Evidence map›Paper›PMID 42622690›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2026

Cross-species urinary metabolomics identifies 2-hydroxyisovalerate as a candidate biomarker for mtDNA-based disorders.

Marianne Venter, Karin Terburgh, Jeremie Z Lindeque, Emi Ogasawara, Mirian C H Janssen, Jan A M Smeitink, Kazuto Nakada, Roan Louw

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Article in Metabolomics : Official journal of the Metabolomic Society, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Marianne Venter *Mitochondria Research Group, Biomedical and Molecular Metabolism Research (BioMMet), North-West University, Potchefstroom, South Africa.
Karin Terburgh *Mitochondria Research Group, Biomedical and Molecular Metabolism Research (BioMMet), North-West University, Potchefstroom, South Africa.
Jeremie Z LindequeMitochondria Research Group, Biomedical and Molecular Metabolism Research (BioMMet), North-West University, Potchefstroom, South Africa.
Emi OgasawaraDepartment of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, 560-0043, Japan.
Mirian C H JanssenDepartment of Pediatrics, Radboud Center for Mitochondrial Medicine, Radboud University Medical Center, Nijmegen, Netherlands.
Jan A M SmeitinkDepartment of Pediatrics, Radboud Center for Mitochondrial Medicine, Radboud University Medical Center, Nijmegen, Netherlands.
Kazuto NakadaInstitute of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan.
Roan LouwMitochondria Research Group, Biomedical and Molecular Metabolism Research (BioMMet), North-West University, Potchefstroom, South Africa. Roan.Louw@nwu.ac.za.ORCID http://orcid.org/0000-0002-6542-8644

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogenic mitochondrial DNA (mtDNA) mutations contribute to a broad spectrum of both common and rare metabolic diseases. However, clinical presentation is highly variable and only partially explained by the proportion of mutant mtDNA or heteroplasmy. With the relationship between mutation burden and clinical manifestation poorly defined, controlled models are required to uncover underlying mechanisms. Here, we explore the metabolic consequences of increasing heteroplasmy in a well-characterised mouse model harbouring a pathogenic mtDNA deletion. Untargeted urinary metabolomics reveals distinct mutation load-dependent metabolic shifts with some metabolites declining early on, while others exhibit threshold-like increases beyond ~ 60% mutation load - the level at which lactic acidemia and OXPHOS defects become apparent in this model. To assess translational relevance, we examined these heteroplasmy-associated metabolites in urine from patients carrying the most common mtDNA mutation, m.3243 A > G. Several of these metabolites were differentially expressed in patients relative to controls, with conserved directionality across species. Among these, 2-hydroxyisovalerate (2-HIVA), which was most strongly affected in the mouse model, also emerged as the top discriminator in patients. Receiver operating characteristic analysis indicated that urinary 2-HIVA has strong discriminatory power, supporting its potential utility as a biomarker for mtDNA-based disorders. These findings enhance our understanding of mtDNA-related disease pathophysiology and establish a foundation for further validation studies.

Indexed as

DNA, MitochondrialMetabolomicsMitochondrial DiseasesValeratesAnimalsBiomarkersDisease Models, AnimalFemaleHeteroplasmyHumansMaleMiceMutationBiomarkersDNA, MitochondrialValerates2-HydroxyisovalerateHeteroplasmyM.3243A > GMetabolomicsMitochondrial diseaseMito-miceMtDNA

Identifiers

PMID42622690
PMCPMC13493467

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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.