Genome-Wide Discovery of Drug-Dependent Human Liver Regulatory Elements
Bibliographic record
Abstract
Inter-individual variation in gene regulatory elements is hypothesized to play a causative role in adverse drug reactions and reduced drug activity. However, relatively little is known about the location and function of drug-dependent elements. To uncover drug-associated elements in a genome-wide manner, we performed RNA-seq and ChIP-seq using antibodies against the pregnane X receptor (PXR) and three active regulatory marks (p300, H3K4me1, H3K27ac) on primary human hepatocytes treated with rifampin or vehicle control. Rifampin and PXR were chosen since they are part of the CYP3A4 pathway, which is known to account for the metabolism of more than 50% of all prescribed drugs. We selected 227 proximal promoters for genes with rifampin-dependent expression or nearby PXR/p300 occupancy sites and assayed their ability to induce luciferase in rifampin-treated HepG2 cells, finding only 10 (4.4%) that exhibited drug-dependent activity. As this result suggested a role for distal enhancer modules, we searched more broadly to identify 1,297 genomic regions bearing a conditional PXR occupancy as well as all three active regulatory marks. These regions are enriched near genes that function in the metabolism of xenobiotics, specifically members of the cytochrome P450 family. We performed enhancer assays in rifampin-treated HepG2 cells for 42 of these sequences as well as 7 sequences that overlap linkage-disequilibrium blocks defined by lead SNPs from pharmacogenomic GWAS studies, revealing 15/42 and 4/7 to be functional enhancers, respectively. A common African haplotype in one of these enhancers in the GSTA locus was found to exhibit potential rifampin hypersensitivity. Combined, our results further suggest that enhancers are the predominant targets of rifampin-induced PXR activation, provide a genome-wide catalog of PXR targets and serve as a model for the identification of drug-responsive regulatory elements.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".