Cell-based analysis of <i>CAD</i> variants identifies individuals likely to benefit from uridine therapy
Bibliographic record
Abstract
ABSTRACT Purpose Pathogenic autosomal recessive variants in CAD , encoding the multienzymatic protein initiating pyrimidine de novo biosynthesis, cause a severe inborn metabolic disorder treatable with a dietary supplement of uridine. This condition is difficult to diagnose given the large size of CAD with over 1000 missense variants and the non-specific clinical presentation. We aimed to develop a reliable and discerning assay to assess the pathogenicity of CAD variants and to select affected individuals that might benefit from uridine therapy. Methods Using CRISPR/Cas9, we generated a human CAD -knockout cell line that requires uridine supplements for survival. Transient transfection of the knockout cells with recombinant CAD restores growth in absence of uridine. This system determines missense variants that inactivate CAD and do not rescue the growth phenotype. Results We identified 25 individuals with biallelic variants in CAD and a phenotype consistent with a CAD deficit. We used the CAD -knockout complementation assay to test a total of 34 variants, identifying 16 as deleterious for CAD activity. Combination of these pathogenic variants confirmed 11 subjects with a CAD deficit, for whom we describe the clinical phenotype. Conclusions We designed a cell-based assay to test the pathogenicity of CAD variants, identifying 11 CAD deficient individuals, who could benefit from uridine therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".