Evidence for regulation of UDP-glucuronosyltransferase (UGT) 1A1 protein expression and activity via DNA methylation in healthy human livers
Bibliographic record
Abstract
OBJECTIVES: Interindividual variability in glucuronidation of bilirubin and drugs by UDP-glucuronosyltransferase 1A1 (UGT1A1) is considerable and only partially explained by genetic polymorphisms and enzyme inducers. Here we determined whether a well-known epigenetic modification, cytosine methylation, explains a proportion of this variability in human liver. METHODS: UGT1A1 phenotypes, including UGT1A1 protein and bilirubin glucuronidation, and UGT1A1*28 genotype 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. KEY FINDINGS: Individual CpG sites showed considerable methylation variability between livers, ranging from 10- to 29-fold variation 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. Exclusion of livers with *28/*28 genotype or alcohol history revealed positive correlations of -4 CpG methylation with bilirubin glucuronidation (R = 0.73, P < 0.00001) and UGT1A1 protein content (R = 0.54, P = 0.008). CONCLUSION: These results suggest that differential methylation of the -4 CpG site located within a known USF response element may explain a proportion of interindividual variability in hepatic glucuronidation by UGT1A1.
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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) | 0.002 | 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".