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Record W7132909012

Associations Between Genetic Variation and Cigarette Smoking and Alcohol Drinking during Youth: Longitudinal Investigations

2023· dissertation· W7132909012 on OpenAlexaff
Alaa Alsaafin

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFatty acid amide hydrolaseBinge drinkingNicotineCohortCotinineProportional hazards modelLongitudinal studyAddictionGenetic predisposition
DOInot available

Abstract

fetched live from OpenAlex

We evaluated genetic-based associations with early smoking and drinking behaviours among European-ancestry youth in a longitudinal cohort design. In Study 1, we examined associations between genetic variation in TAS2R38, which encodes a bitter taste receptor, and early smoking behaviours. Individuals with the PAV/PAV or PAV/AVI diplotypes (i.e., PAV diplotypes) are considered bitter tasters, whereas AVI/AVI (i.e., AVI diplotype) are non-tasters. Cox proportional hazards models estimated associations between TAS2R38 diplotype and time to early smoking outcomes in adolescent incident smokers (i.e., those who initiated smoking during study follow-up). While similar diplotype-based rates to first whole cigarette were found, those with the PAV diplotypes attained monthly smoking and converted to tobacco dependence (measured using three indicators ICD-10, mFTQ, and HONC) faster than those with the AVI diplotype. When these participants reached young adulthood (age 24), those with PAV diplotypes had higher mean cotinine + 3’hydroxycotinine, a biomarker of nicotine intake.In Study 2, we examined associations between genetic variation in fatty acid amide hydrolase (FAAH) and early drinking behaviours, and whether similar associations were observed with early smoking milestones. As part of the endocannabinoid system, which is implicated in psychiatric disorders and drug dependence, FAAH metabolizes endocannabinoids such as anandamide. Individuals with A-group genotypes (C/A or A/A) of a FAAH missense variant (rs324420; C>A) have slower enzymatic activity than those in the C-group (C/C genotype). We first replicated findings from two studies in adults, where those in the A-group had higher odds of past-year binge drinking at ages 20 and 30. Next, Cox proportional hazards models were used to estimate associations during adolescence, where those in the A-group had faster time to drinking initiation and daily drinking. Although the genotype associations extended to faster rates to smoking initiation, associations with early smoking milestones were inconsistent. Thus, the ability to taste bitter compounds increases the risk for early smoking behaviours, while slow FAAH activity increases risk for drug use initiation and harmful drinking behaviours. Our findings underscore the importance of examining genetic associations in acquisition and early drug use behaviours and contribute to our understanding of inter-individual differences in substance use in adolescence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.059
GPT teacher head0.356
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

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