TY - JOUR
T1 - Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies
AU - Young, Alexandra L.
AU - Vogel, Jacob W.
AU - Robinson, John L.
AU - McMillan, Corey T.
AU - Ossenkoppele, Rik
AU - Wolk, David A.
AU - Irwin, David J.
AU - Elman, Lauren
AU - Grossman, Murray
AU - Lee, Virginia M. -Y.
AU - Lee, Edward B.
AU - Hansson, Oskar
N1 - Funding Information: A.L.Y. is supported by a Skills Development Fellowship from the Medical Research Council (MRC) [MR/T027800/1]. J.W.V. acknowledges funding from the National Institutes of Health (NIH) (T32MH019112) and the SciLifeLab & Wallenberg Data Driven Life Science Program (grant: KAW 2020.0239). R.O. has received research funding from European Research Council, ZonMw, NWO, National Institute of Health, Alzheimer Association, Alzheimer Nederland, Stichting Dioraphte, Cure Alzheimer’s fund, Health Holland, ERA PerMed, Alzheimerfonden, Hjarnfonden. D.J.I. was supported by NIH grant R01-NS109260. This work was supported by the Penn Udall Center of Excellence in Parkinson's Disease Research, the Penn Center for Neurodegenerative Disease Research, and the Department of Pathology and Laboratory Medicine of the Penn Alzheimer’s Disease Research Center. The current work and other research at these centres were supported by the NIH (P30 AG072979, P01AG066597, U19AG062418). O.H. was supported by the Swedish Research Council (2016-00906), the Knut and Alice Wallenberg foundation (2017-0383), the Marianne and Marcus Wallenberg foundation (2015.0125), the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932), the Swedish Brain Foundation (FO2021-0293), The Parkinson foundation of Sweden (1280/20), the Cure Alzheimer’s fund, the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, the Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2020-0314) and the Swedish federal government under the ALF agreement (2018-Projekt0279). Funding Information: We would like to acknowledge the late John Q. Trojanowski, MD, PhD, who also participated in study design and interpretation of results. We thank Manuela Neumann and Elisabeth Kremmer for providing the phosphorylation-specific TDP-43 antibody 1D3. A.L.Y. is supported by a Skills Development Fellowship from the Medical Research Council (MRC) [MR/T027800/1]. J.W.V. acknowledges funding from the National Institutes of Health (NIH) (T32MH019112) and the SciLifeLab & Wallenberg Data Driven Life Science Program (grant: KAW 2020.0239). R.O. has received research funding from European Research Council, ZonMw, NWO, National Institute of Health, Alzheimer Association, Alzheimer Nederland, Stichting Dioraphte, Cure Alzheimer’s fund, Health Holland, ERA PerMed, Alzheimerfonden, Hjarnfonden. D.J.I. was supported by NIH grant R01-NS109260. This work was supported by the Penn Udall Center of Excellence in Parkinson’s Disease Research, the Penn Center for Neurodegenerative Disease Research, and the Department of Pathology and Laboratory Medicine of the Penn Alzheimer’s Disease Research Center. The current work and other research at these centres were supported by the NIH (P30 AG072979, P01AG066597, U19AG062418). O.H. was supported by the Swedish Research Council (2016-00906), the Knut and Alice Wallenberg foundation (2017-0383), the Marianne and Marcus Wallenberg foundation (2015.0125), the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932), the Swedish Brain Foundation (FO2021-0293), The Parkinson foundation of Sweden (1280/20), the Cure Alzheimer’s fund, the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, the Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2020-0314) and the Swedish federal government under the ALF agreement (2018-Projekt0279). Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - amyotrophic lateral sclerosis
KW - frontotemporal lobar degeneration
KW - limbic-predominant age-related TDP-43 encephalopathy
KW - machine learning
KW - neuropathological staging
UR - http://www.scopus.com/inward/record.url?scp=85163075205&partnerID=8YFLogxK
U2 - https://doi.org/10.1093/brain/awad145
DO - https://doi.org/10.1093/brain/awad145
M3 - Article
C2 - 37150879
SN - 0006-8950
VL - 146
SP - 2975
EP - 2988
JO - Brain
JF - Brain
IS - 7
ER -