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Record W3126941948 · doi:10.1186/s12889-021-10160-w

Dopamine D4 receptor gene polymorphism (DRD4 VNTR) moderates real-world behavioural response to the food retail environment in children

2021· article· en· W3126941948 on OpenAlexafffundabout
Catherine Paquet, André Krumel Portella, Spencer Moore, Yu Ma, Alain Dagher, Michael J. Meaney, James L. Kennedy, Robert D. Levitan, Patrícia Pelufo Silveira, Laurette Dubé

Bibliographic record

VenueBMC Public Health · 2021
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsCentre for Addiction and Mental HealthMcGill UniversityDouglas Mental Health University InstituteUniversity of TorontoMontreal Neurological Institute and HospitalUniversité Laval
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentCanadian Institutes of Health ResearchNational Institutes of HealthIndian Council of Medical ResearchJacobs FoundationMcGill University
KeywordsBody mass indexMedicineDemographyBiostatisticsObesityCohortGeneticsResidenceGene–environment interactionPolymorphism (computer science)Cohort studyTwin studyEnvironmental healthAlleleGerontologyEpidemiologyGeneBiologyGenotypeInternal medicineHeritability

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence for the impact of the food retailing environment on food-related and obesity outcomes remains equivocal, but only a few studies have attempted to identify sub-populations for whom this relationship might be stronger than others. Genetic polymorphisms related to dopamine signalling have been associated with differences in responses to rewards such as food and may be candidate markers to identify such sub-populations. This study sought to investigate whether genetic variation of the dopamine D4 receptor gene (DRD4 exon III 48 bp VNTR polymorphism) moderated the association between local exposure to food retailers on BMI and diet in a sample of 4 to12-year-old children. METHODS: Data collected from a birth cohort and a community cross-sectional study conducted in Montreal, Canada, were combined to provide DRD4 VNTR polymorphism data in terms of presence of the 7-repeat allele (DRD4-7R) for 322 children aged between 4 and 12 (M (SD): 6.8(2.8) y). Outcomes were Body Mass Index (BMI) for age and energy density derived from a Food Frequency Questionnaire. Food environment was expressed as the proportion of local food retailers classified as healthful within 3 km of participants' residence. Linear regression models adjusted for age, sex, income, cohort, and geographic clustering were used to test gene*environment interactions. RESULTS: A significant gene*food environment interaction was found for energy density with results indicating that DRD4-7R carriers had more energy dense diets than non-carriers, with this effect being more pronounced in children living in areas with proportionally more unhealthy food retailers. No evidence of main or interactive effects of DRD4 VNTR and food environment was found for BMI. CONCLUSIONS: Results of the present study suggest that a genetic marker related to dopamine pathways can identify children with potentially greater responsiveness to unhealthy local food environment. Future studies should investigate additional elements of the food environment and test whether results hold across different 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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.111
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.287
Teacher spread0.234 · 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

Citations15
Published2021
Admission routes3
Has abstractyes

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