Analysis of Acid Sphingomyelinase Activity in Dried Blood Spots Using Tandem Mass Spectrometry
Bibliographic record
Abstract
BACKGROUND: Niemann Pick disease (NP) is a rare, lysosomal storage disorder due to deficiency of the intra-lysosomal enzyme acid sphingomyelinase (ASM) resulting in intracellular accumulation of sphingomyelin. We evaluated a tandem mass spectrometry (MS/MS) method to analyze ASM activity in dried blood spots (DBS) that may be suitable for laboratory diagnosis of NP including high throughput screening of at-risk populations and potentially for newborn screening. METHODS: ASM activity was measured in 3.2 mm punches from DBS. The eluate was incubated with the ASM substrate (N-Hexanoyl-D-erythro-sphingosylphosphorylcholine [C6-sphingomyelin (C(29)H(59)N(2)O(6)P)]) and an internal standard (N-butyroyl-D-erythro-sphingosine [C4-ceramide (C(22)H(43)NO(3))]). ASM product and IS were analyzed using MS/MS in multiple reaction monitoring mode for transitions m/z 370.6>264.3 (ASM internal standard) and m/z 398.6>264.3 (ASM product). RESULTS: ASM activities were stable for up to 2 months at or below 4℃. Position of the punch in the DBS and/or hematocrit of the DBS had a limited effect on ASM activities. Both intra- and inter-assay variability were below 10%. There was no carry-over. The median ASM activity in 2,085 newborn infants was 9.5 µmol/h/L (mean 10.6) with a SD of 5.06 µmol/h/L. Six of 2,085 (0.3%) infants were found to have ASM activities below the cut-off of 2.5 µmol/h/L. ASM activities were below the cut-off level in all 10 previously diagnosed cases with NP (range: 0.16 to 2.08 µmol/h/L). CONCLUSIONS: This MS/MS method for the measurement of ASM activity in DBS is robust and suitable for laboratory diagnosis of NP.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".