CD4+ T Cells Expressing PD-1, TIGIT and LAG-3 Contribute to HIV Persistence during ART
Why this work is in the frame
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Bibliographic record
Abstract
HIV persists in a small pool of latently infected cells despite antiretroviral therapy (ART). Identifying cellular markers expressed at the surface of these cells may lead to novel therapeutic strategies to reduce the size of the HIV reservoir. We hypothesized that CD4+ T cells expressing immune checkpoint molecules would be enriched in HIV-infected cells in individuals receiving suppressive ART. Expression levels of 7 immune checkpoint molecules (PD-1, CTLA-4, LAG-3, TIGIT, TIM-3, CD160 and 2B4) as well as 4 markers of HIV persistence (integrated and total HIV DNA, 2-LTR circles and cell-associated unspliced HIV RNA) were measured in PBMCs from 48 virally suppressed individuals. Using negative binomial regression models, we identified PD-1, TIGIT and LAG-3 as immune checkpoint molecules positively associated with the frequency of CD4+ T cells harboring integrated HIV DNA. The frequency of CD4+ T cells co-expressing PD-1, TIGIT and LAG-3 independently predicted the frequency of cells harboring integrated HIV DNA. Quantification of HIV genomes in highly purified cell subsets from blood further revealed that expressions of PD-1, TIGIT and LAG-3 were associated with HIV-infected cells in distinct memory CD4+ T cell subsets. CD4+ T cells co-expressing the three markers were highly enriched for integrated viral genomes (median of 8.2 fold compared to total CD4+ T cells). Importantly, most cells carrying inducible HIV genomes expressed at least one of these markers (median contribution of cells expressing LAG-3, PD-1 or TIGIT to the inducible reservoir = 76%). Our data provide evidence that CD4+ T cells expressing PD-1, TIGIT and LAG-3 alone or in combination are enriched for persistent HIV during ART and suggest that immune checkpoint blockers directed against these receptors may represent valuable tools to target latently infected cells in virally suppressed individuals.
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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 | 0.000 | 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 | 0.007 |
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 it