Advancing Precision Medicine in Psychiatry: Genetic Insights into Antidepressant Treatment Outcomes
Bibliographic record
Abstract
Major Depressive Disorder (MDD) is a clinically heterogeneous disorder with substantial interindividual variability in antidepressant treatment response and tolerability. Genetic variation, particularly in pharmacokinetic genes such as CYP2C19 (drug metabolizing enzyme) and ABCB1 (encoding the drug-efflux transporter P-glycoprotein), and broader polygenic liability may partly explain this variability. Recent advances in psychiatric genomics have enabled the use of polygenic risk scores (PRSs) to quantify the cumulative genetic predisposition to MDD and treatment outcomes. This thesis investigated the impact of both common pharmacogenetic variants and PRSs on antidepressant response, side effects, and serum exposure using a well-characterized clinical trial from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) and conducting a meta-analysis. In the CAN-BIND-1 trial (N=178), all participants received 8 weeks of open-label escitalopram (ESC, Phase I). At Week 8, participants with <50% symptom improvement from baseline were augmented with aripiprazole (ARI) for an additional 8 weeks, while responders continued ESC monotherapy until trial end or Week 16 (Phase II). The meta-analysis showed a significant association between ABCB1 rs1128503 variant and antidepressant response, with T-allele carriers having higher odds of treatment response. No consistent associations were found for other ABCB1 variants or with ESC or ARI serum levels. As for CYP2C19, intermediate and poor metabolizers exhibited the most consistent effects on ESC pharmacokinetics, showing 1.4–2.3-fold higher ESC concentrations and reduced metabolic conversion compared to normal metabolizers. For the recently discovered CYP2C:TG haplotype, we observed that homozygous TG carriers exhibited higher dose-adjusted ESC concentrations and reduced metabolic ratios. However, these effects diminished when adjusting for CYP2C19 metabolizer status. Our PRS analysis showed that increased polygenic loading for post-traumatic stress syndrome (PTSD), schizophrenia, MDD, and attention-deficit hyperactivity disorder (ADHD) was nominally associated with poorer antidepressant treatment outcomes, while PRS for anxiety was associated with greater early symptom improvement. These associations varied across treatment phases, suggesting that genetic risk may influence antidepressant response trajectories. Overall, while CYP2C19 genotyping remains clinically actionable for ESC pharmacokinetics, integrating polygenic and pharmacogenetic information may enhance personalized treatment strategies. Our findings underscore the potential benefit of incorporating targeted and genome-wide approaches into models of antidepressant 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 | 0.023 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".