Evidence map›Paper›PMID 40863139›Full record

ArticleMetabolites2025

Evaluation of the Metabolomics Profile in Charcot-Marie-Tooth (CMT) Patients: Novel Potential Biomarkers.

Federica Murgia, Martina Cadeddu, Jessica Frau, Giancarlo Coghe, Lorefice Lorena, Alessandro Vannelli, Maria Rita Murru, Martina Spada, Antonio Noto, Luigi Atzori and 1 more

Abstract read
In one paragraph

Article in Metabolites, 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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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Federica MurgiaDepartment of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, 09042 Cagliari, Italy.ORCID 0000-0003-4080-9851
Martina CadedduSchool of Applied Sciences, Edinburgh Napier University, Edinburgh EH11 4BN, UK.ORCID 0009-0008-7159-3428
Jessica FrauMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.
Giancarlo CogheMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.
Lorefice LorenaMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.ORCID 0000-0003-2050-2908
Alessandro VannelliMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.
Maria Rita MurruMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.
Martina SpadaDepartment of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, 09042 Cagliari, Italy.ORCID 0009-0003-9592-1178
Antonio NotoDepartment of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, 09042 Cagliari, Italy.ORCID 0000-0003-3538-0050
Luigi AtzoriDepartment of Biomedical Sciences, Clinical Metabolomics Unit, University of Cagliari, 09042 Cagliari, Italy.ORCID 0000-0002-0606-4959
Eleonora CoccoMultiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, 09126 Cagliari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCharcot-Marie-Tooth (CMT) is a group of inherited diseases impairing the peripheral nervous system. CMT originates from genetic variants that affect proteins fundamental for the myelination of peripheral nerves and survival. Moreover, environmental and humoral factors can impact disease development and evolution. Currently, no therapy is available. Metabolomics is an emerging field of biomedical research that enables the development of novel biomarkers for neurodegenerative diseases by targeting metabolic pathways or metabolites. This study aimed to evaluate the metabolomics profile of CMT disease by comparing patients with healthy individuals.

methodsA total of 22 CMT patients (CMT) were included in this study and were demographically matched with 26 healthy individuals (C). Serum samples were analyzed through Nuclear Magnetic Resonance spectroscopy, and multivariate and univariate statistical analyses were subsequently applied.

resultsA supervised model showed a clear separation (R

conclusionThis study represents a promising starting point, demonstrating the efficacy of metabolomics in evaluating CMT patients and identifying novel potential disease biomarkers.

Indexed as

biomarkersCharcot–Marie–Tooth diseasemetabolic pathwaysmetabolomicsnuclear magnetic resonance

Identifiers

PMID40863139
PMCPMC12388540

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