The B10 <i>Idd9.3</i> Locus Mediates Accumulation of Functionally Superior CD137+ Regulatory T Cells in the Nonobese Diabetic Type 1 Diabetes Model
Bibliographic record
Abstract
CD137 is a T cell costimulatory molecule encoded by the prime candidate gene (designated Tnfrsf9) in NOD.B10 Idd9.3 congenic mice protected from type 1 diabetes (T1D). NOD T cells show decreased CD137-mediated T cell signaling compared with NOD.B10 Idd9.3 T cells, but it has been unclear how this decreased CD137 T cell signaling could mediate susceptibility to T1D. We and others have shown that a subset of regulatory T cells (Tregs) constitutively expresses CD137 (whereas effector T cells do not, and only express CD137 briefly after activation). In this study, we show that the B10 Idd9.3 region intrinsically contributes to accumulation of CD137(+) Tregs with age. NOD.B10 Idd9.3 mice showed significantly increased percentages and numbers of CD137(+) peripheral Tregs compared with NOD mice. Moreover, Tregs expressing the B10 Idd9.3 region preferentially accumulated in mixed bone marrow chimeric mice reconstituted with allotypically marked NOD and NOD.B10 Idd9.3 bone marrow. We demonstrate a possible significance of increased numbers of CD137(+) Tregs by showing functional superiority of FACS-purified CD137(+) Tregs in vitro compared with CD137(-) Tregs in T cell-suppression assays. Increased functional suppression was also associated with increased production of the alternatively spliced CD137 isoform, soluble CD137, which has been shown to suppress T cell proliferation. We show for the first time, to our knowledge, that CD137(+) Tregs are the primary cellular source of soluble CD137. NOD.B10 Idd9.3 mice showed significantly increased serum soluble CD137 compared with NOD mice with age, consistent with their increased numbers of CD137(+) Tregs with age. These studies demonstrate the importance of CD137(+) Tregs in T1D and offer a new hypothesis for how the NOD Idd9.3 region could act to increase T1D susceptibility.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| 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".