Pharmacogenetics of Lethal Opioid Overdose: Review of Current Evidence and Preliminary Results from a Pilot Study
Bibliographic record
Abstract
There has been a worldwide substantial increase in accidental opioid-overdose deaths. The aim of this review, along with preliminary results from our pilot study, is to highlight the use of pharmacogenetics as a tool to predict causes of accidental opioid-overdose death. For this review, a systematic literature search of PubMed® between the time period of January 2000 to March 2023 was carried out. We included study cohorts, case–controls, or case reports that investigated the frequency of genetic variants in opioid-related post-mortem samples and the association between these variants and opioid plasma concentrations. A total of 18 studies were included in our systematic review. The systematic review provides evidence of the use of CYP2D6, and to a lower extent, CYP2B6 and CYP3A4/5 genotyping in identifying unexpectedly high or low opioid and metabolite blood concentrations from post-mortem samples. Our own pilot study provides support for an enrichment of the CYP2B6*4-allele in our methadone-overdose sample (n = 41) compared to the anticipated frequency in the general population. The results from our systematic review and the pilot study highlight the potential of pharmacogenetics in determining vulnerability to overdose of opioids.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".