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Scotton WJ, Shand C, Todd EG, Bocchetta M, Cash DM, VandeVrede L, Heuer HW, Young AL, Oxtoby N, Alexander DC, Rowe JB, Morris HR, Boxer AL, Rohrer JD, Wijeratne PA. Distinct spatiotemporal atrophy patterns in corticobasal syndrome are associated with different underlying pathologies. medRxiv 2024:2024.03.14.24304298. [PMID: 38562801 PMCID: PMC10984071 DOI: 10.1101/2024.03.14.24304298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Objective To identify imaging subtypes of the cortico-basal syndrome (CBS) based solely on a data-driven assessment of MRI atrophy patterns, and investigate whether these subtypes provide information on the underlying pathology. Methods We applied Subtype and Stage Inference (SuStaIn), a machine learning algorithm that identifies groups of individuals with distinct biomarker progression patterns, to a large cohort of 135 CBS cases (52 had a pathological or biomarker defined diagnosis) and 252 controls. The model was fit using volumetric features extracted from baseline T1-weighted MRI scans and validated using follow-up MRI. We compared the clinical phenotypes of each subtype and investigated whether there were differences in associated pathology between the subtypes. Results SuStaIn identified two subtypes with distinct sequences of atrophy progression; four-repeat-tauopathy confirmed cases were most commonly assigned to the Subcortical subtype (83% of CBS-PSP and 75% of CBS-CBD), while CBS-AD was most commonly assigned to the Fronto-parieto-occipital subtype (81% of CBS-AD). Subtype assignment was stable at follow-up (98% of cases), and individuals consistently progressed to higher stages (100% stayed at the same stage or progressed), supporting the model's ability to stage progression. Interpretation By jointly modelling disease stage and subtype, we provide data-driven evidence for at least two distinct and longitudinally stable spatiotemporal subtypes of atrophy in CBS that are associated with different underlying pathologies. In the absence of sensitive and specific biomarkers, accurately subtyping and staging individuals with CBS at baseline has important implications for screening on entry into clinical trials, as well as for tracking disease progression.
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Affiliation(s)
- W J Scotton
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - C Shand
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - E G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - M Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London 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
| | - D M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - L VandeVrede
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - H W Heuer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - A L Young
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - N Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - D C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - J B Rowe
- Cambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust
- Medical Research Council Cognition and Brain Sciences Unit, Cambridge UK
| | - H R Morris
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
- Movement Disorders Centre, University College London Queen Square Institute of Neurology, London, UK
| | - A L Boxer
- 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
| | - J D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - P A Wijeratne
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Department of Informatics, University of Sussex, Brighton, BN1 9RH, UK
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Alexander DM, Williams LM, Gatt JM, Dobson-Stone C, Kuan SA, Todd EG, Schofield PR, Cooper NJ, Gordon E. The contribution of apolipoprotein E alleles on cognitive performance and dynamic neural activity over six decades. Biol Psychol 2007; 75:229-38. [PMID: 17433528 DOI: 10.1016/j.biopsycho.2007.03.001] [Citation(s) in RCA: 104] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2006] [Revised: 03/08/2007] [Accepted: 03/08/2007] [Indexed: 10/23/2022]
Abstract
Neuroimaging shows brain-functional differences due to apolipoprotein E (APOE) polymorphisms may exist decades before the increased risk period for Alzheimer's disease, but little is known about their effect on cognition and brain function in children and young adults. This study assessed 415 healthy epsilon2 and epsilon4 carriers and matched epsilon3/epsilon3 controls, spanning ages 6-65, on a range of cognitive tests. Subjects were also compared on a new dynamical measure of EEG activity during a visual working memory task using alphabetical stimuli. epsilon4 subjects had better verbal fluency compared to epsilon3, an effect that was strongest in 51-65 year-olds. No epsilon4 deficits in cognition were found. In 6-15 year-olds, there were differences in total spatio-temporal wave activity between epsilon3 and epsilon4 subjects in the theta band, approximately 200ms post-stimulus. Differences in brain function in younger epsilon4 subjects and superior verbal fluency across the entire age range suggest that the APOE epsilon4 allele is an example of antagonistic pleiotropy.
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Affiliation(s)
- D M Alexander
- Brain Resource Company and Brain Resource International Database, PO Box 737, Broadway, NSW 2007, Australia.
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