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Genetic Variation\nin 9p21 and the Plasma Proteome

2018· article· en· W6959215833 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsnot available
Fundersnot available
KeywordsApolipoprotein BGenotypeDiseaseProteomeBlood proteinsSingle-nucleotide polymorphismGenetic variationNutrigenomics

Abstract

fetched live from OpenAlex

Single nucleotide polymorphisms (SNPs)\nin the noncoding region\nof 9p21 have been associated with cardiovascular disease (CVD), but\nthe mechanisms by which these genetic variants contribute to the pathogenesis\nof CVD remain unknown since no annotated proteins are present in this\nregion of DNA. The objective of the current study was to determine\nif 9p21 genotypes are associated with distinct plasma proteins in\nyoung adults. Subjects were 1611 young adults aged 20–29 years\nfrom the Toronto Nutrigenomics and Health Study (1098 females and\n513 males). DNA was isolated from fasting blood to analyze four SNPs\nin 9p21 (rs2383206, rs10757274, rs10757278, and rs1333049). Abundant\nplasma proteins (<i>n</i> = 54) were measured using liquid\nchromatography multiple reaction monitoring mass spectrometry. Analysis\nof covariance was used to determine differences in plasma proteins\nbetween genotypes. In Caucasians (<i>n</i> = 524), four\nSNPs were associated with apolipoprotein E and two with haptoglobin-β-chain\nconcentration. In East Asians (<i>n</i> = 388), three SNPs\nwere associated with α-1b-Glycoprotein, two with apolipoprotein\nB-100, one with apolipoprotein E and one with haptoglobin-β-chain\nconcentration. In South Asians (<i>n</i> = 117), one SNP\nwas associated with apolipoprotein B-100 concentration. Our findings\nsuggest that 9p21 genotypes may play a role in various pathophysiological\npathways that contribute to risk of CVD in early adulthood that might\nbe distinct among different ethnocultural groups.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

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)0.0460.001

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 head0.210
Teacher spread0.177 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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