Evidence map›Paper›PMID 41330729›Full record

ReviewJournal of inherited metabolic disease2026

Untargeted Metabolomics for Diagnosis, Monitoring, and Understanding the Pathophysiology of Inherited Metabolic Disorders.

Jonathan Martens, Udo F H Engelke, Ron A Wevers, Dirk J Lefeber, Purva Kulkarni

Abstract readReview
In one paragraph

Review in Journal of inherited metabolic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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.

Jonathan MartensInstitute for Molecules and Materials, FELIX Laboratory, Radboud University, Nijmegen, the Netherlands.ORCID https://orcid.org/0000-0001-9537-4117
Udo F H EngelkeDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Centre, Nijmegen, the Netherlands.
Ron A WeversDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Centre, Nijmegen, the Netherlands.ORCID https://orcid.org/0000-0003-2278-9746
Dirk J LefeberDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Centre, Nijmegen, the Netherlands.
Purva KulkarniDepartment of Human Genetics, Translational Metabolic Laboratory, Radboud University Medical Centre, Nijmegen, the Netherlands.ORCID https://orcid.org/0000-0002-4681-4582

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek
6 · The paper itself

Abstract

Inherited metabolic disorders (IMDs) encompass a diverse and expanding group of rare diseases caused by genetic disruptions mainly in metabolic enzymes and transporters. Clinical diagnosis of IMDs presents significant challenges due to phenotypic heterogeneity, nonspecific symptoms, and the limited scope of current targeted biochemical assays typically available. Recent advances in mass spectrometry-based untargeted metabolomics offer promising solutions to several of these challenges by simultaneous detection and relative quantification of thousands of metabolites, not relying on any prior hypotheses. With the expansion of genetic diagnostics via whole-exome and whole-genome sequencing, metabolic insights are often crucial for understanding the pathogenicity of genetic variants of unknown significance, often enabling a clear diagnosis for patients. This review details current applications of untargeted metabolomics in IMDs, including biomarker discovery and elucidation of previously unknown pathophysiological mechanisms. Successful examples of biomarker identification in well-studied IMDs, such as pyridoxine-dependent epilepsy and phenylketonuria, are highlighted to provide novel disease insights. Additionally, we address technical and interpretation challenges inherent to this methodology, particularly concerning metabolite identification, high-dimensional data complexity, and limited patient numbers. Emerging analytical technologies and data analysis approaches are highlighted that are poised to mitigate these challenges in the upcoming years. Finally, we provide an outlook on future directions, emphasizing the complementary roles of targeted and untargeted metabolomics and the prospects for the identification of new therapeutic targets as well as therapy monitoring for the clinical management of IMDs.

Indexed as

Metabolic DiseasesMetabolism, Inborn ErrorsMetabolomicsBiomarkersHumansMass SpectrometryBiomarkersbiomarkersdark matter of the metabolomede‐VUSingdiagnosticsinborn errors of metabolismmass spectrometrymetabolic disease discoveryuntargeted metabolomics

Identifiers

PMID41330729
PMCPMC12672196

What OpenQuestion holds

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Registered trials

None linked

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.