First Analysis of the Association Between CYP3A4/5, ABCB1 Genetic Polymorphisms and Oxcarbazepine Metabolism and Transport in Chinese Epileptic Patients with Oxcarbazepine Monotherapy and Bitherapy
Bibliographic record
Abstract
PURPOSE: Oxcarbazepine (OXC) is widely used in anti-epileptic treatment. Cytochrome P450 3A4 (CYP3A4), cytochrome P450 3A5(CYP3A5), and ATP-binding cassette sub-family B member 1 (ABCB1) are potential genes involved in OXC metabolisms and transport in vivo. This study aims to examine the genetic effects of CYP3A4, CYP3A5, and ABCB1 on OXC metabolism and transport in Chinese epileptic patients using OXC as monotherapy and bitherapy with lamotrigine (LTG), levetiracetam (LEV), or valproic acid (VPA). METHODS: Sixty-six Chinese epileptic patients were recruited from Xiangya Hospital Central South University, of whom 40 patients were receiving OXC monotherapy, 11 patients were placed in the OXC bitherapy group combined with one enzyme-inducing anti-epileptic drugs (LTG or LEV), and 15 patients were placed in the OXC bitherapy group combined with VPA. Oxcarbazepine and its main metabolite 10-hydrocarbazepine (MHD) plasma concentrations were measured using high performance liquid chromatography (HPLC)-UV method. In addition, eight single nucleotide polymorphisms (SNPs) in CYP3A4, CYP3A5, ABCB1 gene were genotyped by polymerase chain reaction-improved multiple ligase detection reaction (PCR-iMLDR). RESULTS: In the OXC+VPA group, ABCB1 rs2032582 and rs2032582-rs10234411-rs1045642 TAG haplotype were associated with MHD and MHD+OXC plasma concentration before permutation test. In OXC monotherapy and OXC+ LTG/LEV groups, no significant association between genetic polymorphisms in CYP3A4/5, ABCB1 gene and OXC plasma concentration parameters were observed. CONCLUSION: CYP3A4/5 and ABCB1 genetic variants might not take part in the metabolism and transport of MHD and OXC among epileptic patients using OXC monotherapy and bitherapy in combination with LEV, LTG or VPA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".