The association of CNR1 genetic variants with resting-state functional connectivity in youth bipolar disorder
Bibliographic record
Abstract
Cannabinoid 1 receptors coded by the CNR1 gene are implicated in mood disorders and addiction. Given the prevalence and negative correlates of cannabis use in bipolar disorder (BD), we examined CNR1 polymorphism rs1324072 in relation to resting-state functional connectivity (rsFC) in youth BD. Participants included 124 youth, ages 13-20 years: 17 BD G-carriers, 48 BD non-carriers, 16 healthy controls (HC) G-carriers, and 43 HC non-carriers. rsFC was obtained using 3T-MRI. General linear models examined main effects of diagnosis, gene, and diagnosis-by-gene interaction, controlling for age, sex, and race. Regions-of-interests in seed-to-voxel analyses included: bilateral amygdala, hippocampus, nucleus accumbens (NAc), and orbitofrontal cortex (OFC). Main effects of diagnosis were observed for rsFC between the right amygdala seed and right occipital pole, and between the left NAc seed and left superior parietal lobe. Interaction analyses identified 6 significant clusters. G-allele was associated with negative connectivity in BD and positive connectivity in HC for: left amygdala seed with right intracalcarine cortex; right NAc seed with left inferior frontal gyrus; and right hippocampal seed with bilateral cuneal cortex (all p<0.001). G-allele was associated with positive connectivity in BD and negative connectivity in HC for: right hippocampal seed with left central opercular cortex (p = 0.001), and left NAc seed with left middle temporal cortex (p = 0.002). In conclusion, CNR1 rs1324072 was differentially associated with rsFC in youth with BD in regions relevant to reward and emotion. Future studies powered to integrate CNR1 alongside cannabis use are warranted to examine the inter-relationship between rs1324072 G-allele, cannabis use, and BD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".