Direct Multiplex Assay of Lysosomal Enzymes in Dried Blood Spots for Newborn Screening
Bibliographic record
Abstract
BACKGROUND: Newborn screening for deficiency in the lysosomal enzymes that cause Fabry, Gaucher, Krabbe, Niemann-Pick A/B, and Pompe diseases is warranted because treatment for these syndromes is now available or anticipated in the near feature. We describe a multiplex screening method for all five lysosomal enzymes that uses newborn-screening cards containing dried blood spots as the enzyme source. METHODS: We used a cassette of substrates and internal standards to directly quantify the enzymatic activities, and tandem mass spectrometry for enzymatic product detection. Rehydrated dried blood spots were incubated with the enzyme substrates. We used liquid-liquid extraction followed by solid-phase extraction with silica gel to remove buffer components. Acarbose served as inhibitor of an interfering acid alpha-glucosidase present in neutrophils, which allowed the lysosomal enzyme implicated in Pompe disease to be selectively analyzed. RESULTS: We analyzed dried blood spots from 5 patients with Gaucher, 5 with Niemann-Pick A/B, 11 with Pompe, 5 with Fabry, and 12 with Krabbe disease, and in all cases the enzyme activities were below the minimum activities measured in a collection of heterozygous carriers and healthy noncarrier individuals. The enzyme activities measured in 5-9 heterozygous carriers were approximately one-half those measured with 15-32 healthy individuals, but there was partial overlap of each condition between the data sets for carriers and healthy individuals. CONCLUSION: For all five diseases, the affected individuals were detected. The assay can be readily automated, and the anticipated reagent and supply costs are well within the budget limits of newborn-screening centers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".