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Ethnic variation in CYP2A6*7, CYP2A6*8 and CYP2A6*10 as assessed with a novel haplotyping method

2005· article· en· W2004256112 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePharmacogenetics and Genomics · 2005
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsCanada Research ChairsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institute on Alcohol Abuse and AlcoholismUniversity of Toronto
KeywordsCYP2A6HaplotypeAlleleGeneticsSingle-nucleotide polymorphismBiologyAllele frequencySNPGenotypeGene

Abstract

fetched live from OpenAlex

Cytochrome P450 2A6 is the main human nicotine metabolizing enzyme coded for by a highly polymorphic gene, CYP2A6. CYP2A6*7, CYP2A6*8 and CYP2A6*10 are variant alleles common to Asian ethnicities. The CYP2A6*7 and CYP2A6*8 alleles each contain a non-synonymous single nucleotide polymorphism (SNP) 6558T>C and 6600G>T, respectively, whereas the CYP2A6*10 haplotype allele contains both. We have developed the first haplotyping assay; it can unambiguously distinguish the CYP2A6*7, CYP2A6*8 and CYP2A6*10 alleles. The allele frequencies of these three variants were assessed using the novel haplotyping assay in Chinese-Canadian (n=112), Chinese-American (n=221), Taiwanese (n=319), Korean-American (n=207) and Japanese-Canadian (n=64) populations, as well as in Caucasian (n=110) and African-Canadian (n=113) populations. Our new method demonstrated higher frequencies of CYP2A6*7 and CYP2A6*10, and a lower frequency of CYP2A6*8 in Asian populations, but no significant change of allele frequencies in Caucasian or African-Canadian populations.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.457
Teacher spread0.337 · 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