Evidence map›Paper›PMID 30315511›Full record

ArticleJournal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology2019

Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis.

J Singh, M Cerghet, L M Poisson, I Datta, K Labuzek, H Suhail, R Rattan, Shailendra Giri

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In one paragraph

Article in Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

18 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Immune-responsive gene 1: The mitochondrial key to Th17 cell pathogenicity in CNS autoimmunity.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  4. Review
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  11. Review
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  13. Blood-based untargeted metabolomics in relapsing-remitting multiple sclerosis revealed the testable therapeutic target.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  14. Orphanet journal of rare diseases · 2021
    Article
  15. Review
  16. Article
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  18. Observational
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

8 authors at 2 institutions in 2 countries.

J SinghDepartment of Neurology, Henry Ford Health System, E&R Building, Room 4051, Detroit, MI, 48202, USA.
M CerghetDepartment of Neurology, Henry Ford Health System, E&R Building, Room 4051, Detroit, MI, 48202, USA.
L M PoissonCenter for Bioinformatics, Henry Ford Health System, Detroit, MI, 48202, USA.
I DattaCenter for Bioinformatics, Henry Ford Health System, Detroit, MI, 48202, USA.
K LabuzekDepartment of Internal Medicine and Clinical Pharmacology, Medical University of Silesia, 40-752, Katowice, Poland.
H SuhailDepartment of Neurology, Henry Ford Health System, E&R Building, Room 4051, Detroit, MI, 48202, USA.
R RattanDivision of Gynecology Oncology, Department of Women's Health Services, Henry Ford Health System, Detroit, MI, 48202, USA.
Shailendra GiriDepartment of Neurology, Henry Ford Health System, E&R Building, Room 4051, Detroit, MI, 48202, USA. sgiri1@hfhs.org.ORCID 0000-0002-7123-829X
Henry Ford Health System · USMedical University of Silesia · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of non-invasive biomarkers of disease progression in multiple sclerosis (MS) is critically needed for monitoring the disease progression and for effective therapeutic interventions. Urine is an attractive source for non-invasive biomarkers because it is easily obtained in the clinic. In search of a urine metabolite signature of progression in chronic experimental autoimmune encephalomyelitis (EAE), we profiled urine at the chronic stage of the disease (day 45 post immunization) by global untargeted metabolomics. Using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry, we found 105 metabolites (P < 0.05) significantly altered at the chronic stage, indicating a robust alteration in the urine metabolite profile during disease. Assessment of altered metabolites against the Kyoto Encyclopedia of Genes and Genomes revealed distinct non-overlapping metabolic pathways and revealed phenylalanine-tyrosine and associated metabolism being the most impacted. Combined with previously performed plasma profiling, eight common metabolites were significantly altered in both of the biofluids. Metaboanalyst analysis of these common metabolites revealed that phenylalanine metabolism and Valine, leucine, and isoleucine biosynthetic pathways are central metabolic pathways in both bio-fluids and could be analyzed further, either for the discovery of therapeutics or biomarker development. Overall, our study suggests that urine and plasma metabolomics may contribute to the identification of a distinct metabolic fingerprint of EAE disease discriminating from the healthy control which may aid in the development of an objective non-invasive monitoring method for progressive autoimmune diseases like MS. Graphical Abstract Untargeted urinary metabolomics of a chronic mouse model of multiple sclerosis identified Phenylalanine, tyrosine & tryptophan metabolism as the significantly altered metabolic pathway. Eight common metabolites were identified when we combined urinary and plasma metabolic signature, which revealed a perturbation of Phenylalanine metabolism and valine, leucine & isoleucine metabolic pathways, involved in CNS dysfunction during diseases. The identified eight metabolic signature of urine and plasma may be of clinical relevance as potential biomarkers and guide towards the identification of specific metabolic pathways as novel drug targets.

Indexed as

MetabolomicsAmino AcidsAnimalsBiomarkersChromatography, High Pressure LiquidChronic DiseaseDisease ProgressionEncephalomyelitis, Autoimmune, ExperimentalFemaleGas Chromatography-Mass SpectrometryMetabolic Networks and PathwaysMiceMice, Inbred C57BLMultiple SclerosisAmino AcidsBiomarkersBiomarkersEAEGC-MS/LC-MSMetabolic pathwaysMetabolomicsMultiple sclerosisUrine

Identifiers

PMID30315511
OpenAlexW2897201353

What OpenQuestion holds

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Read underepoch 390

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.