Hematopoietic stem cell transplant effectively rescues lymphocyte differentiation and function in DOCK8-deficient patients
Bibliographic record
Abstract
Bi-allelic inactivating mutations in DOCK8 cause a combined immunodeficiency characterised by severe pathogen infections, eczema, allergies, malignancy and impaired humoral responses. These clinical features result from functional defects in most lymphocyte lineages. Thus, DOCK8 plays a key role in immune cell function. Hematopoietic stem cell transplantation (HSCT) is curative for DOCK8 deficiency. While previous reports have described clinical outcomes for DOCK8 deficiency following HSCT, the effect on lymphocyte reconstitution and function has not been investigated. Our study determined whether defects in lymphocyte differentiation and function in DOCK8-deficient patients were restored following HSCT. DOCK8-deficient T and B lymphocytes exhibited aberrant activation and effector function in vivo and in vitro. Frequencies of αβ T and MAIT cells were reduced while γδT cells were increased in DOCK8-deficient patients. HSCT improved, abnormal lymphocyte function in DOCK8-deficient patients. Elevated total and allergen-specific IgE in DOCK8-deficient patients decreased over time following HSCT. Our results document the extensive catalogue of cellular defects in DOCK8-deficient patients, and the efficacy of HSCT to correct these defects, concurrent with improvements in clinical phenotypes. Overall, our findings provide mechanisms at a functional cellular level for improvements in clinical features of DOCK8 deficiency post-HSCT, identify biomarkers that correlate with improved clinical outcomes, and inform the general dynamics of immune reconstitution in patients with monogenic immune disorders following HSCT.
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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) | 0.001 | 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".