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Genetic determinants of plasma triglycerides

2010· review· en· 262 citations· W2080036080 on OpenAlex· 10.1194/jlr.r009720

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

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.

Candidate categories
Research integrity
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.979
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.166
GPT teacher head0.477
Teacher spread
0.311 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Plasma triglyceride (TG) concentration is a complex polygenic trait that follows a rightward-skewed distribution in the population ( Fig. As a clinical measurement, it integrates multiple TG-rich lipoprotein (TRL) species that circulate in plasma, predominantly intestinally synthesized chylomicrons (CMs) in the postprandial state and hepatically synthesized very low density lipoproteins (VLDL) in the fasted state. Epidemiological evidence indicates that plasma TG concentration is a strong independent risk factor for cardiovascular disease (CVD), suggesting that prolonged residence of plasma TRLs, especially in the postprandial state, may contribute to CVD susceptibility ( 1-7 ). Together with environmental infl uences, common and rare variants in multiple genes may collectively determine a patient's plasma TG concentration. Identifying genes and genetic variants associated with plasma TG concentration will enrich our understanding of biochemical pathways involved in TRL metabolism, enabling identifi cation of Abstract Plasma triglyceride (TG) concentration is reemerging as an important cardiovascular disease risk factor. More complete understanding of the genes and variants that modulate plasma TG should enable development of markers for risk prediction, diagnosis, prognosis, and response to therapies and might help specify new directions for therapeutic interventions. Recent genome-wide association studies (GWAS) have identifi ed both known and novel loci associated with plasma TG concentration. However, genetic variation at these loci explains only 10% of overall TG variation within the population. As the GWAS approach may be reaching its limit for discovering genetic determinants of TG, alternative genetic strategies, such as rare variant sequencing studies and evaluation of animal models, may provide complementary information to fl esh out knowledge of clinically and biologically important pathways in TG metabolism. Herein, we review genes recently implicated in TG metabolism and describe how some of these genes likely modulate plasma TG concentration. We also discuss lessons regarding plasma TG metabolism learned from various genomic and genetic experimental approaches. Treatment of patients with moderate to severe hypertriglyceridemia with existing therapies is often challenging; thus, gene products and pathways found in recent genetic research studies provide hope for development of more effective clinical strategies. -

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.

The record

Venue
Journal of Lipid Research
Topic
Lipid metabolism and disorders
Field
Medicine
Canadian institutions
Western University
Funders
Canadian Institutes of Health ResearchOntario GenomicsOntario Genomics InstituteGenome CanadaHeart and Stroke Foundation of Canada
Keywords
Genome-wide association studyHypertriglyceridemiaGenetic variationBiologyComputational biologyGenetic associationGeneGeneticsBioinformaticsPopulationTriglycerideMedicineSingle-nucleotide polymorphismEndocrinologyGenotypeCholesterol
Has abstract in OpenAlex
yes