Increased oral Epstein-Barr virus shedding with HIV-1 co-infection is due to a combination of B cell activation and impaired cellular immune control
Bibliographic record
Abstract
Abstract Epstein-Barr virus (EBV) infection is transmitted by saliva and is a major cause of cancer in people living with HIV/AIDS as well as in the general population. To better understand the determinants of oral EBV shedding we evaluated the frequency and quantity of detectable EBV in the saliva in a prospective cohort study of 85 adults in Uganda, half of whom were co-infected with HIV-1. Participants were not receiving antiviral medications, and those with HIV-1 co-infection had a CD4+ T cell count >200 cells/mm 3 . Daily, self-collected oral swabs were collected over a 4-week period. Compared with HIV-1 uninfected participants, co-infected participants had an increased frequency of oral EBV shedding (IRR=1.27, 95% CI=1.10-1.47). To explain why EBV oral shedding is greater in HIV-1 co-infected participants, we developed a stochastic, mechanistic mathematical model that describes the dynamics of EBV, infected cells, and antiviral cellular immune responses within the tonsillar epithelium, and examined parameter-specific differences between individuals of different HIV-1 infection statuses. We fit the model to our observational data using Approximate Bayesian Computation. After fitting, model simulations showed high fidelity to daily oral shedding time-courses and matched key summary statistics. Examination of the model revealed that higher EBV loads in saliva are driven by B cell activation causing EBV lytic replication in the tonsils, in combination with a less effective EBV-specific cellular immune response. Thus, both these factors contribute to higher and more frequent EBV shedding in HIV-1 co-infected individuals compared to HIV-1 uninfected individuals. These conclusions were further validated by modelling daily oral EBV shedding in a 26-participant North American cohort. Our results provide insights into the determinants of EBV shedding and implicate B cell activation to be a potential therapeutic target to reduce EBV replication in HIV-1 co-infected individuals at high risk for EBV-related malignancies. Author summary Epstein-Barr virus (EBV) is a ubiquitous infection worldwide. Infection with EBV is associated with the development of several kinds of cancer, including B cell lymphoma and nasopharyngeal carcinoma. Rates of EBV replication and disease are higher in individuals who are also infected with HIV-1. HIV-1 infection is associated with increased B cell activation, which is known to induce EBV reactivation, as well as immunodeficiency resulting from loss of T cells. However, whether these factors contribute to higher rates of EBV replication during co-infection, and by how much, was unknown. We analysed oral EBV shedding data in a cohort of adults from Uganda that were chronically infected with EBV. We found that participants that were HIV-1 infected were much more likely to have detectable quantities of EBV in their saliva. Also, when detected, the quantity of EBV present in the saliva was usually higher in HIV-1 infected participants. To better understand these findings, we developed a mathematical model to describe the dynamics of EBV, EBV-infected cells, and the cellular immune response within the tonsils. By rigorously matching our model to our participant data, we determined that high EBV loads in saliva are caused by high rates of infected B cell activation, as well as worse cellular immune control of EBV infection. These results provide an explanation of the impact of HIV-1 on EBV infection. Further, they suggest that strategies that suppress B cell activation may prevent EBV-related malignancy in people who are also infected with HIV-1.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".