Methylation of <i> <scp>OPRL</scp> 1 </i> mediates the effect of psychosocial stress on binge drinking in adolescents
Bibliographic record
Abstract
BACKGROUND: Nociceptin is a key regulator linking environmental stress and alcohol drinking. In a genome-wide methylation analysis, we recently identified an association of a methylated region in the OPRL1 gene with alcohol-use disorders. METHODS: Here, we investigate the biological basis of this observation by analysing psychosocial stressors, methylation of the OPRL1 gene, brain response during reward anticipation and alcohol drinking in 660 fourteen-year-old adolescents of the IMAGEN study. We validate our findings in marchigian sardinian (msP) alcohol-preferring rats that are genetically selected for increased alcohol drinking and stress sensitivity. RESULTS: We found that low methylation levels in intron 1 of OPRL1 are associated with higher psychosocial stress and higher frequency of binge drinking, an effect mediated by OPRL1 methylation. In individuals with low methylation of OPRL1, frequency of binge drinking is associated with stronger BOLD response in the ventral striatum during reward anticipation. In msP rats, we found that stress results in increased alcohol intake and decreased methylation of OPRL1 in the nucleus accumbens. CONCLUSIONS: Our findings describe an epigenetic mechanism that helps to explain how psychosocial stress influences risky alcohol consumption and reward processing, thus contributing to the elucidation of biological mechanisms underlying risk for substance abuse.
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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 | 0.000 |
| 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) | 0.002 | 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".