Analysis of 34 candidate genes in bupropion and placebo remission
Bibliographic record
Abstract
There is considerable variability in the rate of response and remission following treatment with antidepressant drugs or placebo in depression patients. No pharmacogenetic studies of bupropion response have been done. We investigated 532 tagging single nucleotide polymorphisms (SNPs) in 34 candidate genes for association with remission and response to either bupropion (n=319) or placebo (n=257) in patients with major depressive disorder. Analyses were performed using conditional logistic regression. Significant association (gene-wide correction) was observed for remission following treatment with bupropion for a SNP within the serotonin receptor 2A gene (HTR2A rs2770296, p(corrected)=0.02). Response to bupropion treatment was significantly associated with a SNP in the dopamine transporter gene (rs6347, p(corrected)=0.013). Among the patients who received placebo, marginal association for remission was observed between a SNP in HTR2A (rs2296972, p(corrected)=0.055) as well as in the serotonin transporter gene (5-HTT or SLC6A4 rs4251417, p(corrected)=0.050). Placebo response was associated with SNPs in the glucocorticoid receptor gene (NR3C1; rs1048261, p(corrected)=0.040) and monoamine oxidase A gene (MAOA; rs6609257, p corrected=0.046). Although the above observations were significant after gene-wide corrections, none of these would be significant after a more conservative study-wide correction for multiple tests. These results suggest a possible role for HTR2A in remission to bupropion treatment. In accordance with bupropion pharmacology, dopamine transporter may play a role in response. The MAOA gene may be involved in placebo response.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".