Urinary Interleukin 9 in Youth with Type 1 Diabetes Mellitus
Bibliographic record
Abstract
Background: Interleukin-9 (IL9) is a cytokine that promotes podocyte health in mice with Adriamycin-induced nephrotoxicity but its role in human kidney disease is uncertain. Glomerular podocyte stress leads to the release of microparticles (MP) into the urine and we have reported that urinary Podocyte-derived MPs correlate with both eGFR and blood glucose (BG) in youth with type 1 diabetes (T1D). We first sought to relate urinary IL9 levels to Podocyte-derived MPs in youth with T1D. We then studied the impact of cytokines implicated in diabetic nephropathy, including VEGF, TNFα and IL6, on the relationship between IL9 and ACR, a functional measure of podocyte health. Methods: We performed an analysis of urine samples and clinical data from youth with T1D (n = 53). We measured ACR and used flow cytometry to count urinary podocyte-derived MPs and a Luminex platform (Eve Technologies) to measure a panel of urinary cytokines. Results: Mean age was 14.7±1.6 years and the duration of diabetes was 6.7±2.9 yrs. Mean HbA1c was 70.3±13.9 mmol/mmol. The mean ACR was 1.3±1.9 mg/mmol with a mean eGFR of 140.3±32.6 ml/min/1.73 m2. MPs normalised to urinary creatinine (MP/UCr) were inversely related to IL9 (r= -0.56, p< 0.001) in males and females. BG and eGFR values were associated with IL9 (r=-0.44, p<0.001; r=-0.49, p<0.001; respectively) but the relationship between IL9 and ACR was modest (r=-0.26, p=0.06). There was a significant interaction between IL9, MPs, and ACR (p=0.0066). Urinary IL9 and VEGF levels were positively correlated (r= 0.72, p< 0.001) and the relationship of IL9 with ACR depended on VEGF levels (p=0.0032). The relationship between IL9 and ACR was strongly determined by TNFα levels (p=0.014) and IL6 (p=0.0096). Conclusions: Our analyses show that IL9 is a determinant of podocyte health in early T1D, and that there are complex interactions between urinary IL9, inflammatory cytokines, and ACR.A three-dimensional representation of the relationships between IL-9, MPs, and ACR.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".