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Record W2901376861 · doi:10.1002/mds.27506

Parkinsonism due to A53E α‐synuclein gene mutation: Clinical, genetic, epigenetic, and biochemical features

2018· article· en· W2901376861 on OpenAlexafffundabout
Marina Picillo, Karlo J. Lizárraga, Erik Loewen Friesen, Hien Chau, Ming Zhang, Christine Sato, G.B. Rooke, Renato P. Munhoz, Ekaterina Rogaeva, Paul E. Fraser, Suneil K. Kalia, Lorraine V. Kalia

Bibliographic record

VenueMovement Disorders · 2018
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsOccupational Cancer Research CentreToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsParkinsonismEpigeneticsGeneticsDNA methylationBiologyMutationHaplotypeDiseaseGeneMedicineInternal medicineAlleleGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: SNCA mutations cause autosomal dominant parkinsonism and inform our understanding of the molecular underpinnings of synucleinopathies. The most recently identified mutation, p.Ala53Glu (A53E), has only been observed in Finland. The objectives of this study were to examine clinical, genetic, epigenetic, and biochemical features of the first family outside Finland with A53E. METHODS: We examined a Canadian family with parkinsonism because of A53E using haplotype and DNA methylation analyses. We assessed aggregation properties of A53E α-synuclein in vitro. RESULTS: Family members with parkinsonism shared a common haplotype distinct from Finnish patients with A53E. Increased acceleration of DNA methylation age was accompanied by earlier age at onset in the family members. We demonstrate that A53E α-synuclein has a propensity to form oligomers and phosphorylation promotes fibrillation. CONCLUSIONS: A53E as a cause of parkinsonism is not restricted to Finnish individuals. DNA methylation may contribute to disease age at onset. A53E enriches α-synuclein oligomers and fibrils dependent on the phosphorylation state. © 2018 International Parkinson and Movement Disorder Society.

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 score0.704
Threshold uncertainty score0.992

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 head0.014
GPT teacher head0.298
Teacher spread0.283 · 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

Citations36
Published2018
Admission routes3
Has abstractyes

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