Excess BAFF Alters NR4As Expression Levels and Breg Function of Human Precursor-like Marginal Zone B-cells in the Context of HIV-1 infection
Bibliographic record
Abstract
Abstract We have shown that excess B-cell activating factor (BAFF) in the blood of HIV-infected individuals, is concomitant with increased frequencies of precursor-like marginal zone (MZp) B-cells, early on and despite successful antiretroviral therapy (ART). We have recently reported that in HIV-uninfected individuals, MZp possess a strong B-cell regulatory (Breg) potential. As such, MZp B-cells highly express IL-10, the orphan nuclear receptors (NR)4A1, NR4A2, NR4A3, the regulatory molecule CD83, as well as ectonucleotidases CD39 and CD73, all of which are associated with regulation of inflammation. Moreover, the Breg function of MZp B-cells involves CD83 signals. Herein, in order to address the impact of HIV infection and excessive BAFF environment on MZp B-cells and their regulatory capacities, we have performed transcriptomic analyses by RNA-seq of sorted MZp B-cells from the blood of HIV-infected progressors. The Breg profile and function of blood MZp B-cells from HIV-infected progressors were assessed by flow-cytometry and light microscopy high content screening (HCS) analyses, respectively. In addition, the effects of excess BAFF on the Breg profile of MZp B-cells from HIV-uninfected controls were investigated in vitro . We report significant downregulation of NR4A1, NR4A2, NR4A3 and CD83 gene transcripts in blood MZp B-cells from HIV-infected progressors when compared to HIV-uninfected controls. NR4A1, NR4A3 and CD83 protein expression levels and Breg function were also downregulated in blood MZp B-cells from HIV-infected progressors and not restored by ART. Moreover, we observe decreased expression levels of NR4A1, NR4A3, CD83 and IL-10 by blood and tonsillar MZp B-cells from HIV-uninfected individuals following treatment with excess BAFF, which significantly diminished their regulatory function. These findings suggest that excess BAFF contributes to the alteration of the Breg potential of MZp B-cells, which could lead to a loss of “immune surveillance”, during HIV infection and possibly in other situations where BAFF is found in excess. Author Summary The precursor-like marginal zone (MZp) B-cell population, we previously described in human blood and tonsils, presents with an important regulatory “Breg” potential, depicted by elevated nuclear receptor (NR)4As expression levels, similarly to Tregs, and to our knowledge currently underexplored in human Breg studies. Herein, we present the impact that a chronic inflammatory context such as HIV-infection, and its excessive B-cell activating factor (BAFF) environment, may exert on the Breg capacities of MZp, both ex vivo and in vitro , significantly affecting their NR4As expression levels and Breg function. These findings are of growing significance, especially with the recently described importance of MZ B-cell NR4A1 expression in atherosclerosis immune surveillance. The finding that immune surveillance may be altered in circumstances of chronic inflammation and excessive BAFF, is of pivotal interest, as treated HIV-infected individuals often prematurely develop co-morbidities associated with aging such as cardiovascular diseases (CVD). Moreover, excess BAFF has been reported in several inflammatory autoimmune contexts where CVD is the leading cause of death.
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 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 | 0.000 |
| 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) | 0.002 | 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".