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Record W2042213574 · doi:10.1007/s00401-013-1188-4

LRRK2 phosphorylates novel tau epitopes and promotes tauopathy

2013· article· en· W2042213574 on OpenAlexafffund
Rachel M. Bailey, Jason P. Covy, Heather L. Melrose, Linda Rousseau, Ruth Watkinson, Joshua A. Knight, Sarah L. Miles, Matthew J. Farrer, Dennis W. Dickson, Benoit I. Giasson, Jada Lewis

Bibliographic record

VenueActa Neuropathologica · 2013
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthCanada Excellence Research Chairs, Government of CanadaUniversity of FloridaMayo ClinicEllison Medical Foundation
KeywordsTauopathyLRRK2EpitopePhosphorylationKinaseBiologyCell biologyChemistryMolecular biologyBiochemistryGeneGeneticsMutationNeurodegenerationMedicinePathologyDiseaseAntibody

Abstract

fetched live from OpenAlex

Mutations in the gene encoding leucine-rich repeat kinase 2 (LRRK2) are the most frequent cause of familial Parkinson's disease (PD). The neuropathology of LRRK2-related PD is heterogeneous and can include aberrant tau phosphorylation or neurofibrillary tau pathology. Recently, LRRK2 has been shown to phosphorylate tau in vitro; however, the major epitopes phosphorylated by LRRK2 and the physiological or pathogenic consequences of these modifications in vivo are unknown. Using mass spectrometry, we identified multiple sites on recombinant tau that are phosphorylated by LRRK2 in vitro, including pT149 and pT153, which are phospho-epitopes that to date have been largely unexplored. Importantly, we demonstrate that expression of transgenic LRRK2 in a mouse model of tauopathy increased the aggregation of insoluble tau and its phosphorylation at T149, T153, T205, and S199/S202/T205 epitopes. These findings indicate that tau can be a LRRK2 substrate and that this interaction can enhance salient features of human disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.237
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations102
Published2013
Admission routes2
Has abstractyes

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