Clinical, immunological and molecular profiles of DOCK8 deficiency in six patients from a tertiary care centre in North India
Bibliographic record
Abstract
BACKGROUND: Dedicator of cytokinesis protein 8 (DOCK8) deficiency is an autosomal recessive form of combined immunodeficiency. This rare disorder is characterized by an increased predisposition to allergy, autoimmunity and malignancies. OBJECTIVES: To analyse clinical, immunological and molecular profiles of patients with DOCK8 deficiency. METHODS: Clinic records of all patients attending the primary immunodeficiency clinic from 2018 to 2021 were reviewed. Six patients from five families were found to have DOCK8 deficiency. RESULTS: Median age at diagnosis was 7.5 years (range 2-13), with a male/female ratio of 5 : 1. Among the six patients, recurrent eczematous skin lesions were the predominant cutaneous manifestation, present in five patients (83%). Warts and molluscum contagiosum were evident in two patients (33%) and one patient (16%), respectively. Two patients had recalcitrant prurigo nodularis lesions and two had epidermodysplasia verruciformis-like lesions. Food allergies and asthma were reported by one patient each. Of the six patients, recurrent sinopulmonary infections were detected in five (83%). Epstein-Barr virus-driven non-Hodgkin lymphoma with liver metastases was the only case of malignancy, in a 4-year-old boy. IgE was elevated in all patients. Lymphopenia and eosinophilia were observed in three patients (50%) and five patients (83.3%), respectively. Genetic analysis showed DOCK8 pathogenic variants in all patients: homozygous deletion mutations in two patients, compound heterozygous deletion mutations in one, and homozygous nonsense mutations in two. A novel pathogenic homozygous missense variant in the DOCK8 gene was identified in one patient. CONCLUSIONS: DOCK8 deficiency should be considered as a possibility in any patient with early onset eczema, cutaneous viral infections and increased predisposition to allergy, autoimmunity and malignancy.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".