MRP1 Polymorphisms Associated With Citalopram Response in Patients With Major Depression
Bibliographic record
Abstract
Multidrug resistance protein 1 (MRP1, ABCC1) transports antidepressive agents in the endothelial cells of the blood-brain barrier. Therefore, polymorphisms in the MRP1 gene may affect the treatment response of antidepressants. This study was aimed to identify the association between genetic variations in MRP1/ABCC1 and the therapeutic response to the antidepressant citalopram. One hundred and twenty-three patients who had been treated with citalopram monotherapy to control their major depressive disorder were recruited, and genotype data from 64 patients who had completed their 8-week follow-up were evaluated together with those from 100 controls. Nine MRP1 single nucleotide polymorphisms (SNPs) showing more than 5% allele frequency in the Korean population were analyzed. The c.4002G>A, a synonymous SNP in exon 28, showed a strong association with the remission state at 8 weeks (P = 0.005, odds ratio [OR], 4.7, 95% confidence interval [CI], 1.5 approximately 14.7). The c.4002G>A forms a linkage disequilibrium block with 3 other SNPs including c.5462T>A in the 3' untranslated region. Accordingly, the haplotype showed a significant association with the remission state (P = 0.014). Subsequent molecular studies also supported the association between these MRP1 polymorphisms and the citalopram response. Thus, kinetic studies using MRP1-enriched membrane vesicles revealed that citalopram is a substrate of MRP1 (Km = 1.99 microM, Vmax = 137 pmol/min per milligram protein). In addition, individuals with c.4002G>A or c.5462T>A polymorphisms showed higher MRP1 mRNA levels in peripheral blood cells. These results suggest that MRP1 polymorphisms may be a predictive marker of citalopram treatment in major depression.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".