Evidence map›Paper›PMID 32690864›Full record

ArticleJournal of human genetics2020

Identifying potential functional lncRNAs in metabolic syndrome by constructing a lncRNA-miRNA-mRNA network.

Dengju Yao, Zijing Lin, Xiaojuan Zhan, Xiaorong Zhan

Abstract read
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In one paragraph

Article in Journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

12 citing papers in PubMed, 14 citations in OpenAlex.

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  11. Long Non-coding RNAs and CRISPR-Cas Edition in Tumorigenesis.Advances in experimental medicine and biology · 2023
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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

4 authors at 2 institutions in 1 country.

Dengju Yao *School of Software and Microelectronics, Harbin University of Science and Technology, Harbin, Heilongjiang, China.ORCID http://orcid.org/0000-0002-4974-3054
Zijing Lin *Department of Endocrinology and Metabolism, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Xiaojuan ZhanCollege of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China.
Xiaorong ZhanDepartment of Endocrinology and Metabolism, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China. xiaorongzhan@sina.com.
Harbin Medical University · CNHarbin University of Science and Technology · CN

Funding

China Scholarship Council (CSC) 201808930008Natural Science Foundation of Heilongjiang Province LH2019F023
6 · The paper itself

Abstract

The metabolic syndrome (MS) is a cluster of interrelated risk factors including diabetes mellitus, abdominal obesity, high cholesterol, and hypertension, which can significantly increase mortality and disability. Accumulating evidence suggest that long non-coding RNAs (lncRNAs) are involved in the pathogenesis of human metabolic diseases. However, little is known about the regulatory role of lncRNAs in MS. In this work, we proposed a method for identifying potential MS-associated lncRNAs by constructing an lncRNA-miRNA-mRNA network (LMMN). Firstly, we constructed LMMN by integrating MS-associated genes, miRNA-mRNA interactions, miRNA-lncRNA interactions and mRNA/miRNA expression profiles in patients with MS. Then, we predicted potential MS-associated lncRNAs based on the topological properties of LMMN. As a result, we identified XIST as the most important lncRNA in LMMN. Furthermore, we focused on XIST/miR-214-3p and mir-181a-5p/PTEN axis and validated their expression in MS using real-time quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR results showed that the expression of XIST and PTEN was significantly decreased (P < 0.05) while the expression of miR-214-3p was significantly increased (P < 0.05) in peripheral blood mononuclear cells (PBMCs) of patients with MS, compared with healthy controls. In addition, correlation analysis showed that XIST was negatively correlated with serum C peptide and PTEN was positively correlated with BMI of MS patients. Our findings provided new evidence for further exploring the regulatory role of XIST and other lncRNAs in MS.

Indexed as

Gene Regulatory NetworksBiomarkersGene Expression ProfilingHumansMetabolic SyndromeMicroRNAsPTEN PhosphohydrolaseRNA, Long NoncodingRNA, MessengerBiomarkersMicroRNAsPTEN PhosphohydrolasePTEN protein, humanRNA, Long NoncodingRNA, MessengerXIST non-coding RNA

Identifiers

PMID32690864
OpenAlexW3042703370

What OpenQuestion holds

Textmetadata
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.