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Record W7099495525

ORIGINAL ARTICLE RARE ATGL HAPLOTYPES ARE ASSOCIATED WITH INCREASED PLASMA TRIGLYCERIDE CONCENTRATIONS IN THE GREENLAND INUIT

2016· article· en· W7099495525 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsHaplotypeAdipose triglyceride lipaseSingle-nucleotide polymorphismGenotypeTriglycerideGeneGenetic associationPopulation
DOInot available

Abstract

fetched live from OpenAlex

Objectives. To genotype common genetic variants found in the adipose triglyceride lipase (ATGL) gene and test them for association with cardiovascular disease risk factors in the Greenland Inuit. Study design. Candidate gene association study of discrete and quantitative traits related to cardiovascular health. Methods. ATGL was sequenced in 0 European subjects to identify DNA sequence variants. The identified polymorphisms were subsequently genotyped in a population-based cohort of 1,218 unrelated Greenland Inuit subjects, ascertained from the Greenland Population Study. Genotypes and reconstructed haplotypes were tested for association with cardiovascular disease risk factors using additive, dominant or recessive models, corrected for age, sex and body mass index. Results. Five single nucleotide polymorphisms and one 4-base pair deletion were identified in the European sample and were similarly polymorphic in the Greenland Inuit. Independently, variants were not associated with any cardiovascular traits. However, reconstructed rare ATGL haplotypes were associated with increased plasma triglyceride (TG) concentrations compared to the major haplo-type under a dominant model (.±0.7 mmol/L and .±0.6 mmol/L, respectively, p=0.006). Conclusions. Rare ATGL haplotypes are associated with increased plasma TG concentrations in the Greenland Inuit. (Int J Circumpolar Health 2010; 69(1):3–12)

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)0.001
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 score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.067
GPT teacher head0.288
Teacher spread0.222 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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