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Record W3097196054 · doi:10.1101/2020.10.22.20217190

Common and rare variants in HFE are not associated with Parkinson’s disease in Europeans

2020· preprint· en· W3097196054 on OpenAlexafffund
Prabhjyot Saini, Sara Bandrés‐Ciga, José Luis Alcantud, Clara Ruz, Ziv Gan‐Or

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institutes of HealthCanada First Research Excellence FundConsortium canadien en neurodégénérescence associée au vieillissementParkinson CanadaMcGill UniversityFonds de Recherche du Québec - SantéMichael J. Fox Foundation for Parkinson's Research
KeywordsGenome-wide association studyIron homeostasisParkinson's diseaseDiseaseGenetic associationLocus (genetics)PathologicalLRRK2Association testGeneticsMedicineBiologySingle-nucleotide polymorphismGeneGenotypeInternal medicine

Abstract

fetched live from OpenAlex

Abstract A recent study suggested that the p.H63D variant in HFE , a gene involved in iron homeostasis, may modify α-synuclein pathology, the pathological hallmark of Parkinson’s disease (PD). If indeed this gene and specific variant are involved in PD, we expect to find differential distribution of HFE variants when comparing PD patients and controls. We analyzed genome-wide association study (GWAS) data from 14,671 PD patients and 17,667 controls and full sequencing data from additional 1,647 PD patients and 1,050 controls, using logistic regression models, and burden and Kernel tests. The HFE p.H63D variant was not associated with PD, nor did all the other common variants in the HFE locus. We did not find association of rare HFE variants with PD as well in all types of burden and Kernel tests. Our results do not support a role for HFE in 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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.263
Teacher spread0.208 · 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 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

Citations0
Published2020
Admission routes2
Has abstractyes

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