Evidence map›Paper›PMID 31077208›Full record

ArticleLipids in health and disease2019

Lipidomics coupled with pathway analysis characterizes serum metabolic changes in response to potassium oxonate induced hyperuricemic rats.

Fei Yang, Mingyu Liu, Nankun Qin, Shuangshuang Li, Mengqi Yu, Chengxiang Wang, Qun Ma

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 12% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

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  18. High-Throughput Untargeted Serum Metabolomics Analysis of Hyperuricemia Patients by UPLC-Q-TOF/MS.Evidence-based complementary and alternative medicine : eCAM · 2021
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  19. Article
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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

7 authors at 1 institution in 1 country.

Fei YangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Mingyu LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Nankun QinSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Shuangshuang LiSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Mengqi YuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Chengxiang WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Qun MaSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China. 18811398272@163.com.
Beijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperuricemia as a metabolic disease is usually associated with lipid metabolic disorder. The purpose of this study is to identify potential lipid biomarkers and provide the evidence for the relationship between hyperuricemia and lipid-related diseases.

methodsLipidomics-a specialized study of lipid metabolites-has become a highly sensitive and powerful tool for biomarker discovery. In this work, an ultra-performance liquid chromatography-quadruole-time-of-flight tandem mass spectrometry (UPLC-Q-TOF/MS)-based on Lipidomics approach was employed to investigate serum samples from potassium oxonate-treated rats to find potential biomarkers. Principal component analysis (PCA) was used to analyze the MS data to assess the establishment of hyperuricemia model. Orthogonal partial least-squares discriminant analysis (OPLS-DA) in combination with independent samples t-test was performed for biomarker selection and identification.

resultsThirteen potential biomarkers in rat serum were identified in the screen, and two abnormal metabolism pathways were found, namely glycerolphospholipid metabolism and glycosylphosphatidylinositol-anchored protein biosynthesis.

conclusionsIn this work, the Lipidomics approach based on UPLC-Q-TOF/MS was employed to investigate serum metabolic changes in the rat model, 13 potential biomarkers related to hyperuricemia were identified, primarily involved in glycerolphospholipid metabolism and glycosylphosphatidylinositol-anchored protein biosynthesis. Abnormal glycerophospholipid metabolism pathway may be associated with lipid metabolism disorder caused by hyperuricemia, while the relationship between hyperuricemia and glycosylphosphatidylinositol-anchored protein biosynthesis needs further study.

Indexed as

Lipid MetabolismMetabolic Networks and PathwaysMetabolomicsAnimalsBiomarkersChromatography, High Pressure LiquidDiscriminant AnalysisHyperuricemiaLeast-Squares AnalysisLipidsMaleMass SpectrometryMetabolomeMultivariate AnalysisOxonic AcidPrincipal Component AnalysisBiomarkersLipidsOxonic Acidpotassium oxonateUric AcidHyperuricemiaLipidomicsPotassium oxonateUPLS-Q-TOF/MS

Identifiers

PMID31077208
PMCPMC6511199
OpenAlexW2947316660

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LicenceCC BY
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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.