Specific post-translational histone modifications of neutrophil extracellular traps as immunogens and potential targets of lupus autoantibodies
Bibliographic record
Abstract
INTRODUCTION: Autoreactivity to histones is a pervasive feature of several human autoimmune disorders, including systemic lupus erythematosus (SLE). Specific post-translational modifications (PTMs) of histones within neutrophil extracellular traps (NETs) may potentially drive the process by which tolerance to these chromatin-associated proteins is broken. We hypothesized that NETs and their unique histone PTMs might be capable of inducing autoantibodies that target histones. METHODS: We developed a novel and efficient method for the in vitro production, visualization, and broad profiling of histone-PTMs of human and murine NETs. We also immunized Balb/c mice with murine NETs and profiled their sera on autoantigen and histone peptide microarrays for evidence of autoantibody production to their immunogen. RESULTS: We confirmed specificity toward acetyl-modified histone H2B as well as to other histone PTMs in sera from patients with SLE known to have autoreactivity against histones. We observed enrichment for distinctive histone marks of transcriptionally silent DNA during NETosis triggered by diverse stimuli. However, NETs derived from human and murine sources did not harbor many of the PTMs toward which autoreactivity was observed in patients with SLE or in MRL/lpr mice. Further, while murine NETs were weak autoantigens in vivo, there was only partial overlap in the immunoglobulin G (IgG) and IgM autoantibody profiles induced by vaccination of mice with NETs and those seen in patients with SLE. CONCLUSIONS: Isolated in vivo exposure to NETs is insufficient to break tolerance and may involve additional factors that have yet to be identified.
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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 | 0.000 |
| 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 | 0.000 |
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".