Disease‐associated polymorphisms within the conserved ECR1 enhancer differentially regulate the tissue‐specific activity of the cannabinoid‐1 receptor gene promoter; implications for cannabinoid pharmacogenetics
Bibliographic record
Abstract
Cannabinoid receptor-1 (CB1) represents a potential drug target against conditions that include obesity and substance abuse. However, drug trials targeting CB1 (encoded by the CNR1 gene) have been compromised by differences in patient response. Toward addressing the hypothesis that genetic changes within the regulatory regions controlling CNR1 expression contribute to these differences, we characterized the effects of disease-associated allelic variation within a conserved regulatory sequence (ECR1) in CNR1 intron 2 that had previously been shown to modulate cannabinoid response, alcohol intake, and anxiety-like behavior. We used primary cell analysis of reporters carrying different allelic variants of the human ECR1 and found that human-specific C-allele variants of ECR1 (ECR1(C)) drove higher levels of CNR1prom activity in primary hippocampal cells than did the ancestral T-allele and demonstrated a differential response to CB1 agonism. We further demonstrate a role for the AP-1 transcription factor in driving higher ECR1(C) activity and evidence that the ancestral t-allele variant of ECR1 interacted with higher affinity with the insulator binding factor CTCF. The cell-specific approaches used in our study represent an important step in gaining a mechanistic understanding of the roles of noncoding polymorphic variation in disease and in the increasingly important field of cannabinoid pharmacogenetics.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".