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Xie ZF, Wang SY, Gao Y, Zhang YD, Han YN, Huang J, Gao MN, Wang CG. Vagus nerve stimulation (VNS) preventing postoperative cognitive dysfunction (POCD): two potential mechanisms in cognitive function. Mol Cell Biochem 2024:10.1007/s11010-024-05091-0. [PMID: 39138750 DOI: 10.1007/s11010-024-05091-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 08/05/2024] [Indexed: 08/15/2024]
Abstract
Postoperative cognitive dysfunction (POCD) impacts a significant number of patients annually, frequently impairing their cognitive abilities and resulting in unfavorable clinical outcomes. Aimed at addressing cognitive impairment, vagus nerve stimulation (VNS) is a therapeutic approach, which was used in many mental disordered diseases, through the modulation of vagus nerve activity. In POCD model, the enhancement of cognition function provided by VNS was shown, demonstrating VNS effect on cognition in POCD. In the present study, we primarily concentrates on elucidating the role of the VNS improving the cognitive function in POCD, via two potential mechanisms: the inflammatory microenvironment and epigenetics. This study provided a theoretical support for the feasibility that VNS can be a potential method to enhance cognition function in POCD.
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Affiliation(s)
- Zi-Feng Xie
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China
- Department of Anesthesiology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
- The First Clinical Medical College, Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
| | - Sheng-Yu Wang
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China
- Graduate College, Chengde Medical College, Chengde, 067000, Hebei, China
| | - Yuan Gao
- Department of Anesthesiology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
- The First Clinical Medical College, Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
| | - Yi-Dan Zhang
- Department of Anesthesiology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
- The First Clinical Medical College, Jinzhou Medical University, Jinzhou, 121000, Liaoning, China
| | - Ya-Nan Han
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China
- Graduate College, Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Jin Huang
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China
- Graduate College, Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Mei-Na Gao
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China
| | - Chun-Guang Wang
- Department of Anesthesiology, The First Central Hospital of Baoding, Northern Great Wall Street 320#, Baoding, 071000, Hebei, China.
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Gonzalez-Gomez R, Legaz A, Moguilner S, Cruzat J, Hernández H, Baez S, Cocchi R, Coronel-Olivero C, Medel V, Tagliazuchi E, Migeot J, Ochoa-Rosales C, Maito MA, Reyes P, Santamaria Garcia H, Godoy ME, Javandel S, García AM, Matallana DL, Avila-Funes JA, Slachevsky A, Behrens MI, Custodio N, Cardona JF, Brusco IL, Bruno MA, Sosa Ortiz AL, Pina-Escudero SD, Takada LT, Resende EDPF, Valcour V, Possin KL, Okada de Oliveira M, Lopera F, Lawlor B, Hu K, Miller B, Yokoyama JS, Gonzalez Campo C, Ibañez A. Educational disparities in brain health and dementia across Latin America and the United States. Alzheimers Dement 2024. [PMID: 39136296 DOI: 10.1002/alz.14085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 05/09/2024] [Accepted: 05/09/2024] [Indexed: 08/22/2024]
Abstract
BACKGROUND Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown. METHODS A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type. RESULTS Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions. DISCUSSION The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research. HIGHLIGHTS Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.
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Affiliation(s)
- Raul Gonzalez-Gomez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibañez, Santiago, Chile
| | - Agustina Legaz
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Sebastián Moguilner
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Josephine Cruzat
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Hernán Hernández
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Sandra Baez
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Universidad de los Andes, Bogotá, D.C., Colombia
| | - Rafael Cocchi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Carlos Coronel-Olivero
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Valparaíso, Chile
| | - Vicente Medel
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Enzo Tagliazuchi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Departamento de Física, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Instituto de Física de Buenos Aires (FIBA -CONICET), Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Joaquín Migeot
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Carolina Ochoa-Rosales
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Marcelo Adrián Maito
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Pablo Reyes
- Instituto de Envejecimiento, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá D.C., Colombia
| | - Hernando Santamaria Garcia
- Instituto de Envejecimiento, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá D.C., Colombia
- Center for Memory and Cognition, Hospital Universitario San Ignacio Bogotá, San Ignacio, Bogotá D.C., Colombia
| | - Maria E Godoy
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Shireen Javandel
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Adolfo M García
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Diana L Matallana
- Instituto de Envejecimiento, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá D.C., Colombia
- Center for Memory and Cognition, Hospital Universitario San Ignacio Bogotá, San Ignacio, Bogotá D.C., Colombia
| | - José Alberto Avila-Funes
- Dirección de Enseñanza, Instituto Nacional de Ciencias Médicas y Nutrición, Salvador Zubirán, Ciudad de México, D.C., México
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Memory and Neuropsychiatric Center (CMYN), Neurology Department, Hospital del Salvador & Faculty of Medicine, University of Chile, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Program - Institute of Biomedical Sciences (ICBM), Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - María I Behrens
- Faculty of Medicine, University of Chile, Santiago, Chile
- Centro de Investigación Clínica Avanzada (CICA), Universidad de Chile, Santiago, Chile
| | - Nilton Custodio
- Unit Cognitive Impairment and Dementia Prevention, Peruvian Institute of Neurosciences, Lima, Peru
| | - Juan F Cardona
- Facultad de Psicología, Universidad del Valle, Cali, Colombia
| | - Ignacio L Brusco
- Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Martín A Bruno
- Instituto de Ciencias Biomédicas, Universidad Católica de Cuyo, San Juan, Argentina
| | - Ana L Sosa Ortiz
- Instituto Nacional de Neurología y Neurocirugía, Ciudad de México, D.C., México
| | - Stefanie D Pina-Escudero
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | | | - Elisa de Paula França Resende
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Victor Valcour
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Katherine L Possin
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Maira Okada de Oliveira
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Cognitive Neurology and Behavioral Unit (GNCC), University of São Paulo, São Paulo, Brazil
| | - Francisco Lopera
- Neurosicence Research Group (GNA), Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Brian Lawlor
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Kun Hu
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Bruce Miller
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Jennifer S Yokoyama
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California, USA
| | - Cecilia Gonzalez Campo
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Agustin Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- Cognitive Neuroscience Center, Universidad de San Andrés, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, University of California, San Francisco, California, USA
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Hüper L, Steinacker P, Polyakova M, Mueller K, Godulla J, Herzig S, Danek A, Engel A, Diehl‐Schmid J, Classen J, Fassbender K, Fliessbach K, Jahn H, Kassubek J, Kornhuber J, Landwehrmeyer B, Lauer M, Obrig H, Oeckl P, Prudlo J, Saur D, Anderl‐Straub S, Synofzik M, Wagner M, Wiltfang J, Winkelmann J, Volk AE, Huppertz H, Otto M, Schroeter ML. Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration - A transdiagnostic study cross-validating atrophy and fluid biomarkers. Alzheimers Dement 2024; 20:4461-4475. [PMID: 38865340 PMCID: PMC11247715 DOI: 10.1002/alz.13863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/22/2024] [Accepted: 03/24/2024] [Indexed: 06/14/2024]
Abstract
INTRODUCTION Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging. METHODS Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry. RESULTS FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects. DISCUSSION Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy. HIGHLIGHTS Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy.
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Ferreira R, Bastos-Leite AJ. Arterial spin labelling magnetic resonance imaging and perfusion patterns in neurocognitive and other mental disorders: a systematic review. Neuroradiology 2024; 66:1065-1081. [PMID: 38536448 PMCID: PMC11150205 DOI: 10.1007/s00234-024-03323-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 02/24/2024] [Indexed: 04/18/2024]
Abstract
We reviewed 33 original research studies assessing brain perfusion, using consensus guidelines from a "white paper" issued by the International Society for Magnetic Resonance in Medicine Perfusion Study Group and the European Cooperation in Science and Technology Action BM1103 ("Arterial Spin Labelling Initiative in Dementia"; https://www.cost.eu/actions/BM1103/ ). The studies were published between 2011 and 2023 and included participants with subjective cognitive decline plus; neurocognitive disorders, including mild cognitive impairment (MCI), Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB) and vascular cognitive impairment (VCI); as well as schizophrenia spectrum disorders, bipolar and major depressive disorders, autism spectrum disorder, attention-deficit/hyperactivity disorder, panic disorder and alcohol use disorder. Hypoperfusion associated with cognitive impairment was the major finding across the spectrum of cognitive decline. Regional hyperperfusion also was reported in MCI, AD, frontotemporal dementia phenocopy syndrome and VCI. Hypoperfused structures found to aid in diagnosing AD included the precunei and adjacent posterior cingulate cortices. Hypoperfused structures found to better diagnose patients with FTLD were the anterior cingulate cortices and frontal regions. Hypoperfusion in patients with DLB was found to relatively spare the temporal lobes, even after correction for partial volume effects. Hyperperfusion in the temporal cortices and hypoperfusion in the prefrontal and anterior cingulate cortices were found in patients with schizophrenia, most of whom were on medication and at the chronic stage of illness. Infratentorial structures were found to be abnormally perfused in patients with bipolar or major depressive disorders. Brain perfusion abnormalities were helpful in diagnosing most neurocognitive disorders. Abnormalities reported in VCI and the remaining mental disorders were heterogeneous and not generalisable.
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Affiliation(s)
- Rita Ferreira
- Faculty of Medicine, University of Porto, Porto, Portugal
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5
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McInvale JJ, Canoll P, Hargus G. Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia. Brain Pathol 2024; 34:e13231. [PMID: 38246596 PMCID: PMC11189780 DOI: 10.1111/bpa.13231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 11/29/2023] [Indexed: 01/23/2024] Open
Abstract
Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-β, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.
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Affiliation(s)
- Julie J. McInvale
- Department of Pathology and Cell BiologyColumbia UniversityNew YorkNew YorkUSA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia UniversityNew YorkNew YorkUSA
- Medical Scientist Training Program, Columbia UniversityNew YorkNew YorkUSA
| | - Peter Canoll
- Department of Pathology and Cell BiologyColumbia UniversityNew YorkNew YorkUSA
| | - Gunnar Hargus
- Department of Pathology and Cell BiologyColumbia UniversityNew YorkNew YorkUSA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia UniversityNew YorkNew YorkUSA
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6
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Fieldhouse JLP, van Paassen DN, van Engelen MPE, De Boer SCM, Hartog WL, Braak S, Schoonmade LJ, Schouws SNTM, Krudop WA, Oudega ML, Mutsaerts HJMM, Teunissen CE, Vijverberg EGB, Pijnenburg YAL. The pursuit for markers of disease progression in behavioral variant frontotemporal dementia: a scoping review to optimize outcome measures for clinical trials. Front Aging Neurosci 2024; 16:1382593. [PMID: 38784446 PMCID: PMC11112081 DOI: 10.3389/fnagi.2024.1382593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/16/2024] [Indexed: 05/25/2024] Open
Abstract
Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by diverse and prominent changes in behavior and personality. One of the greatest challenges in bvFTD is to capture, measure and predict its disease progression, due to clinical, pathological and genetic heterogeneity. Availability of reliable outcome measures is pivotal for future clinical trials and disease monitoring. Detection of change should be objective, clinically meaningful and easily assessed, preferably associated with a biological process. The purpose of this scoping review is to examine the status of longitudinal studies in bvFTD, evaluate current assessment tools and propose potential progression markers. A systematic literature search (in PubMed and Embase.com) was performed. Literature on disease trajectories and longitudinal validity of frequently-used measures was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. Evaluating current longitudinal data, we propose an adaptive battery, combining a set of sensitive clinical, neuroimaging and fluid markers, adjusted for genetic and sporadic variants, for adequate detection of disease progression in bvFTD.
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Affiliation(s)
- Jay L. P. Fieldhouse
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Dirk N. van Paassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Marie-Paule E. van Engelen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Sterre C. M. De Boer
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Willem L. Hartog
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Simon Braak
- Department of Psychiatry, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands
| | | | - Sigfried N. T. M. Schouws
- Department of Psychiatry, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- GGZ inGeest Mental Health Care, Amsterdam, Netherlands
| | - Welmoed A. Krudop
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- GGZ inGeest Mental Health Care, Amsterdam, Netherlands
| | - Mardien L. Oudega
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Department of Psychiatry, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands
- GGZ inGeest Mental Health Care, Amsterdam, Netherlands
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Charlotte E. Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Everard G. B. Vijverberg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Yolande A. L. Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
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7
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Giannini LAA, Boers RG, van der Ende EL, Poos JM, Jiskoot LC, Boers JB, van IJcken WFJ, Dopper EG, Pijnenburg YAL, Seelaar H, Meeter LH, van Rooij JGJ, Scheper W, Gribnau J, van Swieten JC. Distinctive cell-free DNA methylation characterizes presymptomatic genetic frontotemporal dementia. Ann Clin Transl Neurol 2024; 11:744-756. [PMID: 38481040 DOI: 10.1002/acn3.51997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/01/2023] [Accepted: 12/27/2023] [Indexed: 03/27/2024] Open
Abstract
OBJECTIVE Methylation of plasma cell-free DNA (cfDNA) has potential as a marker of brain damage in neurodegenerative diseases such as frontotemporal dementia (FTD). Here, we study methylation of cfDNA in presymptomatic and symptomatic carriers of genetic FTD pathogenic variants, next to healthy controls. METHODS cfDNA was isolated from cross-sectional plasma of 10 presymptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), 10 symptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), and 9 healthy controls. Genome-wide methylation of cfDNA was determined using a high-resolution sequencing technique (MeD-seq). Cumulative scores based on the identified differentially methylated regions (DMRs) were estimated for presymptomatic carriers (vs. controls and symptomatic carriers), and reevaluated in a validation cohort (8 presymptomatic: 3 C9orf72, 3 GRN, and 2 MAPT; 26 symptomatic: 7 C9orf72, 6 GRN, 12 MAPT, and 1 TARDBP; 13 noncarriers from genetic FTD families). RESULTS Presymptomatic carriers showed a distinctive methylation profile compared to healthy controls and symptomatic carriers. Cumulative DMR scores in presymptomatic carriers enabled to significantly differentiate presymptomatic carriers from healthy controls (p < 0.001) and symptomatic carriers (p < 0.001). In the validation cohort, these scores differentiated presymptomatic carriers from symptomatic carriers (p ≤ 0.007) only. Transcription-start-site methylation in presymptomatic carriers, generally associated with gene downregulation, was enriched for genes involved in ubiquitin-dependent processes, while gene body methylation, generally associated with gene upregulation, was enriched for genes involved in neuronal cell processes. INTERPRETATION A distinctive methylation profile of cfDNA characterizes the presymptomatic stage of genetic FTD, and could reflect neuronal death in this stage.
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Affiliation(s)
- Lucia A A Giannini
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ruben G Boers
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Emma L van der Ende
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jackie M Poos
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lize C Jiskoot
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joachim B Boers
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Wilfred F J van IJcken
- Erasmus Center for Biomics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Elise G Dopper
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC location Vumc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Harro Seelaar
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lieke H Meeter
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jeroen G J van Rooij
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Wiep Scheper
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Human Genetics, Vrije Universiteit, Amsterdam UMC location Vumc, Amsterdam, The Netherlands
| | - Joost Gribnau
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
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8
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Haeger A, Muising J, Romanzetti S, Fimm B, Matz O, Schulz JB, Heim S, Reetz K. Communicative impairment and its neural correlates in Alzheimer's disease and frontotemporal dementia. Brain Behav 2024; 14:e3420. [PMID: 38494763 PMCID: PMC10945087 DOI: 10.1002/brb3.3420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 03/19/2024] Open
Abstract
OBJECTIVE Communication skills can deteriorate in neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD); however, their clinical assessment and treatment in patient care can be challenging. In the present study, we aimed to quantify the distinctive communication resources and barriers reported by patients and their relatives in AD and FTD and associated these communicative characteristics with clinical parameters, such as the degree of cognitive impairment and atrophy in language-associated brain areas. METHODS We assessed self-reported communication barriers and resources in 33 individuals with AD and FTD through an interview on daily-life communication, using the Aachener KOMPASS questionnaire. We correlated reported communication barriers and resources with atrophy from high-resolution 3T brain magnetic resonance imaging, neuropsychological assessment, and neurodegenerative markers from cerebrospinal fluid. RESULTS Communicative impairment was higher in FTD compared to AD. Increased reported communication barriers in our whole sample were associated with the atrophy rate in the left middle temporal lobe, a critical site within the neuronal language network, and with depressive symptoms as well as the semantic word fluency from neuropsychological assessment. The best model for prediction of communicative impairment included the diagnosis (AD or FTD), semantic word fluency, and depressive symptoms. CONCLUSIONS Our study demonstrates that communication barriers and resources can be successfully assessed via a structured interview based on self-report and report of patients' relatives in practice and are reflected in neuroimaging specific for AD and FTD as well as in further clinical parameters specific for these neurodegenerative diseases. This can potentially open new treatment options for clinical practice and patient care.
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Affiliation(s)
- Alexa Haeger
- Department of NeurologyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and NeuroimagingForschungszentrum Jülich GmbH and RWTH Aachen UniversityAachenGermany
| | - Janka Muising
- Department of NeurologyRWTH Aachen UniversityAachenGermany
| | - Sandro Romanzetti
- Department of NeurologyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and NeuroimagingForschungszentrum Jülich GmbH and RWTH Aachen UniversityAachenGermany
| | - Bruno Fimm
- Department of NeurologyRWTH Aachen UniversityAachenGermany
| | - Oliver Matz
- Department of NeurologyRWTH Aachen UniversityAachenGermany
| | - Jörg B. Schulz
- Department of NeurologyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and NeuroimagingForschungszentrum Jülich GmbH and RWTH Aachen UniversityAachenGermany
| | - Stefan Heim
- Department of NeurologyRWTH Aachen UniversityAachenGermany
- Institute of Neuroscience and Medicine (INM‐1)Research Centre JülichJülichGermany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| | - Kathrin Reetz
- Department of NeurologyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and NeuroimagingForschungszentrum Jülich GmbH and RWTH Aachen UniversityAachenGermany
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9
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Matsuura S, Tatebe H, Higuchi M, Tokuda T. Validation of a newly developed immunoassay for TDP-43 in human plasma. Heliyon 2024; 10:e24672. [PMID: 38304795 PMCID: PMC10831789 DOI: 10.1016/j.heliyon.2024.e24672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 11/27/2023] [Accepted: 01/11/2024] [Indexed: 02/03/2024] Open
Abstract
The level of TAR DNA-binding protein 43 (TDP-43) in human blood was reported to have potential for use as a specific fluid biomarker, which represents disease-specific pathologies, for TDP-43 proteinopathies, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), which involves the aggregation and deposition of TDP-43 in the nervous system. However, at present, no reliable immunoassay can precisely quantify TDP-43 in human plasma and detect the difference in plasma TDP-43 levels between patients with ALS and controls. We recently developed a novel ultrasensitive immunoassay to quantify TDP-43 in human plasma, and in this study, we analytically validated this assay for application as a diagnostic biomarker for TDP-43 proteinopathies. The novel TDP-43 assay was assessed for the limit of detection, lower limit of quantification, intra- and interassay variation, linearity, parallelism, and analytical spike recoveries. Additionally, 17 pilot plasma samples obtained from patients with ALS and age-matched controls were analyzed using the assay. Our novel TDP-43 assay showed sufficient analytical performance to quantify TDP-43 in human plasma, with high sensitivity (LOD and LLOQ of 0.109 and 0.759 pg/mL, respectively) and high intra- and interassay precision (%CV) below 15 %. The experimental results for spike recovery, parallelism, and dilution linearity were also acceptable. In addition, despite a small sample size, significant differences in the plasma levels of TDP-43 were found between patients with ALS and controls (ALS, 66.63 ± 20.52 pg/mL; control, 42.70 ± 23.06 pg/mL, p = 0.0330). These results support that our novel TDP-43 assay is a reliable and innovative method for the quantification of TDP-43 in human plasma and can be a potential blood-based biomarker for the diagnosis of TDP-43 proteinopathies. Further large-scale studies are warranted to validate its usefulness.
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Affiliation(s)
- Sayo Matsuura
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Harutsugu Tatebe
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Makoto Higuchi
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Takahiko Tokuda
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
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10
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Pena E, San Martin-Salamanca R, El Alam S, Flores K, Arriaza K. Tau Protein Alterations Induced by Hypobaric Hypoxia Exposure. Int J Mol Sci 2024; 25:889. [PMID: 38255962 PMCID: PMC10815386 DOI: 10.3390/ijms25020889] [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: 11/15/2023] [Revised: 12/21/2023] [Accepted: 01/05/2024] [Indexed: 01/24/2024] Open
Abstract
Tauopathies are a group of neurodegenerative diseases whose central feature is dysfunction of the microtubule-associated protein tau (MAPT). Although the exact etiology of tauopathies is still unknown, it has been hypothesized that their onset may occur up to twenty years before the clear emergence of symptoms, which has led to questions about whether the prognosis of these diseases can be improved by, for instance, targeting the factors that influence tauopathy development. One such factor is hypoxia, which is strongly linked to Alzheimer's disease because of its association with obstructive sleep apnea and has been reported to affect molecular pathways related to the dysfunction and aggregation of tau proteins and other biomarkers of neurological damage. In particular, hypobaric hypoxia exposure increases the activation of several kinases related to the hyperphosphorylation of tau in neuronal cells, such as ERK, GSK3β, and CDK5. In addition, hypoxia also increases the levels of inflammatory molecules (IL-β1, IL-6, and TNF-α), which are also associated with neurodegeneration. This review discusses the many remaining questions regarding the influence of hypoxia on tauopathies and the contribution of high-altitude exposure to the development of these diseases.
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Affiliation(s)
| | | | - Samia El Alam
- High Altitude Medicine Research Center (CEIMA), Arturo Prat University, Iquique 1110939, Chile; (E.P.); (R.S.M.-S.); (K.F.); (K.A.)
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11
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Ducharme S, Pijnenburg Y, Rohrer JD, Huey E, Finger E, Tatton N. Identifying and Diagnosing TDP-43 Neurodegenerative Diseases in Psychiatry. Am J Geriatr Psychiatry 2024; 32:98-113. [PMID: 37741764 PMCID: PMC11270911 DOI: 10.1016/j.jagp.2023.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/02/2023] [Accepted: 08/24/2023] [Indexed: 09/25/2023]
Abstract
Neuropsychiatric symptoms (NPS) are common manifestations of neurodegenerative disorders and are often early signs of those diseases. Among those neurodegenerative diseases, TDP-43 proteinopathies are an increasingly recognized cause of early neuropsychiatric manifestations. TDP-43-related diseases include frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and Limbic-Predominant Age-Related TDP-43 Encephalopathy (LATE). The majority of TDP-43-related diseases are sporadic, but a significant proportion is hereditary, with progranulin (GRN) mutations and C9orf72 repeat expansions as the most common genetic etiologies. Studies reveal that NPS can be the initial manifestation of those diseases or can complicate disease course, but there is a lack of awareness among clinicians about TDP-43-related diseases, which leads to common diagnostic mistakes or delays. There is also emerging evidence that TDP-43 accumulations could play a role in late-onset primary psychiatric disorders. In the absence of robust biomarkers for TDP-43, the diagnosis remains primarily based on clinical assessment and neuroimaging. Given the association with psychiatric symptoms, clinical psychiatrists have a key role in the early identification of patients with TDP-43-related diseases. This narrative review provides a comprehensive overview of the pathobiology of TDP-43, resulting clinical presentations, and associated neuropsychiatric manifestations to help guide clinical practice.
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Affiliation(s)
- Simon Ducharme
- Department of Psychiatry (SD), Douglas Mental Health University Institute, McGill University, Montreal, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (YP), Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease (JDR), UCL Queen Square Institute of Neurology, London, UK
| | - Edward Huey
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Psychiatry (EH), Columbia University, New York, NY
| | - Elizabeth Finger
- London Health Sciences Centre Parkwood Institute (EF), London, ON, Canada
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Andriuta D, Wiener E, Perron A, Ouin E, Masmoudi I, Thibaut W, Martin J, Roussel M, Constans JM, Aarabi A, Godefroy O. Neuroimaging determinants of cognitive impairment in the memory clinic: how important is the vascular burden? J Neurol 2024; 271:504-518. [PMID: 37777991 DOI: 10.1007/s00415-023-12009-1] [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: 05/10/2023] [Revised: 09/14/2023] [Accepted: 09/15/2023] [Indexed: 10/03/2023]
Abstract
While neurodegenerative and vascular neurocognitive disorder (NCD) often co-occur, the contribution of vascular lesions, especially stroke lesions identified on MRI, to global cognition in a real-life memory clinic population remains unclear. The main objective of this retrospective study was to determine NCD neuroimaging correlates: the GM atrophy pattern and vascular lesions (especially stroke lesion localization by voxel-based lesion-symptom mapping, VLSM) in a memory clinic. We included 336 patients with mild or major NCD who underwent cerebral MRI and a neuropsychological assessment. The GM atrophy pattern (obtained by voxel-based morphometry, VBM) and the stroke lesion localization (obtained by VLSM) associated with G5 z-score (a global cognitive score), were included as independent variables with other neuroimaging and clinical indices in a stepwise linear regression model. The mean age was 70.3 years and the mean MMSE score 21.3. On MRI, 75 patients had at least one stroke lesion. The G 5 z-score was associated with GM density in the pattern selected by the VBM analysis (R2 variation = 0.166, p < 0.001) and the presence of a stroke lesion in the region selected by the VSLM analysis (mainly in the right frontal region; R2 variation = 0.018, p = 0.008). The interaction between the two factors was insignificant (p = 0.374). In conclusion, in this first study combining VBM and VLSM analysis in a memory clinic, global cognition was associated with a specific GM atrophy pattern and the presence of a stroke lesion mainly in the right frontal region.
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Affiliation(s)
- Daniela Andriuta
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France.
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France.
| | - Emmanuel Wiener
- Department of Neurology, Versailles - Le Chesnay Medical Center, Le Chesnay-Rocquencourt, France
| | - Alexandre Perron
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
| | - Elisa Ouin
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
| | - Ines Masmoudi
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
| | - William Thibaut
- Department of Neurology, La Reunion University Medical Center, Site South Saint-Pierre, Saint-Pierre, La Reunion, France
| | - Jeanne Martin
- Department of Neurology, Bretagne Atlantique Medical Center, Vannes, France
| | - Martine Roussel
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
| | - Jean-Marc Constans
- Department of Radiology, Amiens University Medical Center, Amiens, France
| | - Ardalan Aarabi
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
| | - Olivier Godefroy
- Department of Neurology, Amiens University Medical Center, Amiens University Hospital, 80054, Amiens, France
- Laboratoire de Neurosciences Fonctionnelles Et Pathologies (UR UPJV 4559), Jules Verne University of Picardy, Amiens, France
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Suh A, Ong J, Kamran SA, Waisberg E, Paladugu P, Zaman N, Sarker P, Tavakkoli A, Lee AG. Retina Oculomics in Neurodegenerative Disease. Ann Biomed Eng 2023; 51:2708-2721. [PMID: 37855949 DOI: 10.1007/s10439-023-03365-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 09/05/2023] [Indexed: 10/20/2023]
Abstract
Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.
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Affiliation(s)
- Alex Suh
- Tulane University School of Medicine, New Orleans, LA, USA.
| | - Joshua Ong
- Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sharif Amit Kamran
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Ethan Waisberg
- University College Dublin School of Medicine, Belfield, Dublin, Ireland
| | - Phani Paladugu
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Nasif Zaman
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Prithul Sarker
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Alireza Tavakkoli
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Andrew G Lee
- Center for Space Medicine, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, 6560 Fannin St #450, Houston, TX, 77030, USA
- The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, TX, USA
- Departments of Ophthalmology, Neurology and Neurosurgery, Weill Cornell Medicine, New York, NY, USA
- Department of Ophthalmology, University of Texas Medical Branch, Galveston, TX, USA
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Texas A&M College of Medicine, Bryan, TX, USA
- Department of Ophthalmology, The University of Iowa Hospitals and Clinics, Iowa City, IA, USA
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14
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Liu Y, Yang W, Xue J, Chen J, Liu S, Zhang S, Zhang X, Gu X, Dong Y, Qiu P. Neuroinflammation: The central enabler of postoperative cognitive dysfunction. Biomed Pharmacother 2023; 167:115582. [PMID: 37748409 DOI: 10.1016/j.biopha.2023.115582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/21/2023] [Accepted: 09/22/2023] [Indexed: 09/27/2023] Open
Abstract
The proportion of advanced age patients undergoing surgical procedures is on the rise owing to advancements in surgical and anesthesia technologies as well as an overall aging population. As a complication of anesthesia and surgery, older patients frequently suffer from postoperative cognitive dysfunction (POCD), which may persist for weeks, months or even longer. POCD is a complex pathological process involving multiple pathogenic factors, and its mechanism is yet unclear. Potential theories include inflammation, deposition of pathogenic proteins, imbalance of neurotransmitters, and chronic stress. The identification, prevention, and treatment of POCD are still in the exploratory stages owing to the absence of standardized diagnostic criteria. Undoubtedly, comprehending the development of POCD remains crucial in overcoming the illness. Neuroinflammation is the leading hypothesis and a crucial component of the pathological network of POCD and may have complex interactions with other mechanisms. In this review, we discuss the possible ways in which surgery and anesthesia cause neuroinflammation and investigate the connection between neuroinflammation and the development of POCD. Understanding these mechanisms may likely ensure that future treatment options of POCD are more effective.
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Affiliation(s)
- Yang Liu
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning province, China
| | - Wei Yang
- Department of Infectious Disease, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning province, China
| | - Jinqi Xue
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning province, China
| | - Juntong Chen
- Zhejiang University School of Medicine, Hangzhou 311121, Zhejiang province, China
| | - Shiqing Liu
- Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
| | - Shijie Zhang
- Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
| | - Xiaohui Zhang
- Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
| | - Xi Gu
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning province, China.
| | - Youjing Dong
- Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China.
| | - Peng Qiu
- Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China.
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Vinceti G, Carbone C, Gallingani C, Fiondella L, Salemme S, Zucchi E, Martinelli I, Gianferrari G, Tondelli M, Mandrioli J, Chiari A, Zamboni G. The association between lifelong personality and clinical phenotype in the FTD-ALS spectrum. Front Neurosci 2023; 17:1248622. [PMID: 37859765 PMCID: PMC10582748 DOI: 10.3389/fnins.2023.1248622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/31/2023] [Indexed: 10/21/2023] Open
Abstract
Introduction Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two phenotypes of the same neurodegenerative disease, the FTD-ALS spectrum. What determines the development of one rather than the other phenotype is still unknown. Based on the clinical observation that patients' personality seems to differ between the two phenotypes, i.e., ALS patients tend to display kind, prosocial behaviors whereas FTD patients tend to present anti-social behaviors, and that these traits are often reported as pre-existing the disease onset by caregivers, we set up to study experimentally patients' personality in their premorbid life. Methods We first tested for differences between groups, then tested the association between premorbid personality and current functional organization of the brain. Premorbid personality of a cohort of forty patients, 27 FTD and 13 ALS, was explored through the NEO Personality Inventory 3 (NEO-PI-3), which analyses the five main personality factors, completed by the caregiver with reference to patient's personality 20 years before symptoms onset (premorbid). A subgroup of patients underwent a brain MRI including structural and resting-state functional MRI (rsfMRI). Results A significant difference between FTD and ALS in premorbid personality emerged in the Openness (133.92 FTD vs. 149.84 ALS, p = 0.01) and Extraversion (136.55 FTD vs. 150.53 ALS, p = 0.04) factors. This suggests that ALS patients had been, in their premorbid life, more open to new experiences, more sociable and optimistic than FTD patients. They also showed greater functional connectivity than both FTD and a control group in the Salience resting state network, over and above differences in gray matter atrophy. Finally, there was a positive correlation between premorbid Openness and functional connectivity in the Salience network across all patients, suggesting a possible association between premorbid personality and current functional organization of the brain, irrespective of the degree of atrophy. Discussion Our proof-of-concept results suggest that premorbid personality may eventually predispose to the development of one, rather than the other, phenotype in the FTD-ALS spectrum.
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Affiliation(s)
- Giulia Vinceti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Chiara Carbone
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Chiara Gallingani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Luigi Fiondella
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Simone Salemme
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Elisabetta Zucchi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Ilaria Martinelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Giulia Gianferrari
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Department of Primary Care, Azienda Unità Sanitaria Locale di Modena, Modena, Italy
| | - Jessica Mandrioli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Annalisa Chiari
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
| | - Giovanna Zamboni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Ospedale Civile Baggiovara, Azienda Ospedaliero Universitaria di Modena, Modena, Italy
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Ghirelli A, Tafuri B, Urso D, Milella G, De Blasi R, Nigro S, Logroscino G. Cortical signature of depressive symptoms in frontotemporal dementia: A surface-based analysis. Ann Clin Transl Neurol 2023; 10:1704-1713. [PMID: 37522381 PMCID: PMC10578898 DOI: 10.1002/acn3.51860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 08/01/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Depressive symptoms are frequently reported in patients affected by frontotemporal dementia (FTD). At structural MRI, cortical features of depressed FTD patients have been poorly described. Our objective was to investigate correlations between cortical measures and depression severity in FTD patients. METHODS Data were obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) database. We included 98 controls and 92 FTD patients, n = 38 behavioral variant FTD (bvFTD), n = 26 non-fluent variant Primary Progressive Aphasia (nfvPPA), and n = 28 semantic variant Primary Progressive Aphasia (svPPA). Patients underwent clinical and cognitive evaluations, as well as a 3D T1-weighted MRI on a 3 Tesla scanner (Siemens, Trio Tim system). Depression was evaluated by means of Geriatric Depression Scale (GDS). Surface-based analysis was performed on T1-weighted images to evaluate cortical thickness, a measure of gray matter integrity, and local gyrification index (lGI), a quantitative metric of cortical folding. RESULTS Patients affected by svPPA were more depressed than controls at NPI and depression severity at GDS was higher in svPPA and bvFTD. Severity of depression correlated with a decrease in lGI in left precentral and superior frontal gyrus, supramarginal and postcentral gyrus and right precentral, supramarginal, superior parietal and superior frontal gyri. Furthermore, depression severity correlated positively with cortical thickness in the left medial orbitofrontal cortex. DISCUSSION We found that lGI was associated with depressive symptoms over brain regions involved in the pathophysiology of major depressive disorder. This finding provides novel insights into the mechanisms underlying psychiatric symptoms in FTD.
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Affiliation(s)
- Alma Ghirelli
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Department of Translational Biomedicine and Neuroscience (DiBraiN)University of Bari ‘Aldo Moro’BariItaly
| | - Benedetta Tafuri
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Department of Translational Biomedicine and Neuroscience (DiBraiN)University of Bari ‘Aldo Moro’BariItaly
| | - Daniele Urso
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Department of Neurosciences, King's College LondonInstitute of Psychiatry, Psychology and NeuroscienceLondonUK
| | - Giammarco Milella
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Department of Translational Biomedicine and Neuroscience (DiBraiN)University of Bari ‘Aldo Moro’BariItaly
| | - Roberto De Blasi
- Department of Diagnostic ImagingPia Fondazione di Culto e Religione “Card. G. Panico”LecceItaly
| | - Salvatore Nigro
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Institute of Nanotechnology (NANOTEC), National Research CouncilLecceItaly
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in NeurologyUniversity of Bari ‘Aldo Moro’, “Pia Fondazione Cardinale G. Panico”LecceItaly
- Department of Diagnostic ImagingPia Fondazione di Culto e Religione “Card. G. Panico”LecceItaly
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Assogna M, Premi E, Gazzina S, Benussi A, Ashton NJ, Zetterberg H, Blennow K, Gasparotti R, Padovani A, Tadayon E, Romanella S, Sprugnoli G, Pascual-Leone A, Di Lorenzo F, Koch G, Borroni B, Santarnecchi E. Association of Choroid Plexus Volume With Serum Biomarkers, Clinical Features, and Disease Severity in Patients With Frontotemporal Lobar Degeneration Spectrum. Neurology 2023; 101:e1218-e1230. [PMID: 37500561 PMCID: PMC10516270 DOI: 10.1212/wnl.0000000000207600] [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: 10/27/2022] [Accepted: 05/15/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Choroid plexus (ChP) is emerging as a key brain structure in the pathophysiology of neurodegenerative disorders. In this observational study, we investigated ChP volume in a large cohort of patients with frontotemporal lobar degeneration (FTLD) spectrum to explore a possible link between ChP volume and other disease-specific biomarkers. METHODS Participants included patients meeting clinical criteria for a probable syndrome in the FTLD spectrum. Structural brain MRI imaging, serum neurofilament light (NfL), serum phosphorylated-Tau181 (p-Tau181), and cognitive and behavioral data were collected. MRI ChP volumes were obtained from an ad-hoc segmentation model based on a Gaussian Mixture Models algorithm. RESULTS Three-hundred and sixteen patients within FTLD spectrum were included in this study, specifically 135 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD), 75 primary progressive aphasia, 46 progressive supranuclear palsy, and 60 corticobasal syndrome. In addition, 82 age-matched healthy participants were recruited as controls (HCs). ChP volume was significantly larger in patients with FTLD compared with HC, across the clinical subtype. Moreover, we found a significant difference in ChP volume between HC and patients stratified for disease-severity based on CDR plus NACC FTLD, including patients at very early stage of the disease. Interestingly, ChP volume correlated with serum NfL, cognitive/behavioral deficits, and with patterns of cortical atrophy. Finally, ChP volume seemed to discriminate HC from patients with FTLD better than other previously identified brain structure volumes. DISCUSSION Considering the clinical, pathologic, and genetic heterogeneity of the disease, ChP could represent a potential biomarker across the FTLD spectrum, especially at the early stage of disease. Further longitudinal studies are needed to establish its role in disease onset and progression. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that choroid plexus volume, as measured on MRI scan, can assist in differentiating patients with FTLD from healthy controls and in characterizing disease severity.
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Affiliation(s)
- Martina Assogna
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Enrico Premi
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Stefano Gazzina
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Alberto Benussi
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Nicholas J Ashton
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Henrik Zetterberg
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Kaj Blennow
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Roberto Gasparotti
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Alessandro Padovani
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Ehsan Tadayon
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Sara Romanella
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Giulia Sprugnoli
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Alvaro Pascual-Leone
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Francesco Di Lorenzo
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Giacomo Koch
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Barbara Borroni
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy
| | - Emiliano Santarnecchi
- From the Precision Neuroscience & Neuromodulation Program (M.A., S.R., G.S., E.S.), Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Non-Invasive Brain Stimulation Unit (M.A., F.D.L., G.K.), Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS; Memory Clinic (M.A.), Department of Systems Medicine, University of Tor Vergata, Rome; Neurology Unit (E.P., S.G., A.B., A.P., B.B.), Department of Clinical and Experimental Sciences, University of Brescia, Italy; Institute of Neuroscience and Physiology (N.J.A.), Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg; Wallenberg Centre for Molecular and Translational Medicine (N.J.A.), University of Gothenburg, Mӧlndal, Sweden; King's College London (N.J.A.), Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation (N.J.A.), United Kingdom; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z., K.B.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z.), London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, Hong Kong, China; Neuroradiology Unit (R.G.), University of Brescia, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation (E.T.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine (G.S.), Surgery and Neuroscience, Siena Brain Investigation & Neuromodulation Laboratory, University of Siena, Siena, Italy; Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife (A.P.-L.); Department of Neurology (A.P.-L.), Harvard MedicalSchool, Boston, MA, USA; and Department of Neuroscience and Rehabilitation (G.K.), University of Ferrara, Italy.
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18
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Giannini LAA, Seelaar H, van der Ende EL, Poos JM, Jiskoot LC, Dopper EGP, Pijnenburg YAL, Willemse EAJ, Vermunt L, Teunissen CE, van Swieten JC, Meeter LH. Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia. Neurology 2023; 101:e1069-e1082. [PMID: 37491327 PMCID: PMC10491440 DOI: 10.1212/wnl.0000000000207581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 05/10/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD. METHODS In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (>3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline. RESULTS We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p < 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p < 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p < 0.001), but conversion-free follow-up time varied greatly across participants. DISCUSSION NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.
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Affiliation(s)
- Lucia A A Giannini
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Harro Seelaar
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Emma L van der Ende
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Jackie M Poos
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lize C Jiskoot
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Elise G P Dopper
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Yolande A L Pijnenburg
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Eline A J Willemse
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lisa Vermunt
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Charlotte E Teunissen
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - John C van Swieten
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands
| | - Lieke H Meeter
- From the Department of Neurology (L.A.A.G., H.S., J.M.P., L.C.J., E.G.P.D., J.C.S., L.H.M.), Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam; Amsterdam Neuroscience (E.L.E., Y.A.L.P., E.A.J.W., L.V., C.E.T.), Neurodegeneration; Neurochemistry Laboratory (E.L.E., E.A.J.W., L.V., C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit; and Alzheimer Center Amsterdam (Y.A.L.P.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, The Netherlands.
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Grossman M, Seeley WW, Boxer AL, Hillis AE, Knopman DS, Ljubenov PA, Miller B, Piguet O, Rademakers R, Whitwell JL, Zetterberg H, van Swieten JC. Frontotemporal lobar degeneration. Nat Rev Dis Primers 2023; 9:40. [PMID: 37563165 DOI: 10.1038/s41572-023-00447-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/12/2023] [Indexed: 08/12/2023]
Abstract
Frontotemporal lobar degeneration (FTLD) is one of the most common causes of early-onset dementia and presents with early social-emotional-behavioural and/or language changes that can be accompanied by a pyramidal or extrapyramidal motor disorder. About 20-25% of individuals with FTLD are estimated to carry a mutation associated with a specific FTLD pathology. The discovery of these mutations has led to important advances in potentially disease-modifying treatments that aim to slow progression or delay disease onset and has improved understanding of brain functioning. In both mutation carriers and those with sporadic disease, the most common underlying diagnoses are linked to neuronal and glial inclusions containing tau (FTLD-tau) or TDP-43 (FTLD-TDP), although 5-10% of patients may have inclusions containing proteins from the FUS-Ewing sarcoma-TAF15 family (FTLD-FET). Biomarkers definitively identifying specific pathological entities in sporadic disease have been elusive, which has impeded development of disease-modifying treatments. Nevertheless, disease-monitoring biofluid and imaging biomarkers are becoming increasingly sophisticated and are likely to serve as useful measures of treatment response during trials of disease-modifying treatments. Symptomatic trials using novel approaches such as transcranial direct current stimulation are also beginning to show promise.
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Affiliation(s)
- Murray Grossman
- Department of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | - William W Seeley
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA.
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA.
| | - Adam L Boxer
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Peter A Ljubenov
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Bruce Miller
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Olivier Piguet
- School of Psychology and Brain and Mind Center, University of Sydney, Sydney, New South Wales, Australia
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Antwerp, Belgium
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The University of Gothenburg, Mölndal, Sweden
- Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
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20
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Magen I, Yacovzada NS, Warren JD, Heller C, Swift I, Bobeva Y, Malaspina A, Rohrer JD, Fratta P, Hornstein E. microRNA-based predictor for diagnosis of frontotemporal dementia. Neuropathol Appl Neurobiol 2023; 49:e12916. [PMID: 37317649 DOI: 10.1111/nan.12916] [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: 01/06/2023] [Revised: 04/28/2023] [Accepted: 06/02/2023] [Indexed: 06/16/2023]
Abstract
AIMS This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis. METHODS We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls). RESULTS On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases. CONCLUSIONS The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.
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Affiliation(s)
- Iddo Magen
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Nancy-Sarah Yacovzada
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Carolin Heller
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Imogen Swift
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Yoana Bobeva
- Centre for Neuroscience and Trauma, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Andrea Malaspina
- Centre for Neuroscience and Trauma, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Pietro Fratta
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Eran Hornstein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
- Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
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21
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Hu F, Chen AA, Horng H, Bashyam V, Davatzikos C, Alexander-Bloch A, Li M, Shou H, Satterthwaite TD, Yu M, Shinohara RT. Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization. Neuroimage 2023; 274:120125. [PMID: 37084926 PMCID: PMC10257347 DOI: 10.1016/j.neuroimage.2023.120125] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/12/2023] [Accepted: 04/19/2023] [Indexed: 04/23/2023] Open
Abstract
Magnetic resonance imaging and computed tomography from multiple batches (e.g. sites, scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to obtain new insights into the human brain. However, significant confounding due to batch-related technical variation, called batch effects, is present in this data; direct application of downstream analyses to the data may lead to biased results. Image harmonization methods seek to remove these batch effects and enable increased generalizability and reproducibility of downstream results. In this review, we describe and categorize current approaches in statistical and deep learning harmonization methods. We also describe current evaluation metrics used to assess harmonization methods and provide a standardized framework to evaluate newly-proposed methods for effective harmonization and preservation of biological information. Finally, we provide recommendations to end-users to advocate for more effective use of current methods and to methodologists to direct future efforts and accelerate development of the field.
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Affiliation(s)
- Fengling Hu
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States.
| | - Andrew A Chen
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Hannah Horng
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Vishnu Bashyam
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, United States
| | - Mingyao Li
- Statistical Center for Single-Cell and Spatial Genomics, Perelman School of Medicine, University of Pennsylvania, United States
| | - Haochang Shou
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; The Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States
| | - Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, United States
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
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22
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Korbmacher M, de Lange AM, van der Meer D, Beck D, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Brain-wide associations between white matter and age highlight the role of fornix microstructure in brain ageing. Hum Brain Mapp 2023; 44:4101-4119. [PMID: 37195079 PMCID: PMC10258541 DOI: 10.1002/hbm.26333] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/16/2023] [Accepted: 04/26/2023] [Indexed: 05/18/2023] Open
Abstract
Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion approaches, we analyzed UK Biobank diffusion magnetic resonance imaging (dMRI) data across midlife and older age (N = 35,749, 44.6-82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities, and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.
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Affiliation(s)
- Max Korbmacher
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- Mohn Medical Imaging and Visualisation Center (MMIV)BergenNorway
| | - Ann Marie de Lange
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- Department of PsychiatryUniversity of OxfordOxfordUK
- LREN, Centre for Research in Neurosciences–Department of Clinical NeurosciencesCHUV and University of LausanneLausanneSwitzerland
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- Faculty of Health, Medicine and Life SciencesMaastricht UniversityMaastrichtNetherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- Department of Psychiatric Research, Diakonhjemmet HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Eli Eikefjord
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
- Mohn Medical Imaging and Visualisation Center (MMIV)BergenNorway
| | - Arvid Lundervold
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
- Mohn Medical Imaging and Visualisation Center (MMIV)BergenNorway
- Department of RadiologyHaukeland University HospitalBergenNorway
- Department of BiomedicineUniversity of BergenBergenNorway
| | - Ole A. Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | - Lars T. Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | - Ivan I. Maximov
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
- NORMENT Centre for Psychosis Research, Division of Mental Health and AddictionUniversity of Oslo and Oslo University HospitalOsloNorway
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23
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Whiteside DJ, Malpetti M, Jones PS, Ghosh BCP, Coyle‐Gilchrist I, van Swieten JC, Seelaar H, Jiskoot L, Borroni B, Sanchez‐Valle R, Moreno F, Laforce R, Graff C, Synofzik M, Galimberti D, Masellis M, Tartaglia MC, Finger E, Vandenberghe R, de Mendonça A, Tagliavini F, Butler CR, Santana I, Ber IL, Gerhard A, Ducharme S, Levin J, Danek A, Otto M, Sorbi S, Pasquier F, Bouzigues A, Russell LL, Rohrer JD, Rowe JB, Rittman T. Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia. Alzheimers Dement 2023; 19:1947-1962. [PMID: 36377606 PMCID: PMC7614527 DOI: 10.1002/alz.12824] [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: 07/05/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD). METHODS For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression. RESULTS We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants. DISCUSSION Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion. HIGHLIGHTS We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.
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Affiliation(s)
- David J. Whiteside
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
| | - Maura Malpetti
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
| | - P. Simon Jones
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
| | - Boyd C. P. Ghosh
- Wessex Neurological CentreUniversity Hospital SouthamptonSouthamptonUK
| | | | | | - Harro Seelaar
- Department of NeurologyErasmus Medical CentreRotterdamNetherlands
| | - Lize Jiskoot
- Department of NeurologyErasmus Medical CentreRotterdamNetherlands
| | - Barbara Borroni
- Centre for Neurodegenerative DisordersDepartment of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Raquel Sanchez‐Valle
- Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital ClínicInstitut d'Investigacións Biomèdiques August Pi I SunyerUniversity of BarcelonaBarcelonaSpain
| | - Fermin Moreno
- Cognitive Disorders UnitDepartment of NeurologyDonostia University HospitalSan SebastianGipuzkoaSpain
- Neuroscience AreaBiodonostia Health Research InstituteSan SebastianGipuzkoaSpain
| | - Robert Laforce
- CHU de Québec, and Faculté de MédecineDépartement des Sciences NeurologiquesClinique Interdisciplinaire de Mémoire, Université LavalQCCanada
| | - Caroline Graff
- Center for Alzheimer ResearchDivision of NeurogeriatricsDepartment of Neurobiology, Care Sciences and SocietyBioclinicum, Karolinska InstitutetSolnaSweden
- Unit for Hereditary Dementias, Theme AgingKarolinska University HospitalSolnaSweden
| | - Matthis Synofzik
- Department of Neurodegenerative DiseasesHertie‐Institute for Clinical Brain ResearchTübingenGermany
- Center of NeurologyUniversity of TübingenTübingenGermany
| | - Daniela Galimberti
- Fondazione IRCCS Ospedale PoliclinicoMilanItaly
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | - Mario Masellis
- Sunnybrook Health Sciences CentreSunnybrook Research InstituteUniversity of TorontoTorontoCanada
| | | | - Elizabeth Finger
- Department of Clinical Neurological SciencesUniversity of Western OntarioLondonOntarioCanada
| | - Rik Vandenberghe
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesKU LeuvenLeuvenBelgium
- Neurology ServiceUniversity Hospitals LeuvenBelgium
- Leuven Brain InstituteKU LeuvenLeuvenBelgium
| | | | | | - Chris R. Butler
- Nuffield Department of Clinical NeurosciencesMedical Sciences DivisionUniversity of OxfordOxfordUK
- Department of Brain SciencesImperial College LondonLondonUK
| | - Isabel Santana
- University Hospital of Coimbra (HUC)Neurology Service, Faculty of MedicineUniversity of CoimbraCoimbraPortugal
- Center for Neuroscience and Cell BiologyFaculty of MedicineUniversity of CoimbraCoimbraPortugal
| | - Isabelle Le Ber
- Paris Brain Institute – Institut du Cerveau – ICMInserm U1127, CNRS UMR 7225, AP‐HP ‐ Hôpital Pitié‐SalpêtrièreSorbonne UniversitéParisFrance
- Centre de référence des démences rares ou précoces, IM2ADépartement de NeurologieAP‐HP ‐ Hôpital Pitié‐SalpêtrièreParisFrance
- Département de NeurologieAP‐HP ‐ Hôpital Pitié‐SalpêtrièreParisFrance
| | - Alexander Gerhard
- Division of Neuroscience and Experimental PsychologyWolfson Molecular Imaging CentreUniversity of ManchesterManchesterUK
- Departments of Geriatric Medicine and Nuclear MedicineUniversity of Duisburg‐ EssenDuisburgGermany
| | - Simon Ducharme
- Department of PsychiatryMcGill University Health CentreMcGill UniversityMontrealQuébecCanada
- Department of Neurology & NeurosurgeryMcConnell Brain Imaging CentreMontreal Neurological InstituteMcGill UniversityMontrealCanada
| | - Johannes Levin
- Neurologische KlinikLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Munich Cluster of Systems NeurologyMunichGermany
| | - Adrian Danek
- Neurologische KlinikLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Markus Otto
- Department of NeurologyUniversity of UlmUlmGermany
| | - Sandro Sorbi
- Department of NeurofarbaUniversity of FlorenceFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Florence Pasquier
- Univ LilleLilleFrance
- Inserm 1172LilleFrance
- CHU, CNR‐MAJ, Labex DistalzLiCEND LilleLilleFrance
| | - Arabella Bouzigues
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - Lucy L. Russell
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - Jonathan D. Rohrer
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Timothy Rittman
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
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24
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Bridel C, van Gils JHM, Miedema SSM, Hoozemans JJM, Pijnenburg YAL, Smit AB, Rozemuller AJM, Abeln S, Teunissen CE. Clusters of co-abundant proteins in the brain cortex associated with fronto-temporal lobar degeneration. Alzheimers Res Ther 2023; 15:59. [PMID: 36949537 PMCID: PMC10035199 DOI: 10.1186/s13195-023-01200-1] [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: 11/07/2022] [Accepted: 02/28/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Frontotemporal lobar degeneration (FTLD) is characterized pathologically by neuronal and glial inclusions of hyperphosphorylated tau or by neuronal cytoplasmic inclusions of TDP43. This study aimed at deciphering the molecular mechanisms leading to these distinct pathological subtypes. METHODS To this end, we performed an unbiased mass spectrometry-based proteomic and systems-level analysis of the middle frontal gyrus cortices of FTLD-tau (n = 6), FTLD-TDP (n = 15), and control patients (n = 5). We validated these results in an independent patient cohort (total n = 24). RESULTS The middle frontal gyrus cortex proteome was most significantly altered in FTLD-tau compared to controls (294 differentially expressed proteins at FDR = 0.05). The proteomic modifications in FTLD-TDP were more heterogeneous (49 differentially expressed proteins at FDR = 0.1). Weighted co-expression network analysis revealed 17 modules of co-regulated proteins, 13 of which were dysregulated in FTLD-tau. These modules included proteins associated with oxidative phosphorylation, scavenger mechanisms, chromatin regulation, and clathrin-mediated transport in both the frontal and temporal cortex of FTLD-tau. The most strongly dysregulated subnetworks identified cyclin-dependent kinase 5 (CDK5) and polypyrimidine tract-binding protein 1 (PTBP1) as key players in the disease process. Dysregulation of 9 of these modules was confirmed in independent validation data sets of FLTD-tau and control temporal and frontal cortex (total n = 24). Dysregulated modules were primarily associated with changes in astrocyte and endothelial cell protein abundance levels, indicating pathological changes in FTD are not limited to neurons. CONCLUSIONS Using this innovative workflow and zooming in on the most strongly dysregulated proteins of the identified modules, we were able to identify disease-associated mechanisms in FTLD-tau with high potential as biomarkers and/or therapeutic targets.
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Affiliation(s)
- Claire Bridel
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospital, Geneva, Switzerland
| | - Juami H. M. van Gils
- Department of Computer Science, Bioinformatics group, VU University, Amsterdam, The Netherlands
| | - Suzanne S. M. Miedema
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands
| | - Jeroen J. M. Hoozemans
- Department of Pathology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Yolande A. L. Pijnenburg
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - August B. Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands
| | | | - Sanne Abeln
- Department of Computer Science, Bioinformatics group, VU University, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam UMC, Amsterdam, The Netherlands
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25
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Prajjwal P, Shashank S, Al-Ezzi SMS, Sharma B, Aubourg O, Kaushish A, Marsool MDM, Nagre A, Asharaf S. Frontotemporal dementia: Addressing the scattered harbingers of genetics and its relationship with glucose metabolism, bipolar disorder, and amyotrophic lateral sclerosis. Dis Mon 2023; 69:101545. [PMID: 36925418 DOI: 10.1016/j.disamonth.2023.101545] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
Frontotemporal Dementia, also known by the name Pick's disease, is a rare form of dementia that can run for several generations. The two key characteristics are argyrophilic, spherical intraneuronal inclusions, which most frequently impact the frontal and temporal poles, and localized cortical atrophy (Pick bodies). Although personality decline and memory loss are frequently more severe than the visuospatial and apraxia disorders that are common in Alzheimer's disease, clinical overlap with other non-Alzheimer degenerative disorders is being increasingly recognized. The limbic system, which includes the hippocampus, entorhinal cortex, and amygdala, typically experiences the greatest levels of neuronal loss and degeneration. In the hippocampus's dentate fascia, several Pick bodies are frequently seen. Leukoencephalopathy and inflated cortical neurons are less specific symptoms (Pick cells). In this paper, we review the factors leading to Picks disease along with its pathophysiology, clinical manifestations, diagnosis, imaging, treatment, prognosis, and a comprehensive discussion on the same. We have also discussed the relationship of frontotemporal dementia with glucose metabolism, bipolar disorder, and amyotrophic lateral sclerosis, all of which are emerging fields of interest and need more studies.
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Affiliation(s)
- Priyadarshi Prajjwal
- Department of Neurology, Bharati Vidyapeeth University Medical College, Pune, India
| | - Singam Shashank
- Department of Neurology, Shadan Institute of Medical Sciences, Hyderabad, India
| | | | - Bhavya Sharma
- Medical Student, Department of Medicine, Medical College, Baroda, Vadodara, Gujarat, India
| | - Obed Aubourg
- Doctor of Medicine, University of Montreal, QC, Canada
| | - Akshita Kaushish
- MSc Biochemistry, Dolphin Institute of Biomedical and Natural Sciences, Dehradun, India
| | | | - Abhijit Nagre
- Medical Student, Department of Medicine, Topiwala National Medical College, Mumbai, India
| | - Shahnaz Asharaf
- Department of Neurology, Travancore Medical College, Kollam, Kerala, India
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26
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Hu Z, Wang L, Zhu D, Qin R, Sheng X, Ke Z, Shao P, Zhao H, Xu Y, Bai F. Retinal Alterations as Potential Biomarkers of Structural Brain Changes in Alzheimer’s Disease Spectrum Patients. Brain Sci 2023; 13:brainsci13030460. [PMID: 36979270 PMCID: PMC10046312 DOI: 10.3390/brainsci13030460] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 03/02/2023] [Accepted: 03/06/2023] [Indexed: 03/11/2023] Open
Abstract
Retinal imaging being a potential biomarker for Alzheimer’s disease is gradually attracting the attention of researchers. However, the association between retinal parameters and AD neuroimaging biomarkers, particularly structural changes, is still unclear. In this cross-sectional study, we recruited 25 cognitively impaired (CI) and 21 cognitively normal (CN) individuals. All subjects underwent retinal layer thickness and microvascular measurements with optical coherence tomography angiography (OCTA). Gray matter and white matter (WM) data such as T1-weighted magnetic resonance imaging and diffusion tensor imaging, respectively, were also collected. In addition, hippocampal subfield volumes and WM tract microstructural alterations were investigated as classical AD neuroimaging biomarkers. The microvascular and retinal features and their correlation with brain structural imaging markers were further analyzed. We observed a reduction in vessel density (VD) at the inferior outer (IO) sector (p = 0.049), atrophy in hippocampal subfield volumes, such as the subiculum (p = 0.012), presubiculum (p = 0.015), molecular_layer_HP (p = 0.033), GC-ML-DG (p = 0.043) and whole hippocampus (p = 0.033) in CI patients. Altered microstructural integrity of WM tracts in CI patients was also discovered in the cingulum hippocampal part (CgH). Importantly, we detected significant associations between retinal VD and gray matter volumes of the hippocampal subfield in CI patients. These findings suggested that the retinal microvascular measures acquired by OCTA may be markers for the early prediction of AD-related structural brain changes.
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Affiliation(s)
- Zheqi Hu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Lianlian Wang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing 210008, China
| | - Dandan Zhu
- Department of Ophthalmology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing 210008, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Xiaoning Sheng
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Zhihong Ke
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Pengfei Shao
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Geriatric Medicine Center, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
- Correspondence: ; Tel.: +86-25-83105960
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Piervincenzi C, Suppa A, Petsas N, Fabbrini A, Trebbastoni A, Asci F, Giannì C, Berardelli A, Pantano P. Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration. Biomedicines 2023; 11:522. [PMID: 36831058 PMCID: PMC9953061 DOI: 10.3390/biomedicines11020522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/07/2023] [Accepted: 02/09/2023] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park-). METHODS Thirty FTD patients (12 Park+, 18 Park-) and 30 healthy controls were enrolled and underwent 3T MRI scanning. MRI analyses included: (1) surface-based morphometry; (2) basal ganglia and thalamic volumetry; (3) diffusion-based probabilistic tractography of fiber tracts connecting the supplementary motor area (SMA) and primary motor cortex (M1) to the putamen, globus pallidus, and thalamus; and (4) resting-state functional connectivity (RSFC) between the aforementioned regions. RESULTS Patients in Park+ and Park- groups showed comparable patterns of cortical thinning in frontotemporal regions and reduced thalamic volume with respect to controls. Only Park+ patients showed reduced putaminal volume and reduced fractional anisotropy of the fibers connecting the SMA to the globus pallidus, putamen, and thalamus, with respect to controls. Park+ patients also showed decreased RSFC between the SMA and putamen with respect to both Park- patients and controls. CONCLUSIONS The present findings support the hypothesis that FTD patients with parkinsonism are characterized by neurodegenerative processes in specific corticobasal ganglia-thalamocortical motor loops.
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Affiliation(s)
- Claudia Piervincenzi
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS NEUROMED, 86077 Pozzilli, Italy
| | - Nikolaos Petsas
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Andrea Fabbrini
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | | | - Francesco Asci
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS NEUROMED, 86077 Pozzilli, Italy
| | - Costanza Giannì
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS NEUROMED, 86077 Pozzilli, Italy
| | - Alfredo Berardelli
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS NEUROMED, 86077 Pozzilli, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS NEUROMED, 86077 Pozzilli, Italy
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28
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Dresang HC, Williamson R, Kim H, Hillis AE, Buxbaum LJ. Gesture profiles distinguish primary progressive aphasia variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.19.524719. [PMID: 36711535 PMCID: PMC9882352 DOI: 10.1101/2023.01.19.524719] [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] [Indexed: 01/22/2023]
Abstract
Primary progressive aphasia (PPA) is a neurodegenerative syndrome characterized by progressive language deficits. There are three main variants of PPA - semantic (svPPA), logopenic (lvPPA), and nonfluent (nfvPPA) - that can be challenging to distinguish. Limb praxis may also be affected in PPA, but it is unclear whether different variants of PPA are associated with differences in gesture production. Prior research with neurotypical individuals indicates that the left temporal lobe is a critical locus of manipulable object and hand posture representations. Moreover, when imitating gestures, individuals whose strokes include the left temporal lobe show reduced benefit of gesture meaning and disproportionate impairment in hand posture as compared to arm kinematics. We tested the hypothesis that svPPA - who typically exhibit primarily temporal lobe atrophy - would differentially show these expected patterns of gesture imitation performance. Nineteen participants with PPA completed meaningful and meaningless gesture imitation tasks, and performance was scored for hand posture and arm kinematics accuracy. Generalized logistic mixed-effect regression models controlling for dementia severity showed overall benefits from gesture meaning, and greater impairments in hand posture than arm kinematics. We also found that svPPA participants were the most impaired in gesture imitation overall. Critically, there was also a significant three-way interaction of group, meaning, and gesture component: only svPPA participants showed relative impairments of hand posture for meaningful gestures as well as meaningless gestures. Thus, unlike lvPPA and nfvPPA, the hand postures of svPPA failed to benefit from gesture meaning. This research extends prior findings on the role of the temporal lobe in hand posture representations associated with manipulable objects, and is the first to indicate that there may be distinct gesture imitation patterns as a function of PPA variant. Characterizing componential gesture deficits in PPA may help to inform differential diagnosis, compensatory communication strategies, and cognitive praxis models of PPA.
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Affiliation(s)
- Haley C. Dresang
- Moss Rehabilitation Research Institute, 50 Township Line Rd, Elkins Park, PA 19027
- University of Pennsylvania, Perelman School of Medicine, Department of Neurology, 3400 Spruce St, Philadelphia, PA 19104
| | - Rand Williamson
- Moss Rehabilitation Research Institute, 50 Township Line Rd, Elkins Park, PA 19027
| | - Hana Kim
- Johns Hopkins University School of Medicine, Department of Neurology, 600 N. Wolfe Street, Baltimore, MD 21287
| | - Argye E. Hillis
- Johns Hopkins University School of Medicine, Department of Neurology, 600 N. Wolfe Street, Baltimore, MD 21287
| | - Laurel J. Buxbaum
- Moss Rehabilitation Research Institute, 50 Township Line Rd, Elkins Park, PA 19027
- Thomas Jefferson University, Department of Rehabilitation Medicine, 901 Walnut Street, Philadelphia, PA 19107
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29
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Lampe L, Huppertz HJ, Anderl-Straub S, Albrecht F, Ballarini T, Bisenius S, Mueller K, Niehaus S, Fassbender K, Fliessbach K, Jahn H, Kornhuber J, Lauer M, Prudlo J, Schneider A, Synofzik M, Kassubek J, Danek A, Villringer A, Diehl-Schmid J, Otto M, Schroeter ML. Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging. Neuroimage Clin 2023; 37:103320. [PMID: 36623349 PMCID: PMC9850041 DOI: 10.1016/j.nicl.2023.103320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/23/2022] [Accepted: 01/04/2023] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI). METHODS Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification). RESULTS The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration. DISCUSSION Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.
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Affiliation(s)
- Leonie Lampe
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Clinic Leipzig, Germany
| | | | | | - Franziska Albrecht
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tommaso Ballarini
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Sandrine Bisenius
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Karsten Mueller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Sebastian Niehaus
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | | | - Klaus Fliessbach
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, and German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Holger Jahn
- Clinic for Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany
| | - Martin Lauer
- Department of Psychiatry and Psychotherapy, University Wuerzburg, Germany
| | - Johannes Prudlo
- Department of Neurology, University of Rostock, and DZNE, Rostock, Germany
| | - Anja Schneider
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, and German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Psychiatry and Psychotherapy, University of Goettingen, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Centre for Neurology & Hertie-lnstitute for Clinical Brain Research, University of Tuebingen, Germany & DZNE, Tuebingen, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-Universität Munich, München, Germany
| | - Arno Villringer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Clinic Leipzig, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Germany; Department of Neurology, University of Halle, Germany
| | - Matthias L Schroeter
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Clinic Leipzig, Germany.
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30
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Gonzalez-Gomez R, Ibañez A, Moguilner S. Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference. Netw Neurosci 2023; 7:322-350. [PMID: 37333999 PMCID: PMC10270711 DOI: 10.1162/netn_a_00285] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 10/03/2022] [Indexed: 04/03/2024] Open
Abstract
Characterizing a particular neurodegenerative condition against others possible diseases remains a challenge along clinical, biomarker, and neuroscientific levels. This is the particular case of frontotemporal dementia (FTD) variants, where their specific characterization requires high levels of expertise and multidisciplinary teams to subtly distinguish among similar physiopathological processes. Here, we used a computational approach of multimodal brain networks to address simultaneous multiclass classification of 298 subjects (one group against all others), including five FTD variants: behavioral variant FTD, corticobasal syndrome, nonfluent variant primary progressive aphasia, progressive supranuclear palsy, and semantic variant primary progressive aphasia, with healthy controls. Fourteen machine learning classifiers were trained with functional and structural connectivity metrics calculated through different methods. Due to the large number of variables, dimensionality was reduced, employing statistical comparisons and progressive elimination to assess feature stability under nested cross-validation. The machine learning performance was measured through the area under the receiver operating characteristic curves, reaching 0.81 on average, with a standard deviation of 0.09. Furthermore, the contributions of demographic and cognitive data were also assessed via multifeatured classifiers. An accurate simultaneous multiclass classification of each FTD variant against other variants and controls was obtained based on the selection of an optimum set of features. The classifiers incorporating the brain's network and cognitive assessment increased performance metrics. Multimodal classifiers evidenced specific variants' compromise, across modalities and methods through feature importance analysis. If replicated and validated, this approach may help to support clinical decision tools aimed to detect specific affectations in the context of overlapping diseases.
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Affiliation(s)
- Raul Gonzalez-Gomez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Cognitive Neuroscience Center, Universidad de San Andres, Buenos Aires, Argentina
- Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA
- Trinity College Dublin, Dublin, Ireland
| | - Sebastian Moguilner
- Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Cognitive Neuroscience Center, Universidad de San Andres, Buenos Aires, Argentina
- Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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31
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Sakurai K, Kaneda D, Morimoto S, Uchida Y, Inui S, Kimura Y, Kato T, Ito K, Hashizume Y. Asymmetric Cerebral Peduncle Atrophy: A Simple Diagnostic Clue for Distinguishing Frontotemporal Lobar Degeneration from Alzheimer's Disease. J Alzheimers Dis 2023; 95:1657-1665. [PMID: 37718809 DOI: 10.3233/jad-230441] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
BACKGROUND Due to confusing clinicoradiological features such as amnestic symptoms and hippocampal atrophy in frontotemporal lobar degeneration (FTLD), antemortem differentiation between FTLD and Alzheimer's disease (AD) can be challenging. Although asymmetric atrophy of the cerebral peduncle is regarded as a representative imaging finding in some disorders of the FTLD spectrum, the utility of this finding has not been sufficiently evaluated for differentiating between FTLD and AD. OBJECTIVE This study aimed to explore the diagnostic performance of asymmetric cerebral peduncle atrophy on axial magnetic resonance imaging as a simple radiological discriminator between FTLD and AD. METHODS Seventeen patients with pathologically confirmed FTLD, including six with progressive supranuclear palsy, three with corticobasal degeneration, eight with TAR DNA-binding protein 43 (FTLD-TDP), and 11 with pathologically confirmed AD, were investigated. Quantitative indices representing the difference between the volumes of the bilateral cerebral peduncles (i.e., cerebral peduncular asymmetry index [CPAI]), the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) Z-score representing the degree of hippocampal atrophy, and semiquantitative visual analysis to evaluate the asymmetry of the cerebral peduncle (visual assessment of cerebral peduncular asymmetry: VACPA) were compared between the two groups. RESULTS Contrary to the VSRAD Z-score, the CPAI and VACPA scores demonstrated higher diagnostic performance in differentiating patients with FTLD from those with AD (areas under the receiver operating characteristic curve of 0.88, 082, and 0.60, respectively). CONCLUSIONS Quantitative and visual analytical techniques can differentiate between FTLD and AD. These simple methods may be useful in daily clinical practice.
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Affiliation(s)
- Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Daita Kaneda
- Choju Medical Institute, Fukushimura Hospital, Aichi, Japan
| | - Satoru Morimoto
- Department of Physiology, School of Medicine, Keio University, Tokyo, Japan
| | - Yuto Uchida
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Aichi, Japan
| | - Shohei Inui
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yasuyuki Kimura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Takashi Kato
- Department of Radiology, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Kengo Ito
- Department of Radiology, National Center for Geriatrics and Gerontology, Aichi, Japan
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32
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Mofrad RB, Del Campo M, Peeters CFW, Meeter LHH, Seelaar H, Koel-Simmelink M, Ramakers IHGB, Middelkoop HAM, De Deyn PP, Claassen JAHR, van Swieten JC, Bridel C, Hoozemans JJM, Scheltens P, van der Flier WM, Pijnenburg YAL, Teunissen CE. Plasma proteome profiling identifies changes associated to AD but not to FTD. Acta Neuropathol Commun 2022; 10:148. [PMID: 36273219 PMCID: PMC9587555 DOI: 10.1186/s40478-022-01458-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 10/06/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process. METHODS Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis. RESULTS Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified. CONCLUSIONS We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.
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Affiliation(s)
- R Babapour Mofrad
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology Amsterdam, Department of Neurology, Neuroscience Campus Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M Del Campo
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.,Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain.,Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - C F W Peeters
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Mathematical and Statistical Methods Group (Biometris), Wageningen University and Research Wageningen, Wageningen, The Netherlands
| | - L H H Meeter
- Alzheimer Center Erasmus MC and Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Seelaar
- Alzheimer Center Rotterdam and Department of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M Koel-Simmelink
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - I H G B Ramakers
- Alzheimer Center Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - H A M Middelkoop
- Institute of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Leiden, the Netherlands.,Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
| | - P P De Deyn
- Laboratory of Neurochemistry and Behavior, Department of Biomedical Sciences, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Department of Neurology and Alzheimer Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - J A H R Claassen
- Department of Geriatric Medicine, Radboud University Medical Center, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - J C van Swieten
- Alzheimer Center Erasmus MC and Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - C Bridel
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - J J M Hoozemans
- Department of Pathology, Amsterdam University Medical Centers Location VUmc, Amsterdam, The Netherlands
| | - P Scheltens
- Alzheimer Center and Department of Neurology Amsterdam, Department of Neurology, Neuroscience Campus Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - W M van der Flier
- Alzheimer Center and Department of Neurology Amsterdam, Department of Neurology, Neuroscience Campus Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Y A L Pijnenburg
- Alzheimer Center and Department of Neurology Amsterdam, Department of Neurology, Neuroscience Campus Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
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33
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Wang R, Gao H, Xie H, Jia Z, Chen Q. Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects. Front Neurol 2022; 13:933217. [PMID: 36051222 PMCID: PMC9424494 DOI: 10.3389/fneur.2022.933217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 07/25/2022] [Indexed: 12/01/2022] Open
Abstract
Familial frontotemporal lobar degeneration (FTLD) is a pathologically heterogeneous group of neurodegenerative diseases with diverse genotypes and clinical phenotypes. Three major mutations were reported in patients with familial FTLD, namely, progranulin (GRN), microtubule-associated protein tau (MAPT), and the chromosome 9 open reading frame 72 (C9orf72) repeat expansion, which could cause neurodegenerative pathological changes years before symptom onset. Noninvasive quantitative molecular imaging with PET or single-photon emission CT (SPECT) allows for selective visualization of the molecular targets in vivo to investigate brain metabolism, perfusion, neuroinflammation, and pathophysiological changes. There was increasing evidence that several molecular imaging biomarkers tend to serve as biomarkers to reveal the early brain abnormalities in familial FTLD. Tau-PET with 18F-flortaucipir and 11C-PBB3 demonstrated the elevated tau position in patients with FTLD and also showed the ability to differentiate patterns among the different subtypes of the mutations in familial FTLD. Furthermore, dopamine transporter imaging with the 11C-DOPA and 11C-CFT in PET and the 123I-FP-CIT in SPECT revealed the loss of dopaminergic neurons in the asymptomatic and symptomatic patients of familial FTLD. In addition, PET imaging with the 11C-MP4A has demonstrated reduced acetylcholinesterase (AChE) activity in patients with FTLD, while PET with the 11C-DAA1106 and 11C-PK11195 revealed an increased level of microglial activation associated with neuroinflammation even before the onset of symptoms in familial FTLD. 18F-fluorodeoxyglucose (FDG)-PET indicated hypometabolism in FTLD with different mutations preceded the atrophy on MRI. Identifying molecular imaging biomarkers for familial FTLD is important for the in-vivo assessment of underlying pathophysiological changes with disease progression and future disease-modifying therapy. We review the recent progress of molecular imaging in familial FTLD with focused on the possible implication of these techniques and their prospects in specific mutation types.
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Affiliation(s)
- Ruihan Wang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Hui Gao
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Hongsheng Xie
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Qin Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Qin Chen
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Neurovascular dysfunction in GRN-associated frontotemporal dementia identified by single-nucleus RNA sequencing of human cerebral cortex. Nat Neurosci 2022; 25:1034-1048. [PMID: 35879464 DOI: 10.1038/s41593-022-01124-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 06/16/2022] [Indexed: 12/13/2022]
Abstract
Frontotemporal dementia (FTD) is the second most prevalent form of early-onset dementia, affecting predominantly frontal and temporal cerebral lobes. Heterozygous mutations in the progranulin gene (GRN) cause autosomal-dominant FTD (FTD-GRN), associated with TDP-43 inclusions, neuronal loss, axonal degeneration and gliosis, but FTD-GRN pathogenesis is largely unresolved. Here we report single-nucleus RNA sequencing of microglia, astrocytes and the neurovasculature from frontal, temporal and occipital cortical tissue from control and FTD-GRN brains. We show that fibroblast and mesenchymal cell numbers were enriched in FTD-GRN, and we identified disease-associated subtypes of astrocytes and endothelial cells. Expression of gene modules associated with blood-brain barrier (BBB) dysfunction was significantly enriched in FTD-GRN endothelial cells. The vasculature supportive function and capillary coverage by pericytes was reduced in FTD-GRN tissue, with increased and hypertrophic vascularization and an enrichment of perivascular T cells. Our results indicate a perturbed BBB and suggest that the neurovascular unit is severely affected in FTD-GRN.
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Ryan B, O’Mara Baker A, Ilse C, Brickell KL, Kersten HM, Williams JM, Addis DR, Tippett LJ, Curtis MA. The New Zealand Genetic Frontotemporal Dementia Study (FTDGeNZ): a longitudinal study of pre-symptomatic biomarkers. J R Soc N Z 2022. [DOI: 10.1080/03036758.2022.2101483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Affiliation(s)
- Brigid Ryan
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Ashleigh O’Mara Baker
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Christina Ilse
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Kiri L. Brickell
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Hannah M. Kersten
- School of Optometry and Vision Science, University of Auckland, Auckland, New Zealand
| | - Joanna M. Williams
- Department of Anatomy, University of Otago, Dunedin, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Donna Rose Addis
- School of Psychology, University of Auckland, Auckland, New Zealand
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Lynette J. Tippett
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
| | - Maurice A. Curtis
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, New Zealand
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Nigro S, Filardi M, Tafuri B, De Blasi R, Cedola A, Gigli G, Logroscino G. The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia. Front Neurol 2022; 13:910054. [PMID: 35837233 PMCID: PMC9275562 DOI: 10.3389/fneur.2022.910054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/02/2022] [Indexed: 11/21/2022] Open
Abstract
Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.
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Affiliation(s)
- Salvatore Nigro
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Salvatore Nigro
| | - Marco Filardi
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - 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”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Roberto De Blasi
- Department of Radiology, “Pia Fondazione Cardinale G. Panico”, Tricase, Lecce, Italy
| | - Alessia Cedola
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
- Department of Mathematics and Physics “Ennio De Giorgi”, University of Salento, 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”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- *Correspondence: Giancarlo Logroscino
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Kamalian A, Khodadadifar T, Saberi A, Masoudi M, Camilleri JA, Eickhoff CR, Zarei M, Pasquini L, Laird AR, Fox PT, Eickhoff SB, Tahmasian M. Convergent regional brain abnormalities in behavioral variant frontotemporal dementia: A neuroimaging meta-analysis of 73 studies. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12318. [PMID: 35664889 PMCID: PMC9148620 DOI: 10.1002/dad2.12318] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/13/2022] [Accepted: 04/10/2022] [Indexed: 12/19/2022]
Abstract
Introduction Numerous studies have reported brain alterations in behavioral variant frontotemporal dementia (bvFTD). However, they pointed to inconsistent findings. Methods We used a meta‐analytic approach to identify the convergent structural and functional brain abnormalities in bvFTD. Following current best‐practice neuroimaging meta‐analysis guidelines, we searched PubMed and Embase databases and performed reference tracking. Then, the coordinates of group comparisons between bvFTD and controls from 73 studies were extracted and tested for convergence using activation likelihood estimation. Results We identified convergent abnormalities in the anterior cingulate cortices, anterior insula, amygdala, paracingulate, striatum, and hippocampus. Task‐based and resting‐state functional connectivity pointed to the networks that are connected to the obtained consistent regions. Functional decoding analyses suggested associated dysfunction of emotional processing, interoception, reward processing, higher‐order cognitive functions, and olfactory and gustatory perceptions in bvFTD. Discussion Our findings highlighted the key role of the salience network and subcortical regions in the pathophysiology of bvFTD.
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Affiliation(s)
- Aida Kamalian
- School of Medicine Tehran University of Medical Sciences Tehran Iran
| | - Tina Khodadadifar
- School of Cognitive Sciences Institute for Research in Fundamental Sciences Tehran Iran
| | - Amin Saberi
- Institute of Neuroscience and Medicine Brain and Behavior (INM-7) Research Center Jülich Jülich Germany.,Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany
| | - Maryam Masoudi
- School of Medicine Tehran University of Medical Sciences Tehran Iran
| | - Julia A Camilleri
- Institute of Neuroscience and Medicine Brain and Behavior (INM-7) Research Center Jülich Jülich Germany.,Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany
| | - Claudia R Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology Heinrich Heine University Düsseldorf Düsseldorf Germany.,Institute of Neuroscience and Medicine Research Center Jülich Structural and Functional Organisation of the Brain (INM-1) Jülich Germany
| | - Mojtaba Zarei
- Institute of Medical Science and Technology Shahid Beheshti University Tehran Iran
| | - Lorenzo Pasquini
- Department of Neurology Memory and Aging Center University of California-San Francisco San Francisco California USA
| | - Angela R Laird
- Department of Physics Florida International University Miami Florida USA
| | - Peter T Fox
- Research Imaging Institute University of Texas Health Science Center San Antonio Texas USA.,South Texas Veterans Health Care System San Antonio Texas USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine Brain and Behavior (INM-7) Research Center Jülich Jülich Germany.,Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany
| | - Masoud Tahmasian
- Institute of Neuroscience and Medicine Brain and Behavior (INM-7) Research Center Jülich Jülich Germany.,Institute for Systems Neuroscience Medical Faculty Heinrich-Heine University Düsseldorf Düsseldorf Germany
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Studart-Neto A, Coutinho AM. From clinical phenotype to proteinopathy: molecular neuroimaging in neurodegenerative dementias. ARQUIVOS DE NEURO-PSIQUIATRIA 2022; 80:24-35. [PMID: 35976328 PMCID: PMC9491407 DOI: 10.1590/0004-282x-anp-2022-s138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Neurodegenerative dementias are characterized by the abnormal accumulation of misfolded proteins. However, its diagnostic criteria are still based on the clinical phenotype. The development of biomarkers allowed in vivo detection of pathophysiological processes. This article aims to make a non-systematic review of the use of molecular neuroimaging as a biomarker. Molecular neuroimaging is based on the use of radiotracers for image acquisition. The radiotracer most used in PET is 18F-fluorodeoxyglucose (FDG), with which it is possible to study the regional brain glucose metabolism. The pattern of regional hypometabolism provides neuroanatomical information on the neurodegenerative process, which, in turn, has a good specificity for each type of proteinopathy. FDG is very useful in the differential diagnosis of neurodegenerative dementias through the regional pattern of involvement, including dementia with Lewy bodies and the spectrum of frontotemporal dementia. More recently, radiotracers with specific ligands to some of the pathological proteins have been developed. Pittsburgh compound B (PIB) labeled with 11C and the ligands that use 18F (florbetapir, florbetaben and flutemetamol) are the most used radiotracers for the detection of insoluble β-amyloid peptide in Alzheimer's disease (AD). A first generation of ligands for tau protein has been developed, but it has some affinity for other non-tau protein aggregates. A second generation has the advantage of having a higher affinity for hyperphosphorylated tau protein, including in primary tauopathies.
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Affiliation(s)
- Adalberto Studart-Neto
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo, SP, Brazil
| | - Artur Martins Coutinho
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Radiologia e Oncologia, Divisão e Laboratório de Medicina Nuclear (LIM 43), São Paulo, SP, Brazil
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Manzine PR, Vatanabe IP, Grigoli MM, Pedroso RV, de Almeida MPOMEP, de Oliveira DDSMS, Crispim Nascimento CM, Peron R, de Souza Orlandi F, Cominetti MR. Potential Protein Blood-Based Biomarkers in Different Types of Dementia: A Therapeutic Overview. Curr Pharm Des 2022; 28:1170-1186. [DOI: 10.2174/1381612828666220408124809] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 02/24/2022] [Indexed: 11/22/2022]
Abstract
Abstract:
Biomarkers capable of identifying and distinguishing types of dementia such as Alzheimer's disease (AD), Parkinson's disease dementia (PDD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) have been become increasingly relentless. Studies of possible biomarker proteins in the blood that can help formulate new diagnostic proposals and therapeutic visions of different types of dementia are needed. However, due to several limitations of these biomarkers, especially in discerning dementia, their clinical applications are still undetermined. Thus, the updating of biomarker blood proteins that can help in the diagnosis and discrimination of these main dementia conditions is essential to enable new pharmacological and clinical management strategies, with specificities for each type of dementia. To review the literature concerning protein blood-based AD and non-AD biomarkers as new pharmacological targets and/or therapeutic strategies. Recent findings for protein-based AD, PDD, LBD, and FTD biomarkers are focused on in this review. Protein biomarkers were classified according to the pathophysiology of the dementia types. The diagnosis and distinction of dementia through protein biomarkers is still a challenge. The lack of exclusive biomarkers for each type of dementia highlights the need for further studies in this field. Only after this, blood biomarkers may have a valid use in clinical practice as they are promising to help in diagnosis and in the differentiation of diseases.
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Affiliation(s)
- Patricia Regina Manzine
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | - Izabela Pereira Vatanabe
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | - Marina Mantellatto Grigoli
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | - Renata Valle Pedroso
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | | | | | | | - Rafaela Peron
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | - Fabiana de Souza Orlandi
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
| | - Márcia Regina Cominetti
- Department of Gerontology, Federal University of Sao Carlos, Brazil. Highway Washington Luis, Km 235. Monjolinho
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40
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Masrori P, Beckers J, Gossye H, Van Damme P. The role of inflammation in neurodegeneration: novel insights into the role of the immune system in C9orf72 HRE-mediated ALS/FTD. Mol Neurodegener 2022; 17:22. [PMID: 35303907 PMCID: PMC8932121 DOI: 10.1186/s13024-022-00525-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 02/25/2022] [Indexed: 12/13/2022] Open
Abstract
Neuroinflammation is an important hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). An inflammatory reaction to neuronal injury is deemed vital for neuronal health and homeostasis. However, a continued activation of the inflammatory response can be detrimental to remaining neurons and aggravate the disease process. Apart from a disease modifying role, some evidence suggests that neuroinflammation may also contribute to the upstream cause of the disease. In this review, we will first focus on the role of neuroinflammation in the pathogenesis of chromosome 9 open reading frame 72 gene (C9orf72) hexanucleotide repeat expansions (HRE)-mediated ALS/FTD (C9-ALS/FTD). Additionally, we will discuss evidence from ex vivo and in vivo studies and finally, we briefly summarize the trials and progress of anti-inflammatory therapies.
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Affiliation(s)
- Pegah Masrori
- Department of Neurosciences, Experimental Neurology, and Leuven Brain Institute (LBI), KU Leuven-University of Leuven, 3000, Leuven, Belgium.,Laboratory of Neurobiology, Experimental Neurology, Center for Brain and Disease Research, VIB, Campus Gasthuisberg, O&N5, Herestraat 49, 602, 3000, Leuven, PB, Belgium.,Neurology Department, University Hospitals Leuven, Campus Gasthuisberg, Herestraat 49, 3000, Leuven, Belgium.,Department of Neurology, University Hospital Antwerp, 2650, Edegem, Belgium
| | - Jimmy Beckers
- Department of Neurosciences, Experimental Neurology, and Leuven Brain Institute (LBI), KU Leuven-University of Leuven, 3000, Leuven, Belgium.,Laboratory of Neurobiology, Experimental Neurology, Center for Brain and Disease Research, VIB, Campus Gasthuisberg, O&N5, Herestraat 49, 602, 3000, Leuven, PB, Belgium
| | - Helena Gossye
- Department of Neurology, University Hospital Antwerp, 2650, Edegem, Belgium.,VIB Center for Molecular Neurology, Neurodegenerative Brain Diseases, University of Antwerp, 2000, Antwerp, Belgium.,Department of Biomedical Sciences, University of Antwerp, 2000, Antwerp, Belgium
| | - Philip Van Damme
- Department of Neurosciences, Experimental Neurology, and Leuven Brain Institute (LBI), KU Leuven-University of Leuven, 3000, Leuven, Belgium. .,Laboratory of Neurobiology, Experimental Neurology, Center for Brain and Disease Research, VIB, Campus Gasthuisberg, O&N5, Herestraat 49, 602, 3000, Leuven, PB, Belgium. .,Neurology Department, University Hospitals Leuven, Campus Gasthuisberg, Herestraat 49, 3000, Leuven, Belgium.
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Tisdall MD, Ohm DT, Lobrovich R, Das SR, Mizsei G, Prabhakaran K, Ittyerah R, Lim S, McMillan CT, Wolk DA, Gee J, Trojanowski JQ, Lee EB, Detre JA, Yushkevich P, Grossman M, Irwin DJ. Ex vivo MRI and histopathology detect novel iron-rich cortical inflammation in frontotemporal lobar degeneration with tau versus TDP-43 pathology. Neuroimage Clin 2022; 33:102913. [PMID: 34952351 PMCID: PMC8715243 DOI: 10.1016/j.nicl.2021.102913] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 10/28/2021] [Accepted: 12/08/2021] [Indexed: 02/08/2023]
Abstract
Comparative study of whole-hemisphere ex vivo T2*-weighted MRI and histopathology. Sample of FTLD-Tau and FTLD-TDP subtypes with reference to healthy and AD brain. Novel focal upper cortical-layer iron-rich pathology distinguishes FTLD-TDP from clinically-similar FTLD-Tau and AD. Distinct novel iron-rich FTLD-Tau pathology in mid-to-deep cortical-layers and WM. T2*-weighted MRI signatures offer in vivo biomarker targets for FTLD proteinopathy.
Frontotemporal lobar degeneration (FTLD) is a heterogeneous spectrum of age-associated neurodegenerative diseases that include two main pathologic categories of tau (FTLD-Tau) and TDP-43 (FTLD-TDP) proteinopathies. These distinct proteinopathies are often clinically indistinguishable during life, posing a major obstacle for diagnosis and emerging therapeutic trials tailored to disease-specific mechanisms. Moreover, MRI-derived measures have had limited success to date discriminating between FTLD-Tau or FTLD-TDP. T2*-weighted (T2*w) ex vivo MRI has previously been shown to be sensitive to non-heme iron in healthy intracortical lamination and myelin, and to pathological iron deposits in amyloid-beta plaques and activated microglia in Alzheimer’s disease neuropathologic change (ADNC). However, an integrated, ex vivo MRI and histopathology approach is understudied in FTLD. We apply joint, whole-hemisphere ex vivo MRI at 7 T and histopathology to the study autopsy-confirmed FTLD-Tau (n = 4) and FTLD-TDP (n = 3), relative to ADNC disease-control brains with antemortem clinical symptoms of frontotemporal dementia (n = 2), and an age-matched healthy control. We detect distinct laminar patterns of novel iron-laden glial pathology in both FTLD-Tau and FTLD-TDP brains. We find iron-positive ameboid and hypertrophic microglia and astrocytes largely in deeper GM and adjacent WM in FTLD-Tau. In contrast, FTLD-TDP presents prominent superficial cortical layer iron reactivity in astrocytic processes enveloping small blood vessels with limited involvement of adjacent WM, as well as more diffuse distribution of punctate iron-rich dystrophic microglial processes across all GM lamina. This integrated MRI/histopathology approach reveals ex vivo MRI features that are consistent with these pathological observations distinguishing FTLD-Tau and FTLD-TDP subtypes, including prominent irregular hypointense signal in deeper cortex in FTLD-Tau whereas FTLD-TDP showed upper cortical layer hypointense bands and diffuse cortical speckling. Moreover, differences in adjacent WM degeneration and iron-rich gliosis on histology between FTLD-Tau and FTLD-TDP were also readily apparent on MRI as hyperintense signal and irregular areas of hypointensity, respectively that were more prominent in FTLD-Tau compared to FTLD-TDP. These unique histopathological and radiographic features were distinct from healthy control and ADNC brains, suggesting that iron-sensitive T2*w MRI, adapted to in vivo application at sufficient resolution, may eventually offer an opportunity to improve antemortem diagnosis of FTLD proteinopathies using tissue-validated methods.
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Affiliation(s)
- M Dylan Tisdall
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States.
| | - Daniel T Ohm
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Rebecca Lobrovich
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sandhitsu R Das
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Gabor Mizsei
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Karthik Prabhakaran
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Ranjit Ittyerah
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sydney Lim
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Corey T McMillan
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David A Wolk
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - James Gee
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - John Q Trojanowski
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - Edward B Lee
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - John A Detre
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States; Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Paul Yushkevich
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Murray Grossman
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David J Irwin
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States; Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States.
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42
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Katzeff JS, Bright F, Phan K, Kril JJ, Ittner LM, Kassiou M, Hodges JR, Piguet O, Kiernan MC, Halliday GM, Kim WS. Biomarker discovery and development for frontotemporal dementia and amyotrophic lateral sclerosis. Brain 2022; 145:1598-1609. [PMID: 35202463 PMCID: PMC9166557 DOI: 10.1093/brain/awac077] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 02/08/2022] [Accepted: 02/13/2022] [Indexed: 11/12/2022] Open
Abstract
Frontotemporal dementia refers to a group of neurodegenerative disorders characterized by behaviour and language alterations and focal brain atrophy. Amyotrophic lateral sclerosis is a rapidly progressing neurodegenerative disease characterized by loss of motor neurons resulting in muscle wasting and paralysis. Frontotemporal dementia and amyotrophic lateral sclerosis are considered to exist on a disease spectrum given substantial overlap of genetic and molecular signatures. The predominant genetic abnormality in both frontotemporal dementia and amyotrophic lateral sclerosis is an expanded hexanucleotide repeat sequence in the C9orf72 gene. In terms of brain pathology, abnormal aggregates of TAR-DNA-binding protein-43 are predominantly present in frontotemporal dementia and amyotrophic lateral sclerosis patients. Currently, sensitive and specific diagnostic and disease surveillance biomarkers are lacking for both diseases. This has impeded the capacity to monitor disease progression during life and the development of targeted drug therapies for the two diseases. The purpose of this review is to examine the status of current biofluid biomarker discovery and development in frontotemporal dementia and amyotrophic lateral sclerosis. The major pathogenic proteins implicated in different frontotemporal dementia and amyotrophic lateral sclerosis molecular subtypes and proteins associated with neurodegeneration and the immune system will be discussed. Furthermore, the use of mass spectrometry-based proteomics as an emerging tool to identify new biomarkers in frontotemporal dementia and amyotrophic lateral sclerosis will be summarized.
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Affiliation(s)
- Jared S Katzeff
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia
| | - Fiona Bright
- The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia.,Dementia Research Centre and Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia
| | - Katherine Phan
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia
| | - Jillian J Kril
- The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia.,Dementia Research Centre and Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia
| | - Lars M Ittner
- Dementia Research Centre and Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia
| | - Michael Kassiou
- The University of Sydney, School of Chemistry, Sydney, NSW, Australia
| | - John R Hodges
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia
| | - Olivier Piguet
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,The University of Sydney, School of Psychology, Sydney, NSW, Australia
| | - Matthew C Kiernan
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,Institute of Clinical Neurosciences, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Glenda M Halliday
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia
| | - Woojin Scott Kim
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, Australia.,The University of Sydney, School of Medical Sciences, Sydney, NSW, Australia
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43
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Garrett LR, Niccoli T. Frontotemporal Dementia and Glucose Metabolism. Front Neurosci 2022; 16:812222. [PMID: 35281504 PMCID: PMC8906510 DOI: 10.3389/fnins.2022.812222] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/18/2022] [Indexed: 12/02/2022] Open
Abstract
Frontotemporal dementia (FTD), hallmarked by antero-temporal degeneration in the human brain, is the second most common early onset dementia. FTD is a diverse disease with three main clinical presentations, four different identified proteinopathies and many disease-associated genes. The exact pathophysiology of FTD remains to be elucidated. One common characteristic all forms of FTD share is the dysregulation of glucose metabolism in patients’ brains. The brain consumes around 20% of the body’s energy supply and predominantly utilizes glucose as a fuel. Glucose metabolism dysregulation could therefore be extremely detrimental for neuronal health. Research into the association between glucose metabolism and dementias has recently gained interest in Alzheimer’s disease. FTD also presents with glucose metabolism dysregulation, however, this remains largely an unexplored area. A better understanding of the link between FTD and glucose metabolism may yield further insight into FTD pathophysiology and aid the development of novel therapeutics. Here we review our current understanding of FTD and glucose metabolism in the brain and discuss the evidence of impaired glucose metabolism in FTD. Lastly, we review research potentially suggesting a causal relationship between FTD proteinopathies and impaired glucose metabolism in FTD.
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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. 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: 28] [Impact Index Per Article: 14.0] [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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45
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Assogna M, Sprugnoli G, Press D, Dickerson B, Macone J, Bonnì S, Borghi I, Connor A, Hoffman M, Grover N, Wong B, Shen C, Martorana A, O'Reilly M, Ruffini G, El Fakhri G, Koch G, Santarnecchi E. Gamma-induction in frontotemporal dementia (GIFTeD) randomized placebo-controlled trial: Rationale, noninvasive brain stimulation protocol, and study design. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 7:e12219. [PMID: 35141396 PMCID: PMC8813035 DOI: 10.1002/trc2.12219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 08/02/2021] [Accepted: 09/20/2021] [Indexed: 11/30/2022]
Abstract
INTRODUCTION Frontotemporal dementia (FTD) is a neurodegenerative disorder for which there is no effective pharmacological treatment. Recently, interneuron activity responsible for fast oscillatory brain activity has been found to be impaired in a mouse model of FTD with consequent cognitive and behavioral alterations. In this study, we aim to investigate the safety, tolerability, and efficacy of a novel promising therapeutic intervention for FTD based on 40 Hz transcranial alternating current stimulation (tACS), a form of non-invasive brain stimulation thought to engage neural activity in a frequency-specific manner and thus suited to restore altered brain oscillatory patterns. METHODS This is a multi-site, randomized, double-blind, placebo-controlled trial on 50 patients with a diagnosis of behavioral variant FTD (bvFTD). Participants will be randomized to undergo either 30 days of 1-hour daily tACS or Sham (placebo) tACS. The outcomes will be assessed at baseline, right after the intervention and at a 3- to 6-months follow-up. The primary outcome measures are represented by the safety and feasibility of tACS administration, which will be assessed considering the nature, frequency, and severity of adverse events as well as attrition rate, respectively. To assess secondary outcomes, participants will undergo extensive neuropsychological and behavioral assessments and fluorodeoxyglucose (FDG)-positron emission tomography (PET) scans to evaluate changes in brain metabolism, functional and structural magnetic resonance imaging (MRI), resting and evoked electroencephalography, as well as blood biomarkers to measure changes in neurodegenerative and neuroinflammatory markers. RESULTS The trial started in October 2020 and will end in October 2023. Study protocols have been approved by the local institutional review board (IRB) at each data-collection site. DISCUSSION This study will evaluate the safety and tolerability of 40 Hz tACS in bvFTD patients and its efficacy on gamma oscillatory activity, cognitive function, and brain glucose hypometabolism.
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Affiliation(s)
- Martina Assogna
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
- Non‐Invasive Brain Stimulation UnitDepartment of Behavioural and Clinical NeurologySanta Lucia Foundation IRCCSRomeItaly
| | - Giulia Sprugnoli
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
- Radiology UnitDepartment of Medicine and SurgeryUniversity of ParmaParmaItaly
| | - Daniel Press
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | - Brad Dickerson
- Frontotemporal Disorders Unit and Alzheimer's Disease Research CenterDepartments of Psychiatry and NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Joanna Macone
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | - Sonia Bonnì
- Non‐Invasive Brain Stimulation UnitDepartment of Behavioural and Clinical NeurologySanta Lucia Foundation IRCCSRomeItaly
| | - Ilaria Borghi
- Non‐Invasive Brain Stimulation UnitDepartment of Behavioural and Clinical NeurologySanta Lucia Foundation IRCCSRomeItaly
| | - Ann Connor
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | - Megan Hoffman
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | - Nainika Grover
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | - Bonnie Wong
- Frontotemporal Disorders Unit and Alzheimer's Disease Research CenterDepartments of Psychiatry and NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Changyu Shen
- Richard and Susan Smith Center for Outcomes Research in CardiologyDivision of CardiologyBeth Israel Deaconess Medical and Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Molly O'Reilly
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
| | | | - Georges El Fakhri
- Gordon Center for Medical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Giacomo Koch
- Non‐Invasive Brain Stimulation UnitDepartment of Behavioural and Clinical NeurologySanta Lucia Foundation IRCCSRomeItaly
| | - Emiliano Santarnecchi
- Berenson‐Allen Center for Noninvasive Brain StimulationBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMassachusettsUSA
- Gordon Center for Medical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
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46
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McCarthy J, 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, Frisoni G, Ghidoni R, Sorbi S, Jiskoot LC, Seelaar H, van Swieten JC, Rohrer JD, Iturria‐Medina Y, Ducharme S. Data-driven staging of genetic frontotemporal dementia using multi-modal MRI. Hum Brain Mapp 2022; 43:1821-1835. [PMID: 35118777 PMCID: PMC8933323 DOI: 10.1002/hbm.25727] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 11/02/2021] [Accepted: 11/11/2021] [Indexed: 12/01/2022] Open
Abstract
Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high‐dimensional large‐scale population datasets to obtain individual scores of disease stage. We used cross‐sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting‐state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI‐obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre‐dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.
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Affiliation(s)
- Jillian McCarthy
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Raquel Sanchez‐Valle
- Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d'Investigacións Biomèdiques August Pi I SunyerUniversity of BarcelonaBarcelonaSpain
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of NeurologyDonostia University HospitalSan SebastianGipuzkoaSpain
- Neuroscience AreaBiodonostia Health Research InstituteSan SebastianGipuzkoaSpain
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de MédecineUniversité LavalQuebecQuebecCanada
| | - Caroline Graff
- Department of Geriatric MedicineKarolinska University Hospital‐HuddingeStockholmSweden
- Unit for Hereditary DementiasTheme Aging, Karolinska University HospitalSolnaSweden
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie‐Institute for Clinical Brain Research and Center of NeurologyUniversity of TübingenTübingenGermany
- Center for Neurodegenerative Diseases (DZNE)TübingenGermany
| | - Daniela Galimberti
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoNeurodegenerative Diseases UnitMilanItaly
- Department of Biomedical, Surgical, and Dental SciencesUniversity of Milan, Dino Ferrari CenterMilanItaly
| | - James B. Rowe
- University of Cambridge Department of Clinical NeurosciencesCambridge University Hospitals NHS Trust, and RC Cognition and Brain Sciences UnitCambridgeUK
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research InstituteUniversity of TorontoTorontoOntarioCanada
| | - Maria Carmela Tartaglia
- Toronto Western HospitalTanz Centre for Research in Neurodegenerative DiseaseTorontoOntarioCanada
| | - Elizabeth Finger
- Department of Clinical Neurological SciencesUniversity of Western OntarioLondonOntarioCanada
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of NeurosciencesKU LeuvenLeuvenBelgium
- Neurology ServiceUniversity Hospitals LeuvenBelgium
- Leuven Brain InstituteKU LeuvenLeuvenBelgium
| | | | - Fabrizio Tagliavini
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologico Carlo BestaMilanItaly
| | - Isabel Santana
- Neurology DepartmentCentro Hospitalar e Universitário de CoimbraCoimbraPortugal
- Center for Neuroscience and Cell Biology, Faculty of MedicineUniversity of CoimbraCoimbraPortugal
| | - Chris Butler
- Department of Clinical NeurologyUniversity of OxfordOxfordUK
- Department of Brain SciencesImperial College LondonUK
| | - Alex Gerhard
- Division of Neuroscience & Experimental Psychology, Faculty of Medicine, Biology, and HealthUniversity of ManchesterManchesterUK
- Departments of Geriatric Medicine and Nuclear MedicineEssen University HospitalEssenGermany
| | - Adrian Danek
- Ludwig‐Maximilians‐Universität MünchenMunichGermany
| | - Johannes Levin
- Ludwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Munich Cluster of Systems Neurology (SyNergy)MunichGermany
| | - Markus Otto
- Department of NeurologyUniversity Hospital UlmUlmGermany
| | - Giovanni Frisoni
- LANE ‐ Laboratory of Alzheimer's Neuroimaging and EpidemiologyIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- Memory Clinic and LANVIE‐Laboratory of Neuroimaging of AgingUniversity Hospitals and University of GenevaGenevaSwitzerland
| | - Roberta Ghidoni
- Molecular Markers LaboratoryIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Sandro Sorbi
- Department of NeurofarbaUniversity of FlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Lize C. Jiskoot
- Department of NeurologyErasmus University Medical CentreRotterdamNetherlands
| | - Harro Seelaar
- Department of NeurologyErasmus University Medical CentreRotterdamNetherlands
| | - John C. van Swieten
- Department of NeurologyErasmus University Medical CentreRotterdamNetherlands
| | - Jonathan D. Rohrer
- Department of Neurodegenerative Disease, Dementia Research CentreUCL Institute of NeurologyLondonUK
| | - Yasser Iturria‐Medina
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
- Neurology and Neurosurgery Department, Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
- Ludmer Centre for Neuroinformatics & Mental HealthMcGill UniversityMontrealCanada
| | - Simon Ducharme
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
- Douglas Mental Health University Institute, Department of PsychiatryMcGill UniversityMontrealCanada
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Ni R. Magnetic Resonance Imaging in Tauopathy Animal Models. Front Aging Neurosci 2022; 13:791679. [PMID: 35145392 PMCID: PMC8821905 DOI: 10.3389/fnagi.2021.791679] [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: 10/08/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer's disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.
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Affiliation(s)
- Ruiqing Ni
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
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48
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Savard M, Pascoal TA, Servaes S, Dhollander T, Iturria-Medina Y, Kang MS, Vitali P, Therriault J, Mathotaarachchi S, Benedet AL, Gauthier S, Rosa-Neto P. Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia. eLife 2022; 11:73510. [PMID: 35073256 PMCID: PMC8824472 DOI: 10.7554/elife.73510] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 01/23/2022] [Indexed: 11/21/2022] Open
Abstract
Recent studies suggest a framework where white-matter (WM) atrophy plays an important role in fronto-temporal dementia (FTD) pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of grey-matter (GM) atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Using a common factor analysis to extract a semantic and an executive factor, we aimed to test the relative contribution of WM and GM of specific tracts in predicting cognition in the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI). We found that semantic symptoms were mainly dependent on short-range WM fibre disruption, while damage to long-range WM fibres was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. These results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep WM disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.
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Affiliation(s)
- Melissa Savard
- Translational Neuroimaging Laboratory, McGill University
| | | | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University
| | | | | | - Min Su Kang
- Translational Neuroimaging Laboratory, McGill University
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, McGill University
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49
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Yang Z, Sheng X, Qin R, Chen H, Shao P, Xu H, Yao W, Zhao H, Xu Y, Bai F. Cognitive Improvement via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Amnesic Mild Cognitive Impairment Patients. J Alzheimers Dis 2022; 86:537-551. [PMID: 35068464 DOI: 10.3233/jad-215390] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Stimulating superficial brain regions highly associated with the hippocampus by repetitive transcranial magnetic stimulation (rTMS) may improve memory of Alzheimer’s disease (AD) spectrum patients. Objective: We recruited 16 amnesic mild cognitive impairment (aMCI) and 6 AD patients in the study. All the patients were stimulated to the left angular gyrus, which was confirmed a strong link to the hippocampus through neuroimaging studies, by the neuro-navigated rTMS for four weeks. Methods: Automated fiber quantification using diffusion tensor imaging metrics and graph theory analysis on functional network were employed to detect the neuroplasticity of brain networks. Results: After neuro-navigated rTMS intervention, the episodic memory of aMCI patients and Montreal Cognitive Assessment score of two groups were significantly improved. Increased FA values of right anterior thalamic radiation among aMCI patients, while decreased functional network properties of thalamus subregions were observed, whereas similar changes not found in AD patients. It is worth noting that the improvement of cognition was associated with the neuroplasticity of thalamic system. Conclusion: We speculated that the rTMS intervention targeting left angular gyrus may be served as a strategy to improve cognitive impairment at the early stage of AD patients, supporting by the neuroplasticity of thalamic system.
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Affiliation(s)
- Zhiyuan Yang
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Xiaoning Sheng
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Hengheng Xu
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Weina Yao
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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50
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Reyes-Leiva D, Dols-Icardo O, Sirisi S, Cortés-Vicente E, Turon-Sans J, de Luna N, Blesa R, Belbin O, Montal V, Alcolea D, Fortea J, Lleó A, Rojas-García R, Illán-Gala I. Pathophysiological Underpinnings of Extra-Motor Neurodegeneration in Amyotrophic Lateral Sclerosis: New Insights From Biomarker Studies. Front Neurol 2022; 12:750543. [PMID: 35115992 PMCID: PMC8804092 DOI: 10.3389/fneur.2021.750543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 12/09/2021] [Indexed: 11/13/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) lie at opposing ends of a clinical, genetic, and neuropathological continuum. In the last decade, it has become clear that cognitive and behavioral changes in patients with ALS are more frequent than previously recognized. Significantly, these non-motor features can impact the diagnosis, prognosis, and management of ALS. Partially overlapping neuropathological staging systems have been proposed to describe the distribution of TAR DNA-binding protein 43 (TDP-43) aggregates outside the corticospinal tract. However, the relationship between TDP-43 inclusions and neurodegeneration is not absolute and other pathophysiological processes, such as neuroinflammation (with a prominent role of microglia), cortical hyperexcitability, and synaptic dysfunction also play a central role in ALS pathophysiology. In the last decade, imaging and biofluid biomarker studies have revealed important insights into the pathophysiological underpinnings of extra-motor neurodegeneration in the ALS-FTLD continuum. In this review, we first summarize the clinical and pathophysiological correlates of extra-motor neurodegeneration in ALS. Next, we discuss the diagnostic and prognostic value of biomarkers in ALS and their potential to characterize extra-motor neurodegeneration. Finally, we debate about how biomarkers could improve the diagnosis and classification of ALS. Emerging imaging biomarkers of extra-motor neurodegeneration that enable the monitoring of disease progression are particularly promising. In addition, a growing arsenal of biofluid biomarkers linked to neurodegeneration and neuroinflammation are improving the diagnostic accuracy and identification of patients with a faster progression rate. The development and validation of biomarkers that detect the pathological aggregates of TDP-43 in vivo are notably expected to further elucidate the pathophysiological underpinnings of extra-motor neurodegeneration in ALS. Novel biomarkers tracking the different aspects of ALS pathophysiology are paving the way to precision medicine approaches in the ALS-FTLD continuum. These are essential steps to improve the diagnosis and staging of ALS and the design of clinical trials testing novel disease-modifying treatments.
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Affiliation(s)
- David Reyes-Leiva
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Oriol Dols-Icardo
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Sonia Sirisi
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Elena Cortés-Vicente
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Janina Turon-Sans
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Noemi de Luna
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Olivia Belbin
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Ricard Rojas-García
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Ignacio Illán-Gala
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
- *Correspondence: Ignacio Illán-Gala
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