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Jia H, Li Z, Guo F, Hua Z, Zhou X, Li X, Li R, Liu Q, Liu Y, Dong H. Cortical structure and the risk of amyotrophic lateral sclerosis: A bidirectional Mendelian randomization study. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110872. [PMID: 37827425 DOI: 10.1016/j.pnpbp.2023.110872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 09/06/2023] [Accepted: 10/08/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Current observational studies indicate progressive brain atrophy is closely associated with the clinical feature of amyotrophic lateral sclerosis. However, it is unclear whether the changes in cortical structure are the cause or result of ALS. Our study aimed to investigate the causal relationship between cortical structure and ALS risk using a bidirectional two-sample MR study. METHODS We collected publicly available genome-wide association studies' summary statistics for cortical structure from UK Biobank and ENIGMA consortium (n = 33,992) and ALS from the Project MinE (n = 138,086). We used the inverse variance weighted method (IVW) as primary analysis in order to evaluate the causal effects. In addition, the weighted median and MR Egger methods were performed to ensure the robustness and reliability of the IVW results. RESULTS We found the decreased surface of the paracentral lobule and thickness of the frontal pole and middle temporal lobe were suggestively associated with an increased risk of ALS as well as the increased surface of medial orbitofrontal and middle temporal lobe. In another aspect, the causalities between the susceptibility to ALS and the volume of the transverse temporal gyrus and superior temporal gyrus were negative. Besides, the susceptibility to ALS might also contribute to an increased thickness of the postcentral gyrus and superior parietal gyrus. CONCLUSION In this two-sample MR analysis, we observed that multiple cortical brain regions are associated with a higher ALS risk. Further research into the underlying mechanisms is required to back up our findings.
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Affiliation(s)
- Hongning Jia
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China; Department of Neurology, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Zhiguang Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; Department of Neurology, Xingtai Third Hospital, Xingtai, China
| | - Fei Guo
- Department of Basic Medicine, Xingtai Medical College, Xingtai, China
| | - Zixin Hua
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Xiaomeng Zhou
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Xin Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Rui Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Qi Liu
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Yaling Liu
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China.
| | - Hui Dong
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China.
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2
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Alosco ML, White M, Bell C, Faheem F, Tripodis Y, Yhang E, Baucom Z, Martin B, Palmisano J, Dams-O'Connor K, Crary JF, Goldstein LE, Katz DI, Dwyer B, Daneshvar DH, Nowinski C, Cantu RC, Kowall NW, Stern RA, Alvarez VE, Huber BR, Stein TD, McKee AC, Mez J. Cognitive, functional, and neuropsychiatric correlates of regional tau pathology in autopsy-confirmed chronic traumatic encephalopathy. Mol Neurodegener 2024; 19:10. [PMID: 38317248 PMCID: PMC10845638 DOI: 10.1186/s13024-023-00697-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/11/2023] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease characterized by hyperphosphorylated tau (p-tau) accumulation. The clinical features associated with CTE pathology are unclear. In brain donors with autopsy-confirmed CTE, we investigated the association of CTE p-tau pathology density and location with cognitive, functional, and neuropsychiatric symptoms. METHODS In 364 brain donors with autopsy confirmed CTE, semi-quantitative p-tau severity (range: 0-3) was assessed in 10 cortical and subcortical regions. We summed ratings across regions to form a p-tau severity global composite (range: 0-30). Informants completed standardized scales of cognition (Cognitive Difficulties Scale, CDS; BRIEF-A Metacognition Index, MI), activities of daily living (Functional Activities Questionnaire), neurobehavioral dysregulation (BRIEF-A Behavioral Regulation Index, BRI; Barratt Impulsiveness Scale, BIS-11), aggression (Brown-Goodwin Aggression Scale), depression (Geriatric Depression Scale-15, GDS-15), and apathy (Apathy Evaluation Scale, AES). Ordinary least squares regression models examined associations between global and regional p-tau severity (separate models for each region) with each clinical scale, adjusting for age at death, racial identity, education level, and history of hypertension, obstructive sleep apnea, and substance use treatment. Ridge regression models that incorporated p-tau severity across all regions in the same model assessed which regions showed independent effects. RESULTS The sample was predominantly American football players (333; 91.2%); 140 (38.5%) had low CTE and 224 (61.5%) had high CTE. Global p-tau severity was associated with higher (i.e., worse) scores on the cognitive and functional scales: MI ([Formula: see text] standardized = 0.02, 95%CI = 0.01-0.04), CDS ([Formula: see text] standardized = 0.02, 95%CI = 0.01-0.04), and FAQ ([Formula: see text] standardized = 0.03, 95%CI = 0.01-0.04). After false-discovery rate correction, p-tau severity in the frontal, inferior parietal, and superior temporal cortex, and the amygdala was associated with higher CDS ([Formula: see text] sstandardized = 0.17-0.29, ps < 0.01) and FAQ ([Formula: see text] sstandardized = 0.21-0.26, ps < 0.01); frontal and inferior parietal cortex was associated with higher MI ([Formula: see text] sstandardized = 0.21-0.29, ps < 0.05); frontal cortex was associated with higher BRI ([Formula: see text] standardized = 0.21, p < 0.01). Regions with effects independent of other regions included frontal cortex (CDS, MI, FAQ, BRI), inferior parietal cortex (CDS) and amygdala (FAQ). P-tau explained 13-49% of variance in cognitive and functional scales and 6-14% of variance in neuropsychiatric scales. CONCLUSION Accumulation of p-tau aggregates, especially in the frontal cortex, are associated with cognitive, functional, and certain neurobehavioral symptoms in CTE.
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Affiliation(s)
- Michael L Alosco
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Micaela White
- Davis School of Medicine, University of California, Sacramento, CA, USA
| | - Carter Bell
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA
| | - Farwa Faheem
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Eukyung Yhang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Zachary Baucom
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph Palmisano
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Kristen Dams-O'Connor
- Department of Rehabilitation and Human Performance, Brain Injury Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Crary
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lee E Goldstein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Departments of Biomedical, Electrical & Computer Engineering, Boston University College of Engineering, Boston, MA, USA
| | - Douglas I Katz
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Braintree Rehabilitation Hospital, Braintree, MA, USA
| | - Brigid Dwyer
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Braintree Rehabilitation Hospital, Braintree, MA, USA
| | - Daniel H Daneshvar
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA
| | - Christopher Nowinski
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Concussion Legacy Foundation, Boston, MA, USA
| | - Robert C Cantu
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Concussion Legacy Foundation, Boston, MA, USA
- Department of Neurosurgery, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurosurgery, Emerson Hospital, Concord, MA, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurosurgery, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Victor E Alvarez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- System, U.S. Department of Veteran Affairs, VA Boston Healthcare, Boston, MA, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Bertrand Russell Huber
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- System, U.S. Department of Veteran Affairs, VA Boston Healthcare, Boston, MA, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- System, U.S. Department of Veteran Affairs, VA Boston Healthcare, Boston, MA, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- System, U.S. Department of Veteran Affairs, VA Boston Healthcare, Boston, MA, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
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3
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Eldaief MC, Brickhouse M, Katsumi Y, Rosen H, Carvalho N, Touroutoglou A, Dickerson BC. Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks. Brain 2023; 146:4476-4485. [PMID: 37201288 PMCID: PMC10629759 DOI: 10.1093/brain/awad167] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 04/10/2023] [Accepted: 04/16/2023] [Indexed: 05/20/2023] Open
Abstract
The identification of a neurodegenerative disorder's distributed pattern of atrophy-or atrophy 'signature'-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.
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Affiliation(s)
- Mark C Eldaief
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Michael Brickhouse
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Yuta Katsumi
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Howard Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nicole Carvalho
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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4
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Abrahams S. Neuropsychological impairment in amyotrophic lateral sclerosis-frontotemporal spectrum disorder. Nat Rev Neurol 2023; 19:655-667. [PMID: 37828358 DOI: 10.1038/s41582-023-00878-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2023] [Indexed: 10/14/2023]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with a rapid course, characterized by motor neuron dysfunction, leading to progressive disability and death. This Review, which is aimed at neurologists, psychologists and other health professionals who follow evidence-based practice relating to ALS and frontotemporal dementia (FTD), examines the neuropsychological evidence that has driven the reconceptualization of ALS as a spectrum disorder ranging from a pure motor phenotype to ALS-FTD. It focuses on changes in cognition and behaviour, which vary in severity across the spectrum: around 50% individuals with ALS are within the normal range, 15% meet the criteria for ALS-FTD, and the remaining 35% are in the mid-spectrum range with milder and more focal impairments. The cognitive impairments include deficits in verbal fluency, executive functions, social cognition and language, and apathy is the most prevalent behavioural change. The pattern and severity of cognitive and behavioural change predicts underlying regional cerebral dysfunction from brain imaging and post-mortem pathology. Our increased recognition of cognition and behaviour as part of the ALS phenotype has led to the development and standardization of assessment tools, which have been incorporated into research and clinical care. Measuring change over the course of the disease is vital for clinical trials, and neuropsychology is proving to be a biomarker for the earliest preclinical changes.
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Affiliation(s)
- Sharon Abrahams
- Human Cognitive Neuroscience, Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK.
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK.
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5
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Bussy A, Levy JP, Best T, Patel R, Cupo L, Van Langenhove T, Nielsen JE, Pijnenburg Y, Waldö ML, Remes AM, Schroeter ML, Santana I, Pasquier F, Otto M, Danek A, Levin J, Le Ber I, Vandenberghe R, Synofzik M, Moreno F, de Mendonça A, Sanchez-Valle R, Laforce R, Langheinrich T, Gerhard A, Graff C, Butler CR, Sorbi S, Jiskoot L, Seelaar H, van Swieten JC, Finger E, Tartaglia MC, Masellis M, Tiraboschi P, Galimberti D, Borroni B, Rowe JB, Bocchetta M, Rohrer JD, Devenyi GA, Chakravarty MM, Ducharme S. Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia. Hum Brain Mapp 2023; 44:2684-2700. [PMID: 36895129 PMCID: PMC10089095 DOI: 10.1002/hbm.26220] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 03/11/2023] Open
Abstract
Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.
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Affiliation(s)
- Aurélie Bussy
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Jake P Levy
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Tristin Best
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Raihaan Patel
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Lani Cupo
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | | | - Jørgen E Nielsen
- Neurogenetics Clinic & Research Lab, Danish Dementia Research Centre, Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria Landqvist Waldö
- Division of Clinical Sciences Helsingborg, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Anne M Remes
- Research Unit of Clinical Medicine, Neurology, University of Oulu, Finland
- Medical Research Center, Oulu University Hospital, Oulu, Finland
| | - Matthias L Schroeter
- Clinic for Cognitive Neurology, University Clinic Leipzig, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Clinic Leipzig, Leipzig, Germany
| | - Isabel Santana
- University Hospital of Coimbra (HUC), Neurology Service, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Florence Pasquier
- Universite de Lille, Lille, France
- Inserm 1172, Lille, France
- CHU, CNR-MAJ, Labex Distalz, Lille, France
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Adrian Danek
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
| | - Johannes Levin
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute-Institut du Cerveau-ICM, Inserm U1127, Paris, France
- Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
- Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Rik Vandenberghe
- Department of Neurosciences, Laboratory for Cognitive Neurology, Leuven, Belgium
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
| | - Fermin Moreno
- Neuroscience Area, Biodonostia Health Research Institute, San Sebastian, Spain
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain
| | | | - 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
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, Quebec, Canada
| | - Tobias Langheinrich
- Division of Neuroscience, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Cerebral Function Unit, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK
| | - Alexander Gerhard
- Division of Neuroscience, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg, Essen, Germany
| | - Caroline Graff
- Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden
- Unit for Hereditary Dementias, Theme Inflammation and Aging, Karolinska University Hospital, Solna, Sweden
| | - Chris R Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Sandro Sorbi
- Department of Neurofarba, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Lize Jiskoot
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Harro Seelaar
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | | | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | | | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Centre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
| | | | - Gabriel A Devenyi
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - M Mallar Chakravarty
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Simon Ducharme
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Wang Y, Shen D, Hou B, Sun X, Yang X, Gao J, Liu M, Feng F, Cui L. Brain structural and perfusion changes in amyotrophic lateral sclerosis-frontotemporal dementia patients with cognitive and motor onset: a preliminary study. Brain Imaging Behav 2022; 16:2164-2174. [PMID: 35838935 DOI: 10.1007/s11682-022-00686-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2022] [Indexed: 11/27/2022]
Abstract
Amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD) is rare but exhibits worse prognosis than either ALS or FTD alone. However, cognitive onset ALS-FTD (ALS-FTD-C) confers significantly better patient survival than does motor onset ALS-FTD (ALS-FTD-M), underscoring a meager understanding of pathological group differences. This study aimed to assess disparities in cortical atrophy and perfusion shown by patients with the above disease variants. A total of 38 participants (ALS-FTD-C, 8; ALS-FTD-M, 6; simultaneous-onset ALS-FTD [ALS-FTD-S], 4; healthy controls [HC], 20) qualified for the study and underwent magnetic resonance imaging scan. Three-dimensional T1-weighted structural brain imaging and 3D-pseudocontinuous arterial spin-labeled imaging were routinely collected. Gray matter volume (GMV) and cerebral blood flow (CBF) in ALS-FTD-C and ALS-FTD-M were compared through voxel-based analysis. Correlations between imaging parameters and clinical data were also assessed. Compared with HC, ALS-FTD had significant GMV reduction mainly in bilateral limbic system. GMV reduction in ALS-FTD-C was similar in pattern but less widespread, whereas ALS-FTD-M lacked any significant GMV reduction. In CBF analyses, ALS-FTD displayed hypoperfusion in bilateral motor cortex, frontotemporal lobe, and left basal ganglia. Hypoperfusion involved bilateral temporal lobe, prefrontal cortex, and putamen in ALS-FTD-C but was limited to left parahippocampal gyrus in ALS-FTD-M. Correlations between clinical data and GMV/CBF changes in specific regions were also identified in ALS-FTD. Group-specific patterns of cortical atrophy and perfusion were evident in ALS-FTD-C and ALS-FTD-M. ALS-FTD-C showed pronounced cortical atrophy and hypoperfusion, which were otherwise minimal in ALS-FTD-M. Above findings preliminarily revealed the pathological group differences that may help in classifying patients with ALS-FTD.
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Affiliation(s)
- Yanying Wang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Dongchao Shen
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Bo Hou
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Xiaohan Sun
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Xunzhe Yang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Jing Gao
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Mingsheng Liu
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Liying Cui
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China.
- Neuroscience Centre, Chinese Academy of Medical Sciences, Beijing, China.
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Kocar TD, Müller HP, Ludolph AC, Kassubek J. Feature selection from magnetic resonance imaging data in ALS: a systematic review. Ther Adv Chronic Dis 2021; 12:20406223211051002. [PMID: 34729157 PMCID: PMC8521429 DOI: 10.1177/20406223211051002] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/15/2021] [Indexed: 12/23/2022] Open
Abstract
Background: With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection. Methods: We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported. Results: Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS. Conclusions: These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.
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Affiliation(s)
- Thomas D Kocar
- Department of Neurology, University of Ulm, Ulm, Germany
| | | | - Albert C Ludolph
- Department of Neurology, University of Ulm, Ulm, Germany Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Oberer Eselsberg 45, 89081 Ulm, Germany
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Galvin JE, Cohen I, Greenfield KK, Walker M. The Frontal Behavioral Battery: A Measure of Frontal Lobe Symptoms in Brain Aging and Neurodegenerative Disease. J Alzheimers Dis 2021; 83:721-739. [PMID: 34366351 PMCID: PMC10731583 DOI: 10.3233/jad-210446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Approximately 90%of persons living with dementia experience behavioral symptoms, including frontal lobe features involving motivation, planning, social behavior, language, personality, mood, swallowing, and gait. OBJECTIVE We conducted a two-stage study with a development sample (n = 586) and validation sample (n = 274) to evaluate a brief informant-rated measure of non-cognitive features of frontal lobe dysfunction: the Frontal Behavioral Battery (FBB). METHODS In the development sample, internal consistency, principal factor analysis, and correlations between the FBB and outcomes were evaluated. In the validation sample, we examined (a) FBB scores by diagnosis, (b) known-group validity by demographics, subjective complaints, and dementia staging, and (c) correlation between FBB and MRI volumes. Receiver operator characteristic curves assessed the ability of the FBB to discriminate individuals with frontal lobe features due to a neurodegenerative disease. RESULTS The FBB characterized 11 distinct frontal lobe features. Individuals with dementia with Lewy bodies and frontotemporal degeneration had the greatest number of frontal lobe features. Premorbid personality traits of extroversion, agreeableness, and openness were associated with fewer frontal lobe behavioral symptoms, while subjective cognitive complaints were associated with greater symptoms. The FBB provided very good discrimination between individuals with and without cognitive impairment (diagnostic odds ratio: 13.1) and between individuals with and without prominent frontal lobe symptoms (diagnostic odds ratio: 84.8). CONCLUSION The FBB may serve as an effective and efficient method to assess the presence of non-cognitive symptoms associated with frontal lobe dysfunction, but in a brief fashion that could facilitate its use in clinical care and research.
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Affiliation(s)
- James E. Galvin
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Iris Cohen
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Keri K. Greenfield
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Marcia Walker
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
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