HIV Pre-exposure Prophylaxis and Its Impact on the Gut Microbiome in Men Having Sex With Men
Bibliographic record
Abstract
HIV/AIDS still imposes a high epidemiological and societal burden. Together with antiretroviral therapy, pre-exposure prophylaxis (PrEP) represents a fundamental tool in the fight against HIV/AIDS. PrEP is considered effective and safe, even though it may affect organs like the kidney, bone, and liver, as shown by randomized clinical trials (RCTs). These side effects may be mediated by alterations of the gut microbiome. Whilst the impact of the human rectal and vaginal microbiome on HIV prevention has been highly investigated among women, less is known about its effect among men having sex with men (MSM), a vulnerable population at high risk for HIV and disproportionately affected by HIV/AIDS. In the present paper, we will overview the effects of PrEP on the gut microbiota in MSM. Mining PubMed/MEDLINE, we identified three studies that have found significant changes affecting the gut microbiota. However, these shifts in the gut microbiome composition are variable, probably due to methodological differences, even though all studies reviewed in the present overview consistently report aberrations at the level of the gut microbiota. More data are needed, especially concerning the long-term side effects of PrEP: despite the studies included being a high-quality RCT, and two well-designed cross-sectional studies, evidence related to the impact of HIV PrEP on the gut microbiome in MSM is scarce and based on small populations. A better understanding of the interactions between the gut microbiota, sexual orientation/identity, and HIV prevention is expected to improve PrEP adherence and devise strategies to counteract PrEP-related side effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".