Diagnosis of glutaric aciduria type 1 by measuring 3‐hydroxyglutaric acid in dried urine spots by liquid chromatography tandem mass spectrometry
Bibliographic record
Abstract
Accumulation of glutaric acid (GA) and 3-hydroxyglutaric acid (3HGA) in body fluids is the biochemical hallmark of type 1 glutaric aciduria (GA1), a disorder characterized by acute striatal degeneration and a subsequent dystonia. To date, methods for quantification of 3HGA are mainly based on stable isotope dilution gas chromatography mass spectrometry (GC-MS) and require extensive sample preparation. Here we describe a simple liquid chromatography tandem MS (LC-MS/MS) method to quantify this important metabolite in dried urine spots (DUS). This method is based on derivatization with 4-[2-(N,N-dimethylamino)ethylaminosulfonyl]-7-(2-aminoethylamino)-2,1,3-benzoxadiazole (DAABD-AE). Derivatization was adopted to improve the chromatographic and mass spectrometric properties of the studied analytes. Derivatization was performed directly on a 3.2-mm disc of DUS as a sample without extraction. Sample mixture was heated at 60°C for 45 min, and 5 μl of the reaction solution was analyzed by LC-MS/MS. Reference ranges obtained were in excellent agreement with the literature. The method was applied retrospectively for the analysis of DUS samples from established low- and high-excreter GA1 patients as well as controls (n = 100). Comparison of results obtained versus those obtained by GC-MS was satisfactory (n = 14). In populations with a high risk of GA1, this approach will be useful as a primary screening method for high- or low-excreter variants. In these populations, however, DUS analysis should not be implemented before completing a parallel comparative study with the standard screening method (i.e., molecular testing). In addition, follow-up DUS GA and 3HGA testing of babies with elevated dried blood spot C5DC acylcarnitines will be useful as a first-tier diagnostic test, thus reducing the number of cases requiring enzymatic and molecular analyses to establish or refute the diagnosis of GA1.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".