<i>CYP2C19</i> genotype predicts steady state escitalopram concentration in GENDEP
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Bibliographic record
Abstract
In vitro work shows CYP2C19 and CYP2D6 contribute to the metabolism of escitalopram to its primary metabolite, N-desmethylescitalopram. We report the effect of CYP2C19 and CYP2D6 genotypes on steady state morning concentrations of escitalopram and N-desmethylescitalopram and the ratio of this metabolite to the parent drug in 196 adult patients with depression in GENDEP, a clinical pharmacogenomic trial. Subjects who had one CYP2D6 allele associated with intermediate metabolizer phenotype and one associated with poor metabolizer (i.e. IM/PM genotypic category) had a higher mean logarithm escitalopram concentration than CYP2D6 extensive metabolizers (EMs) (p = 0.004). Older age was also associated with higher concentrations of escitalopram. Covarying for CYP2D6 and age, we found those homozygous for the CYP2C19*17 allele associated with ultrarapid metabolizer (UM) phenotype had a significantly lower mean escitalopram concentration (2-fold, p = 0.0001) and a higher mean metabolic ratio (p = 0.0003) than EMs, while those homozygous for alleles conferring the PM phenotype had a higher mean escitalopram concentration than EMs (1.55-fold, p = 0.008). There was a significant overall association between CYP2C19 genotypic category and escitalopram concentration (p = 0.0003; p = 0.0012 Bonferroni corrected). In conclusion, we have demonstrated an association between CYP2C19 genotype, including the CYP2C19*17 allele, and steady state escitalopram concentration.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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 it