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Record W2888721862

Genetics of disc-related disorders: current findings and lessons from other complex diseases

2014· article· en· W2888721862 on OpenAlexaff
Annu Näkki, Michele C. Battié, Jaakko Kaprio

Bibliographic record

VenueSTM:n Hallinnonalan avoin julkaisuarkisto (Julkari) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeneticsBiologyContext (archaeology)HeritabilityGenome-wide association studyCandidate geneGenetic associationGeneDiseaseEvolutionary biologyGenotypeMedicineSingle-nucleotide polymorphismPathology
DOInot available

Abstract

fetched live from OpenAlex

Disc-related disorders are highly genetic conditions with heritability estimates of up to 75 % and yet, few genomic locations have been moderately associated with the disorders. Candidate gene studies have shown possible disease associations on loci and genes of 1p21.1 (COL11A1), 6q27 (THBS2), 9q22.31 (ASPN), 10p12.31 (SKT), 20q11.2 (GDF5) and 20q13.12 (MMP9). More recently, in 2012, the first genome-wide association study revealed variants on loci and genes of 3p26.2, 6p21.32 (HLA region) and 6q26 (PARK2) that associate with disc-related disorders. In many other complex diseases, large meta-analyses of hundreds of thousands of study subjects and loci have revealed remarkable pathways. As methodology is evolving rapidly, we have already stepped into the era of routinely sequencing all bases in all human exons and we are approaching the era of sequencing the entire genome of study subjects with common diseases. The past decade has taught us that the common variants seen throughout populations seem to have low effects in many common diseases, explain relatively little of the overall heritability of the diseases and demand thousands of study subjects to identify associations. It seems that familial rare variants play an important role in many common diseases leading us back to valuing studies with large families and isolated populations. Moreover, careful characterization of environmental conditions are needed to explore and determine gene–environment interactions as genes that increase disease risk in one context may not do so under another context.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.971

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)0.0010.000

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 head0.034
GPT teacher head0.273
Teacher spread0.239 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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