Evidence map›Paper›PMID 30824724›Full record

ArticleScientific reports2019

Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis.

Jin Shang, Shuai Wang, Yumin Jiang, Yiqi Duan, Genyang Cheng, Dong Liu, Jing Xiao, Zhanzheng Zhao

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

15 citing papers in PubMed, 24 citations in OpenAlex.

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  13. Long Non-Coding RNAs in Kidney Disease.International journal of molecular sciences · 2019
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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

8 authors at 1 institution in 1 country.

Jin ShangDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Shuai WangDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Yumin JiangDepartment of Emergency, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Yiqi DuanDepartment of Pharmacy, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Genyang ChengDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Dong LiuDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Jing XiaoDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China.
Zhanzheng ZhaoDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, P.R. China. zhanzhengzhao@zzu.edu.cn.
First Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

LncRNA is reported to have important role in diabetic nephropathy (DN). Here, we aim to identify key lncRNAs of DN using bioinformatics and systems biological methods.

methodFive microarray data sets from Gene Expression Omnibus (GEO) database were included. Probe sets were re-annotated. In the training set, differential expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was constructed to screen diabetic-related hub genes and reveal their potential biological function. Two more human data sets and mouse data sets were used as validation sets.

resultsA total of 424 DEGs, including 10 lncRNAs, were filtered in the training data set. WGCNA and enrichment analysis of hub genes showed that inflammation and metabolic disorders are prominent in DN. Three key lncRNAs (NR_130134.1, NR_029395.1 and NR_038335.1) were identified. These lncRNAs are also differently expressed in another two human data sets. Functional enrichment of the mouse data sets showed consistent changes with that in human, indicating similar changes in gene expression pattern of DN and confirmed confidence of our analysis. Human podocytes and mesangial cells were culture in vitro. QPCR and fluorescence in situ hybridization were taken out to validate the expression and relationship of key lncRNAs and their related mRNAs. Results were also consistent with our analysis.

conclusionsInflammation and metabolic disorders are prominent in DN. We identify three lncRNAs that are involved in these processes possibly by interacting with co-expressed mRNAs.

Indexed as

Databases, Nucleic AcidDiabetic NephropathiesGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksRNA, Long NoncodingAnimalsHumansIn Situ Hybridization, FluorescenceMiceRNA, Long Noncoding

Identifiers

PMID30824724
PMCPMC6397236
OpenAlexW2919765805

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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.