Functional characterisation of a novel homozygous p.Y227C ADA2 variant in a child with deficiency of adenosine deaminase type 2
Bibliographic record
Abstract
OBJECTIVES: Deficiency of adenosine deaminase 2 (DADA2) is a rare inflammatory disorder caused by biallelic loss-of-function mutations in ADA2. We sought to functionally characterise a novel homozygous ADA2 variant, p.Y227C (c.680A>G), identified in a six-year-old patient presenting with recurrent fevers, erythema nodosum, and tumor necrosis factor (TNF) inhibitor-responsive myositisMETHODS: Monocyte-derived macrophages from the patient were analysed for ADA2 protein expression, enzymatic activity, and TNFα secretion. To model the inflammatory phenotype in vitro, THP-1 cells were engineered to express the p.Y227C variant. Lentiviral gene correction with wild-type ADA2 was performed to assess rescue of enzymatic function and inflammatory responses. RESULTS: Patient-derived macrophages exhibited markedly reduced ADA2 protein levels and enzymatic activity, accompanied by increased TNFα secretion. THP-1 cells expressing the p.Y227C variant recapitulated this proinflammatory phenotype. Lentiviral reconstitution with wild-type ADA2 restored protein expression and enzymatic activity and normalised TNFα release. CONCLUSIONS: The p.Y227C ADA2 variant is pathogenic and promotes inflammation through loss of ADA2 function. Functional rescue following gene correction confirms the causal role of this mutation and underscores the therapeutic potential of restoring ADA2 activity in DADA2.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".