FTD variant (bvFTD), characterized by a deterioration in social function, behavior, and personality; and primary progressive aphasias (PPA), characterized by a deficit in language skills. There are other types of FTD-related disorders that present motor impairment and/or parkinsonism, including FTD with motor neuron disease (FTD-MND), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS). The FTD and its associated disorders present great clinical heterogeneity. The diagnosis of FTD is based on the identification through clinical assessments of a specific clinical phenotype of impairments in different domains, complemented by an evaluation through instruments, i.e., tests and questionnaires, validated for the population under study, thus, achieving timely detection and treatment. While the prevalence of dementia in Latin America and the Caribbean (LAC) is increasing rapidly, there is still a lack of standardized instruments and consensus for FTD diagnosis. In this context, it is important to review the published tests and questionnaires adapted and/or validated in LAC for the assessment of cognition, behavior, functionality, and gait in FTD and its spectrum. Therefore, our paper has three main goals. First, to present a narrative review of the main tests and questionnaires published in LAC for the assessment of FTD and its spectrum in six dimensions: (i) Cognitive screening; (ii) Neuropsychological assessment divided by cognitive domain; (iii) Gait assessment; (iv) Behavioral and neuropsychiatric symptoms; (v) Functional assessment; and (vi) Global Rating Scale. Second, to propose a multidimensional clinical assessment of FTD in LAC identifying the main gaps. Lastly, it is proposed to create a LAC consortium that will discuss strategies to address the current challenges in the field.
Collapse
Affiliation(s)
- Fernando Henríquez
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department – Institute of Biomedical Sciences (ICBM), Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
- Laboratory for Cognitive and Evolutionary Neuroscience (LaNCE), Department of Psychiatry, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Victoria Cabello
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department – Institute of Biomedical Sciences (ICBM), Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Sandra Baez
- Universidad de los Andes, Departamento de Psicología, Bogotá, Colombia
| | - Leonardo Cruz de Souza
- Programa de Pós-Graduação em Neurociências da Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
- Departamento de Clínica Médica, Faculdade de Medicina da Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Patricia Lillo
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Departamento de Neurología Sur, Facultad de Medicina, Universidad de Chile, Santiago, Chile
- Unidad de Neurología, Hospital San José, Santiago, Chile
| | - David Martínez-Pernía
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile
- Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
| | - Loreto Olavarría
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department – Institute of Biomedical Sciences (ICBM), Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Teresa Torralva
- Institute of Cognitive and Translational Neuroscience (INCYT), Instituto de Neurología Cognitiva Foundation, Favaloro University, Buenos Aires, Argentina
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department – Institute of Biomedical Sciences (ICBM), Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
- Department of Neurology and Psychiatry, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| |
Collapse
|
9
|
Magdy R, Hussein M. Cognitive, Psychiatric, and Motor Symptoms-Based Algorithmic Approach to Differentiate Among Various Types of Dementia Syndromes. J Nerv Ment Dis 2022; 210:129-135. [PMID: 35080518 DOI: 10.1097/nmd.0000000000001428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
ABSTRACT It may be difficult to distinguish among the various dementia syndromes due to the overlap in many common clinical features across the dementias. Accurate diagnosis of dementia type is increasingly important in an era when promising disease-modifying agents can be marketed soon. In this review, we outline a clinical algorithmic approach particularly tailored to the major forms of dementia in the clinic and refined from our accumulated experience of these patients. We first present an algorithmic approach for patients presenting with predominant deficits in episodic memory, executive function, language, visuospatial, and apraxia. We then consider types of dementia that mainly cause behavioral and psychiatric changes. Finally, we illustrate clinical pearls regarding motor deficits as key associations of each syndrome.
Collapse
Affiliation(s)
- Rehab Magdy
- Kasr Al-Ainy Faculty of Medicine, Cairo University, Cairo
| | | |
Collapse
|
10
|
Sun W, Matsuoka T, Narumoto J. Decision-Making Support for People With Alzheimer's Disease: A Narrative Review. Front Psychol 2021; 12:750803. [PMID: 34867639 PMCID: PMC8633444 DOI: 10.3389/fpsyg.2021.750803] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/25/2021] [Indexed: 01/01/2023] Open
Abstract
The proportion of people with dementia has been increasing yearly, and the decision-making capacity of these people has become a major concern in fields such as the financial industry and in medical settings. In this narrative review, we discuss decision-making in people with Alzheimer’s disease (AD), and we propose the support for decision-making in people with AD, especially financial and medical decision-making. We summarize several hypotheses and theories on the decision-making capacity of people with AD. These include the frontal lobe hypothesis, physiological theory, dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, and the Person-Task-Fit (PTF) framework. Both internal and external factors can affect decision-making by people with AD. Internal factors are affected by changes in the brain and neurotransmitters, as well as alterations in cognitive ability and emotion. External factors include task characters, task contents, and situation influence. Since feedback has a significant effect on decision-making capacity, a series of suggestions may be helpful to improve this capacity, such as explicit advice, simple options, pleasant rewards, the Talking Mats approach, memory and organizational aid, support by caregivers, cognitive training and feedback. Thus, in providing decision-making support for people with AD, it is important to identify the internal and external factors that impair this process and to deal with these factors.
Collapse
Affiliation(s)
- Weiyi Sun
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Teruyuki Matsuoka
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Jin Narumoto
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| |
Collapse
|
11
|
Ossenkoppele R, Singleton EH, Groot C, Dijkstra AA, Eikelboom WS, Seeley WW, Miller B, Laforce RJ, Scheltens P, Papma JM, Rabinovici GD, Pijnenburg YAL. Research Criteria for the Behavioral Variant of Alzheimer Disease: A Systematic Review and Meta-analysis. JAMA Neurol 2021; 79:48-60. [PMID: 34870696 PMCID: PMC8649917 DOI: 10.1001/jamaneurol.2021.4417] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Importance The behavioral variant of Alzheimer disease (bvAD) is characterized by early and predominant behavioral deficits caused by AD pathology. This AD phenotype is insufficiently understood and lacks standardized clinical criteria, limiting reliability and reproducibility of diagnosis and scientific reporting. Objective To perform a systematic review and meta-analysis of the bvAD literature and use the outcomes to propose research criteria for this syndrome. Data Sources A systematic literature search in PubMed/MEDLINE and Web of Science databases (from inception through April 7, 2021) was performed in duplicate. Study Selection Studies reporting on behavioral, neuropsychological, or neuroimaging features in bvAD and, when available, providing comparisons with typical amnestic-predominant AD (tAD) or behavioral variant frontotemporal dementia (bvFTD). Data Extraction and Synthesis This analysis involved random-effects meta-analyses on group-level study results of clinical data and systematic review of the neuroimaging literature. The study was performed following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Main Outcomes and Measures Behavioral symptoms (neuropsychiatric symptoms and bvFTD core clinical criteria), cognitive function (global cognition, episodic memory, and executive functioning), and neuroimaging features (structural magnetic resonance imaging, [18F]fluorodeoxyglucose-positron emission tomography, perfusion single-photon emission computed tomography, amyloid positron emission tomography, and tau positron emission tomography). Results The search led to the assessment of 83 studies, including 13 suitable for meta-analysis. Data were collected for 591 patients with bvAD. There was moderate to substantial heterogeneity and moderate risk of bias across studies. Cases with bvAD showed more severe behavioral symptoms than tAD (standardized mean difference [SMD], 1.16 [95% CI, 0.74-1.59]; P < .001) and a trend toward less severe behavioral symptoms compared with bvFTD (SMD, -0.22 [95% CI, -0.47 to 0.04]; P = .10). Meta-analyses of cognitive data indicated worse executive performance in bvAD vs tAD (SMD, -1.03 [95% CI, -1.74 to -0.32]; P = .008) but not compared with bvFTD (SMD, -0.61 [95% CI, -1.75 to 0.53]; P = .29). Cases with bvAD showed a nonsignificant difference of worse memory performance compared with bvFTD (SMD, -1.31 [95% CI, -2.75 to 0.14]; P = .08) but did not differ from tAD (SMD, 0.43 [95% CI, -0.46 to 1.33]; P = .34). The neuroimaging literature revealed 2 distinct bvAD neuroimaging phenotypes: an AD-like pattern with relative frontal sparing and a relatively more bvFTD-like pattern characterized by additional anterior involvement, with the AD-like pattern being more prevalent. Conclusions and Relevance These data indicate that bvAD is clinically most similar to bvFTD, while it shares most pathophysiological features with tAD. Based on these insights, we propose research criteria for bvAD aimed at improving the consistency and reliability of future research and aiding the clinical assessment of this AD phenotype.
Collapse
Affiliation(s)
- Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.,Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - Ellen H Singleton
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Colin Groot
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Anke A Dijkstra
- Department of Pathology, Amsterdam Neuroscience, Amsterdam University Medical Centre, Location VUMC, Amsterdam, the Netherlands
| | - Willem S Eikelboom
- Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco
| | - Bruce Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Centre Hospitalier Universitaire de Québec, Québec, Canada
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Janne M Papma
- Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco.,Weill Institute for Neurosciences, University of California, San Francisco, San Francisco.,Associate Editor, JAMA Neurology
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| |
Collapse
|
12
|
Lau A, Beheshti I, Modirrousta M, Kolesar TA, Goertzen AL, Ko JH. Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases. Diagnostics (Basel) 2021; 11:diagnostics11112023. [PMID: 34829370 PMCID: PMC8624480 DOI: 10.3390/diagnostics11112023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/29/2021] [Accepted: 10/29/2021] [Indexed: 12/13/2022] Open
Abstract
Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.
Collapse
Affiliation(s)
- Angus Lau
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
- Undergraduate Medical Education, University of Manitoba, Winnipeg, MB R3E 3P5, Canada
| | - Iman Beheshti
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
| | - Mandana Modirrousta
- Department of Psychiatry, University of Manitoba, Winnipeg, MB R3E 3N4, Canada;
| | - Tiffany A. Kolesar
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
| | - Andrew L. Goertzen
- Department of Radiology, University of Manitoba, Winnipeg, MB R3T 2N2, Canada;
- Graduate Program in Biomedical Engineering, University of Manitoba, Winnipeg, MB R3E 5V6, Canada
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
- Graduate Program in Biomedical Engineering, University of Manitoba, Winnipeg, MB R3E 5V6, Canada
- Correspondence: ; Tel.: +1-204-318-2566
| |
Collapse
|
13
|
Wittens MMJ, Allemeersch GJ, Sima DM, Naeyaert M, Vanderhasselt T, Vanbinst AM, Buls N, De Brucker Y, Raeymaekers H, Fransen E, Smeets D, van Hecke W, Nagels G, Bjerke M, de Mey J, Engelborghs S. Inter- and Intra-Scanner Variability of Automated Brain Volumetry on Three Magnetic Resonance Imaging Systems in Alzheimer's Disease and Controls. Front Aging Neurosci 2021; 13:746982. [PMID: 34690745 PMCID: PMC8530224 DOI: 10.3389/fnagi.2021.746982] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 09/08/2021] [Indexed: 12/02/2022] Open
Abstract
Magnetic Resonance Imaging (MRI) has become part of the clinical routine for diagnosing neurodegenerative disorders. Since acquisitions are performed at multiple centers using multiple imaging systems, detailed analysis of brain volumetry differences between MRI systems and scan-rescan acquisitions can provide valuable information to correct for different MRI scanner effects in multi-center longitudinal studies. To this end, five healthy controls and five patients belonging to various stages of the AD continuum underwent brain MRI acquisitions on three different MRI systems (Philips Achieva dStream 1.5T, Philips Ingenia 3T, and GE Discovery MR750w 3T) with harmonized scan parameters. Each participant underwent two subsequent MRI scans per imaging system, repeated on three different MRI systems within 2 h. Brain volumes computed by icobrain dm (v5.0) were analyzed using absolute and percentual volume differences, Dice similarity (DSC) and intraclass correlation coefficients, and coefficients of variation (CV). Harmonized scans obtained with different scanners of the same manufacturer had a measurement error closer to the intra-scanner performance. The gap between intra- and inter-scanner comparisons grew when comparing scans from different manufacturers. This was observed at image level (image contrast, similarity, and geometry) and translated into a higher variability of automated brain volumetry. Mixed effects modeling revealed a significant effect of scanner type on some brain volumes, and of the scanner combination on DSC. The study concluded a good intra- and inter-scanner reproducibility, as illustrated by an average intra-scanner (inter-scanner) CV below 2% (5%) and an excellent overlap of brain structure segmentation (mean DSC > 0.88).
Collapse
Affiliation(s)
- Mandy Melissa Jane Wittens
- Reference Center for Biological Markers of Dementia, Laboratory of Neurochemistry and Behavior, University of Antwerp, Antwerp, Belgium.,Center for Neurosciences (C4N) and Department of Neurology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Gert-Jan Allemeersch
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | | | - Maarten Naeyaert
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Tim Vanderhasselt
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Anne-Marie Vanbinst
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Nico Buls
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Yannick De Brucker
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Hubert Raeymaekers
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Erik Fransen
- StatUa Center for Statistics, University of Antwerp, Antwerp, Belgium
| | | | | | - Guy Nagels
- Center for Neurosciences (C4N) and Department of Neurology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia, Laboratory of Neurochemistry and Behavior, University of Antwerp, Antwerp, Belgium.,Center for Neurosciences (C4N) and Department of Neurology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Johan de Mey
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia, Laboratory of Neurochemistry and Behavior, University of Antwerp, Antwerp, Belgium.,Center for Neurosciences (C4N) and Department of Neurology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium
| |
Collapse
|
14
|
Balachandran S, Matlock EL, Conroy ML, Lane CE. Behavioral Variant Frontotemporal Dementia: Diagnosis and Treatment Interventions. CURRENT GERIATRICS REPORTS 2021. [DOI: 10.1007/s13670-021-00360-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Abstract
Purpose of Review
The diagnosis and treatment of behavioral variant frontotemporal dementia is challenging and often delayed because of overlapping symptoms with more common dementia syndromes or primary psychiatric illnesses. The purpose of this paper is to explore the relevant presentation, diagnostic workup, pathophysiology, and both pharmacologic and non-pharmacologic management.
Recent Findings
Behavioral variant frontotemporal dementia is a highly heritable disorder. The gradual accumulation of diseased protein culminates in the destruction of those brain circuits responsible for much of one’s emotional and social functioning.
Summary
Behavioral variant frontotemporal dementia is a progressive neurodegenerative disorder with a far-reaching impact on patients and caregivers. Patients often present with emotional blunting, lack of empathy, apathy, and behavioral disinhibition. Non-pharmacologic interventions and caregiver support are the cornerstone of treatment. The use of cholinesterase inhibitors and memantine is not supported by the evidence. While current pharmacologic therapies target only certain symptoms, there are disease modifying agents currently in or nearing the clinical research stage.
Collapse
|
15
|
Musa G, Slachevsky A, Muñoz-Neira C, Méndez-Orellana C, Villagra R, González-Billault C, Ibáñez A, Hornberger M, Lillo P. Alzheimer's Disease or Behavioral Variant Frontotemporal Dementia? Review of Key Points Toward an Accurate Clinical and Neuropsychological Diagnosis. J Alzheimers Dis 2021; 73:833-848. [PMID: 31884475 DOI: 10.3233/jad-190924] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the most common neurodegenerative early-onset dementias. Despite the fact that both conditions have a very distinctive clinical pattern, they present with an overlap in their cognitive and behavioral features that may lead to misdiagnosis or delay in diagnosis. The current review intends to summarize briefly the main differences at the clinical, neuropsychological, and behavioral levels, in an attempt to suggest which aspects would facilitate an adequate diagnosis in a clinical setting, especially in Latin American and low- and middle-income countries, where the resources needed for a differential diagnosis (such as MRI or biomarkers) are not always available. A timely diagnosis of AD and FTD have significant implications for the medical management and quality of life of patients and careers.
Collapse
Affiliation(s)
- Gada Musa
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Department of Physiopathology, ICBM, Department of Neurosciences, Department of East Neuroscience, Faculty of Medicine, University of Chile, Providencia, Santiago, Chile.,Universidad de los Andes, Santiago, Chile.,Capredena, Health and Rehabilitation Center, Santiago, Chile
| | - Andrea Slachevsky
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Department of Physiopathology, ICBM, Department of Neurosciences, Department of East Neuroscience, Faculty of Medicine, University of Chile, Providencia, Santiago, Chile.,Gerosciences Center for Brain Health and Metabolism (GERO), Providencia, Santiago, Chile.,Memory and Neuropsychiatric Clinic (CMYN) Neurology Department- Hospital del Salvador and University of Chile, Providencia, Santiago, Chile.,Departamento de Medicina, Servicio de Neurología, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Carlos Muñoz-Neira
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department- Hospital del Salvador and University of Chile, Providencia, Santiago, Chile.,Research into Memory, Brain Sciences and Dementia Group (ReMemBr Group), Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
| | - Carolina Méndez-Orellana
- Carrera de Fonoaudiología, Departamento Ciencias de la Salud, Facultad de Medicina, Universidad Católica de Chile, Santiago, Chile
| | - Roque Villagra
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Department of Physiopathology, ICBM, Department of Neurosciences, Department of East Neuroscience, Faculty of Medicine, University of Chile, Providencia, Santiago, Chile.,Gerosciences Center for Brain Health and Metabolism (GERO), Providencia, Santiago, Chile
| | - Christian González-Billault
- Gerosciences Center for Brain Health and Metabolism (GERO), Providencia, Santiago, Chile.,Department of Biology, Faculty of Sciences, Universidad de Chile, Santiago, Chile.,The Buck Institute for Research on Aging, Novato, CA, USA
| | - Agustín Ibáñez
- Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Universidad Autónoma del Caribe, Barranquilla, Colombia.,Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile.,Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR), Sydney, Australia
| | | | - Patricia Lillo
- Gerosciences Center for Brain Health and Metabolism (GERO), Providencia, Santiago, Chile.,Department of Neurology South, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| |
Collapse
|
16
|
Shea YF, Pan Y, Mak HKF, Bao Y, Lee SC, Chiu PKC, Chan HWF. A systematic review of atypical Alzheimer's disease including behavioural and psychological symptoms. Psychogeriatrics 2021; 21:396-406. [PMID: 33594793 DOI: 10.1111/psyg.12665] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 01/06/2021] [Accepted: 01/25/2021] [Indexed: 12/20/2022]
Abstract
Alzheimer's disease (AD) is the commonest cause of dementia, characterized by the clinical presentation of progressive anterograde episodic memory impairment. However, atypical presentation of patients is increasingly recognized. These atypical AD include logopenic aphasia, behavioural variant AD, posterior cortical atrophy, and corticobasal syndrome. These atypical AD are more common in patients with young onset AD before the age of 65 years old. Since medical needs (including the behavioural and psychological symptoms of dementia) of atypical AD patients could be different from typical AD patients, it is important for clinicians to be aware of these atypical forms of AD. In addition, disease modifying treatment may be available in the future. This review aims at providing an update on various important subtypes of atypical AD including behavioural and psychological symptoms.
Collapse
Affiliation(s)
- Yat-Fung Shea
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Yining Pan
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Yiwen Bao
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Shui-Ching Lee
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Patrick Ka-Chun Chiu
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Hon-Wai Felix Chan
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| |
Collapse
|
17
|
Bellomo G, Indaco A, Chiasserini D, Maderna E, Paolini Paoletti F, Gaetani L, Paciotti S, Petricciuolo M, Tagliavini F, Giaccone G, Parnetti L, Di Fede G. Machine Learning Driven Profiling of Cerebrospinal Fluid Core Biomarkers in Alzheimer's Disease and Other Neurological Disorders. Front Neurosci 2021; 15:647783. [PMID: 33867925 PMCID: PMC8044304 DOI: 10.3389/fnins.2021.647783] [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: 12/30/2020] [Accepted: 03/08/2021] [Indexed: 12/19/2022] Open
Abstract
Amyloid-beta (Aβ) 42/40 ratio, tau phosphorylated at threonine-181 (p-tau), and total-tau (t-tau) are considered core biomarkers for the diagnosis of Alzheimer’s disease (AD). The use of fully automated biomarker assays has been shown to reduce the intra- and inter-laboratory variability, which is a critical factor when defining cut-off values. The calculation of cut-off values is often influenced by the composition of AD and control groups. Indeed, the clinically defined AD group may include patients affected by other forms of dementia, while the control group is often very heterogeneous due to the inclusion of subjects diagnosed with other neurological diseases (OND). In this context, unsupervised machine learning approaches may overcome these issues providing unbiased cut-off values and data-driven patient stratification according to the sole distribution of biomarkers. In this work, we took advantage of the reproducibility of automated determination of the CSF core AD biomarkers to compare two large cohorts of patients diagnosed with different neurological disorders and enrolled in two centers with established expertise in AD biomarkers. We applied an unsupervised Gaussian mixture model clustering algorithm and found that our large series of patients could be classified in six clusters according to their CSF biomarker profile, some presenting a typical AD-like profile and some a non-AD profile. By considering the frequencies of clinically defined OND and AD subjects in clusters, we subsequently computed cluster-based cut-off values for Aβ42/Aβ40, p-tau, and t-tau. This approach promises to be useful for large-scale biomarker studies aimed at providing efficient biochemical phenotyping of neurological diseases.
Collapse
Affiliation(s)
- Giovanni Bellomo
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Antonio Indaco
- Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Davide Chiasserini
- Section of Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Emanuela Maderna
- Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | | | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Silvia Paciotti
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Maya Petricciuolo
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Fabrizio Tagliavini
- Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Giorgio Giaccone
- Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Lucilla Parnetti
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.,Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Giuseppe Di Fede
- Neurology 5/Neuropathology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| |
Collapse
|
18
|
Li CH, Fan SP, Chen TF, Chiu MJ, Yen RF, Lin CH. Frontal variant of Alzheimer's disease with asymmetric presentation mimicking frontotemporal dementia: Case report and literature review. Brain Behav 2020; 10:e01548. [PMID: 31989779 PMCID: PMC7066333 DOI: 10.1002/brb3.1548] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 01/01/2020] [Accepted: 01/04/2020] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Frontal variant of Alzheimer's disease (fvAD) is a rare nonamnestic syndrome of Alzheimer's disease (AD). Differentiating it from behavior variant of frontotemporal dementia (bvFTD), which has implications for treatment responses and prognosis, remains a clinical challenge. METHODS Molecular neuroimaging and biofluid markers were performed for the index patient for accurate premortem diagnosis of fvAD. The clinical, neuroimaging, and biofluid characteristics of the patient were compared to those reported in previous studies of fvAD from 1999 to 2019. RESULTS A 66-year-old man presented with progressive executive dysfunction, personality and behavioral changes, and memory decline since age 59. He had no family history of neurodegenerative disorders. A stimulus-sensitive myoclonus was noted over his left upper extremity. Neuropsychological assessment revealed moderate dementia with a Mini-Mental State Exam score of 10/30 and compromised executive and memory performance. Brain imaging showed asymmetrical atrophy and hypometabolism over the right frontal and temporal areas, mimicking bvFTD. However, we observed increased tau depositions based on 18 F-labeled T807 Tau PET in these areas and diffusely increased amyloid deposition based on 11 C-labeled Pittsburgh compound B positron emission tomography (PET). Plasma biomarker measures indicated an AD profile with increased Aβ1-42 (18.66 pg/ml; cutoff: 16.42 pg/ml), Aβ1-42/Aβ1-40 ratio (0.45; cutoff: 0.30), total tau (29.78 pg/ml; cutoff: 23.89 pg/ml), and phosphorylated tau (4.11 pg/ml; cutoff: 3.08 pg/ml). These results supported a diagnosis of fvAD. CONCLUSIONS Our results with asymmetrical presentations extend current knowledge about this rare AD variant. Application of biofluid and molecular imaging markers could assist in early, accurate diagnosis.
Collapse
Affiliation(s)
- Cheng-Hsuan Li
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, Hsinchu, Taiwan
| | - Sung-Pin Fan
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Biomedical Engineering and Bioinformatics, National Taiwan University, Taipei, Taiwan.,Graduate institute of Psychology, National Taiwan University, Taipei, Taiwan
| | - Ruoh-Fang Yen
- Department of Nuclear Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Chin-Hsien Lin
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| |
Collapse
|
19
|
Amen DG, Taylor DV, Meysami S, Raji CA. Deficits in Regional Cerebral Blood Flow on Brain SPECT Predict Treatment Resistant Depression. J Alzheimers Dis 2019; 63:529-538. [PMID: 29578481 DOI: 10.3233/jad-170855] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Depression remains an important risk factor for Alzheimer's disease, yet few neuroimaging biomarkers are available to identify treatment response in depression. OBJECTIVE To analyze and compare functional perfusion neuroimaging in persons with treatment resistant depression (TRD) compared to those experiencing full remission. METHODS A total of 951 subjects from a community psychiatry cohort were scanned with perfusion single photon emission computed tomography (SPECT) of the brain in both resting and task related settings. Of these, 78% experienced either full remission (n = 506) or partial remission (n = 237) and 11% were minimally responsive (n = 103) or non-responsive (11%. n = 106). Severity of depression symptoms were used to define these groups with changes in the Beck Depression Inventory prior to and following treatment. Voxel-based analyses of brain SPECT images from full remission compared to the worsening group was conducted with the statistical parametric mapping software, version 8 (SPM 8). Multiple comparisons were accounted for with a false discovery rate (p < 0.001). RESULTS Persons with depression that worsened following treatment had reduced cerebral perfusion compared to full remission in the multiple regions including the bilateral frontal lobes, right hippocampus, left precuneus, and cerebellar vermis. Such differences were observed on both resting and concentration SPECT scans. CONCLUSION Our findings identify imaging-based biomarkers in persons with depression related to treatment response. These findings have implications in understanding both depression to prognosis and its role as a risk factor for dementia.
Collapse
|
20
|
Forouzannezhad P, Abbaspour A, Fang C, Cabrerizo M, Loewenstein D, Duara R, Adjouadi M. A survey on applications and analysis methods of functional magnetic resonance imaging for Alzheimer’s disease. J Neurosci Methods 2019; 317:121-140. [DOI: 10.1016/j.jneumeth.2018.12.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 12/04/2018] [Accepted: 12/17/2018] [Indexed: 12/23/2022]
|
21
|
Bonham LW, Steele NZR, Karch CM, Manzoni C, Geier EG, Wen N, Ofori-Kuragu A, Momeni P, Hardy J, Miller ZA, Hess CP, Lewis P, Miller BL, Seeley WW, Baranzini SE, Desikan RS, Ferrari R, Yokoyama JS. Protein network analysis reveals selectively vulnerable regions and biological processes in FTD. Neurol Genet 2018; 4:e266. [PMID: 30283816 PMCID: PMC6167176 DOI: 10.1212/nxg.0000000000000266] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Accepted: 07/31/2018] [Indexed: 11/15/2022]
Abstract
OBJECTIVE The neuroanatomical profile of behavioral variant frontotemporal dementia (bvFTD) suggests a common biological etiology of disease despite disparate pathologic causes; we investigated the genetic underpinnings of this selective regional vulnerability to identify new risk factors for bvFTD. METHODS We used recently developed analytical techniques designed to address the limitations of genome-wide association studies to generate a protein interaction network of 63 bvFTD risk genes. We characterized this network using gene expression data from healthy and diseased human brain tissue, evaluating regional network expression patterns across the lifespan as well as the cell types and biological processes most affected in bvFTD. RESULTS We found that bvFTD network genes show enriched expression across the human lifespan in vulnerable neuronal populations, are implicated in cell signaling, cell cycle, immune function, and development, and are differentially expressed in pathologically confirmed frontotemporal lobar degeneration cases. Five of the genes highlighted by our differential expression analyses, BAIAP2, ERBB3, POU2F2, SMARCA2, and CDC37, appear to be novel bvFTD risk loci. CONCLUSIONS Our findings suggest that the cumulative burden of common genetic variation in an interacting protein network expressed in specific brain regions across the lifespan may influence susceptibility to bvFTD.
Collapse
Affiliation(s)
- Luke W Bonham
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Natasha Z R Steele
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Celeste M Karch
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Claudia Manzoni
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Ethan G Geier
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Natalie Wen
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Aaron Ofori-Kuragu
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Parastoo Momeni
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - John Hardy
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Zachary A Miller
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Christopher P Hess
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Patrick Lewis
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Bruce L Miller
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - William W Seeley
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Sergio E Baranzini
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Rahul S Desikan
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Raffaele Ferrari
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| | - Jennifer S Yokoyama
- Department of Neurology (L.W.B., N.Z.R.S., E.G.G., Z.A.M., B.L.M., W.W.S., J.S.Y.), Memory and Aging Center, University of California, San Francisco; Department of Psychiatry (C.M.K., N.W., A.O.-K.), Washington University, St. Louis, MO; School of Pharmacy (C.M., P.L.), University of Reading, Reading, UK; Laboratory of Neurogenetics (P.M.), Texas Tech University Health Science Center, Lubbock; Department of Molecular Neuroscience (C.M., J.H., P.L., R.F.), UCL Institute of Neurology, London, UK; Department of Radiology and Biomedical Imaging, Neuroradiology Section (C.P.H., R.S.D.), University of California, San Francisco; and Department of Neurology (S.E.B.), University of California, San Francisco
| |
Collapse
|