Evidence map›Paper›PMID 34603851›Full record

ArticlePeerJ2021

Identification and validation of hub genes for diabetic retinopathy.

Li Peng, Wei Ma, Qing Xie, Baihua Chen

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Li PengDepartment of Ophthalmology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Wei MaDepartment of Ophthalmology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Qing XieDepartment of Ophthalmology, Central South University Xiangya School of Medicine Affiliated Haikou Hospital, Haikou, Hainan, China.
Baihua ChenDepartment of Ophthalmology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Central South University · CNSecond Xiangya Hospital of Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR) is characterized by a gradually progressive alteration in the retinal microvasculature that leads to middle-aged adult acquired persistent blindness. Limited research has been conducted on DR pathogenesis at the gene level. Thus, we aimed to reveal novel key genes that might be associated with DR formation via a bioinformatics analysis.

methodsThe GSE53257 dataset from the Gene Expression Omnibus was downloaded for gene co-expression analysis. We identified significant gene modules via the Weighted Gene Co-expression Network Analysis, which was conducted by the Protein-Protein Interaction (PPI) Network via Cytoscape and from this we screened for key genes and gene sets for particular functional and pathway-specific enrichments. The hub gene expression was verified by real-time PCR in DR rats modeling and an external database.

resultsTwo significant gene modules were identified. Significant key genes were predominantly associated with mitochondrial function, fatty acid oxidation and oxidative stress. Among all key genes analyzed, six up-regulated genes (

conclusionGene co-expression network analysis highlights the importance of mitochondria and oxidative stress in the pathophysiology of DR. DR co-expressing gene module was constructed and key genes were identified, and both SLC25A33 and NDUFS1 may serve as potential biomarker and therapeutic target for DR.

Indexed as

Diabetic retinopathyKey genesNDUFS1SLC25A33Weighted gene co-expression network analysis

Identifiers

PMID34603851
PMCPMC8445088
OpenAlexW3200080469

What OpenQuestion holds

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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.