ReviewDiagnostics (Basel, Switzerland)2026
Emerging Quantitative Targeted Metabolomics Approaches for Future Inborn Errors of Metabolism Screening.
Review in Diagnostics (Basel, Switzerland), 2026. 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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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.
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0 citing papers in PubMed.
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Authors and funding
5 authors.
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Abstract
Inborn errors of metabolism (IEMs) are a group of inherited genetic conditions that, in general, result from a specific enzyme defect. Clinical consequences caused by abnormal enzyme levels often disrupt affected metabolic pathways and their intermediary metabolites. Because diagnostic outcomes depend on early intervention, a timely and accurate diagnosis is essential. Quantitative targeted metabolomics (QTM) is an analytical approach that quantifies predefined metabolites and generates interpretable biochemical phenotypes. Instead of focusing solely on screening, expanded QTM methods enable higher coverage with multi-analyte profiling that can provide more comprehensive characterization of disease-associated metabolic perturbations, particularly in IEMs with overlapping biochemical profiles. This review summarizes diagnostic techniques for IEMs, outlines the principles and advantages of QTM, and evaluates its established role and emerging opportunities and limitations in advancing method development and deep metabolic phenotyping to support precision medicine.
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