UCL Discovery Stage
UCL home » Library Services » Electronic resources » UCL Discovery Stage

Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies

Young, Alexandra L; Vogel, Jacob W; Robinson, John L; McMillan, Corey T; Ossenkoppele, Rik; Wolk, David A; Irwin, David J; ... Hansson, Oskar; + view all (2023) Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies. Brain , 146 (7) pp. 2975-2988. 10.1093/brain/awad145. Green open access

[thumbnail of awad145.pdf]
Preview
PDF
awad145.pdf - Published Version

Download (1MB) | Preview

Abstract

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.

Type: Article
Title: Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/brain/awad145
Publisher version: https://doi.org/10.1093/brain/awad145
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Science & Technology, Life Sciences & Biomedicine, Clinical Neurology, Neurosciences, Neurosciences & Neurology, machine learning, neuropathological staging, limbic-predominant age-related TDP-43 encephalopathy, amyotrophic lateral sclerosis, frontotemporal lobar degeneration, FRONTOTEMPORAL LOBAR DEGENERATION, AMYOTROPHIC-LATERAL-SCLEROSIS, PATHOLOGICAL HETEROGENEITY, HEXANUCLEOTIDE REPEAT, ALZHEIMERS-DISEASE, PTDP-43 PATHOLOGY, ATROPHY PATTERNS, CLASSIFICATION, DEMENTIA, EXPANSION
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10176450
Downloads since deposit
1,479Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item