Good parent-child relationship protects against alcohol use in maltreated adolescent females carrying the MAOA-uVNTR susceptibility allele
Bibliographic record
Abstract
Introduction: Risk-allele carriers of a Monoamine oxidase A (MAOA) gene, short-allele (MAOA-S) in males and long-allele (MAOA-L) in females, in the presence of a negative environment, are associated with alcohol misuse. Whether MAOA-S/L alleles also present susceptibility to a positive environment to mitigate the risk of alcohol misuse is unknown. Thus, we assessed the association of the three-way interaction of MAOA, maltreatment, and positive parent-child relationship with alcohol consumption among adolescents. Methods: This prospective study included 1416 adolescents (females: 59.88%) aged 16 - 19 years from Sweden, enrolled in the "Survey of Adolescent Life in Västmanland" in 2012. Adolescents self-reported alcohol consumption, maltreatment by a family (FM) or non-family member (NFM), parent-child relationship, and left saliva for MAOA genotyping. Results and discussion: We observed sex-dependent results. Females carrying MAOA-L with FM or NFM and a good parent-child relationship reported lower alcohol consumption than those with an average or poor parent-child relationship. In males, the interactions were not significant. Results suggest MAOA-L in females, conventionally regarded as a "risk", is a "plasticity" allele as it is differentially susceptible to negative and positive environments. Results highlight the importance of a good parent-child relationship in mitigating the risk of alcohol misuse in maltreated individuals carrying genetic risk. However, the interactions were not significant after adjusting to several environmental and behavioural covariates, especially parent's alcohol use, negative parent-child relationship, and nicotine use (smoking and/or snus), suggesting predictor and outcome intersection. Future studies and frameworks for preventive strategies should consider these covariates together with alcohol consumption. More studies with larger sample sizes are needed to replicate the findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".