Sequence‐Based Screening of Patients With Idiopathic Polyarteritis Nodosa, Granulomatosis With Polyangiitis, and Microscopic Polyangiitis for Deleterious Genetic Variants in <i>ADA2</i>
Bibliographic record
Abstract
OBJECTIVE: Deficiency of adenosine deaminase 2 (DADA2) is a monogenic form of vasculitis that can resemble polyarteritis nodosa (PAN). This study was undertaken to identify potential disease-causing sequence variants in ADA2 in patients with idiopathic PAN, granulomatosis with polyangiitis (GPA), or microscopic polyangiitis (MPA). METHODS: Patients with idiopathic PAN (n = 118) and patients with GPA or MPA (n = 1,107) were screened for rare nonsynonymous variants in ADA2 using DNA sequencing methods. ADA-2 enzyme activity was assessed in selected serum samples. RESULTS: Nine of 118 patients with PAN (7.6%) were identified as having rare nonsynonymous variants in ADA2. Four patients (3.4%) were biallelic for pathogenic or likely pathogenic variants, and 5 patients (4.2%) were monoallelic carriers for 3 variants of uncertain significance and 2 likely pathogenic variants. Serum samples from 2 patients with PAN with biallelic variants were available and showed markedly reduced ADA-2 enzyme activity. ADA-2 enzyme testing of 86 additional patients revealed 1 individual with strongly reduced ADA-2 activity without detectable pathogenic variants. Patients with PAN and biallelic variants in ADA2 were younger at diagnosis than patients with 1 or no variant in ADA2, with no other clinical differences noted. None of the patients with GPA or MPA carried biallelic variants in ADA2. CONCLUSION: A subset of patients with idiopathic PAN meet genetic criteria for DADA2. Given that tumor necrosis factor inhibition is efficacious in DADA2 but is not conventional therapy for PAN, these findings suggest that ADA-2 testing should strongly be considered in patients with hepatitis B virus-negative idiopathic PAN.
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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 | 0.002 |
| 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 | 0.000 | 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".