Evidence map›Paper›PMID 31615521›Full record

ArticleBMC medical genomics2019

Transcriptome analysis identified a novel 3-LncRNA regulatory network of transthyretin attenuating glucose induced hRECs dysfunction in diabetic retinopathy.

Jun Shao, Yunbin Zhang, Guangming Fan, Yu Xin, Yong Yao

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

19 citing papers in PubMed, 27 citations in OpenAlex.

  1. FTO-modulated mJournal of translational medicine · 2026
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  6. Transcriptome Analysis of Sesame (International journal of molecular sciences · 2024
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  16. Hyperglycemia-induced increasing ofAnnals of translational medicine · 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

5 authors at 3 institutions in 1 country.

Jun ShaoDepartment of Ophthalmology, Wuxi People's Hospital affiliated to Nanjing Medical University, Wuxi, 214023, Jiangsu, China.
Yunbin ZhangInstitute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China.
Guangming FanKey Laboratory of Industry Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122, Jiangsu, China.
Yu XinKey Laboratory of Industry Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122, Jiangsu, China. yuxin@jiangnan.edu.cn.
Yong YaoDepartment of Ophthalmology, Wuxi People's Hospital affiliated to Nanjing Medical University, Wuxi, 214023, Jiangsu, China. yaoyongchina@outlook.com.
Jiangnan University · CNNanjing Medical University · CNCenter for Excellence in Molecular Cell Science · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR) is the leading cause of blindness in the working age population. Transthyretin (TTR) showed a significantly decreased concentration in DR patients and exerted a visual protective effect by repressing neovascularization. This work intended to identify long non coding RNAs (lncRNAs) and explore their potential mechanism underlying the protective role of TTR.

methodsTranscriptome of human retinal endothelial cells (hRECs) treated with low glucose (LG), high glucose (HG) or high glucose with 4 μM TTR (HG + TTR) was conducted. Differentially expressed lncRNAs, mRNAs and TTR related lncRNAs and mRNA were acquired. Functional annotation and Gene Set Enrichment Analysis were applied to analyse TTR affected pathways and processes. Weighted gene co-expression network analysis (WGCNA) was implemented to obtain hub modules and genes. LncRNA-mRNA regulatory networks were constructed based on cis, trans and competing endogenous RNAs acting mode. QRT-PCR was conducted to validate the expression of lncRNAs in aqueous humor and serum samples from 30 DR patients and 10 normal controls.

resultsRNA-sequencing of hRECs treated with low glucose (LG), high glucose (HG) or high glucose with 4 μM TTR (HG + TTR) was conducted. 146,783 protein-coding transcripts, 12,403 known lncRNA transcripts and 1184 novel non-coding transcripts were characterized. A total of 11,407 differentially expressed mRNAs (DE-mRNAs), 679 differentially expressed lncRNAs (DE-lncRNAs) in HG group versus LG group, 6206 DE-mRNAs and 194 DE-lncRNAs in HG + TTR versus HG group were obtained, respectively. 853 TTR-mRNAs and 48 TTR-lncRNAs were acquired, and functionally involved in cell cycle, apoptosis, inflammation signalling pathway, response to oxidative stress, neovascularization and autophagy. The WGCNA analysis identified a hub module of 133 genes, with the core function of oxidative stress response, angiogenesis, MAPK pathway, cell proliferation and apoptosis. After qRT-PCR validation, a 3-lncRNA regulatory network was proposed. At last, lncRNAs MSTRG.15047.3 and AC008403.3 showed significantly relative higher expression levels in both aqueous humor and serum samples, compared with normal controls, and FRMD6-AS2 was significantly down-regulated.

conclusionsTTR regulated mRNAs and biological processes including oxidative stress, inflammation signalling and autophagy. A 3-lncRNA regulatory network was characterized underlying TTR repressing neovascularization, and showed potential diagnostic performance in DR.

Indexed as

TranscriptomeBiomarkersCase-Control StudiesDiabetic RetinopathyEndothelial CellsGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGlucoseHumansPrealbuminProtein Interaction MapsRetinaRNA, Long NoncodingRNA, MessengerBiomarkersGlucosePrealbuminRNA, Long NoncodingRNA, Messenger3-lncRNA regulatory network, diagnosisDiabetic retinopathyTranscriptomeTransthyretin

Identifiers

PMID31615521
PMCPMC6794807
OpenAlexW2981153829

What OpenQuestion holds

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LicenceCC BY
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.