LncRNA IL21‐AS1 interacts with hnRNPU protein to promote IL21 overexpression and aberrant differentiation of Tfh cells in systemic lupus erythematosus
Bibliographic record
Abstract
BACKGROUND: The aberrant differentiation of T follicular helper (Tfh) cells plays an important role in the pathogenesis of systemic lupus erythematosus (SLE). However, the mechanism of regulating Tfh cells differentiation remains unclear. Long noncoding RNAs (lncRNAs) act as important regulators in the processes of innate and adaptive immune response. Whether lncRNAs are involved in regulating Tfh cell differentiation and autoimmune responses need to be further identified. METHODS: The characters and functions of human IL21-AS1 and its mouse homologous lncRNA (mIl21-AS) were investigated by a series of biochemical assays and cell transfection assay. mIl21-AS1 regulating humoral immune response in vivo was explored by keyhole limpet haemocyanin (KLH) and chronic graft versus host disease (cGVHD) model. RESULTS: T cells of SLE patients and Tfh cells, which promoted differentiation of Tfh cells. Mechanistically, IL21-AS1 bound heterogeneous nuclear ribonucleoprotein U and recruited acetyltransferases CREB-binding protein to the promoter of IL21, leading to the transcriptional activation of IL21 and Tfh cells differentiation through increasing Histone H3 acetylation level on IL21 promoter. Moreover, Tfh proportion and antibodies production were significantly increased in mIl21-AS knock-in mice immunized with KLH. mIl21-AS1 overexpression also exacerbated the lupus-like phenotype in cGVHD mice model. CONCLUSIONS: Our results demonstrate that IL21-AS1 activates IL21 transcription via epigenetic mechanism to promote germinal centre response, adding insight into the molecular regulation of autoimmune pathogenesis and providing a novel target for SLE treatment.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".