Tregs from T1D subjects with a susceptible IL-2R gene SNP, respond aberrantly to IL-2 stimulation. (P4080)
Bibliographic record
Abstract
Abstract Type 1 diabetes (T1D) results from the destruction of beta cells by autoreactive lymphocytes. Regulatory T cells (Tregs) maintain self-tolerance in part by suppressing the effector functions of self-reactive lymphocytes. Tregs require the cytokine interleukin-2 (IL-2) for survival and maintenance of their suppressive function. IL-2 binds to the high-affinity IL-2 receptor (IL-2R), leading to phosphorylation of signal transducer and activator of transcription 5 (STAT5) and downstream transcription of effector proteins.The IL-2 receptor gene has single nucleotide polymorphisms (SNPs), which are associated with T1D incidence. We hypothesized that T1D subjects with SNPs in the IL-2R gene possess Tregs that respond aberrantly to IL-2 and do not optimally induce signaling in the STAT5 pathway. PBMC from T1D subjects with a homozygous susceptible (GG), heterozygous (AG) and homozygous wild-type (AA) genotype for a SNP located in the rs3118470 locus of the IL-2R gene were stimulated with IL-2. Our results indicate that Tregs from individuals with the homozygous susceptible GG genotype have reduced levels of pSTAT5 compared to those with the AA genotype (p=0.0133). This provides evidence that Tregs from T1D subjects with SNPs in the rs3118470 locus of the IL-2R gene have diminished STAT5 phosphorylation in response to IL-2. This is a potential mechanism of defective Treg function in a genetically identifiable subset of children with T1D.
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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) | 0.004 | 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".