A167 UNDERSTANDING THE IMPACT OF DOWNSTREAM OF KINASE 4 (DOK4) DAMAGING GENETIC VARIANTS IN THE PATHOGENESIS OF PEDIATRIC INFLAMMATORY BOWEL DISEASE (IBD).
Bibliographic record
Abstract
Abstract Background IBD is a chronic inflammatory disorder of the gastrointestinal (GI) tract whose precise pathological mechanisms remain elusive. It is thought that in pediatric IBD, pathogenic exposure does not appear sufficient to cause disease, thus genetic variations are critical to disease pathogenesis. The Muise Lab uses genetic sequencing of patients with IBD from all over the world to identify crucial genetic variations that are critical to IBD development. We report two patients with IBD from unrelated families with mutations in DOK4. Both patients had profound extra-intestinal disease complicating their IBD. Downstream of kinase (DOK) proteins are a family of adaptor molecules that are important in regulating cell signaling, especially in immune cells. They are known to suppress MAPK and PI3K/AKT pathways, whose dysregulation result in cancer. DOK4 has not been extensively studied, but research suggests that this gene produces two isoforms. It is known to have negative regulatory effects on immune cell activation but is also expressed across various other tissues, where its function is yet to be determined. Aims We hypothesize that these variations in DOK4 lead to immune cell dysregulation, which manifests in both gastrointestinal and systemic chronic inflammatory disease. Through this study, we aim to elucidate the mechanism of novel genetic defects in DOK4. Methods It will be critical to understand how variants within both patients are contributing to the onset of IBD through in vitro studies. Therefore, we will characterize and quantify how changes in expression of DOK4 alters essential cell signaling pathways. We have established immortalized cell lines from patients bearing these mutations to specifically characterize potential immune defects. We will also be using knock out cell models to understand the effect of loss of function of DOK4 in different cell types. Results Preliminary data shows variation in expression of the protein within patient peripheral blood mononuclear cells (PBMCs) compared to a healthy donor. Overexpression in HEK293T cells shows changes in MAPK and NFkB signaling. Conclusions With this study, we hope to identify new therapeutic targets for patients with DOK4 mutations. Funding Agencies CIHRThe Leona M. and Harry B. Helmsley Charitable Trust
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".