ArticlemedRxiv : the preprint server for health sciences2024
Distinct spatiotemporal atrophy patterns in corticobasal syndrome are associated with different underlying pathologies.
W J Scotton, C Shand, E G Todd, M Bocchetta, D M Cash, L VandeVrede, H W Heuer, A L Young, N Oxtoby, D C Alexander and 7 more
Abstract readPreprint
In one paragraphArticle in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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What it found
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2 · The registryThe trial behind it
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3 · Its place in the literatureWho cites it
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4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
17 authors.
W J ScottonDementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-0607-3190 C ShandCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.ORCID 0000-0002-1299-890X E G ToddDementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK.
M BocchettaDementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-1814-5024 D M CashDementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0001-7833-616X L VandeVredeDepartment of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA.
H W HeuerDepartment of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA.
A L YoungCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
N OxtobyCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
D C AlexanderCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.ORCID 0000-0003-2439-350X J B RoweCambridge University Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust.ORCID 0000-0001-7216-8679 H R MorrisDepartment of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK.ORCID 0000-0002-5473-3774 PROSPECT Consortium
A L BoxerCentre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK.
4RTNI Consortium
J D RohrerDementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0002-6155-8417 P A WijeratneCentre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
Funding
The Alzheimer's Clinical Trial Consortium - Down Syndrome Network (ACTC- DSN)U24AG057437 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Paul S. Aisen, RONALD C PETERSEN · 2018 to 2026
$198.4MTechnology and Remote Assessment CoreU19AG063911 · NIA · MAYO CLINIC ROCHESTER · PI KEJAL KANTARCI · 2019 to 2026
$120.9MTDP-43 Loss-of-Function: Biology to BiomarkersP01AG019724 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jennifer Merrilees · 2002 to 2026
$67.2MThe Alzheimer's Disease Tau Platform Clinical TrialR01AG078457 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOXER, ADAM L., JOHNSON, KEITH A. · 2023 to 2024
$60.7MThe Four Repeat Tauopathy Neuroimaging InitiativeR01AG038791 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOXER, ADAM L. · 2010 to 2020
$18.1MBiomarker Evaluation in Young Onset Dementia from Diverse Populations (BEYONDD)R56AG075744 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOXER, ADAM L., BYRD, DESIREE A · 2022 to 2022
$6.1MNeurodevelopment in children from families with genetic frontotemporal dementia and Alzheimer’s diseaseR01AG071756 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SUZEE EURIE LEE · 2022 to 2026
$4.1MVeri-T: A phase 1 Placebo-Controlled Trial of Verdiperstat in Semantic Variant Primary Progressive Aphasia Due to Underlying FTLD-TDPR01AG073482 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ADAM L. BOXER, Peter Alexander Ljubenkov · 2021 to 2026
$3.3MValidating remote digital assessments for familial frontotemporal dementiaRF1AG077557 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STAFFARONI, ADAM MARK · 2022 to 2022
$2.4MValidation of Novel Plasma Biomarkers for Mixed Etiology DementiaK23AG073514 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VANDEVREDE, LAWREN · 2021 to 2025
$1.0MNIA NIH HHS K23 AG073514NIA NIH HHS P01 AG019724NIA NIH HHS R01 AG038791NIA NIH HHS R01 AG071756NIA NIH HHS R01 AG073482NIA NIH HHS R01 AG078457NIA NIH HHS R56 AG075744NIA NIH HHS RF1 AG077557NIA NIH HHS U19 AG063911NIA NIH HHS U24 AG057437Wellcome Trust
6 · The paper itselfAbstract
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 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.
Indexed as
biomarkersCortico-basal syndromedisease progressionmachine learningSubtype and Stage Inference
Identifiers
PMID38562801
PMCPMC10984071
What OpenQuestion holds
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