Enhanced differentiation between 3‐hydroxyglutaric and 2‐hydroxyglutaric acids facilitates diagnostic testing for glutaric aciduria type 1
Bibliographic record
Abstract
Abstract Glutaric aciduria type 1 (GA1) is an inherited neurometabolic disorder, in which deficiency of glutaryl‐CoA dehydrogenase leads to accumulation of glutaric acid (GA) and 3‐hydroxyglutaric acid (3‐HG). Some low excretors may exhibit only slight elevation of urinary 3‐HG, with normal urinary GA, yet are at significant risk of severe clinical disease. Accurate quantitation of urinary 3‐HG is crucial in diagnostic workup for GA1, but in this context, current gas chromatography–mass spectrometry (GC–MS) methods have inherent analytical challenges. Co‐elution and spectral similarities of the 3‐HG and 2‐HG structural isomers can cause difficulties in quantitation of slightly elevated 3‐HG. Our laboratory recently acquired a gas chromatography system coupled to a triple quadrupole mass spectrometer (GC–MS/MS), and we took advantage of its increased sensitivity and specificity to improve our existing GC–MS method. A stable isotope dilution process is used, with sample treatment consisting of a double liquid–liquid extraction followed by a trimethylsilyl derivatization. The transitions m/z 349 → 333 for 3‐HG and m/z 349 → 321 for 2‐HG were selected to differentiate these two isobaric molecules based on their characteristic fragments, thus minimizing interferences despite co‐elution. Method validation demonstrated satisfactory precision and accuracy. Using GC–MS/MS instead of GC–MS allowed us to decrease the required specimen volume, number of sample processing steps, chromatographic run time, and instrument maintenance. This enhanced assay facilitates clinical laboratory testing for GA1, both in confirmatory protocols following positive newborn screening and in diagnostic investigation of patients with suggestive signs or symptoms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".