Haplotype structure of CYP2B6 and association with plasma efavirenz concentrations in a Chilean HIV cohort
Bibliographic record
Abstract
OBJECTIVES: Efavirenz is extensively metabolized by CYP2B6, and associations between CYP2B6 polymorphisms and plasma efavirenz exposure have been reported. The objective of this study was to investigate CYP2B6 haplotype structure and functional consequences in a Latin American population. PATIENTS AND METHODS: Two hundred and nineteen patients were recruited at Fundación Arriarán, Chile, between September and December 2008. Plasma efavirenz concentrations were determined using liquid chromatography with mass spectrometry. Genotyping for 30 single nucleotide polymorphisms (SNPs) with a minor allele frequency of >0.05 in the HapMap CEU population at intervals of approximately 1 kb across the CYP2B6 locus was conducted using Sequenom iPLEX MALDI-TOF. RESULTS: Thirteen SNPs passed quality control and, of these, statistically significant associations (P < 0.001) with plasma efavirenz concentrations were observed for 11. Pairwise tagging SNP analysis (R(2) > 0.8) identified 3 SNPs (rs10403955, rs2279345 and rs8192719) representative of the 11 associated SNPs. A composite genetic model of these three alleles was constructed, and an association between carriers of four to six of these alleles and the risk of efavirenz plasma concentrations >4 microg/mL was identified with an odds ratio of 48.1 (95% confidence interval: 13.5-207.7). This represents a positive predictive value of 80.9% and a negative predictive value of 91.8%, with sensitivity of 57.9% and specificity of 97.2%. CONCLUSIONS: A composite genetic model of CYP2B6 SNPs in a Chilean HIV-positive cohort may have value in predicting concentrations of efavirenz associated with a higher likelihood of CNS toxicity. Further investigation of the functional basis of these associations is now required.
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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 | 0.000 |
| 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) | 0.003 | 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".