ACMG/AMP variant classification framework in arginase 1 deficiency: Implications for birth prevalence estimates and diagnostics
Bibliographic record
Abstract
Purpose Arginase 1 (ARG1) deficiency manifests with hyperargininemia and progressive neurological impairment. Recent estimates of birth prevalence using allele frequencies of ARG1 variants do not sufficiently distinguish benign from pathogenic variants. Additionally, ongoing discussions of reproductive carrier screening for diseases such as ARG1 creates a need for improved understanding of ARG1 variant classification. Here, we incorporate American College of Medical Genetics and Genomics/Association for Molecular Pathology–developed guidelines for interpreting gene variants and in silico predictions to select allele frequencies for estimation of global birth prevalence of ARG1 deficiency. Methods We interrogated Genome Aggregation Database and PubMed for published (defined as identified in patients with clinically defined arginase deficiency in scientific literature, n = 73) and unpublished ARG1 variants (defined as variants present in Genome Aggregation Database, unique to ARG1 , but not yet associated with clinical arginase deficiency, n = 302). American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines were applied to classify variants using Franklin Genoox artificial intelligence–powered platform and manual review. Results Of 73 published ARG1 variants, 16 classified as pathogenic, 30 as likely pathogenic, and 27 as variant of uncertain significance. Of 302 unpublished ARG1 variants, 3 classified as pathogenic, 28 likely pathogenic, and 229 variant of uncertain significance. Mutant allele frequency estimates ranged from 17 to 266 per 100,000 and birth prevalence from 1 in 141,331 to 34,602,076. Conclusion We show that a large proportion of ARG1 variants lack adequate evidence of pathogenicity. These findings underscore the significance of functional studies and accumulating clinical data for determination of variant pathogenicity and for improved understanding of global birth prevalence of ARG1 deficiency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".