ArticleTalanta open2025
A multiplexed LC-MS/MS assay for comprehensive screening of amino acid metabolism disorders.
Article in Talanta open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) are redefining the landscape of clinical diagnostics, particularly in the context of newborn screening for inborn errors of metabolism. Conventional analytical platforms are often limited by a small number of analytes and require multiple platforms for subsequent analyses, thereby impacting timely diagnosis and management. This study describes the development of a multiplexed targeted mass spectrometry-based assay for simultaneous detection and quantitation of amines, including amino acids and their derivatives, from plasma, urine and dried blood spots. The method utilizes a single step derivatization strategy based on one step click chemistry that simplifies sample preparation while improving analytical sensitivity allowing for detection of analytes at sub-picomolar concentrations. Furthermore, we adopted a strategy of generating heavy isotopically labeled standards by chemically modifying the corresponding light standards using a stable isotope labeled derivatizing agent, enabling their use as internal standards for quantification. This approach can offer a cost-effective and scalable solution for the early detection and management of inherited metabolic disorders, particularly in cases where accurate detection of amines is critical.
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Registered trials
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 Socratic graph.