Upregulation of IL-32 Isoforms in Virologically Suppressed HIV-Infected Individuals: Potential Role in Persistent Inflammation and Transcription From Stable HIV-1 Reservoirs
Bibliographic record
Abstract
BACKGROUND: Human IL-32 is a polyfunctional cytokine that was initially reported to inhibit HIV-1 infection. However, recent data suggest that IL-32 may enhance HIV-1 replication by activating the HIV-1 primary targets, CD4 T-cells. Indeed, IL-32 is expressed in multiple isoforms, some of which are proinflammatory, whereas others are anti-inflammatory. SETTING AND METHODS: Here, we aimed to determine the relative expression of IL-32 isoforms and to test their inflammatory nature and potential to induce HIV-1 production in latently infected cells from virologically suppressed HIV-infected individuals. IL-32 and other cytokines were quantified from plasma and supernatant of CD4 T-cells by ELISA. Transcripts of IL-32 isoforms were quantified by qRT-PCR in peripheral blood mononuclear cells. The impact of recombinant human IL-32 isoforms on HIV-1 transcription was assessed in CD4 T-cells from HIV-1cART individuals by qRT-PCR. RESULTS: All IL-32 isoforms were significantly upregulated in HIV-1cART compared to HIV individuals with IL-32β representing the dominantly expressed isoform, mainly in T-cells and NK-cells. At the functional level, although IL-32γ induced typical proinflammatory cytokines (IL-6 and IFN-γ) in TCR-activated CD4 T-cells, IL-32α showed an anti-inflammatory profile by inducing IL-10 but not IL-6 or IFN-γ. However, IL-32β showed a dual phenotype by inducing both pro- and anti-inflammatory cytokines. Interestingly, consistent with its highly pro-inflammatory nature, IL-32γ, but not IL-32α or IL-32β, induced HIV-1 production in latently infected CD4 T-cells isolated from combined antiretroviral therapy-treated individuals. CONCLUSIONS: Our data report on the differential expression of IL-32 isoforms and highlight the potential role of IL-32, particularly the γ isoform, in fueling persistent inflammation and transcription of viral reservoir in HIV-1 infection.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".