HIV-1 Alters Intestinal Expression of Drug Transporters and Metabolic Enzymes: Implications for Antiretroviral Drug Disposition
Bibliographic record
Abstract
This study investigated the effects of HIV-1 infection and antiretroviral therapy (ART) on the expression of intestinal drug efflux transporters, i.e., P-glycoprotein (Pgp), multidrug resistance-associated proteins (MRPs), and breast cancer resistance protein (BCRP), and metabolic enzymes, such as cytochrome P450s (CYPs), in the human upper intestinal tract. Intestinal biopsy specimens were obtained from HIV-negative healthy volunteers, ART-naive HIV-positive (HIV(+)) subjects, and HIV(+) subjects receiving ART (10 in each group). Intestinal tissue expression of drug transporters and metabolic enzymes was examined by microarray, real-time quantitative reverse transcription-PCR (qPCR), and immunohistochemistry analyses. Microarray analysis demonstrated significantly lower expression of CYP3A4 and ABCC2/MRP2 in the HIV(+) ART-naive group than in uninfected subjects. qPCR analysis confirmed significantly lower expression of ABCC2/MRP2 in ART-naive subjects than in the control group, while CYP3A4 and ABCG2/BCRP showed a trend toward decreased expression. Protein expression of MRP2 and BCRP was also significantly lower in the HIV(+) naive group than in the control group and was partially restored to baseline levels in HIV(+) subjects receiving ART. In contrast, gene and protein expression of ABCB1/Pgp was significantly increased in HIV(+) subjects on ART relative to HIV(+) ART-naive subjects. These data demonstrate that the expression of drug-metabolizing enzymes and efflux transporters is significantly altered in therapy-naive HIV(+) subjects and in those receiving ART. Since CYP3A4, Pgp, MRPs, and BCRP metabolize or transport many antiretroviral drugs, their altered expression with HIV infection may negatively impact drug pharmacokinetics in HIV(+) subjects. This has clinical implications when using data from healthy volunteers to guide ART.
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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 | 0.000 |
| 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) | 0.001 | 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 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".