Quantitative profiling of cytokines and chemokines in <scp>DOCK</scp>8‐deficient and atopic dermatitis patients
Bibliographic record
Abstract
BACKGROUND: Hyper-IgE syndromes (HIES) are a clinically overlapping, heterogeneous group of inborn errors of immunity characterized by elevated serum IgE level, eosinophilia, atopy, and immune dysregulation. Deficiency of DOCK8 protein is potentially a life-threatening autosomal recessive HIES and only curable with bone marrow transplantation. Hence, the diagnosis of DOCK8 deficiency is critical and should be sought at an early stage to initiate definitive therapy. METHODS: Serum samples from patients with DOCK8 deficiency and atopic dermatitis were profiled on a cytokine/chemokine panel for potential differential expression. RESULTS: CXCL10 and TNF-A were upregulated in DOCK8 patients when compared to AD, possibly contributing toward increased susceptibility to infections and cancer. In contrast, epidermal growth factor (EGF) was significantly downregulated in a subgroup of DOCK8-deficient and AD patients, while IL-31 expression was comparable between both DOCK8-deficient and AD cohorts, possibly contributing toward pruritus seen in both groups. CONCLUSION: This comprehensive cytokine profile in HIES patients reveals distinctive biomarkers that differentiate between the DOCK8-deficient and AD patients. The unique expression profile of various inflammatory cytokines in patients with DOCK8 deficiency vs atopic dermatitis likely reflects disease-specific perturbations in multiple cellular processes and pathways leading to a predisposition to infections and allergies seen in these patients. These data agree with the role for EGF replacement therapy in EGF-deficient individuals with AD as well as DOCK8 deficiency through a potential shared pathway. In addition, these novel biomarkers may be potentially useful in distinguishing DOCK8 deficiency from AD allowing early-targeted treatment options.
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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 | 0.000 | 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) | 0.000 | 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".