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Record W4402623736 · doi:10.1101/2024.09.13.24313644

Plasma glucosylceramide levels are regulated by <i>ATP10D</i> and are not involved in Parkinson’s disease pathogenesis

2024· preprint· en· W4402623736 on OpenAlexafffund
Emma N. Somerville, Alva James, Christian Beetz, Robert Schwieger, Gal Barrel, Krishna Kumar Kandaswamy, Marius I. Iurascu, Peter Bauer, Michael Ta, Hirotaka Iwaki, Konstantin Senkevich, Eric Yu, Roy N. Alcalay, Ziv Gan‐Or

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute on AgingFonds de Recherche du Québec - SantéAvid RadiopharmaceuticalsGenentechSun PharmaH. Lundbeck A/SServierAllerganCanada First Research Excellence FundParkinson CanadaNeurocrine BiosciencesMcGill UniversityBiogenCelgeneJazz PharmaceuticalsVerily Life SciencesTeva Pharmaceutical IndustriesPfizerEli Lilly and CompanyBristol-Myers SquibbSanofiMichael J. Fox Foundation for Parkinson's Research
KeywordsPathogenesisGlucocerebrosidaseDiseaseParkinson's diseaseRegulatorImmunologyMedicineBiologyBioinformaticsInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

Abstract GBA1 variants and decreased glucocerebrosidase (GCase) activity are implicated in Parkinson’s disease (PD). We investigated the hypothesis that increased levels of glucosylceramide (GlcCer), one of GCase main substrates, are involved in PD pathogenesis. Using multiple genetic methods, we show that ATP10D , not GBA1 , is the main regulator of plasma GlcCer levels, yet it is not involved in PD pathogenesis. Plasma GlcCer levels were associated with PD, but not in a causative manner, and are not predictive of disease status. These results argue against targeting GlcCer in GBA1 -PD and underscore the need to explore alternative mechanisms and biomarkers for PD.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.285
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2024
Admission routes2
Has abstractyes

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