Strong Human Endogenous Retrovirus-Specific T Cell Responses Are Associated with Control of HIV-1 in Chronic Infection
Bibliographic record
Abstract
Eight percent of the human genome is composed of human endogenous retroviruses (HERVs), which are thought to be inactive remnants of ancient infections. Previously, we showed that individuals with early HIV-1 infection have stronger anti-HERV T cell responses than uninfected controls. In this study, we investigated whether these responses persist in chronic HIV-1 infection and whether they have a role in the control of HIV-1. Peripheral blood mononuclear cells (PBMCs) from 88 subjects diagnosed with HIV-1 infection for at least 1 year (median duration of diagnosis, 13 years) were tested for responses against HERV peptides in gamma interferon (IFN-γ) enzyme immunospot (ELISPOT) assays. Individuals who control HIV-1 viremia without highly active antiretroviral therapy (HAART) had stronger and broader HERV-specific T cell responses than HAART-suppressed patients, virologic noncontrollers, immunologic progressors, and uninfected controls (P < 0.05 for each pairwise comparison). In addition, the magnitude of the anti-HERV T cell response was inversely correlated with HIV-1 viral load (r(2) = 0.197, P = 0.0002) and associated with higher CD4(+) T cell counts (r(2) = 0.072, P = 0.027) in untreated patients. Flow cytometric analyses of an HLA-B51-restricted CD8(+) HERV response in one HIV-1-infected individual revealed a less activated and more differentiated phenotype than that stimulated by a homologous HIV-1 peptide. HLA-B51 tetramer dual staining within this individual confirmed two different T cell populations corresponding to these HERV and HIV-1 epitopes, ruling out cross-reactivity. These findings suggest a possible role for anti-HERV immunity in the control of chronic HIV-1 infection and provide support for a larger effort to design an HIV-1 vaccine that targets conserved antigens such as HERV.
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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 | 0.001 | 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 | 0.000 |
| 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".