Evidence map›Paper›PMID 31992312›Full record

ArticleJournal of translational medicine2020

Establishment of the circadian metabolic phenotype strategy in spontaneously hypertensive rats: a dynamic metabolomics study.

Huanjun Wang, Xiaoming Wang, Dongmei Qi, Mengjia Sun, Qingqing Hou, Yunlun Li, Haiqiang Jiang

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

16 citing papers in PubMed, 28 citations in OpenAlex.

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  13. Renal metabolism and hypertension.Nature communications · 2021
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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.

Huanjun WangSchool of Pharmaceutical Sciences, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China.ORCID http://orcid.org/0000-0002-9865-5421
Xiaoming WangExperimental Center, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China.
Dongmei QiExperimental Center, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China.
Mengjia SunSchool of Pharmaceutical Sciences, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China.
Qingqing HouSchool of Pharmaceutical Sciences, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China.
Yunlun LiTCM Clinical Research Base for Hypertension, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, 250011, People's Republic of China. li.yunlun@163.com.
Haiqiang JiangExperimental Center, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People's Republic of China. jhq12723@163.com.
Shandong University of Traditional Chinese Medicine · CN

Funding

Key Technology Research and Development Program of Shandong 2018GSF119007Major Basic Research Projects of Shandong Natural Science Foundation ZR2018ZC1157National Natural Science Foundation of China 81774173Shandong Province major scientific and technological innovation 2017CXGC1307
6 · The paper itself

Abstract

backgroundCircadian rhythms play a fundamental role in the progression of cardiovascular events. Almost all cardiovascular diseases have a circadian misalignment usually characterized by changes in metabolites. This study aimed to dynamically monitor rhythmic biomarkers, to elucidate the metabolic pathways that are potentially under circadian control in spontaneously hypertensive rats (SHRs), and to eventually establish a circadian metabolic phenotype strategy based on metabolomics.

methodsIn this study, an untargeted metabolomics technology was used to dynamically monitor changes in serum metabolites between SHR model group and WKY control group. Liquid chromatography-mass spectrometry (LC-MS) combined with multivariate statistical analysis was applied to identify markers of hypertension rhythm imbalance. The concentrations of amino acids and their metabolites identified as markers were quantified by a subsequent targeted metabolomics analysis. Overall, these approaches comprehensively explored the rhythm mechanism and established a circadian metabolic phenotype strategy.

resultsThe metabolic profile revealed a disorder in the diurnal metabolism pattern in SHRs. Moreover, multivariate statistical analysis revealed metabolic markers of rhythm homeostasis, such as arginine, proline, phenylalanine, citric acid, L-malic acid, succinic acid, etc., accompanied by an imbalance in hypertension. The key metabolic pathways related to rhythm imbalance in hypertension were found by enrichment analysis, including amino acid metabolism, and the tricarboxylic acid cycle (TCA). In addition, the quantitative analysis of amino acids and their metabolites showed that the changes in leucine, isoleucine, valine, taurine, serine, and glycine were the most obvious.

conclusionsIn summary, this study illustrated the relationship between metabolites and the pathways across time on hypertension. These results may provide a theoretical basis for personalized treatment programmes and timing for hypertension.

Indexed as

Circadian ClocksAmino AcidsAnimalsBiomarkersChronobiology DisordersMaleMetabolomicsRatsRats, Inbred SHRAmino AcidsBiomarkersAmino acidsCircadian rhythmHypertensionMetabolomics

Identifiers

PMID31992312
PMCPMC6988197
OpenAlexW3009823433

What OpenQuestion holds

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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.