Evidence map›Paper›PMID 37820575›Full record

ReviewMolecular genetics and metabolism2023

Newborn screening for the full set of mucopolysaccharidoses in dried blood spots based on first-tier enzymatic assay followed by second-tier analysis of glycosaminoglycans.

Zackary M Herbst, Xinying Hong, Martin Sadilek, Maria Fuller, Michael H Gelb

Abstract readReview
In one paragraph

Review in Molecular genetics and metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zackary M HerbstDept. of Chemistry, University of Washington, Seattle, WA 98195, USA.
Xinying HongDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Martin SadilekDept. of Chemistry, University of Washington, Seattle, WA 98195, USA.
Maria FullerGenetics and Molecular Pathology, SA Pathology at Women's and Children's Hospital, North Adelaide 5006, Australia; School of Biological Sciences and Adelaide Medical School, University of Adelaide, Adelaide 5005, Australia. Electronic address: maria.fuller@adelaide.edu.au.
Michael H GelbDept. of Chemistry, University of Washington, Seattle, WA 98195, USA; Dept. of Biochemistry, University of Washington, Seattle, WA 98195, USA. Electronic address: gelb@uw.edu.

Funding

Multiplex Analysis of Inborn Errors of MetabolismR01DK067859 · NIDDK · UNIVERSITY OF WASHINGTON · PI GELB, MICHAEL H · 2003 to 2025
$9.8M
NIDDK NIH HHS R01 DK067859
6 · The paper itself

Abstract

Newborn screening (NBS) for the full set of mucopolysaccharidoses (MPSs) is now possible by either measuring all of the relevant enzymatic activities in dried blood spots (DBS) using tandem mass spectrometry followed by measurement of accumulated glycosaminoglycans (GAGs) or the vice-versa approach. In this study we considered multiple factors in detail including reagent costs, time per analysis, false positive rates, instrumentation requirements, and multiplexing capability. Both NBS approaches are found to provide acceptable solutions for comprehensive MPS NBS, but the enzyme-first approach allows for better multiplexing to include numerous additional diseases that are appropriate for NBS expansion. By using a two-tier NBS approach, the false positive and false negatives rates are expected to acceptably low and close to zero.

Indexed as

GlycosaminoglycansMucopolysaccharidosesEnzyme AssaysHumansInfant, NewbornNeonatal ScreeningTandem Mass SpectrometryGlycosaminoglycansBiochemical geneticsInborn errors of metabolismLysosomal storage diseasesNewborn screeningTandem mass spectrometry

Identifiers

PMID37820575
PMCPMC10841861

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.