Evidence map›Paper›PMID 32747831›Full record

ArticleNature biomedical engineering2020

Defining and predicting transdiagnostic categories of neurodegenerative disease.

Eli J Cornblath, John L Robinson, David J Irwin, Edward B Lee, Virginia M-Y Lee, John Q Trojanowski, Danielle S Bassett

Abstract read
In one paragraph

Article in Nature biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Autonomic dysfunction in neurodegenerative disease.Nature reviews. Neuroscience · 2025
    Review
  6. Review
  7. Article
  8. Caregiver perspectives enable accurate diagnosis of neurodegenerative disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Artificial intelligence for dementia genetics and omics.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Neuropathology and emerging biomarkers in corticobasal syndrome.Journal of neurology, neurosurgery, and psychiatry · 2022
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Eli J CornblathDepartment of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-2619-8778
John L RobinsonCenter for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
David J IrwinDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Edward B LeeTranslational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Virginia M-Y LeeCenter for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
John Q TrojanowskiCenter for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-9239-8794
Danielle S BassettDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. dsb@seas.upenn.edu.ORCID http://orcid.org/0000-0002-6183-4493

Funding

Transgenic Mouse Models of Tau PathologiesP01AG017586 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LEE, VIRGINIA M · 2000 to 2021
$37.3M
UPenn ADCC Biomarker CoreP30AG010124 · NIA · UNIVERSITY OF PENNSYLVANIA · PI XIE, SHARON XIANGWEN · 1991 to 2020
$35.1M
Understanding Environmental Contributions to Heterogeneity in bvFTD.P01AG066597 · NIA · UNIVERSITY OF PENNSYLVANIA · PI David John Irwin, Corey T McMillan · 2020 to 2026
$18.8M
Project IV "Tackling Heterogeneity of Cognitive Trajectory in LBD"U19AG062418 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LEE, VIRGINIA M · 2019 to 2023
$18.1M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Linguistic and NonLinguistic Functions of Frontal CortexR01DC009209 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI THOMPSONSCHILL, SHARON L · 2008 to 2018
$5.2M
Microscopic and Large-Scale Networks of Molecular Pathology in Frontotemporal Lobar DegenerationR01NS109260 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI IRWIN, DAVID JOHN · 2019 to 2023
$3.8M
Virtual Resection to Treat EpilepsyR01NS099348 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, LITT, BRIAN · 2016 to 2019
$2.3M
Multimodal brain maturation indices modulating psychopathology and neurocognitionR01MH107235 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RUBEN C. · 2015 to 2017
$1.5M
Evolution of the Linked Architecture of Network Control and Executive Function in AdolescenceR21MH106799 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, SATTERTHWAITE, THEODORE · 2016 to 2017
$515k
CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic NetworksR01HD086888 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH · 2015 to 2018
$506k
Structural constraints on large-scale brain activity in psychosis associated with chromosome 22q11.2 deletion syndromeF30MH118871 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI CORNBLATH, ELI · 2018 to 2021
$133k
NIA NIH HHS P01 AG017586NIA NIH HHS P01 AG066597NIA NIH HHS P30 AG010124NIA NIH HHS U19 AG062418NICHD NIH HHS R01 HD086888NIDCD NIH HHS R01 DC009209NIMH NIH HHS F30 MH118871NIMH NIH HHS R01 MH107235NIMH NIH HHS R01 MH112847NIMH NIH HHS R21 MH106799NINDS NIH HHS R01 NS099348NINDS NIH HHS R01 NS109260
6 · The paper itself

Abstract

The prevalence of concomitant proteinopathies and heterogeneous clinical symptoms in neurodegenerative diseases hinders the identification of individuals who might be candidates for a particular intervention. Here, by applying an unsupervised clustering algorithm to post-mortem histopathological data from 895 patients with degeneration in the central nervous system, we show that six non-overlapping disease clusters can simultaneously account for tau neurofibrillary tangles, α-synuclein inclusions, neuritic plaques, inclusions of the transcriptional repressor TDP-43, angiopathy, neuron loss and gliosis. We also show that membership to the six transdiagnostic disease clusters, which explains more variance in cognitive phenotypes than can be explained by individual diagnoses, can be accurately predicted from scores of the Mini-Mental Status Exam, protein levels in cerebrospinal fluid, and genotype at the APOE and MAPT loci, via cross-validated multiple logistic regression. This combination of unsupervised and supervised data-driven tools provides a framework that could be used to identify latent disease subtypes in other areas of medicine.

Indexed as

BiomarkersBrainCluster AnalysisGenotypeHumansMachine LearningNeurodegenerative DiseasesPhenotypeProtein Aggregation, PathologicalBiomarkers

Identifiers

PMID32747831
PMCPMC7946378

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.