Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies.
amyotrophic lateral sclerosis
frontotemporal lobar degeneration
limbic-predominant age-related TDP-43 encephalopathy
machine learning
neuropathological staging
Journal
Brain : a journal of neurology
ISSN: 1460-2156
Titre abrégé: Brain
Pays: England
ID NLM: 0372537
Informations de publication
Date de publication:
03 07 2023
03 07 2023
Historique:
received:
31
01
2023
revised:
27
03
2023
accepted:
16
04
2023
medline:
5
7
2023
pubmed:
8
5
2023
entrez:
8
5
2023
Statut:
ppublish
Résumé
TAR DNA-binding protein-43 (TDP-43) accumulation is the primary pathology underlying several neurodegenerative diseases. Charting the progression and heterogeneity of TDP-43 accumulation is necessary to better characterize TDP-43 proteinopathies, but current TDP-43 staging systems are heuristic and assume each syndrome is homogeneous. Here, we use data-driven disease progression modelling to derive a fine-grained empirical staging system for the classification and differentiation of frontotemporal lobar degeneration due to TDP-43 (FTLD-TDP, n = 126), amyotrophic lateral sclerosis (ALS, n = 141) and limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) with and without Alzheimer's disease (n = 304). The data-driven staging of ALS and FTLD-TDP complement and extend previously described human-defined staging schema for ALS and behavioural variant frontotemporal dementia. In LATE-NC individuals, progression along data-driven stages was positively associated with age, but negatively associated with age in individuals with FTLD-TDP. Using only regional TDP-43 severity, our data driven model distinguished individuals diagnosed with ALS, FTLD-TDP or LATE-NC with a cross-validated accuracy of 85.9%, with misclassifications associated with mixed pathological diagnosis, age and genetic mutations. Adding age and SuStaIn stage to this model increased accuracy to 92.3%. Our model differentiates LATE-NC from FTLD-TDP, though some overlap was observed between late-stage LATE-NC and early-stage FTLD-TDP. We further tested for the presence of subtypes with distinct regional TDP-43 progression patterns within each diagnostic group, identifying two distinct cortical-predominant and brainstem-predominant subtypes within FTLD-TDP and a further two subcortical-predominant and corticolimbic-predominant subtypes within ALS. The FTLD-TDP subtypes exhibited differing proportions of TDP-43 type, while there was a trend for age differing between ALS subtypes. Interestingly, a negative relationship between age and SuStaIn stage was seen in the brainstem/subcortical-predominant subtype of each proteinopathy. No subtypes were observed for the LATE-NC group, despite aggregating individuals with and without Alzheimer's disease and a larger sample size for this group. Overall, we provide an empirical pathological TDP-43 staging system for ALS, FTLD-TDP and LATE-NC, which yielded accurate classification. We further demonstrate that there is substantial heterogeneity amongst ALS and FTLD-TDP progression patterns that warrants further investigation in larger cross-cohort studies.
Identifiants
pubmed: 37150879
pii: 7156599
doi: 10.1093/brain/awad145
pmc: PMC10317181
doi:
Substances chimiques
DNA-Binding Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2975-2988Subventions
Organisme : NIMH NIH HHS
ID : T32 MH019112
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG062418
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS109260
Pays : United States
Organisme : NIA NIH HHS
ID : P01 AG066597
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG072979
Pays : United States
Commentaires et corrections
Type : UpdateOf
Type : CommentIn
Informations de copyright
© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.
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