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Data-driven modelling of tau pathology reveals distinct progressive supranuclear palsy subtypes.

Overview

Authors: Patrick W Cullinane1,2,3,4, Jacy Bezerra Parmera2,5, Hemanth Nelvagal1,2, Toby Curless2, Leckhna Paras Chajed2, Sarah Wrigley1,3, Walter Sifontes Valladares2, Maggie Burrows1,2, Kirsten Ebanks1,2, Lesley Wu1, Lawrence P Binding6, Jaime Anton1,2, Tamas Revesz2,7, Raquel Real1,4, David P Vaughan1, Edwin Jabbari1, Huw R Morris1,4, Sebastian Brandner7,8, Alexandra L Young6, Glen Hoti2
and 7 other authorsYangxinrui Ma2, Mariam Bechtawi1,2, Nancy Chiraki1,2, Eduardo de Pablo-Fernández1,2,3,9, Yau Mun Lim7,8, Thomas T Warner1,2,3,4, Zane Jaunmuktane1,2,3,8
  1. Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
  2. Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
  3. Reta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
  4. Queen Square Movement Disorders Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
  5. Department of Neurology, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo (HC-FMUSP), São Paulo 05402 000, Brazil
  6. UCL Hawkes Institute, Department of Computer Science, University College London, London WC1V 6LJ, UK
  7. Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
  8. Division of Neuropathology, National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London WC1N 3BG, UK
  9. Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London EC1M 6BQ, UK
Journal: Brain : a journal of neurology, volume 149, issue 9, pages 3080-3094
Dates: received 2 August 2025; accepted 19 March 2026; published online 13 April 2026; in print September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1093/brain/awag131 · PMID 41974128 · PMCID PMC13548875 · OpenAlex W4413030704
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), Alzheimer's / dementia (population)
Methods: Statistics, Machine learning, Preprocessing, Connectivity, fMRI & imaging
Keywords: tauopathy, phenotypic heterogeneity, machine learning, disease progression modelling
MeSH: Brain*, Supranuclear Palsy, Progressive*, tau Proteins*, Aged, Aged, 80 and over, Disease Progression, Female, Humans, Male, Middle Aged, Phenotype, Tauopathies (* major topic)
Topic: Parkinson's Disease Mechanisms and Treatments (Neurology, Medicine), according to OpenAlex
Funding: Medical Research Council (MR/T018569/1); Edmond J. Safra Foundation; UKRI; Wellcome Trust (227341/Z/23/Z); Edmond J. Safra Philanthropic Foundation; Parkinson's UK; Reta Lila Weston Trust; Reta Lila Weston Trust for Medical Research
Citations: cited by 1 paper (Europe PMC); 74 references in the paper
Notices: A comment on this paper has been published (42560124, from Europe PMC)

Abstract

Progressive supranuclear palsy (PSP) is a heterogeneous neurodegenerative disease characterized by the accumulation of misfolded 4-repeat tau within neurons and glial cells. There are limited longitudinal data on pathologically confirmed PSP patients with phenotypes other than classic Richardson’s syndrome (RS) and the pathomechanisms responsible for the broad variability in clinical phenotype and progression are not well understood. An unresolved question in this context is whether distinct spatiotemporal patterns of tau pathology propagation exist within the clinicopathological spectrum of PSP.

We included 241 consecutive, pathologically confirmed patients with PSP from the Queen Square Brain Bank for Neurological Disorders (2010–2022). Phenotyping was performed based on clinical features present within the first 3 years from symptom onset according to the Movement Disorder Society (MDS) criteria, and specific clinical features and disease milestones were recorded. Genotyping was performed using Illumina NeuroBooster and NeuroChip arrays and MAPT haplotype, APOE genotype, TRIM11 rs564309 and SLC2A13 rs2242367 single nucleotide polymorphism data were collated. Tissue sections from eight brain regions, mounted on glass slides, were immunostained for hyperphosphorylated tau and digitized using whole-slide scanning. Forty-one anatomical regions of interest were manually segmented, and total tau pathology burden was quantified using an automated, machine learning-based algorithm. The associations between survival and both clinicogenetic features and regional tau pathology burden were modelled using Cox regression and generalized linear models, respectively, and the Subtype and Stage Inference (SuStaIn) algorithm was used to identify subgroups with distinct progression patterns.

We have identified: (i) several clinical predictors of survival in PSP and the relationship between regional tau pathology burden and survival; (ii) novel anatomical reference standards for the expected distribution of tau pathology across MDS-defined PSP phenotypes, including region-specific white matter involvement in patients with corticobasal syndrome and speech/language variants; (iii) associations potentially linking biological sex, MAPT haplotype and TAR DNA-binding protein 43 (TDP-43) co-pathology to clinical phenotype and regional tau pathology burden; (iv) patterns of covariance in regional tau pathology implicating inter-regional connectivity in tau spreading; and (v) three distinct spatiotemporal patterns of tau pathology progression: one characterized by initial involvement of subcortical grey matter followed by rostral spread to cortical regions and two characterized by early, simultaneous involvement of subcortical grey matter and cortical regions. Taken together, these results indicate that PSP clinicopathological heterogeneity is mediated by propagation of tau pathology along anatomically connected networks and via intrinsic regional susceptibility mechanisms, possibly influenced by sex, genetic factors and co-pathology.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

JaunmuktaneLab

License: none: the authors keep all their rights
State: the link answers, verified on 26 September 2026
Evidence: the link answers
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
  • 26 September 2026: the link answers (HTTP 200)

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

Anonymized clinical and quantitative tau pathology data may be shared upon reasonable request by qualified investigators for purposes of replicating procedures and results, if in compliance with ethical approval. All custom Python and Groovy scripts used for the quantitative digital pathology pipeline are openly available in a public GitHub repository (https://github.com/JaunmuktaneLab).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 27 authors, 4 keywords, 12 MeSH terms, 8 funders, 73 references, 1 integrity notice.

Cite

This paper

Cullinane, P. W., Parmera, J. B., Nelvagal, H., Curless, T., Chajed, L. P., Wrigley, S., Sifontes Valladares, W., Burrows, M., Ebanks, K., Wu, L., Binding, L. P., Anton, J., Revesz, T., Real, R., Vaughan, D. P., Jabbari, E., Morris, H. R., Brandner, S., Young, A. L., . . . Jaunmuktane, Z. (2026). Data-driven modelling of tau pathology reveals distinct progressive supranuclear palsy subtypes. Brain : a journal of neurology, 149(9), 3080-3094. https://doi.org/10.1093/brain/awag131

BibTeX

@article{cullinane2026data,
author = {Cullinane, Patrick W and Parmera, Jacy Bezerra and Nelvagal, Hemanth and Curless, Toby and Chajed, Leckhna Paras and Wrigley, Sarah and Sifontes Valladares, Walter and Burrows, Maggie and Ebanks, Kirsten and Wu, Lesley and Binding, Lawrence P and Anton, Jaime and Revesz, Tamas and Real, Raquel and Vaughan, David P and Jabbari, Edwin and Morris, Huw R and Brandner, Sebastian and Young, Alexandra L and Hoti, Glen and Ma, Yangxinrui and Bechtawi, Mariam and Chiraki, Nancy and de Pablo-Fernández, Eduardo and Lim, Yau Mun and Warner, Thomas T and Jaunmuktane, Zane},
title = {{Data-driven modelling of tau pathology reveals distinct progressive supranuclear palsy subtypes}},
journal = {Brain : a journal of neurology},
year = {2026},
month = sep,
volume = {149},
number = {9},
pages = {3080--3094},
publisher = {Oxford University Press},
issn = {0006-8950},
doi = {10.1093/brain/awag131},
url = {https://doi.org/10.1093/brain/awag131},
pmid = {41974128},
pmcid = {PMC13548875}
}

RIS

TY - JOUR
AU - Cullinane, Patrick W
AU - Parmera, Jacy Bezerra
AU - Nelvagal, Hemanth
AU - Curless, Toby
AU - Chajed, Leckhna Paras
AU - Wrigley, Sarah
AU - Sifontes Valladares, Walter
AU - Burrows, Maggie
AU - Ebanks, Kirsten
AU - Wu, Lesley
AU - Binding, Lawrence P
AU - Anton, Jaime
AU - Revesz, Tamas
AU - Real, Raquel
AU - Vaughan, David P
AU - Jabbari, Edwin
AU - Morris, Huw R
AU - Brandner, Sebastian
AU - Young, Alexandra L
AU - Hoti, Glen
AU - Ma, Yangxinrui
AU - Bechtawi, Mariam
AU - Chiraki, Nancy
AU - de Pablo-Fernández, Eduardo
AU - Lim, Yau Mun
AU - Warner, Thomas T
AU - Jaunmuktane, Zane
TI - Data-driven modelling of tau pathology reveals distinct progressive supranuclear palsy subtypes
T2 - Brain : a journal of neurology
J2 - Brain
PY - 2026
DA - 2026/09/01
VL - 149
IS - 9
SP - 3080
EP - 3094
SN - 0006-8950
PB - Oxford University Press
DO - 10.1093/brain/awag131
UR - https://doi.org/10.1093/brain/awag131
LA - en
ER -

CSL-JSON

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