Plasma miR-26a as a Diagnostic Biomarker Regulates Cytokine Expression in Systemic Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: We sought to identify specific microRNA (miRNA) for systemic juvenile idiopathic arthritis (sJIA) and to determine the involvement of these miRNA in regulating the expression of cytokines. METHODS: Microarray profiling was performed to identify differentially expressed miRNA in sJIA plasma. Levels of candidate miRNA and mRNA were assessed by real-time PCR, and cytokines were measured by ELISA. Dual-luciferase reporter assay was used to validate the direct interaction between miR-26a and interleukin 6 (IL-6). RESULTS: Forty-eight miRNA were differentially expressed in the plasma of patients with sJIA compared with healthy controls (HC). Five miRNA were selected for further validation. The expression level of miR-26a was exclusively elevated in the plasma of patients with sJIA as compared with 4 rheumatic diseases and 2 subtypes of JIA (oligoarticular and polyarticular). The levels of IL-6, IL-1β, and tumor necrosis factor-α in the plasma of patients with sJIA were increased, and only IL-6 presented a positive correlation with miR-26a (r = 0.539, p < 0.0001). After stimulation with IL-6, miR-26a expression was upregulated in THP-1 cells, while the supernatant level of IL-6 was downregulated by transfection of miR-26a mimics. Consistently, direct target relationship between miR-26a and IL-6 was confirmed. CONCLUSION: This study demonstrates that miR-26a is expressed specifically and highly in sJIA plasma and suggests that miR-26a may regulate the levels of cytokines in sJIA. Our findings highlight miR-26a as a potential biomarker for the diagnosis as well as differential diagnosis of sJIA.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".