CD4 T cell counts are inversely correlated with anti-gp120 cluster A antibodies in antiretroviral therapy-treated PLWH
Bibliographic record
Abstract
Background While antiretroviral therapy (ART) efficiently suppresses viral replication, inflammation and immune dysfunction persist in some people living with HIV-1 (PLWH). HIV-1 soluble gp120 (sgp120) has been detected in PLWH plasma and its presence is linked to immune dysfunction. It was reported that sgp120 binding to CD4 on uninfected bystander CD4 + T cells sensitises them to cellular death via antibody-dependent cellular cytotoxicity (ADCC) mediated by non-neutralising anti-cluster A antibodies (Abs) present in PLWH plasma. Methods We included plasma from 520 PLWH on ART from three independent cohorts for measurements of anti-cluster A Abs and anti-CD4 binding site (anti-CD4BS) Abs. Associations between CD4 + T cell counts and anti-cluster A Abs was assessed using generalised least squares linear regression models, adjusting for potential confounders including age, sex, nadir CD4 and duration of ART. The role of anti-CD4BS Abs was evaluated using flow-cytometry based ADCC assays with primary CD4 + T cells. Findings We observed that non-neutralising anti-cluster A Abs are negatively associated with CD4 + T cell counts. Anti-CD4BS antibodies blocked the coating of uninfected bystander cells by sgp120, thereby preventing their elimination by ADCC. Supporting a protective role of anti-CD4BS antibodies, their presence in PLWH plasma abrogated the negative association between CD4 counts and anti-cluster A Abs. Interpretation Our results reveal that anti-cluster A Abs are associated with immune dysfunction in PLWH and anti-CD4BS antibodies might have a beneficial impact in these individuals. Funding This study was supported by the Canadian Institutes of Health Research, the Canada Foundation for Innovation, the Fonds de Recherche du Québec-Santé, and the National Institutes of Health.
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 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 | 0.001 |
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".