Evidence for epigenetic regulation of UGT1A1 protein expression and activity in healthy human livers
Bibliographic record
Abstract
Interindividual variability in UDP‐glucuronosyltransferase 1A1 (UGT1A1) is only partially explained by genetic polymorphisms and enzyme inducers. Here we determined whether cytosine methylation explains an additional proportion of this variability in human liver. UGT1A1 phenotypes, including UGT1A1 protein and bilirubin glucuronidation, and UGT1A1*28 were determined using a human liver bank (n=46). Methylation levels were quantified at 5 CpG sites associated with known transcription factor response elements in the UGT1A1 promoter and distal enhancer, as well as a CpG‐rich island 1.5 kb further upstream. Individual CpG sites showed considerable methylation variability ranging from 10‐ to 29‐fold difference with average methylation levels from 25 to 41%. Multivariate regression analysis identified *28/*28 genotype, −4 CpG site methylation, and alcohol history as significant predictors of UGT1A1 protein content, accounting for 12%, 11%, and 9% of the variability (R2=0.32, p=0.003). Similarly, −4 CpG methylation and alcohol history accounted for 13% and 12% of the variability in bilirubin glucuronidation (R2=0.25, p=0.005). These results suggest that differential methylation of the −4 CpG site located within a known USF response element may explain a proportion of variability in hepatic glucuronidation by UGT1A1. Funded by NIH‐R01‐ GM061834 (to MHC) and NIH‐N01‐DK‐7–0004/ HHSN267200700004C.
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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 | 0.000 | 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) | 0.000 | 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".