F190. EFFECT OF SELECTED GENE VARIANTS ON THE RELATIONSHIP BETWEEN EARLY CANNABIS USE AND AGE OF ONSET OF PSYCHOSIS
Bibliographic record
Abstract
Cannabis use, particularly regular use in adolescence, is associated with an increased risk of developing psychosis earlier. An earlier age of onset negates the protective effects of more mature psychosocial and individual variables, thus the potential for worse outcomes. Genetic variations in this relationship are important to understand as this will allow not only a better understanding of the biological interaction of cannabis and psychosis, but would inform future genetic approaches to risk identification as well. We uniquely examined the mediation of this association (gene x cannabis associations in age of onset of psychosis (AoP)) in 3 genetic variants which, while each have been examined separately, not in combination in the same population. We examined: 1) COMT Val158Met (rs4680) 2) BDNF Val66Met (rs6265) and 3) the AKT1 variant rs2494732. 168 subjects with a diagnosis of psychosis were recruited from 2 sites in Canada, Edmonton Alberta and Halifax Nova Scotia. Cannabis use data (age at first and regular use) were collected using an electronic self-report survey (to address potential minimization of use to a researcher) and saliva samples were used for genotyping. Kaplan-Meier and Cox regression analyses were used to study the gene – cannabis effects. In those who had used cannabis, first use of cannabis prior to 20 years of age was associated with earlier AoP (p = .005). In those who used cannabis before age 20, rs4680 had a trend level association with AoP (log rank test: p=0.0617). A trend effect for an rs6265 x gender interaction (HR = 2.08, p = 0.067) on AoP, controlling for regular cannabis use was also observed. No association was observed between rs2494732 and rs6265 - rs2494732 interaction, and AoP. The trends in our associations are in keeping with previous literature, however our gender analyses underscores the importance of examining sex and gender as we further move towards risk identification for the cannabis and psychosis interaction. Our results also suggest that not all genetic variants associated with psychosis are involved with the association between cannabis and AoP. While our results offer support for future research in this area, larger sample sizes are required to test the gene-cannabis-AoP relationship.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.001 |
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".