Evidence map›Paper›PMID 33255934›Full record

ArticleInternational journal of molecular sciences2020

Urinary Metabolomic Profiling in Streptozotocin-Induced Diabetic Mice after Treatment with Losartan.

Jin Seong Hyeon, Youngae Jung, Gayoung Lee, Hunjoo Ha, Geum-Sook Hwang

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. Metabolomics and bioinformatics study of baicalin in treating pulmonary fibrosis.Naunyn-Schmiedeberg's archives of pharmacology · 2026
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  3. Scientific reports · 2024
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  6. Biomarker identification and pathway analysis ofFrontiers in pharmacology · 2023
    Article
  7. Article
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  9. Review
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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 at 2 institutions in 1 country.

Jin Seong HyeonIntegrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Korea.
Youngae JungIntegrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Korea.
Gayoung LeeGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.
Hunjoo HaGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea.ORCID 0000-0002-5601-1265
Geum-Sook HwangIntegrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Korea.
Ewha Womans University · KRKorea Basic Science Institute · KR

Funding

Korea Basic Science Institute C060200National Research Foundation (NRF) NRF-2017M3A9D5A01052449, NRF-2019R1A2C2002720
6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease and end-stage kidney disease. Renin-angiotensin system inhibitors such as losartan are the predominant therapeutic options in clinical practice to treat DKD. Therefore, it is necessary to identify DKD-related metabolic profiles that are affected by losartan. To investigate the change in metabolism associated with the development of DKD, we performed global and targeted metabolic profiling using 800 MHz nuclear magnetic resonance spectroscopy of urine samples from streptozotocin-induced diabetic mice (DM) with or without losartan administration. A principal component analysis plot showed that the metabolic pattern in the losartan-treated diabetic mice returned from that in the DM group toward that in the control mice (CM). We found that 33 urinary metabolites were significantly changed in DM compared with CM, and the levels of 16 metabolites among them, namely, glucose, mannose, myo-inositol, pyruvate, fumarate, 2-hydroxyglutarate, isobutyrate, glycine, threonine, dimethylglycine, methyldantoin, isoleucine, leucine, acetylcarnitine, 3-hydroxy-3-methylglutarate, and taurine, shifted closer to the control level in response to losartan treatment. Pathway analysis revealed that these metabolites were associated with branched-chain amino acid degradation; taurine and hypotaurine metabolism; glycine, serine, and threonine metabolism; the tricarboxylic acid cycle; and galactose metabolism. Our results demonstrate that metabolomic analysis is a useful tool for identifying the metabolic pathways related to the development of DKD affected by losartan administration and may contribute to the discovery of new therapeutic agents for DKD.

Indexed as

MetabolomeAnimalsDiabetes Mellitus, ExperimentalDiscriminant AnalysisLeast-Squares AnalysisLosartanMetabolic Networks and PathwaysMetabolomicsMice, Inbred C57BLPattern Recognition, AutomatedPrincipal Component AnalysisStreptozocinLosartanStreptozocindiabetic kidney diseaselosartanmetabolomicsNMR

Identifiers

PMID33255934
PMCPMC7730544
OpenAlexW3107970455

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.