Unravelling Variability in Antidepressant Outcomes using Pharmacogenetic and Pharmacokinetic Strategies
Bibliographic record
Abstract
Genetic factors play a significant role in the interindividual variability of antidepressant response. This PhD thesis comprises three studies that investigate how genetic variations influence antidepressant treatment outcomes. The first study analyzed data from the STOP-PD II trial (N = 171), where participants with psychotic depression were treated with sertraline and olanzapine for up to 20 weeks, followed by a randomized phase of 36 weeks when participants received sertraline and olanzapine or sertraline and placebo. Using genome-wide association studies (GWAS), we identified suggestive genomic associations for remission. When using polygenic risk scores (PRS), we found associations between remission and PRS for antidepressant response, as well as between relapse and PRS for Alzheimer’s disease. These findings provide insights into the genetic architecture of treatment outcomes in psychotic depression. The second study focused on pharmacokinetic factors, leveraging data from the IRL-GRey study (N = 325), where older adults with depression were treated with venlafaxine (VEN) for 12 weeks. We adapted and improved a population pharmacokinetic model for VEN and its active metabolite, O-desmethylvenlafaxine (ODV). Incorporating CYP2D6 metabolizer status significantly enhanced the model’s predictive accuracy. CYP2D6 metabolizers showed different VEN clearance, VEN exposure, and active moiety (VEN plus ODV) exposure, where differences were mostly driven by CYP2D6 poor metabolizers. The study highlights the importance of CYP2D6 metabolizer status in optimizing VEN dosing strategies. Using the pharmacokinetic data deriving from our model, the third study examined the relationship between VEN exposure and clinical outcomes in the same sample. Higher exposures to VEN, ODV, and its active moiety were associated with an increased risk of adverse effects, particularly nausea/vomiting and orthostatic dizziness. The findings underscore the clinical relevance of pharmacokinetic monitoring to minimize antidepressant adverse effects in older adults with depression. Together, the three studies underscore the critical role of pharmacogenetics and pharmacokinetics in advancing precision psychiatry. By elucidating the genetic and pharmacokinetic factors influencing antidepressant treatment outcomes, the thesis provides a foundation for optimizing and personalizing pharmacotherapy for depression.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".