MétaCan
Menu
Back to cohort
Record W2108981555 · doi:10.1371/journal.pone.0041859

Genome Wide Assessment of Young Onset Parkinson’s Disease from Finland

2012· article· en· W2108981555 on OpenAlexfundno aff
Dena G. Hernandez, Michael A. Nalls, Pauli Ylikotila, Margaux F. Keller, John Hardy, Kari Majamaa, Andrew Singleton

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsnot available
FundersNational Institute on AgingParkinsonfondenInstitute of GeneticsAcademy of FinlandHelsingin YliopistoParkinson's UKMichael J. Fox Foundation for Parkinson's ResearchHelsingin ja Uudenmaan SairaanhoitopiiriNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsDiseasePenetranceCohortGenome-wide association studyAge of onsetGeneticsPopulationCohort studyParkinson's diseaseMedicineBiologyInternal medicineGenotypePhenotypeSingle-nucleotide polymorphismGene

Abstract

fetched live from OpenAlex

In the current study we undertook a series of experiments to test the hypothesis that a monogenic cause of disease may be detectable within a cohort of Finnish young onset Parkinson's disease patients. In the first instance we performed standard genome wide association analyses, and subsequent risk profile analysis. In addition we performed a series of analyses that involved testing measures of global relatedness within the cases compared to controls, searching for excess homozygosity in the cases, and examining the cases for signs of excess local genomic relatedness using a sliding window approach. This work suggested that the previously identified common, low risk alleles, and the risk models associated with these alleles, were generalizable to the Finnish Parkinson's disease population. However, we found no evidence that would suggest a single common high penetrance mutation exists in this cohort of young onset patients.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.253
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.070
GPT teacher head0.271
Teacher spread0.201 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicNeurological diseases and metabolismFrench-language works237,207