Genetics of dopamine receptors and drug addiction: a comprehensive review
Bibliographic record
Abstract
Drug dependence is a chronic, relapsing disorder in which compulsive drug-seeking and drug-taking behaviours persist despite serious negative consequences. Addictive substances, such as opioids, ethanol, psychostimulants and nicotine, induce pleasant states or relieve distress, effects that contribute to their recreational use. Dopamine is critically involved in drug addiction processes. However, the role of the various dopaminergic receptor subtypes has been difficult to delineate. Here, we will review the information collected implicating the receptors of the D1 family (DRD1 and DRD5) and of the D2 family (DRD2, DRD3 and DRD4) in drug addiction. We will summarize the distribution of these receptors in the brain, the preclinical experiments carried out with pharmacological and transgenic approaches and the genetic studies carried out linking genetic variants of these receptors to drug addiction phenotypes. A meta-analysis of the studies carried out evaluating DRD2 and alcohol dependence is also provided, which indicates a significant association. Overall, this review indicates that different aspects of the addiction phenotype are critically influenced by dopaminergic receptors and that variants of those genes seem to influence some addiction phenotypes in humans.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".